Effects of Probiotics on Markers of Oxidative/Nitrosative Stress and Damage Associated with Inflammation in Non-Communicable Diseases: a Systematic Review and Meta-Analysis of Randomized Placebo-Controlled Trials

Effects of Probiotics on Markers of Oxidative/Nitrosative Stress and Damage Associated with Inflammation in Non-Communicable Diseases: a Systematic Review and Meta-Analysis of Randomized Placebo-Controlled Trials | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Effects of Probiotics on Markers of Oxidative/Nitrosative Stress and Damage Associated with Inflammation in Non-Communicable Diseases: a Systematic Review and Meta-Analysis of Randomized Placebo-Controlled Trials Natanny Swerts Silva, Cláudio Daniel Cerdeira, Tiago Marques Reis, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5791482/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Inflammation and oxidative/nitrosative stress (O&NS) are serious complications in non-communicable diseases (NCDs), including endocrine & metabolic and neurodegenerative diseases. The beneficial probiotic microbes, such as Lactobacillus , Bifidobacterium and Streptococcus , can decrease O&NS and inflammation. We conducted this systematic review and meta-analysis of randomized controlled trials (RCTs) to elucidate the effects of probiotics on O&NS and inflammation in NCDs. A systematic search of PubMed, Scopus and EMBASE resulted in the inclusion of studies if they met the eligibility criteria. Methodological quality was assessed using the Cochrane Risk of Bias 2 tool. Data (combined effect size) were analyzed using Meta Essentials software. Fifteen studies/16 trials with a total of 837 participants were reviewed. There was high and moderate certainty of evidence (GRADE) for the effectiveness of probiotic intervention ( vs . placebo) in increasing (↑) glutathione (GSH) levels [SMD(SE) = 0.89 (0.51)/ p < 0.05, 95%CI -0.23 to 2.1, I 2 = 92.77%] and total antioxidant capacity (TAC) [SMD(SE) = 0. 75 (0.22)/ p < 0.01, 95%CI 0.28 to 1.23, I 2 = 87.50%] as well as decreased (↓) malondialdehyde (MDA) (SMD(SE) = 1.03 (0.31)/ p < 0. 01, 95%CI 0.37 to 1.7, I 2 = 93.88%) and C-reactive protein (hsCRP) (SMD(SE) = 0.74 (0.36)/ p < 0.05, 95%CI -0.07 to 1.55, I 2 = 94.32%). There was no effects on nitric oxide, 8-hydroxy-2′-deoxyguanosine, interleukin-6, and tumor necrosis factor-α. Subgroup analysis to reduce heterogeneity indicated probiotic effectiveness on strain number (one/↑GSH), age bracket (41–60 year./↓MDA or > 61 year./↓hsCRP) and NCD (nervous system/neurodegenerative diseases/↑GSH and ↓hsCRP or rheumatoid arthritis/polycystic ovary syndrome/↑TAC). An overall low risk of bias was observed. In conclusion, probiotics may have beneficial effects on markers of O&NS and inflammation in patients with NCDs. Total antioxidant capacity. GSH. CRP. Lactobacillus. Bifidobacterium. Dysbiosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The gut microbiota, consisting of bacteria, fungi, viruses, and other microorganisms, serves as a secondary organ system with critical functions for the human host. Several factors disrupt the gut microbiota, including age, genetic specificity, diet, disease, and medications [ 1 , 2 ]. Probiotic microbes, part of the gut microbiota, are strongly associated with health benefits such as disease prevention and comorbidity. On the other hand, a dysregulated gut microbiota (dysbiosis) has a lower number of beneficial bacteria (decreased diversity) and a higher number of pathogenic bacteria, such as enterobacteria (gamma-proteobacteria) [ 3 , 4 ]. Among the most important beneficial microorganisms as protective factors in the human gut microbiota are high levels of colony forming units (CFU) of bacteria belonging to the genus Lactobacillus , Bifidobacterium and Streptococcus , among others [ 3 ]. Thus, it is becoming increasingly common to use probiotic formulations (non-pathogenic live microorganisms) containing these microorganisms or those with similar effects, either in the prevention or as an adjuvant in the treatment of diseases [ 5 ]. Dysbiosis per se or exacerbation of pathological conditions may promote increases in inflammatory markers [such as C-reactive protein (CRP), interleukin (IL)-6, and tumor necrosis factor (TNF)-α] and reactive oxygen/nitrogen species (ROS/RNS) [ 2 , 6 , 7 ]. Chronic increases in ROS [superoxide (O 2 •− ), hydrogen peroxide (H 2 O 2 ), hydroxyl radical (HO • ), hypochlorous acid (HOCl)] and RNS [nitric oxide (NO) and peroxynitrite (ONOO − ), among others] can lead to oxidative & nitrosative stress (O&NS), conditions in which such oxidants exceed the body's detoxification capacity despite a reduction in antioxidant defenses [e.g., superoxide dismutase (SOD), catalase (cat), glutathione peroxidase (GPx), and glutathione (GSH)]. In addition, associated biomolecule damage (lipid, protein, and DNA damage) can occur if O&NS is not controlled [ 7 , 8 , 9 , 10 ]. Currently, gut microbiota dysbiosis has been implicated in chronic non-communicable diseases (NCDs). For example, these include neurodegenerative and autoimmune diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD) [ 11 , 12 , 13 , 14 ] and multiple sclerosis (MS) [ 7 ]; in addition to some symptoms of autism spectrum disorder (ASD) and other psychiatric conditions such as anxiety, depression, and bipolar disorder (BD) [ 6 , 15 , 16 ]. Dysbiosis has also been implicated in other systemic diseases, including non-alcoholic fatty liver disease (NAFLD) [ 2 ], coronary heart disease (CHD) and chronic heart failure (CHF) [ 1 , 17 ], rheumatoid arthritis [ 18 , 19 ], and diabetes mellitus and gestational diabetes mellitus (DM and GDM) [ 20 – 23 ]. Studies show that dysbiosis in these NCDs are also coupled with inflammation and O&NS [ 24 ], in which a favorable prognosis may be achieved with the use of probiotics, although species and amount (which reflects potency) are still unclear [ 5 ]. In this sense, various randomized controlled trials (RCTs) and systematic review and meta-analysis (SR&MA) of RCTs have explored whether such use can favor adequate immunomodulation, decreasing/preventing O&NS and other damage coupled with the inflammatory process (↓ serum level of cytokines IL-6 and TNF-α, and hsCRP) and attenuating damage associated with pathogenic enterobacteria [ 25 – 30 ]. Moreover, studies have pointed out the antioxidant and anti-inflammatory properties of probiotics [ 5 ]. In that way, we conducted this SR&MA of RCTs to elucidate the effects of probiotics (oral bacteriotherapy) in attenuating O&NS and oxidative biomolecule damage, as well as the inflammatory process in NCDs, avoiding that the nutritional and clinical indication of probiotics be mainly based on trial and error. Methods Register This SR&MA of RCTs is part of a study aimed at clarifying and updating the knowledge on the influence of probiotics on inflammatory processes and oxidative stress associated with some chronic diseases, previously registered in PROSPERO, registration number: CRD42023440106 [ 31 ]. Condition being studied, review question, and study design The PICOS framework was developed as follows (Table 1 ): Table 1 PICOS tool/framework used to develop review question(s) and then bias-free and comprehensive literature search strategies as well inclusions of studies Description: P ( P opulation) Patients (no age or biological sex restrictions) with non-communicable diseases that have an inflammatory process and oxidative stress. I ( I ntervention) Probiotics and/or probiotic supplementation containing a mix of CFU of microorganisms [multispecies probiotic supplement: Lactobacillus spp. and/or Bifidobacterium spp.; and or Streptococcus spp., among others (also other microorganisms)], at any dose, frequency, and duration. C ( C omparison) Only placebo. O ( O utcome) Primary/main a : Markers of oxidative stress (O&NS ) and or nitrosative stress (NS) measured through antioxidant defense [superoxide dismutase (SOD), catalase (cat), glutathione peroxidase (GPx), GSH levels or the ratio of reduced to oxidized GSH (GSH:GSSG ratio); or total antioxidant capacity – TAC; oxidants levels [superoxide (O 2 •− ), hydrogen peroxide (H 2 O 2 ), hydroxyl radical (HO • ), hypochlorous acid (HOCl)] or nitric oxide (NO) or peroxynitrite anion (ONOO − ); and or oxidative biomolecule damage (lipid peroxidation/Malondialdehyde - MDA levels (TBARS), protein oxidation – protein carbonyl (PCO), or oxidative DNA damage − 8OHdG); 3-NT, 8-iso-prostaglandin, among others here not specified, but representing a marker or other metabolic/biochemical profile of O&NS. Secondary : markers of inflammation [high sensitivity C-reactive protein (hsCRP), TNF-α or IL-6 levels]. S ( S tudy type) Randomized placebo-controlled trials (RCTs). a Cooke et al. (2003); Jomova et al. (2023) Based on the PICOS: "In patients with inflammatory processes in NCDs, how does probiotic consumption compare to placebo in the effect of decreasing O&NS and damage and/or inflammation? Eligibility criteria, search strategy and study selection Eligibility criteria were as follows: only randomized controlled trials (RCTs) with a well-defined treatment protocol (i.e. type of probiotic, doses and duration); appropriate control group (placebo); viable outcome data (Table 1 ); adequate data: results reported as mean difference (MD) or standardized mean difference (SMD) and associated SD/SE. Only studies that clearly addressed NCDs and had patients diagnosed according to clear criteria were included in this review. Studies were included if at least three studies reported the same at least one of the primary outcomes (O&NS markers) shown in Table 1 . Exclusion criteria: studies not demonstrating the clinical outcomes of interest (Table 1 ) or relevance to the topic; missing protocols; full text not available; non-viable primary and secondary endpoint data. The study was a non-RCT: for example, review, meta-analysis, or any clinical trial without a control group), or the study was conducted in animals or in vitro . In addition, exclusion criteria were as follows: no NCDs (healthy, pregnant, and overweight). In addition, infectious diseases and inflammatory bowel diseases (irritable bowel syndrome, Crohn's disease) were not included in this study to avoid niche bias of the gut microbiota. We did not include studies of patients undergoing treatment for chronic conditions (e.g., hemodialysis) where the underlying cause may be microbial; the association of complex conditions (more than two) with an unknown or undiagnosed underlying cause; or conditions such as overweight or obesity. We did not include studies in which the authors administered probiotics in combination with another nutraceutical (prebiotics, postbiotics, milk, among others) and/or those in which the intervention was not only an association of microorganisms or those in which the composition left doubts. Studies in which the control group included the association of placebos with probiotics or other agents/drugs [active controls, including inulin, fructooligosaccharide, etc.] as well as prebiotics, symbiotics, etc.] were not accepted. The following online resources were searched electronically, and there were no time (date of publication) or language restrictions ( Supplementary appendix, Table S1 ) for RCTs: PubMed, Scopus, and EMBASE. We also searched the reference lists of studies obtained from PubMed, Scopus, and EMBASE. Finally, we contacted recognized experts in the field. After removing the duplicates, two authors (N.S.S. and C.D.C.) independently read the titles and abstracts and, among the selected references, read them in full. Articles selected after reading the titles and abstracts were analyzed for full text and included whether they met the eligibility criteria. Two authors (N.S.S. and C.D.C.) who assessed the eligibility of the studies; and they settled disagreements by discussion at the end of the process, if necessary, with either TMR or MRR. The agreement between the authors in the selection phase was also analyzed by the kappa coefficient (adequate when > 80%, here 92%), using BioEstat (Version 5.0, Brazil, 2007). Data extraction and collection Two authors (N.S.S. and C.D.C.) extracted the data into an Excel spreadsheet (Microsoft Corp, Redmond, Washington, USA). Data were independently coded using a standardized table that collected the following variables: (i.) study characteristics: author, year of publication, type of study (RCTs); (ii.) participant characteristics: total number of participants (biological sex, M/F; age) and disease type; and criteria used to define the specific NCD evaluated; (iii.) intervention details: dose, frequency, and duration of probiotic intervention; number of participants receiving probiotics; (iv) Comparator details: placebo; drug, dose, frequency, and duration of other drug; number of participants receiving placebo or other drug. (v.) Outcome details: general data (MD, SE, etc.) and significance of primary (O&NS markers) and secondary (inflammatory markers) outcome measures. The collected data were then initially processed in Excel. Quality of studies included: risk of bias assessment The revised Cochrane Risk-of-Bias (RoB 2) tool for RCTs (Intention-to-Treat/Trials) was independently performed by two reviewers (N.S.S. and C.D.C.) to assess the methodological quality of the included trials [ 32 – 34 ]; addressing at least five domains of bias: (1.) arising from the randomization process; (2.) due to deviations from intended intervention; (3.) due to missing outcome data; (4.) in measurement of the outcome; and (5.) in selection of the reported result. Robvis plot was used (available at: https://mcguinlu.shinyapps.io/robvis ). A trial was considered to have an overall low risk of bias if it had a low risk in all four quality criteria proposed by Marušić et al. [ 35 ] (random sequence generation, allocation concealment, blinding of outcome assessors, and completeness of outcome data; or equivalent in five domains); a high risk of bias if any domain was considered high risk, or if more than one of the four quality criteria had some concerns [ 34 ]. There was no need to request information from the study authors, as data affecting the RoB2 assessment were accessible, and there were no relevant missing data to request. Data synthesis: outcome measures of effects and statistical analysis The data were pooled and, depending on the heterogeneity of the studies, two effects models were considered as follows: (i.) random-effects model, when there is increased heterogeneity (criteria presented below), in this case is plausible two sources contributing with the variance (from within each study and those among studies); and (ii.) fixed-effect model, when there is decreased heterogeneity (criteria presented below), variance only from within each study. The effects of probiotic/intervention on markers of O&NS and inflammation/outcomes, compared with placebo (comparison group), were analyzed as follows: in the data synthesis (meta-analysis), the compiled data from at least four studies were primarily analyzed in separate (for each variable) pooled effect sizes, presented in Forest plot(s) (effect estimates) as background. The analyses were performed and Forest plots generated using Meta-essentials [ 36 ]. The primary outcome was the effect of probiotics on O&NS markers (GSH, TAC, MDA, NO, and 8-OHdG). The secondary outcome: markers of inflammation (hsCRP, IL-6, and TNF-α). To measure the magnitude of effect (absolute value of effect) in patients on probiotic treatment, first, whether positive (+) or negative (-), the interpretation of the magnitude of effect previously calculated is the same when absolute value was used. Then, we considered the direction of the effect of probiotic intervention by appropriate interpretation of the included results; i.e., (+) value: it favors intervention or the positive effect of probiotic treatment toward decreased (↓) hsCRP, IL-6, TNF-α (inflammatory marker), MDA or 8-OHdG levels or increased (↑) GSH levels or TAC (markers of O&NS ); (-) value: it favors placebo with increased (↑) hsCRP, IL-6, TNF-α, MDA or 8-OHdG levels or decreased (↓) GSH levels or TAC. To normalize the data for summarizing statistics of continuous data with different measurements or units [ 37 ], mean differences (MD: probiotic vs . placebo groups) from individual studies were converted to a common measure (SMD) using Cohen's d or the modified methods of Cohen's d, Glass' delta or Hedges' g. In this situation, these effect sizes (SMDs) for each individual study (k) were calculated using an online effect size calculator available at: https://www.socscistatistics.com/effectsize/default3.aspx . The associated standard error (SE) for unadjusted comparisons was obtained using a formula from Hedges [38]. The forest plot was interpreted as follows: values (+) that favor probiotic intervention is found at the right corner of the forest plot; values (-) that favor placebo is found at the left side of the forest plot. Data are expressed as SMD plus SE, with 95% confidence interval (CI). Further analyses of pooled data (Z statistic and one-tailed/two-tailed p -values) were considered statistically significant when p < 0.05. Heterogeneity and subgroup analysis The statistical heterogeneity of effect size among trials (inter-study heterogeneity) can be estimated using Cochrane's Q, which indicates whether or not heterogeneity is present (X 2 p < 0.10, a low p -value or a large chi-squared statistic provides evidence of significant heterogeneity), however, when only a few studies are included and their sample sizes are different, Cochrane's Q is not recommended; in this way, it is recommended to make an interpretation based only on the magnitude of heterogeneity, which is quantified by I 2 , being I 2 ≤ 40% and p -value ≥ 0.1 considered as low heterogeneity or no clinically important heterogeneity (fixed-effect model); or heterogeneity was set as moderate (40% 70%) (random-effects model) [ 28 , 39 ]. Subgroup analysis was used as indicated when I 2 is large, with a threshold of 50% for substantial heterogeneity indicating the need for subgroup analysis in meta-analysis with I 2 > 50% [ 34 ]. Conversely, if I 2 is low, then there is nothing to be explored in a subgroup analysis. If I 2 is low (fixed-effect model), at least one of the subgroups can be considered a homogeneous population (in which the estimate of the "true" effect size is the same), whereas the entire set of studies cannot be considered studies of a (homogeneous) population. Publication bias analysis Because the meta-analysis included more than 10 studies, publication bias was assessed by the asymmetry of the funnel plot, using Egger's test as the statistical method ( p -value < 0.05) in Meta-Essentials [ 28 , 36 ]. Grading the quality of evidence Regarding the level of evidence for each outcome, the Grade of Recommendations Assessment, Development, and Evaluation (GRADE) approach was adopted to assess the overall quality and certainty of evidence according to the GRADEprofiler software (Version 3.6, Grade Working Group, 2004/2007) with some modification [ 40 , 41 ]. Each outcome measure was graded as high, moderate, low, or very low certainty of evidence, and interpretations were made according to Ryan and Hill [ 41 ] as follows: (i) Risk of bias: Most information is from studies at low risk of bias (do not downgrade), Most information is from studies at low or unclear risk of bias (do not downgrade or downgrade one level), the proportion of information from studies at high risk of bias (downgrade two levels); (ii) Heterogeneity (inconsistency) was evaluated as: low heterogeneity ( I 2 ≤ 40%), moderate (40% 70%); (iii) Indirectness: indirect population intervention, comparator, outcome, or indirect comparison; (iv) Imprecision: number of patients (participants is less than 400, downgrade 1) and CIs (if the upper or lower confidence limit crosses the effect size (eg. SMD) of 0.5, downgrade 1); and (v) publication bias: undetected (do not downgrade) and strongly suspected (downgrade one level). Quality of RS&MA The AMSTAR 2 tool [ 42 ] was used to assess the methodological quality of the present RS&MA. The result was reported as a score from the checklist available at: https://amstar.ca/Amstar_Checklist.php . Report The reporting of this SR&MA of RCTs followed the methodological expectations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist (PRISMA flow diagram updated) [ 43 ], and based on the recommendations of the Cochrane Handbook [ 32 , 33 ]. Results Search and selection of studies: included studies in the meta-analysis Initially, after removing duplicates, the search strategy retrieved 782 records. After inclusion of studies from the reference lists of the primary records, fifteen studies [ 1 , 2 , 7 , 11 – 13 , 15 , 16 , 19 , 20 , 22 , 23 , 44 – 46 ] (one out the 15 studies reported two trials) were eligible (Fig. 1 ) and included in the quantitative synthesis (meta-analysis), evaluating 837 participants (Table 2 ). The PRISMA flow diagram showing the included studies and criteria is presented below (Fig. 1 ), highlighting the steps of the study selection process from “identification” to “inclusion” of RCTs in the meta-analysis. Table 2 Characteristics of included studies reporting randomized controlled trials (RCTs) aimed at assessing the effects of probiotics on oxidative/nitrosative stress (O&NS) and inflammation General study characteristics Characteristics of RCT Trial Year Place Non-communicable disease Disease, comorbid and complications Design Total sample size a (age interval-yr/mean age. and biological sex) Probiotic intervention b Conclusions/ main findings (Probiotic v s. Placebo) Endocrine & metabolic diseases Chong et al. 2021 UK Non-alcoholic fatty liver disease (NAFLD) Disease associated to metabolic syndrome (obesity and T2DM) with inflammation and O&NS complications leading to liver injury Randomized, placebo-controlled, proof-of-concept trial n = 35 (25–70/ Placebo: 58 Probiotic: 57; M and F) VSL#3: Streptococcus thermophilus, Bifidobacterium breve, B. longum, B. infantis, Lactobacillus acidophilus, L. plantarum, L. paracasei , and L. bulgaricus ; 2 sachets/twice daily/10 wk. Trial does not support the hypothesis that probiotics improve markers of O&NS (GSH and TAC) and inflammation (hsCRP). Hajifaraji et al. 2018 Iran Gestational diabetes mellitus (GDM) Hyperglycemia can lead to inflammation and O&NS Randomized, double blinded, placebo-controlled clinical trial n = 56 (18–45 Placebo: 26.5 Probiotic: 28.1; F) L. acidophilus LA- 5, Bifidobacterium BB-12, S. thermophilus STY-31 and L. delbrueckii bulgaricus LBY-2; 1 ×/day, for 8 wk. Probiotic supplements improved some O&NS (↑ GSH and ↓ MDA) and inflammation (hsCRP) markers. Soleimani et al. 2017 Iran Diabetic patients (on hemodialysis) DM + comorbid (renal failure) can aggravate inflammation and O&NS Randomized, double-blind, placebo-controlled clinical trial n = 60 (18–80 Placebo: 59.4 Probiotic: 54.0; M and F) L. acidophilus, L. casei , and B. bifidum; daily, for 12 wk. Probiotic supplementations had beneficial effects on O&NS (prevented ↑ in MDA levels) and inflammation Asemi et al. 2013 Iran Type 2 DM Chronic hyperglycemia can lead to inflammation and O&NS /NS Randomized, placebo-controlled clinical trial n = 54 (NI/ Placebo: 52.59 Probiotic: 50.51; M and F) L. acidophilus , L. casei , L. rhamnosus , L. bulgaricus , B. breve , B. longum , and S. thermophilus , for 8 wk. Probiotic promoted ↑ GSH and ↓ hCRP levels. Mafi et al. 2018 Iran Diabetic Nephropathy Uncontrolled hyperglycemia can lead to inflammation and O&NS exacerbated by comorbid Randomized, placebo-controlled clinical trial n = 60 (Placebo: 60.9 Probiotic: 58.9;M and F) L. acidophilus strain ZT-L1, B. bifidum strain ZT-B1, L. reuteri strain ZT-Lre, and L. fermentum strain ZT-L3, Probiotic supplementation ↑ GSH and ↓ MDA levels. Mohseni et al. 2018 Iran Type 2 DM/foot ulcer O&NS and inflammation take part in the complications from DM. Randomized double-blind placebo-controlled clinical trial n = 60 (40–85/ Placebo: 58.5 Probiotic: 62.6; M and F) L. acidophilus , L. casei , L. Fermentum , and B. bifidum , for 12 wk. Probiotic supplementation resulted in significant ↓ hsCRP and MDA levels and ↑ NO levels and TAC. Raygan et al. 2018 Iran Type 2 DM and coronary heart disease (CHD) Hyperglycemia can predispose patients to have CHD and aggravates inflammation/O&NS Randomized, double-blind, placebo-controlled trial n = 60 (40–85/ Placebo: 61.8 Probiotic: 60.7; M and F) B. bifidum , L. casei , L. acidophilus; 1 ×/day for 12 wk. Probiotic intervention improved antioxidant defense (↑ GSH and TAC) and ↓ hsCRP levels. Diseases of the Nervous system (NS)/neurodegenerative diseases (NDs)/psychiatric disorders Tamtaji et al. 2019 Iran Parkinson's disease (PD) O&NS from mitochondrial dysfunction and from phagocytes in inflammation process can exacerbate neuronal degeneration of PD Randomized, double-blind, placebo-controlled trial n = 60 (50–59/ Placebo: 67.7 Probiotic: 68.2; NI) L. acidophilus, B. bifidum, L. reuteri , and L. fermentum , for 12 wk. Probiotic supplementation ↓ hsCRP and MDA levels, and ↑ GSH levels. Agahi et al. 2018 Iran Alzheimer’s disease (AD) ROS and RNS released during inflammation also take part in the pathogenesis of AD Randomized, placebo-controlled clinical trial n = 48 (65–90/ Placebo: 80.57 Probiotic: 79.70; M and F) L.fermentum , L.plantarum , B.lactis , L.acidophilus , B.bifidum , B.longum , for 12 wk O&NS markers (NO, GSH, TAC, MDA, and 8-OHdG) were negligible to the probiotic supplementation. Akhgarjand et al. 2024 Iran Alzheimer’s disease (AD) Besides amyloid plaques and TAU dysfunctions in the genesis of AD, O&NS and inflammation are speculated as adjuvant and triggers of neurodegeneration. Randomized, double-blind, placebo-controlled trial n = 90 c (50–90/ Placebo: 67.77 L. rhamnosus : 67.93 B. longum : 67.90; M and F) 12-week supplementation with: L. rhamnosus HA-114 Two trials: Probiotic supplementation (2 different probiotic groups) ↑ GSH levels and ↓ MDA and 8OHdG levels. 12-week supplementation with: B. longum R0175 Asghari et al. 2023 Iran Multiple Sclerosis (MS) Chronic demyelination with possible inflammation and O&NS Randomized, double blinded, placebo-controlled clinical trial n = 40 (18–55/ Placebo: 34.95 Probiotic: 33.8; M and F) Saccharomyces boulardii daily for 4 months. (16 wk.) Probiotic intervention increased TAC (↑ antioxidant defense). Sabouri et al. 2022 Iran Bipolar Disorder (BD) Dysbiosis with ↑ inflammation and O&NS links BD impairments because interconnections —the gut-brain axis. Randomized, double-blind, placebo-controlled trial n = 38 (18–65/ Placebo: 35 Probiotic: 38.89; M and F) B. bifidum , B. lactis , B. langum , and L. acidophilus , for 8 wk. Probiotic supplementation did not improve O&NS markers (MDA levels) Akkasheh et al. 2016 Iran Major depressive disorder (MDD) Evidences that O&NS have a role in the pathogenesis of MDD, as possible cause or consequence. Randomized, double-blind, placebo-controlled trial n = 40 (20–55/ Placebo: 36.2 Probiotic: 38.3; M and F) L.acidophilu, L.casei ,and B.bifidum for 8 wk. Probiotic supplementation ↑ GSH and ↓ hsCRP levels. Other diseases Vaghef-Mehrabany et al. 2016 Iran Rheumatoid arthritis (RA) RA is an autoimmune inflammatory disease in which O&NS can play a role in its physiopathology Randomized, placebo-controlled clinical trial n = 46 (20–80/ Placebo: 44.29 Probiotic: 41.14; F) L. casei 01, for 8 wk. There was no significant difference between probiotic vs . placebo for markers of O&NS . Karamali et al 2018 Iran Polycystic ovary syndrome (POC) Inflammation and O&NS are players in POC pathogenesis Randomized, double-blind, placebo-controlled trial n = 60 (18–40/ Placebo: 27.7 Probiotic: 27.2; F) L. acidophilus , L. casei , and B. bifidum , for 12 wk. Probiotic intervention ↑ TAC and ↓ MDA hsCRP levels. Total of participants into both groups (probiotic and placebo) from all RCTs 837 Caption : GSH - glutathione, TAC - total antioxidant capacity, NO - nitric oxide, MDA - malondialdehyde, 8-OHdG − 8-hydroxy-2′-deoxyguanosine, hsCRP - high sensitivity C-reactive protein, IL-6 - interleukin-6, TNF-α – tumor necrosis factor-α. a : Total of participants randomized into control (placebo) and treatment (probiotic intervention) groups (concluded the study). b : in most of the included studies, probiotics were administered in capsules, containing the probiotics plus adjuvant (lactose or dextrose anhydrous/filler, magnesium acetate or stearate/lubricant, oil; all of them with no interferences on outcomes). Placebo (non-containing probiotic) treatments were administered with equal conditions (formula and period of administration). c Two probiotic groups: 30 patients into each group; plus 30 patients into placebo group. ↑: increase/high ↓: decrease/low. NI: Not informed. Study characteristics The characteristics of the studies included in this SR&MA are shown in Table 2 . Non-communicable diseases varied among studies, with DM (or DM types or plus comorbid) being the most common. The most common country was Iran, and the publication period (from 2013 to 2023) spanned the last decade, demonstrating a current trend to explore this topic. Probiotic supplementation protocols were similar in terms of frequency of administration (daily) and time of intervention (wk, between 8 and 16, the most common being 12 wk - as seen in 9 studies), but varied considerably in terms of number of microorganisms (from 1 to 8 strains) and CFU, and when (two or more strains) combined to yield different supplements (Table 3 ). Table 3 Impact of probiotic intervention on primary and secondary outcomes in the included randomized placebo-controlled trials (RCTs), highlighting details of microbial load versus effect size for each individual study RCTs Amount (potency) of probiotic (Intervention) Study effect size ( k ) for impact of probiotic intervention on primary and secondary endpoints (↑ or ↓ markers) compared to placebo group. Primary outcomes: O&NS Secondary outcomes: inflammation Number of microorganisms Dosage of CFU and duration of intervention Total CFU (wks a ) GSH levels TAC NO MDA levels 8-OHdG hsCRP levels IL-6 TNF-α Desirable (positive) outcome on marker levels ↑ ↑ ↑↓ b ↓ ↓ ↓ ↓ ↓ Chong et al. 8: Streptococcus thermophilus, Bifidobacterium breve, B. longum, B. infantis, Lactobacillus acidophilus, L. plantarum, L. paracasei , and L. bulgaricus 2 sachets twice a day for 10 wk. At least 112.5 × 10 9 CFU/sachet. 1.6 ×10 13 0.44 (↑) 0.43 (↑) ---- ---- ---- -0.25 (↑) ---- ---- Hajifaraji et al. 4: L. acidophilus LA- 5, Bifidobacterium BB-12, S. thermophilus STY-31, and L. delbrueckii bulgaricus LBY-2 Once daily > 4 × 10 9 CFU each for 8 wk. 8.9 ×10 11 2.92 (↑) 1.8 (↑) ---- 3.75 (↓) ---- 3.35 (↓) 0.97 (↓) 2.9 (↓) Soleimani et al. 3: L. acidophilus, L. casei , and B. bifidum Once daily 2 × 10 9 CFU each (totally 6 10 9 CFU per capsule) for 12 wk. 5 ×10 11 -0.07 (↓) -0.28 (↓) -0.23 (↑↓) 0.97 (↓) ---- 0.28 (↓) ---- ---- Asemi et al. 7: L. acidophilus , L. casei , L. rhamnosus , L. bulgaricus , B. breve , B. longum , and S. thermophilus Once day, for 8 wk: 2 × 10 9 CFU, 7 × 10 9 CFU, 1.5 × 10 9 CFU, 2 × 10 8 CFU, 2 × 10 10 CFU, 7 × 10 9 CFU, 1.5 × 10 9 CFU, respectively 1.3 ×10 12 6.5 (↑) 1.44 (↑) ---- ---- ---- 1.81 (↓) ---- ---- Mafi et al. 4: L. acidophilus strain ZT-L1, B. bifidum strain ZT-B1, L. reuteri strain ZT-Lre, and L. fermentum strain ZT-L3 Each 2 × 10 9 CFU (totally 8 10 9 CFU per capsule), for 12 wk. 6.7 ×10 11 0.1 (↑) -0.14 (↓) -0.43 (↑↓) 1.1 (↓) ---- 0.87 (↓) ---- ---- Mohseni et al. 4: L. acidophilus , L. casei , L. Fermentum , and B. bifidum 2 × 10 9 CFU/g each, for 12 wk. 6.7 ×10 11 0.32 (↑) 0.88 (↑) 0.86 (↑↓) 0.49 (↓) ---- 0.13 (↓) ---- ---- Raygan et al. 3: B. bifidum , L. casei , L. acidophilus 2×10 9 CFU each, once daily, for 12 wk. 5 ×10 11 0.87 (↑) 0.64 (↑) 0.29 (↑↓) -0.09 (↑) ---- 0.23 (↓) ---- ---- Tamtaji et al. 4: L. acidophilus, B. bifidum, L.reuteri , and L. fermentum 12-week supplementation with 2×10 9 CFU once daily, each bacterial (8×10 9 CFU, total) 6.7 ×10 11 -0.21 (↓) 0.12 (↑) ---- 0 ---- 0.41 (↓) ---- ---- Agahi et al. 2 capsules containing each 3 bacteria: L.fermentum , L.plantarum , and B.lactis ; or L.acidophilus , B.bifidum , B.longum A total dosage of 3 × 10 9 (10 9 each strain) CFU/day, for 12 wk. 2.5 ×10 11 0.81 (↑) 2.1 (↑) -3.75 (↑↓) 1.65 (↓) -0.18 (↑) 1.03 (↓) -0.83 (↑) 0.67 (↓) Akhgarjand et al. 1: Lacticaseibacillus rhamnosus HA-114 Once daily 7.5 × 10 9 , for 12 wk. 6.3 ×10 11 -0.18 (↓) ---- ---- 1.65 (↓) 1.2 (↓) ---- 1.58 (↓) 0.76 (↓) Akhgarjand et al. 1: Bifidobacterium longum R0175 Once daily 7.5 × 10 9 , for 12 wk. 6.3 ×10 11 -0.22 (↓) ---- ---- 2 (↓) 1.23 (↓) ---- 1.65 (↓) 0.76 (↓) Asghari et al. 1: Saccharomyces boulardii Once daily 250 mg (10 10 CFU)/4 months (16 wk) 1.1 ×10 12 ---- 1.8 (↑) ---- 0.34 (↓) ---- 1.03 (↓) ---- ---- Sabouri et al. 4: B. bifidum , B. lactis , B. langum , and L. acidophilus , 1.8 × 10 9 CFU of each bacterial strain, once daily for 8 wk. 4 ×10 11 ---- ---- ---- -0.27 (↑) ---- ---- -0.03 (↑) 0.2 (↓) Akkasheh et al. 3: L.acidophilus , L.casei , and B.bifidum 6 × 10 9 CFU/day (2 × 10 9 each strain), for 8 wk. 3.4 ×10 11 ---- 0.2 (↑) ---- ---- ---- ---- ---- ---- Vaghef-Mehrabany et al. 1: L. casei 01 10 8 CFU/day, for 8 wk. 5.6 ×10 9 ---- 0.4 (↑) ---- 0.34 (↓) ---- ---- ---- ---- Karamali et al 3: L. acidophilus , L. casei , and B. bifidum 2 × 10 9 CFU/g each, 12 wk. 5 ×10 11 0.95 (↑) 0.4 (↑) 0.4 (↑↓) 1.47 (↓) ---- -0.48 (↑) ---- ---- Total of participants into both groups (probiotic and placebo) from all RCTs by outcome 673 679 348 (↑↓) 708 168 545 262 262 Caption : CFU: colony-forming units. GSH - glutathione, TAC - total antioxidant capacity, NO - nitric oxide, MDA - malondialdehyde, 8-OHdG − 8-hydroxy-2′-deoxyguanosine, hsCRP - high sensitivity C-reactive protein, IL-6 - interleukin-6, TNF-α – tumor necrosis factor-α. Comparisons probiotic vs . placebo: + values of k (desirable), effect favors probiotic; - values of k, favors placebo. ↑: increased levels ↓: decreased levels. a Without considering possible differences among potencies of different microorganisms, just considering the total CFU amount from all microorganisms administered during whole period of study. b This interpretation is factually contextual. Quality assessment: risk of bias The risk of bias is shown in Fig. 2 . All studies were based on the intention-to-treat principle. In general, for the five domains considered, most studies had a complete overall low risk of bias, although two of these studies had some concerns. Among some concerns and high risk of bias, those related to randomization and related intervention were the most common, in which some studies did not report in the paper an adequate method of concealment of allocation and investigators. Thus, some studies are actually randomized single-blind (or non-blind) placebo-controlled trials (Table 2 ). Other areas of concern include the conditions of the probiotic intervention and the appropriate analysis used to estimate the effect of assigning participants to it. Forest plots of effect sizes: the effects of probiotic intervention on markers of O&NS and inflammation Figures from 3 to 5 show the individual Forest plots for each outcome measure. Effect sizes for probiotic intervention on O&NS markers (GSH, NO levels, and TAC) and O&NS-related biomolecule damage (MDA and 8-OHdG levels) and markers of inflammation (hsCRP, IL-6, and TNF-α levels) were considered. Study weights (blue circle size) in forest plots were similar for all outcomes. Overall effect (pooled result, green) in Forest plots for almost all outcomes (except NO) show the positive effects of probiotic intervention (positive values on the right side of each Forest plot), with p -values and IC lower and upper bounds showing that increases in GSH levels and TAC and decreases in MDA and hsCRP levels favor probiotic intervention. There was high heterogeneity ( I 2 > 75%) for all outcome measures evaluated. Table 4 summarizes the Forest plots and shows significant positive effects (effect size) of probiotic intervention ( vs . placebo). Table 5 shows that the exclusion of studies with a high risk of bias did not have a significant effect on the parameters (outcomes) evaluated here. There was no significant number of included studies (> 3) reporting other O&NS markers (e.g.., SOD, Cat, GPx, etc.; or biomolecule damage markers: protein oxidation among others). Table 4 Key findings from the meta-analysis based on Forest plots interpretations highlighting the impact of probiotic intervention on markers of oxidative/nitrosative stress and inflammation Measures and Interpretations Outcomes/endpoints Oxidative stress markers Inflammation markers Antioxidant defense RNS Biomolecule damage (reflects oxidants attack) Specific Total Precursor of potent RNS Lipid Peroxidation Oxidative DNA damage General acute phase General acute phase/Immune mediators GSH TAC NO MDA 8-OHdG hsCRP IL-6 TNF-α Impact of probiotic intervention a Positive: ↑ levels Positive: ↑ capacity ----:↓ levels Positive: ↓ levels Positive: ↓ levels Positive: ↓ levels Positive: ↓ levels Positive: ↓ levels Pooled effect size (SE) 0.89 (0.51) 0.75 (0.22) − 0.47 (0.68) 1.03 (0.31) 0.75 (0.46) 0.74 (0.36) 0.67 (0.48) 1.06 (0.47) Confidence Interval -0.23 to 2.1 0.28 to 1.23 -2.22 to 1.27 0.37 to 1.7 -1.24 to 2.75 -0.07 to 1.55 -0.66 to 2.01 -0.25 to 2.38 p -value b Significant Significant Not significant Significant Not significant Significant Not significant Significant Effect size interpretation c Large Medium ---- Large Medium Medium Medium Large % placebo group below mean probiotic group d 79–91% 59–78% ---- 79–91% 59–78% 59–78% 59–78% 79–91% Heterogeneity (I 2 ) ↑ ↑ ↑ ↑ ↑ ↑ ↑ ↑ Caption : GSH - glutathione, TAC - total antioxidant capacity, NO - nitric oxide, MDA - malondialdehyde, 8-OHdG − 8-hydroxy-2′-deoxyguanosine, hsCRP - high sensitivity C-reactive protein, IL-6 - interleukin-6, TNF-α – tumor necrosis factor-α, RNS – Reactive nitrogen species. ↑ high or increase; ↓ low or decrease. a based on overall (pooled) effect size (SMD). b p < 0.05: effects those are statistically significant. c Interpretation of relative size (Cohen’s d): 0 to 0.49 – small ( d 0–58%); 0.5 to 0.79 – medium ( d 59–78%); ≥0.8 – large ( d 0.8 to 1.39 = 79–91%; ≥1.4 = ≥ 92%) (Lakens, 2013). Table 5 Key findings of the meta-analysis based on Forest plots interpretations highlighting the impact of probiotic intervention on markers of oxidative/nitrosative stress and inflammation, excluding studies with high risk of bias Measures and Interpretations Outcomes/endpoints Oxidative stress markers Inflammation markers Antioxidant defense RNS Biomolecule damage (reflects oxidants attack) Specific Total Precursor of potent RNS Lipid Peroxidation Oxidative DNA damage General acute phase General acute phase/Immune mediators GSH TAC NO MDA 8-OHdG hsCRP IL-6 TNF-α Remaining studies 9 10 4 11 2 8 4 4 Impact of probiotic intervention a Positive: ↑ levels Positive: ↑ capacity ----: ↑ levels Positive: ↓ levels Positive: ↓ levels Positive: ↓ levels Positive: ↓ levels Positive: ↓ levels Pooled effect size (SE) 0.51 (0.32) 0.64 (0.22) 0.33 (0.22) 0.97 (0.36) 1.22 (0.02) 0.59 (0.43) 1.06 (0.38) 1.16 (0.60) Confidence Interval -0.24 to 1.26 0.15 to 1.13 -0.38 to 1.04 0.17 to 1.77 1.02 to 1.41 -0.42 to 1.60 -0.17 to 2.28 -0.74 to 3.06 p -value b Not significant Significant Not significant Significant Significant Not significant Significant Significant Effect size interpretation c Medium Medium Small Large Large Medium Large Large % placebo group below mean probiotic group d 59–78% 59–78% 0–58% 79–91% 79–91% 59–78% 79–91% 79–91% Heterogeneity (I 2 ) ↑ (88.40%) ↑ (83.10%) Moderate (65.06%) ↑ (94.78%) ↓ (0.00%) ↑ (95.01%) ↑ (85.42%) ↑ (94.71%) Caption : GSH - glutathione, TAC - total antioxidant capacity, NO - nitric oxide, MDA - malondialdehyde, 8-OHdG − 8-hydroxy-2′-deoxyguanosine, hsCRP - high sensitivity C-reactive protein, IL-6 - interleukin-6, TNF-α – tumor necrosis factor-α, RNS – Reactive nitrogen species. ↑ high or increase; ↓ low or decrease. a based on overall (pooled) effect size (SMD). b p < 0.05: effects those are statistically significant. c Interpretation of relative size (Cohen’s d): 0 to 0.49 – small ( d 0–58%); 0.5 to 0.79 – medium ( d 59–78%); ≥0.8 – large ( d 0.8 to 1.39 = 79–91%; ≥1.4 = ≥ 92%) (Lakens, 2013). Excluded studies with high risk of bias: Asemi et al., Mafi et al., Agahi et al. Subgroup analysis Since I 2 was large, we proceeded with subgroup analysis to investigate the source of variation: dosage of CFU/quantity of strains; age (mean years); and type of NCDs. As interpretation of the pooled effect size (and its intervals) is not recommended, only heterogeneity was considered in the subgroup analysis, as shown in Table 6 . Factors related to intervention (dose and number of strains) and population (age and NCDs) were adjusted for. Table 6 Subgroup analysis on variables of interest SUBGROUP NUMBER OF STUDIES Q I 2 T 2 GSH Total CFU < 5 ×10 11 CFU 1 ---- ---- ---- ≥ 5 ×10 11 and ≤ 10 12 CFU 9 69.86 0.89 0.59 ≥ 10 12 CFU 2 63.98 0.98 ---- Number of strains 1 2 0.01 0.00 0.00 ≥ 2 ≤ 6 8 59.95 0.88 0..60 ≥ 7 2 63.98 0.98 4.25 Mean age (yr) 18–40 2 17.35 0.94 1.83 41–60 5 85.18 0.95 1.99 > 61 5 17.09 0.77 0.24 Disease group Endocrine & metabolic 7 123.18 0.95 1.91 NS/ND 4 9.32 0.68 0.16 Others 1 ---- ---- ---- TAC Total CFU < 5 ×10 11 CFU 3 25 0.92 1.05 ≥ 5 ×10 11 and ≤ 10 12 CFU 7 43.22 0.86 0.43 ≥ 10 12 CFU 3 9.64 0.79 0.35 Number of strains 1 2 10.32 0.90 0.89 ≥ 2 ≤ 6 9 74.08 0.89 0.61 ≥ 7 2 5.67 0.82 0.42 Mean age (yr) 18–40 4 26.92 0.89 0.66 41–60 6 29.25 0.83 0.38 > 61 3 27.66 0.93 0.94 Disease group Endocrine & metabolic 7 50.08 0.88 0.54 NS/ND 4 38.96 0.92 1.03 Others 2 0.00 0.00 0.00 MDA Total CFU < 5 ×10 11 CFU 3 22.03 0.91 0.9 ≥ 5 ×10 11 and ≤ 10 12 CFU 9 157.95 0.95 1.31 ≥ 10 12 CFU 1 ---- ---- ---- Number of strains 1 4 27.65 0.89 0.67 ≥ 2 ≤ 6 9 167.50 0.95 1.47 ≥ 7 ---- ---- ---- ---- Mean age (yr) 18–40 4 117 0.97 3.16 41–60 4 5.27 0.43 0.03 > 61 5 56.81 0.93 0.95 Disease group Endocrine & metabolic 5 124.63 0.97 2.11 NS/ND 6 60.33 0.92 0.89 Others 2 7.98 0.87 0.56 hsCRP Total CFU < 5 ×10 11 CFU 0 ---- ---- ---- ≥ 5 ×10 11 and ≤ 10 12 CFU 7 132.12 0.95 1.47 ≥ 10 12 CFU 3 23.58 0.92 0.99 Number of strains 1 ---- ---- ---- ---- ≥ 2 ≤ 6 7 132.12 0.95 1.47 ≥ 7 2 23.58 0.96 2.03 Mean age (yr) 18–40 3 105.99 0.98 4.09 41–60 5 33.08 0.88 0.55 > 61 2 0.23 0 0 Disease group Endocrine & metabolic 7 129.37 0.95 1.52 NS/ND 2 2.26 0.56 0.11 Others 1 ---- ---- ---- Caption : [↓ Heterogeneity (< 50% or < 75%)]. CFU - colony-forming units. GSH - glutathione, hsCRP - high sensitivity C-reactive protein, MDA - malondialdehyde, NDs - neurodegenerative diseases, NS - Nervous system, Others: Rheumatoid arthritis and polycystic ovary syndrome, TAC - total antioxidant capacity. Publication Bias The results of Egger's test (Table 7 ) showed no evidence of significant publication bias for TAC ( p = 0.722), MDA ( p = 0.201), hsCRP ( p = 0.659), IL-6 (0.220), and TNF-α (0.389). There was evidence of publication bias ( p < 0.05) for GSH, NO and 8-OHdG. Table 7 Publication bias analysis Marker Number of studies Adjusted I 2 (%) p -value (Egger’s test) Oxidative & nitrosative stress GSH 12 94.9 0.000 TAC 13 92.3 0.722 NO 6 97.2 0.003 MDA 13 93.9 0.201 8-OHdG 3 a 88.2 0.012 Inflammation hsCRP 10 94.3 0.659 IL-6 5 93.3 0.220 TNF-α 5 93.3 0.389 Grading of evidence The results of the GRADE analysis are presented in Table 8 , with key findings highlighted. Finally, complementing the evidence based on the pooled effect size (and its intervals), the GRADE profiles confirm the positive effects of the probiotic intervention ( vs . placebo) on markers of O&NS (GSH, TAC, and MDA) and inflammation (hsCRP). Qualities of evidence were: high () for the effectiveness of probiotic in decreasing MDA levels in patients with NCDs; and moderate () for the impact of probiotic in increasing GSH levels and TAC and decreasing hsCRP levels in patients with NCDs. Table 8 Grading the quality of evidence in this systematic review and meta-analysis for the effects of probiotic interventions on various markers of oxidative/nitrosative stress and inflammation P Patients with non-communicable diseases that have an inflammatory process and oxidative stress. I Probiotic (one strain) and/or probiotic supplementation containing a mix (more than one strain) of microorganisms. C Placebo. O Primary: GSH, TAC, NO, MDA, and 8-OHdG. Secondary: hsCRP, IL-6, and TNF-α S Randomized placebo-controlled trials STUDY DESIGN: STARTS AS HIGH QUALITY Outcome measure N. studies/N. Partic. Downgrading (levels, -1 or -2) Upgrading (levels + 1 or + 2) Key findings Risk of bias Inconsistency Indirectness Imprecision Publication bias Magnitude/effect Dose-response gradient Others a Quality of evidence GSH 12/ 673 No serious risk of bias Very Serious I 2 > 75% (-2) Not at all Not at all Strongly suspected (-1) Large effect size (+ 1) ---- No Plausible confounding (+ 1) The use of probiotics in patients with NCD probably increases GSH levels TAC 12/ 679 No serious risk of bias Very Serious I 2 > 75% (-2) Not at all Not at all Undetected ---- ---- No Plausible confounding (+ 1) The use of probiotics in patients with NCD probably increases TAC levels NO 6/ 348 Serious risk of bias (-1) Very Serious I 2 > 75% (-2) Not at all Very Serious (-2) Strongly suspected (-1) ---- ---- No Plausible confounding (+ 1) There was no evidence of the effect estimate. MDA 13/ 708 No serious risk of bias Very Serious I 2 > 75% (-2) Not at all Not at all Undetected Large effect size (+ 1) ---- No Plausible confounding (+ 1) The use of probiotics in patients with NCD does decrease MDA levels 8-OHdG 3/ 168 Serious risk of bias (-1) Very Serious I 2 > 75% (-2) Not at all Very Serious (-2) Strongly suspected (-1) ---- ---- No Plausible confounding (+ 1) There was no evidence of the effect estimate. hsCRP 10/ 545 No serious risk of bias Very Serious I 2 > 75% (-2) Not at all Not at all Undetected ---- ---- No Plausible confounding (+ 1) The use of probiotics in patients with NCD probably decreases hsCRP levels IL-6 5/ 262 No serious risk of bias Very Serious I 2 > 75% (-2) Not at all Very Serious (-2) Undetected ---- ---- No Plausible confounding (+ 1) There was no evidence of the effect estimate. TNF-α 5/ 262 No serious risk of bias Very Serious I 2 > 75% (-2) Not at all Serious (-1) Undetected Large effect size (+ 1) ---- No Plausible confounding (+ 1) There was no evidence of the effect estimate. Quality of this RS&MA According to the AMSTAR 2, this RS&MA is a High Quality Review. Discussion Based on the review question highlighting the effects of probiotic consumption in improving conditions (O&NS markers and inflammatory process) associated with NCDs, we conducted this SR&MA. Fifteen studies (16 trials) were included, generally with patients between 18–90 years of age and both biological sexes included, with few exceptions. First, the quality of the studies included in this SR&MA was assessed. A low risk of bias was observed in most of the studies. In most them, there was an ideal randomization process (1:1 ratio of treatment to placebo arms) using a computer-generated code with randomly permuted blocks of randomly varying size. In most trials, the investigators and participants were also blinded throughout the trial, supporting the term "double-blind". However, some trials did not report whether there were measures to conceal allocation (participants and investigators). Other domains of risk of bias were in most cases in line with good practice for conducting RCTs. In general, it is important to note that the inclusion of three trials with high risk of bias [ 11 , 20 , 44 ] in this RS&MA did not have a relevant impact on the effect sizes or other parameters reported here, justifying such inclusions, which ultimately did not affect the quality of the present work. Regarding the population, among the NCDs, endocrine & metabolic, with DM or DM plus comorbid, and one study with NAFLD were most commonly reported. Neurodegenerative diseases (PD and AD) were also frequently reported. The number of different NCDs may be reflected in different degrees of outcomes (O&NS and inflammation) and different need for formulations of probiotics. Although, for example, MS is a disease in which women are three times more likely to develop it, protocols among all trails provided that the mean age was matched, as well as biological sex when studies involved both sexes. In terms of intensity, the degree of O&NS and inflammation may vary according to the reported NCDs. For example, O&NS seems to be intense in different types of uncontrolled DM [ 47 ], while inflammation is a chronic complication that is relatively more pronounced in RA [ 19 , 48 ]. Current evidence suggests a relevant role for inflammation and O&NS in NAFLD and MS [ 2 , 7 ], as well as AD, PD and other psychiatric disorders [ 24 ]. Thus, in addition to probiotic formulation and dosage, disease severity and timing of administration have a profound impact on intervention outcomes. Regarding the markers employed here, (hs)CRP, IL-6 and TNF-α are commonly used as appropriate inflammatory markers [ 2 , 13 , 23 , 25 , 26 , 28 – 30 , 49 ]. The overall effect size showed a positive effect of probiotic intervention to reduce hsCRP levels, with evidence for its indication. In contrast, there was no evidence of probiotic effectiveness to decrease IL-6 and TNF-α levels. An optimum redox steady state (i.e. equilibrium of oxidants and antioxidants tone) is a physiological condition in healthy people. Oxidative/nitrosative stress represents a disruption in redox homeostasis when the generation of ROS/RNS exceeds the body's detoxification capacity, resulting in damage if not controlled by antioxidant defenses (i.e., measured by individual antioxidants from the human body, such as SOD, catalase, and GSH; or ultimately TAC) [ 8 , 10 ]. Total antioxidant capacity (TAC) represents the amount of oxidants scavenged in an appropriate assay, so it reflects the total antioxidant defense of the body. An established framework of O&NS leads to biomolecule damage, e.g. lipid peroxidation upon hydrogen peroxide (H 2 O 2 ) attack; this is tracked by plasma MDA levels as a by-product of such peroxidation, as it is a widely used marker of OS-mediated lipid damage [ 7 ]. Studies have pointed out that peroxidative tissue damage correlates with some NCDs severity, and also the significant impact of probiotics in preventing it [ 7 ]. In relation to nitrosative stress, this condition is caused only when a joint reaction of NO and O 2 •− occurs in the body (commonly when OS has already occurred), producing ONOO − [ 10 ]. This last RNS can nitrate biomolecules, including proteins, lipids, and DNA, for example, yielding 3-nitrotyrosine (3-NT) [ 10 ]. In this sense, interpretation of nitrosative stress in health and disease conditions is complex and contextual. In terms of O&NS, the probiotic intervention promoted an overall effect (pooled result) with positive effects, i.e. increasing GSH levels and TAC, and decreasing MDA levels, with proven evidence of its effectiveness. Of clinical relevance, the extraction and presentation of O&NS markers from separate Forest plots was ideal because, as observed, there was evidence for a proven positive effect of the probiotic only to increase GSH levels and TAC and decrease MDA levels (and not for NO and 8-OHdG levels), so it is not recommended to generalize all of the markers (they are different from each other) in a single forest plot as for "O&NS". Also, it is biologically plausible as an interpretation, whereas a high total antioxidant defense (TAC, non-specific) does not necessarily increase a specific antioxidant defense, but was attested by an apparent effectiveness of probiotic in decreasing the levels of MDA, a lipid peroxidation product that appears when there is inefficiency of the specific defense against hydrogen peroxide, i.e. increased levels of the antioxidant enzyme catalase that detoxifies this oxidant, preventing attack on lipids. For example, SOD (not evaluated, it acts on O 2 •− ) and GSH itself, associated with other type of antioxidant protection. This fact is confirmed, for example, by individual findings of Soleimani et al. [ 22 ] and Karamali et al. [ 46 ], who showed that probiotic interventions significantly increased plasma TAC compared to placebo, but did not affect plasma NO and GSH levels. The Forest plots show that individual research results may in some cases have "conflicting" or "ambiguous" results regarding effect size measures. Most studies have shown significant positive effects (in favor of probiotics). In contrast, some other studies have shown negative effects. In health sciences, since physicians and policy makers (public health measures, for a decision on implementing a specific intervention) is not only interested in whether there is only a positive effect of supplemental probiotics on healthy biomarkers, but mainly in how large such effect is, as subgroup analysis can specify interventions to particular subgroups (as discussed below). To explain the possible positive effect of probiotics according to the effect size analysis, heterogeneity highlights that the results among studies can be different and this inconsistency within a single meta-analysis can be quantified with a statistical test (e.g. I 2 ) to assess whether the variation among studies is due to real differences (true heterogeneity) and not to chance. In terms of heterogeneity, there was a high degree of heterogeneity for all outcomes analyzed, with differences among studies mainly due to design, population (individual biology: age, genetic specificity, health and disease states; among others; or sample size), and mainly different treatment protocols with probiotic [ 50 ]. For this purpose, the sample size of each trial was relatively small and there was considerable evidence of heterogeneity among trials. Frequency and duration of intervention were similar, but the number of microorganisms and CFUs varied considerably among trials. Due to the lack of evidence on an appropriate dosage of probiotics for patients with NCDs, different protocols were seen in the meta-analyzed trials. Other meta-analyses on this topic corroborate our findings [ 25 , 26 , 28 – 30 ], and the comparisons regarding the results for the outcome measures are summarized in Table 9 . As clinical and methodological heterogeneity is common in the biomedical sciences, statistical heterogeneity is inevitable, as usually observed in a meta-analysis [ 50 ]. Table 9 Summary of comparisons among systematic reviews and meta-analyses (SR&MAs) for the effects of probiotic interventions on markers of oxidative and nitrosative stress (O&NS) and inflammation SR&MA Disease model Markers of O&NS Markers of inflammation GSH TAC NO MDA 8-OHdG hsCRP IL-6 TNF-α Main findings for the impact of probiotic on markers Present NCD Evidence a to ↑ levels Evidence to ↑ No evidence Evidence to ↓ levels No evidence Evidence to ↓ levels No evidence No evidence Bohlouli et al. (2021) Diabetic nephropathy ↑ levels b ↑ No evidence ↓ levels ---- ↓ levels ---- ---- Dai et al. (2022) Diabetic kidney disease ↑ levels b ↑ ↑ levels ↓ levels ---- ↓ levels ---- ---- Deng et al. (2020) Alzheimer’s disease No evidence No evidence No evidence ↓ levels b ---- ↓ levels ---- ---- Tabrizi et al. (2019) Polycystic ovary syndrome ↑ levels b ↑ ↑ levels ↓ levels ---- ↓ levels ---- ---- Furthermore, most of the included studies, when analyzed individually, reported that after weeks of probiotic consumption (baseline/pre-treatment vs . intervention/post-treatment, as well as probiotic vs . placebo), significant effects of probiotic supplementation were observed (improvement in markers of inflammation, O&NS, and biomolecule damage), even reinforcing the fact that the pooled effect size (SMD) is sovereign over the statistical individualities and p -values from isolated studies. However, the high heterogeneity means that the effect size of the meta-analysis for the variables analyzed may be related to the large variation in effect size among studies. Thus, it is considered likely that the studies in the meta-analysis are not estimating the exact same effect size, which added to other parameters, i.e. imprecision (CI, number of participants), must be taken into account to interpret evidence of the true impact of probiotic intervention, or lead to uncertainty of the evidence toward the effects in favor of placebo or probiotic. Exception for the outcomes GSH, TAC, MDA, and hsCRP, for which, despite heterogeneity, consistent evidence confirmed by the GRADE system supports the effectiveness of probiotic intervention on these markers of O&NS and inflammation in patients with NCDs. In that way, also aiming to better guide public health measures, i.e. decision on implementing a specific intervention, subgroup analysis was performed to solve the heterogeneity, in some subgroups it indicated specificity of probiotic effectiveness on some markers of O&NS and inflammation, particularly, for age bracket between 41–60 (↓MDA levels) and > 61 years (↓hsCRP levels) and type of NCDs (NS/NDs, ↑GSH and ↓hsCRP, respectively) or RA and POS (both with ↑TAC); and strain number (in this case, only one strain) promotes an increase in GSH levels. As a limitation, the number of publications found in this study may be related to the fact that this is an emerging field/area of study that is still under construction, which is also confirmed by other studies [ 5 , 25 , 26 , 28 – 30 , 50 ], which reported ∼ 4–15 trials on this topic, supporting our findings. Moreover, not all included studies evaluated the same outcome variables selected in this SR&MA. In fact, with respect to the variables of O&NS, they showed a large variation among the studies. Suggestions to strengthen the association between probiotic treatment and outcomes include the evaluation of gut microbiota. Most of the included RCTs did not measure such characteristics (e.g., fecal microbial load) before and after probiotic treatment, as well as characterization of the microbiome at baseline and after interventions. Strains of probiotic microorganisms for human consumption are usually derived from the human intestinal tract and are able to survive the rigors of the gastrointestinal tract and possibly colonize it, being biologically active against the target [ 11 ]. In this sense, most of the studies included in this SR&MA used them (mainly Lactobacillus , Bifidobacterium and Streptococcus ). In conclusion, this is a high quality SR&MA of RCTs that provide evidence of the positive effects (effectiveness) of probiotics in increasing GSH levels and TAC, and decreasing MDA and hsCRP levels (4 out of 8 analyzed markers of O&NS and inflammation) in NCDs. Nevertheless, what is the most effective species and amount (dosage of CFUs, which reflects potency) are still unclear. Most of the information in this SR&MA comes from trials with a low risk of bias. To address questions about heterogeneity, subgroup analyses indicated some variables that may be related to heterogeneity, such as number of strains, age group, and type of NCD. In addition, the GRADE profiles indicated the certainty of evidence for the effectiveness of probiotic intervention on these markers. Declarations Author contribution N.S.S. participated in development, searching for trials, eligibility screening, quality assessment, data extraction, data analysis, comment on drafts and review and is the guarantor of this SR&MA. C.D.C. conceived the concept and designed the study, data curation, searching for trials, eligibility screening, quality assessment of studies, data extraction, data analysis, writing and update of the text, comment on drafts and review, Writing - Review & Editing (final version), and is the guarantor of this SR&MA. T.M.R. participated in protocol development, comment on drafts and review; update of the text. M.R.R. participated in development, comment on drafts and review; update of the text, and supervision/advice. Data Availability No datasets were generated during the current study. Conflict of Interests The authors declare no competing interests. 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Grading quality of evidence and strength of recommendations. BMJ 328:1490 [CrossRef] Ryan R, Hill S (2016) How to GRADE the quality of the evidence. Cochrane Consumers and Communication Group, available at http://cccrg.cochrane.org/author-resources . Version 3.0 December 2016 Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C et al (2017) AMSTAR 2: a critical appraisal tool for systematic reviews that include randomized or non-randomized studies of healthcare interventions, or both. BMJ 358:j4008 [CrossRef] Page MJ, McKenzie JE, Bossuyt PM et al (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic review. BMJ 372. [CrossRef] Mafi A, Namazi G, Soleimani A, Bahmani F, Aghadavod E, Asemi Z (2018) Metabolic and genetic response to probiotics supplementation in patients with diabetic nephropathy: a randomized, double-blind, placebo-controlled trial. Food Funct 9(9):4763–4770 [CrossRef] Mohseni S, Bayani M, Bahmani F, Tajabadi-Ebrahimi M, Bayani MA et al (2018) The beneficial effects of probiotic administration on wound healing and metabolic status in patients with diabetic foot ulcer: a randomized, double-blind, placebo-controlled trial. Diabetes Metab Res Rev 34(3):e2970 [CrossRef] Karamali M, Eghbalpour S, Rajabi S, Jamilian M, Bahmani F et al (2018) Effects of probiotic supplementation on hormonal profiles, biomarkers of inflammation and oxidative stress in women with polycystic ovary syndrome: a randomized, double-blind, placebo-controlled trial. Arch Iran Med 21:1–7 Zhu C, Yang H, Geng Q, Ma Q, Long Y, Zhou C, Chen M (2015) Association of oxidative stress biomarkers with gestational diabetes mellitus in pregnant women: a case-control study. PLoS ONE 10:e0126490 [CrossRef] Filippin LI, Vercelio R, Marroni NP, Xavier RM (2008) Redox signaling and inflammatory response in rheumatoid arthritis. 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Supplementary Files SupplementaryTable.doc Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 05 Feb, 2025 Reviews received at journal 04 Feb, 2025 Reviews received at journal 30 Jan, 2025 Reviewers agreed at journal 11 Jan, 2025 Reviewers agreed at journal 11 Jan, 2025 Reviewers invited by journal 11 Jan, 2025 Editor assigned by journal 10 Jan, 2025 Submission checks completed at journal 10 Jan, 2025 First submitted to journal 08 Jan, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5791482","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":400856299,"identity":"421127d7-9843-4c72-a556-43df83362d97","order_by":0,"name":"Natanny Swerts Silva","email":"","orcid":"","institution":"Federal University of Alfenas","correspondingAuthor":false,"prefix":"","firstName":"Natanny","middleName":"Swerts","lastName":"Silva","suffix":""},{"id":400856300,"identity":"0e1853ad-21fc-476c-82ce-510040b7ea2d","order_by":1,"name":"Cláudio Daniel Cerdeira","email":"data:image/png;base64,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","orcid":"","institution":"Independent Researcher","correspondingAuthor":true,"prefix":"","firstName":"Cláudio","middleName":"Daniel","lastName":"Cerdeira","suffix":""},{"id":400856301,"identity":"97f66e96-fa8f-4200-854a-08ffd2c3a98f","order_by":2,"name":"Tiago Marques Reis","email":"","orcid":"","institution":"Federal University of Alfenas","correspondingAuthor":false,"prefix":"","firstName":"Tiago","middleName":"Marques","lastName":"Reis","suffix":""},{"id":400856302,"identity":"d95042ca-2dfe-409a-95de-c5459a3aa3b9","order_by":3,"name":"Maria Rita Rodrigues","email":"","orcid":"","institution":"Federal University of Alfenas","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Rita","lastName":"Rodrigues","suffix":""}],"badges":[],"createdAt":"2025-01-08 19:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5791482/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5791482/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73867831,"identity":"e8567f05-e235-434f-be71-b3972d4b03b0","added_by":"auto","created_at":"2025-01-15 12:02:16","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1005655,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flow diagram highlighting the steps used to select randomized controlled trials (RCTs) that had evaluated the effect of probiotic intervention on markers of oxidative and nitrosative stress (O\u0026amp;NS) in patients with non-communicable diseases (NCDs)\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5791482/v1/062671975c68f45716b07aca.jpg"},{"id":73867438,"identity":"9113dc5d-d5a3-4b38-8d25-ca5995b95a5f","added_by":"auto","created_at":"2025-01-15 11:54:15","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":518563,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of Bias (RoB 2, Intention-to-Treat) in the included studies\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCaption\u003c/strong\u003e: 15 studies/16 trials, A. Assessments by trial (author) \u003cem\u003evs\u003c/em\u003e. domains; B. Summary of RoB 2 assessments (by domains, %)\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5791482/v1/d36813ea7ee3d12d827beea9.jpg"},{"id":73867427,"identity":"ec0bfc98-47aa-48c6-8be8-eccd0c214f01","added_by":"auto","created_at":"2025-01-15 11:54:14","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":272165,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots of probiotic intervention effect size on oxidative and nitrosative stress markers (antioxidant defenses and oxidant markers)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCaption\u003c/strong\u003e:\u003csup\u003e \u003c/sup\u003e\u0026nbsp;SMD - standardized mean difference. SE - standard error. CI - confidence Interval. A. serum glutathione (GSH) levels; B. total antioxidant capacity (TAC); C. nitric oxide (NO) levels\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5791482/v1/a7562ff137a08a498260eff8.jpg"},{"id":73867496,"identity":"63214b8d-1707-4428-8daf-2f375645a735","added_by":"auto","created_at":"2025-01-15 11:54:19","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":170722,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots of effect size of probiotic intervention on markers of oxidative and nitrosative stress (biomolecule damage markers)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCaption\u003c/strong\u003e:\u003csup\u003e \u003c/sup\u003e\u0026nbsp;SMD - standardized mean difference. SE - standard error. CI - confidence Interval. A. serum malondialdehyde (MDA) levels; B. serum 8-hydroxy-2′-deoxyguanosine (8-OHdG) levels\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5791482/v1/1a282bed85f6c54f6c203b69.jpg"},{"id":73867475,"identity":"a0283340-3913-4025-9c9c-5a0597588808","added_by":"auto","created_at":"2025-01-15 11:54:18","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":232865,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots of effect size of probiotic intervention on inflammatory markers\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCaption\u003c/strong\u003e:\u003csup\u003e\u0026nbsp; \u003c/sup\u003eSMD - standardized mean difference. SE - standard error. CI - confidence Interval. A. serum high sensitivity C-reactive protein (hsCRP) levels\u003cstrong\u003e; \u003c/strong\u003eB. serum interleukin (IL)-6 levels; C. serum tumor necrosis factor (TNF)-α levels\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5791482/v1/e119d7126e1d3c5cea43d5d4.jpg"},{"id":73869781,"identity":"00b56374-300d-4004-8a52-0c8e3446c7c6","added_by":"auto","created_at":"2025-01-15 12:10:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5448669,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5791482/v1/42496e5f-1faf-4ffe-8bd9-b9a309ad10ed.pdf"},{"id":73867415,"identity":"24a2e4d8-6e0c-4b15-8aa7-d93f8b63b782","added_by":"auto","created_at":"2025-01-15 11:54:13","extension":"doc","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":45568,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.doc","url":"https://assets-eu.researchsquare.com/files/rs-5791482/v1/684ee4eb5934534a8161614b.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of Probiotics on Markers of Oxidative/Nitrosative Stress and Damage Associated with Inflammation in Non-Communicable Diseases: a Systematic Review and Meta-Analysis of Randomized Placebo-Controlled Trials","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe gut microbiota, consisting of bacteria, fungi, viruses, and other microorganisms, serves as a secondary organ system with critical functions for the human host. Several factors disrupt the gut microbiota, including age, genetic specificity, diet, disease, and medications [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eProbiotic microbes, part of the gut microbiota, are strongly associated with health benefits such as disease prevention and comorbidity. On the other hand, a dysregulated gut microbiota (dysbiosis) has a lower number of beneficial bacteria (decreased diversity) and a higher number of pathogenic bacteria, such as enterobacteria (gamma-proteobacteria) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong the most important beneficial microorganisms as protective factors in the human gut microbiota are high levels of colony forming units (CFU) of bacteria belonging to the genus \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eStreptococcus\u003c/em\u003e, among others [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Thus, it is becoming increasingly common to use probiotic formulations (non-pathogenic live microorganisms) containing these microorganisms or those with similar effects, either in the prevention or as an adjuvant in the treatment of diseases [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDysbiosis per se or exacerbation of pathological conditions may promote increases in inflammatory markers [such as C-reactive protein (CRP), interleukin (IL)-6, and tumor necrosis factor (TNF)-α] and reactive oxygen/nitrogen species (ROS/RNS) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Chronic increases in ROS [superoxide (O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026bull;\u0026minus;\u003c/sup\u003e), hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e), hydroxyl radical (HO\u003csup\u003e\u0026bull;\u003c/sup\u003e), hypochlorous acid (HOCl)] and RNS [nitric oxide (NO) and peroxynitrite (ONOO\u003csup\u003e\u0026minus;\u003c/sup\u003e), among others] can lead to oxidative \u0026amp; nitrosative stress (O\u0026amp;NS), conditions in which such oxidants exceed the body's detoxification capacity despite a reduction in antioxidant defenses [e.g., superoxide dismutase (SOD), catalase (cat), glutathione peroxidase (GPx), and glutathione (GSH)]. In addition, associated biomolecule damage (lipid, protein, and DNA damage) can occur if O\u0026amp;NS is not controlled [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCurrently, gut microbiota dysbiosis has been implicated in chronic non-communicable diseases (NCDs). For example, these include neurodegenerative and autoimmune diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and multiple sclerosis (MS) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]; in addition to some symptoms of autism spectrum disorder (ASD) and other psychiatric conditions such as anxiety, depression, and bipolar disorder (BD) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Dysbiosis has also been implicated in other systemic diseases, including non-alcoholic fatty liver disease (NAFLD) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], coronary heart disease (CHD) and chronic heart failure (CHF) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], rheumatoid arthritis [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and diabetes mellitus and gestational diabetes mellitus (DM and GDM) [\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStudies show that dysbiosis in these NCDs are also coupled with inflammation and O\u0026amp;NS [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], in which a favorable prognosis may be achieved with the use of probiotics, although species and amount (which reflects potency) are still unclear [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In this sense, various randomized controlled trials (RCTs) and systematic review and meta-analysis (SR\u0026amp;MA) of RCTs have explored whether such use can favor adequate immunomodulation, decreasing/preventing O\u0026amp;NS and other damage coupled with the inflammatory process (\u0026darr; serum level of cytokines IL-6 and TNF-α, and hsCRP) and attenuating damage associated with pathogenic enterobacteria [\u003cspan additionalcitationids=\"CR26 CR27 CR28 CR29\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Moreover, studies have pointed out the antioxidant and anti-inflammatory properties of probiotics [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn that way, we conducted this SR\u0026amp;MA of RCTs to elucidate the effects of probiotics (oral bacteriotherapy) in attenuating O\u0026amp;NS and oxidative biomolecule damage, as well as the inflammatory process in NCDs, avoiding that the nutritional and clinical indication of probiotics be mainly based on trial and error.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eRegister\u003c/h2\u003e \u003cp\u003eThis SR\u0026amp;MA of RCTs is part of a study aimed at clarifying and updating the knowledge on the influence of probiotics on inflammatory processes and oxidative stress associated with some chronic diseases, previously registered in PROSPERO, registration number: CRD42023440106 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCondition being studied, review question, and study design\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe PICOS framework was developed as follows (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e):\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePICOS tool/framework used to develop review question(s) and then bias-free and comprehensive literature search strategies as well inclusions of studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDescription:\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e (\u003cb\u003eP\u003c/b\u003eopulation)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatients (no age or biological sex restrictions) with non-communicable diseases that have an inflammatory process and oxidative stress.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eI\u003c/b\u003e (\u003cb\u003eI\u003c/b\u003entervention)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProbiotics and/or probiotic supplementation containing a mix of CFU of microorganisms [multispecies probiotic supplement: \u003cem\u003eLactobacillus\u003c/em\u003e spp. and/or \u003cem\u003eBifidobacterium\u003c/em\u003e spp.; and or \u003cem\u003eStreptococcus\u003c/em\u003e spp., among others (also other microorganisms)], at any dose, frequency, and duration.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e (\u003cb\u003eC\u003c/b\u003eomparison)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnly placebo.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eO\u003c/b\u003e (\u003cb\u003eO\u003c/b\u003eutcome)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePrimary/main\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e: Markers of oxidative stress (O\u0026amp;NS ) and or nitrosative stress (NS) measured through antioxidant defense [superoxide dismutase (SOD), catalase (cat), glutathione peroxidase (GPx), GSH levels or the ratio of reduced to oxidized GSH (GSH:GSSG ratio); or total antioxidant capacity \u0026ndash; TAC; oxidants levels [superoxide (O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026bull;\u0026minus;\u003c/sup\u003e), hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e), hydroxyl radical (HO\u003csup\u003e\u0026bull;\u003c/sup\u003e), hypochlorous acid (HOCl)] or nitric oxide (NO) or peroxynitrite anion (ONOO\u003csup\u003e\u0026minus;\u003c/sup\u003e); and or oxidative biomolecule damage (lipid peroxidation/Malondialdehyde - MDA levels (TBARS), protein oxidation \u0026ndash; protein carbonyl (PCO), or oxidative DNA damage \u0026minus;\u0026thinsp;8OHdG); 3-NT, 8-iso-prostaglandin, among others here not specified, but representing a marker or other metabolic/biochemical profile of O\u0026amp;NS.\u003c/p\u003e \u003cp\u003e\u003cb\u003eSecondary\u003c/b\u003e: markers of inflammation [high sensitivity C-reactive protein (hsCRP), TNF-α or IL-6 levels].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eS\u003c/b\u003e (\u003cb\u003eS\u003c/b\u003etudy type)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRandomized placebo-controlled trials (RCTs).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ea\u003c/sup\u003e Cooke et al. (2003); Jomova et al. (2023)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on the PICOS: \"In patients with inflammatory processes in NCDs, how does probiotic consumption compare to placebo in the effect of decreasing O\u0026amp;NS and damage and/or inflammation?\u003c/p\u003e\n\u003ch3\u003eEligibility criteria, search strategy and study selection\u003c/h3\u003e\n\u003cp\u003eEligibility criteria were as follows: only randomized controlled trials (RCTs) with a well-defined treatment protocol (i.e. type of probiotic, doses and duration); appropriate control group (placebo); viable outcome data (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e); adequate data: results reported as mean difference (MD) or standardized mean difference (SMD) and associated SD/SE. Only studies that clearly addressed NCDs and had patients diagnosed according to clear criteria were included in this review. Studies were included if at least three studies reported the same at least one of the primary outcomes (O\u0026amp;NS markers) shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eExclusion criteria: studies not demonstrating the clinical outcomes of interest (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) or relevance to the topic; missing protocols; full text not available; non-viable primary and secondary endpoint data. The study was a non-RCT: for example, review, meta-analysis, or any clinical trial without a control group), or the study was conducted in animals or \u003cem\u003ein vitro\u003c/em\u003e. In addition, exclusion criteria were as follows: no NCDs (healthy, pregnant, and overweight). In addition, infectious diseases and inflammatory bowel diseases (irritable bowel syndrome, Crohn's disease) were not included in this study to avoid niche bias of the gut microbiota. We did not include studies of patients undergoing treatment for chronic conditions (e.g., hemodialysis) where the underlying cause may be microbial; the association of complex conditions (more than two) with an unknown or undiagnosed underlying cause; or conditions such as overweight or obesity. We did not include studies in which the authors administered probiotics in combination with another nutraceutical (prebiotics, postbiotics, milk, among others) and/or those in which the intervention was not only an association of microorganisms or those in which the composition left doubts. Studies in which the control group included the association of placebos with probiotics or other agents/drugs [active controls, including inulin, fructooligosaccharide, etc.] as well as prebiotics, symbiotics, etc.] were not accepted.\u003c/p\u003e \u003cp\u003eThe following online resources were searched electronically, and there were no time (date of publication) or language restrictions (\u003cb\u003eSupplementary appendix, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e) for RCTs: PubMed, Scopus, and EMBASE. We also searched the reference lists of studies obtained from PubMed, Scopus, and EMBASE. Finally, we contacted recognized experts in the field. After removing the duplicates, two authors (N.S.S. and C.D.C.) independently read the titles and abstracts and, among the selected references, read them in full. Articles selected after reading the titles and abstracts were analyzed for full text and included whether they met the eligibility criteria. Two authors (N.S.S. and C.D.C.) who assessed the eligibility of the studies; and they settled disagreements by discussion at the end of the process, if necessary, with either TMR or MRR. The agreement between the authors in the selection phase was also analyzed by the kappa coefficient (adequate when \u0026gt;\u0026thinsp;80%, here 92%), using BioEstat (Version 5.0, Brazil, 2007).\u003c/p\u003e\n\u003ch3\u003eData extraction and collection\u003c/h3\u003e\n\u003cp\u003eTwo authors (N.S.S. and C.D.C.) extracted the data into an Excel spreadsheet (Microsoft Corp, Redmond, Washington, USA). Data were independently coded using a standardized table that collected the following variables: (i.) study characteristics: author, year of publication, type of study (RCTs); (ii.) participant characteristics: total number of participants (biological sex, M/F; age) and disease type; and criteria used to define the specific NCD evaluated; (iii.) intervention details: dose, frequency, and duration of probiotic intervention; number of participants receiving probiotics; (iv) Comparator details: placebo; drug, dose, frequency, and duration of other drug; number of participants receiving placebo or other drug. (v.) Outcome details: general data (MD, SE, etc.) and significance of primary (O\u0026amp;NS markers) and secondary (inflammatory markers) outcome measures. The collected data were then initially processed in Excel.\u003c/p\u003e\n\u003ch3\u003eQuality of studies included: risk of bias assessment\u003c/h3\u003e\n\u003cp\u003e The revised Cochrane Risk-of-Bias (RoB 2) tool for RCTs (Intention-to-Treat/Trials) was independently performed by two reviewers (N.S.S. and C.D.C.) to assess the methodological quality of the included trials [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]; addressing at least five domains of bias: (1.) arising from the randomization process; (2.) due to deviations from intended intervention; (3.) due to missing outcome data; (4.) in measurement of the outcome; and (5.) in selection of the reported result. Robvis plot was used (available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://mcguinlu.shinyapps.io/robvis\u003c/span\u003e\u003cspan address=\"https://mcguinlu.shinyapps.io/robvis\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). A trial was considered to have an overall low risk of bias if it had a low risk in all four quality criteria proposed by Marušić et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] (random sequence generation, allocation concealment, blinding of outcome assessors, and completeness of outcome data; or equivalent in five domains); a high risk of bias if any domain was considered high risk, or if more than one of the four quality criteria had some concerns [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. There was no need to request information from the study authors, as data affecting the RoB2 assessment were accessible, and there were no relevant missing data to request.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData synthesis: outcome measures of effects and statistical analysis\u003c/h2\u003e \u003cp\u003eThe data were pooled and, depending on the heterogeneity of the studies, two effects models were considered as follows: (i.) random-effects model, when there is increased heterogeneity (criteria presented below), in this case is plausible two sources contributing with the variance (from within each study and those among studies); and (ii.) fixed-effect model, when there is decreased heterogeneity (criteria presented below), variance only from within each study. The effects of probiotic/intervention on markers of O\u0026amp;NS and inflammation/outcomes, compared with placebo (comparison group), were analyzed as follows: in the data synthesis (meta-analysis), the compiled data from at least four studies were primarily analyzed in separate (for each variable) pooled effect sizes, presented in Forest plot(s) (effect estimates) as background. The analyses were performed and Forest plots generated using Meta-essentials [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe primary outcome was the effect of probiotics on O\u0026amp;NS markers (GSH, TAC, MDA, NO, and 8-OHdG). The secondary outcome: markers of inflammation (hsCRP, IL-6, and TNF-α). To measure the magnitude of effect (absolute value of effect) in patients on probiotic treatment, first, whether positive (+) or negative (-), the interpretation of the magnitude of effect previously calculated is the same when absolute value was used. Then, we considered the direction of the effect of probiotic intervention by appropriate interpretation of the included results; i.e., (+) value: it favors intervention or the positive effect of probiotic treatment toward decreased (\u0026darr;) hsCRP, IL-6, TNF-α (inflammatory marker), MDA or 8-OHdG levels or increased (\u0026uarr;) GSH levels or TAC (markers of O\u0026amp;NS ); (-) value: it favors placebo with increased (\u0026uarr;) hsCRP, IL-6, TNF-α, MDA or 8-OHdG levels or decreased (\u0026darr;) GSH levels or TAC. To normalize the data for summarizing statistics of continuous data with different measurements or units [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], mean differences (MD: probiotic \u003cem\u003evs\u003c/em\u003e. placebo groups) from individual studies were converted to a common measure (SMD) using Cohen's d or the modified methods of Cohen's d, Glass' delta or Hedges' g. In this situation, these effect sizes (SMDs) for each individual study (k) were calculated using an online effect size calculator available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.socscistatistics.com/effectsize/default3.aspx\u003c/span\u003e\u003cspan address=\"https://www.socscistatistics.com/effectsize/default3.aspx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The associated standard error (SE) for unadjusted comparisons was obtained using a formula from Hedges [38].\u003c/p\u003e \u003cp\u003eThe forest plot was interpreted as follows: values (+) that favor probiotic intervention is found at the right corner of the forest plot; values (-) that favor placebo is found at the left side of the forest plot. Data are expressed as SMD plus SE, with 95% confidence interval (CI). Further analyses of pooled data (Z statistic and one-tailed/two-tailed \u003cem\u003ep\u003c/em\u003e-values) were considered statistically significant when \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHeterogeneity and subgroup analysis\u003c/h3\u003e\n\u003cp\u003eThe statistical heterogeneity of effect size among trials (inter-study heterogeneity) can be estimated using Cochrane's Q, which indicates whether or not heterogeneity is present (X\u003csup\u003e2\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.10, a low \u003cem\u003ep\u003c/em\u003e-value or a large chi-squared statistic provides evidence of significant heterogeneity), however, when only a few studies are included and their sample sizes are different, Cochrane's Q is not recommended; in this way, it is recommended to make an interpretation based only on the magnitude of heterogeneity, which is quantified by \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e, being \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u003cem\u003e\u0026le;\u003c/em\u003e\u0026thinsp;40% and \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u003cem\u003e\u0026ge;\u003c/em\u003e\u0026thinsp;0.1 considered as low heterogeneity or no clinically important heterogeneity (fixed-effect model); or heterogeneity was set as moderate (40% \u0026lt; \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u003cem\u003e\u0026le;\u003c/em\u003e\u0026thinsp;70%) or high (\u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;70%) (random-effects model) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Subgroup analysis was used as indicated when \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e is large, with a threshold of 50% for substantial heterogeneity indicating the need for subgroup analysis in meta-analysis with \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;50% [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Conversely, if \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e is low, then there is nothing to be explored in a subgroup analysis. If \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e is low (fixed-effect model), at least one of the subgroups can be considered a homogeneous population (in which the estimate of the \"true\" effect size is the same), whereas the entire set of studies cannot be considered studies of a (homogeneous) population.\u003c/p\u003e\n\u003ch3\u003ePublication bias analysis\u003c/h3\u003e\n\u003cp\u003eBecause the meta-analysis included more than 10 studies, publication bias was assessed by the asymmetry of the funnel plot, using Egger's test as the statistical method (\u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in Meta-Essentials [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eGrading the quality of evidence\u003c/h2\u003e \u003cp\u003eRegarding the level of evidence for each outcome, the Grade of Recommendations Assessment, Development, and Evaluation (GRADE) approach was adopted to assess the overall quality and certainty of evidence according to the GRADEprofiler software (Version 3.6, Grade Working Group, 2004/2007) with some modification [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Each outcome measure was graded as high, moderate, low, or very low certainty of evidence, and interpretations were made according to Ryan and Hill [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] as follows: (i) Risk of bias: Most information is from studies at low risk of bias (do not downgrade), Most information is from studies at low or unclear risk of bias (do not downgrade or downgrade one level), the proportion of information from studies at high risk of bias (downgrade two levels); (ii) Heterogeneity (inconsistency) was evaluated as: low heterogeneity (\u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u003cem\u003e\u0026le;\u003c/em\u003e\u0026thinsp;40%), moderate (40% \u0026lt; \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u003cem\u003e\u0026le;\u003c/em\u003e\u0026thinsp;70%) or high (\u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;70%); (iii) Indirectness: indirect population intervention, comparator, outcome, or indirect comparison; (iv) Imprecision: number of patients (participants is less than 400, downgrade 1) and CIs (if the upper or lower confidence limit crosses the effect size (eg. SMD) of 0.5, downgrade 1); and (v) publication bias: undetected (do not downgrade) and strongly suspected (downgrade one level).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eQuality of RS\u0026amp;MA\u003c/h2\u003e \u003cp\u003eThe AMSTAR 2 tool [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] was used to assess the methodological quality of the present RS\u0026amp;MA. The result was reported as a score from the checklist available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://amstar.ca/Amstar_Checklist.php\u003c/span\u003e\u003cspan address=\"https://amstar.ca/Amstar_Checklist.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eReport\u003c/h2\u003e \u003cp\u003eThe reporting of this SR\u0026amp;MA of RCTs followed the methodological expectations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist (PRISMA flow diagram updated) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], and based on the recommendations of the Cochrane Handbook [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eSearch and selection of studies: included studies in the meta-analysis\u003c/h2\u003e \u003cp\u003eInitially, after removing duplicates, the search strategy retrieved 782 records. After inclusion of studies from the reference lists of the primary records, fifteen studies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] (one out the 15 studies reported two trials) were eligible (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and included in the quantitative synthesis (meta-analysis), evaluating 837 participants (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The PRISMA flow diagram showing the included studies and criteria is presented below (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), highlighting the steps of the study selection process from \u0026ldquo;identification\u0026rdquo; to \u0026ldquo;inclusion\u0026rdquo; of RCTs in the meta-analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of included studies reporting randomized controlled trials (RCTs) aimed at assessing the effects of probiotics on oxidative/nitrosative stress (O\u0026amp;NS) and inflammation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eGeneral study characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eCharacteristics of RCT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrial\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlace\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-communicable disease\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDisease, comorbid and complications\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal sample size\u003csup\u003ea\u003c/sup\u003e (age interval-yr/mean age. and biological sex)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eProbiotic intervention\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eConclusions/\u003c/p\u003e \u003cp\u003emain findings\u003c/p\u003e \u003cp\u003e(Probiotic \u003cem\u003ev\u003c/em\u003es. Placebo)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eEndocrine \u0026amp; metabolic diseases\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChong et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-alcoholic fatty liver disease (NAFLD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDisease associated to metabolic syndrome (obesity and T2DM) with inflammation and O\u0026amp;NS complications leading to liver injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, placebo-controlled,\u003c/p\u003e \u003cp\u003eproof-of-concept trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;35\u003c/p\u003e \u003cp\u003e(25\u0026ndash;70/ Placebo: 58 Probiotic: 57; M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eVSL#3: \u003cem\u003eStreptococcus thermophilus, Bifidobacterium breve, B. longum, B. infantis, Lactobacillus acidophilus, L. plantarum, L. paracasei\u003c/em\u003e, and \u003cem\u003eL. bulgaricus\u003c/em\u003e; 2 sachets/twice daily/10 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTrial does not support the hypothesis that probiotics improve markers of O\u0026amp;NS (GSH and TAC) and inflammation (hsCRP).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHajifaraji et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGestational diabetes mellitus (GDM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHyperglycemia can lead to inflammation and O\u0026amp;NS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, double blinded, placebo-controlled clinical trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;56\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45 Placebo: 26.5 Probiotic: 28.1; F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL. acidophilus\u003c/em\u003e LA- 5, \u003cem\u003eBifidobacterium\u003c/em\u003e BB-12, \u003cem\u003eS. thermophilus\u003c/em\u003e STY-31 and \u003cem\u003eL. delbrueckii bulgaricus\u003c/em\u003e LBY-2; 1 \u0026times;/day, for 8 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic supplements improved some O\u0026amp;NS (\u0026uarr; GSH and \u0026darr; MDA) and inflammation (hsCRP) markers.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoleimani et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiabetic patients (on hemodialysis)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDM\u0026thinsp;+\u0026thinsp;comorbid (renal failure) can aggravate inflammation and O\u0026amp;NS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, double-blind, placebo-controlled clinical trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;60\u003c/p\u003e \u003cp\u003e(18\u0026ndash;80 Placebo: 59.4 Probiotic: 54.0; M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL. acidophilus, L. casei\u003c/em\u003e, and \u003cem\u003eB. bifidum;\u003c/em\u003e daily, for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic\u003c/p\u003e \u003cp\u003esupplementations had beneficial effects on O\u0026amp;NS (prevented \u0026uarr; in MDA levels) and inflammation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsemi et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eType 2 DM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eChronic hyperglycemia can lead to inflammation and O\u0026amp;NS /NS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, placebo-controlled clinical trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;54\u003c/p\u003e \u003cp\u003e(NI/ Placebo: 52.59 Probiotic: 50.51; M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL. acidophilus\u003c/em\u003e, \u003cem\u003eL. casei\u003c/em\u003e, \u003cem\u003eL. rhamnosus\u003c/em\u003e, \u003cem\u003eL. bulgaricus\u003c/em\u003e, \u003cem\u003eB. breve\u003c/em\u003e, \u003cem\u003eB. longum\u003c/em\u003e, and \u003cem\u003eS. thermophilus\u003c/em\u003e, for 8 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic promoted \u0026uarr; GSH and \u0026darr; hCRP levels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMafi et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiabetic\u003c/p\u003e \u003cp\u003eNephropathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUncontrolled hyperglycemia can lead to inflammation and O\u0026amp;NS exacerbated by comorbid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, placebo-controlled clinical trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;60\u003c/p\u003e \u003cp\u003e(Placebo: 60.9 Probiotic: 58.9;M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL. acidophilus\u003c/em\u003e strain ZT-L1, \u003cem\u003eB. bifidum\u003c/em\u003e strain ZT-B1, \u003cem\u003eL. reuteri\u003c/em\u003e strain ZT-Lre, and \u003cem\u003eL. fermentum\u003c/em\u003e strain ZT-L3,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic\u003c/p\u003e \u003cp\u003esupplementation \u0026uarr; GSH and \u0026darr; MDA levels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMohseni et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eType 2 DM/foot\u003c/p\u003e \u003cp\u003eulcer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eO\u0026amp;NS and inflammation take part in the complications from DM.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized double-blind placebo-controlled clinical trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;60\u003c/p\u003e \u003cp\u003e(40\u0026ndash;85/ Placebo: 58.5 Probiotic: 62.6; M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL. acidophilus\u003c/em\u003e, \u003cem\u003eL. casei\u003c/em\u003e, \u003cem\u003eL. Fermentum\u003c/em\u003e, and \u003cem\u003eB. bifidum\u003c/em\u003e, for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic supplementation resulted in significant \u0026darr; hsCRP and MDA levels and \u0026uarr; NO levels and TAC.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRaygan et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eType 2 DM and coronary heart disease (CHD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHyperglycemia can predispose patients to have CHD and aggravates inflammation/O\u0026amp;NS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, double-blind, placebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;60\u003c/p\u003e \u003cp\u003e(40\u0026ndash;85/ Placebo: 61.8 Probiotic: 60.7; M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eB. bifidum\u003c/em\u003e, \u003cem\u003eL. casei\u003c/em\u003e, \u003cem\u003eL. acidophilus;\u003c/em\u003e 1 \u0026times;/day for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic intervention improved antioxidant defense (\u0026uarr; GSH and TAC) and \u0026darr; hsCRP levels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiseases of the Nervous system (NS)/neurodegenerative diseases (NDs)/psychiatric disorders\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTamtaji et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eParkinson's disease (PD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eO\u0026amp;NS from mitochondrial dysfunction and from phagocytes in inflammation process can exacerbate neuronal degeneration of PD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, double-blind, placebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;60\u003c/p\u003e \u003cp\u003e(50\u0026ndash;59/ Placebo: 67.7 Probiotic: 68.2; NI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL. acidophilus, B. bifidum, L. reuteri\u003c/em\u003e, and \u003cem\u003eL. fermentum\u003c/em\u003e, for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic supplementation \u0026darr; hsCRP and MDA levels, and \u0026uarr; GSH levels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgahi et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAlzheimer\u0026rsquo;s disease (AD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eROS and RNS released during inflammation also take part in the pathogenesis of AD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, placebo-controlled clinical trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;48\u003c/p\u003e \u003cp\u003e(65\u0026ndash;90/ Placebo: 80.57 Probiotic: 79.70; M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL.fermentum\u003c/em\u003e, \u003cem\u003eL.plantarum\u003c/em\u003e, \u003cem\u003eB.lactis\u003c/em\u003e,\u003c/p\u003e \u003cp\u003e\u003cem\u003eL.acidophilus\u003c/em\u003e, \u003cem\u003eB.bifidum\u003c/em\u003e, \u003cem\u003eB.longum\u003c/em\u003e, for 12 wk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eO\u0026amp;NS markers (NO, GSH, TAC, MDA, and 8-OHdG) were negligible to the probiotic supplementation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAkhgarjand et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlzheimer\u0026rsquo;s disease (AD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBesides amyloid plaques and TAU dysfunctions in the genesis of AD, O\u0026amp;NS and inflammation are speculated as adjuvant and triggers of neurodegeneration.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRandomized, double-blind, placebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;90\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(50\u0026ndash;90/ Placebo: 67.77 \u003cem\u003eL. rhamnosus\u003c/em\u003e: 67.93 \u003cem\u003eB. longum\u003c/em\u003e: 67.90; M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12-week supplementation with: \u003cem\u003eL. rhamnosus\u003c/em\u003e\u003c/p\u003e \u003cp\u003eHA-114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTwo trials: Probiotic supplementation (2 different probiotic groups) \u0026uarr; GSH levels and \u0026darr; MDA and 8OHdG levels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12-week supplementation with: \u003cem\u003eB. longum\u003c/em\u003e R0175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsghari et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMultiple Sclerosis (MS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eChronic demyelination with possible inflammation and O\u0026amp;NS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, double blinded, placebo-controlled clinical trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;40\u003c/p\u003e \u003cp\u003e(18\u0026ndash;55/ Placebo: 34.95 Probiotic: 33.8; M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eSaccharomyces boulardii\u003c/em\u003e daily for 4 months.\u003c/p\u003e \u003cp\u003e(16 wk.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic intervention increased TAC (\u0026uarr; antioxidant defense).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSabouri et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBipolar\u003c/p\u003e \u003cp\u003eDisorder (BD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDysbiosis with \u0026uarr; inflammation and O\u0026amp;NS links BD impairments because interconnections \u003c/p\u003e \u003cp\u003e\u0026mdash;the gut-brain axis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, double-blind, placebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;38\u003c/p\u003e \u003cp\u003e(18\u0026ndash;65/ Placebo: 35 Probiotic: 38.89; M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eB. bifidum\u003c/em\u003e, \u003cem\u003eB. lactis\u003c/em\u003e, \u003cem\u003eB. langum\u003c/em\u003e, and \u003cem\u003eL. acidophilus\u003c/em\u003e, for 8 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic supplementation did not improve O\u0026amp;NS markers (MDA levels)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAkkasheh\u003c/p\u003e \u003cp\u003eet al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMajor depressive disorder (MDD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEvidences that O\u0026amp;NS have a role in the pathogenesis of MDD, as possible cause or consequence.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, double-blind, placebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;40\u003c/p\u003e \u003cp\u003e(20\u0026ndash;55/ Placebo: 36.2 Probiotic: 38.3; M and F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL.acidophilu, L.casei\u003c/em\u003e,and \u003c/p\u003e \u003cp\u003e\u003cem\u003eB.bifidum\u003c/em\u003e for 8 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic supplementation \u0026uarr; GSH and \u0026darr; hsCRP levels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther diseases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaghef-Mehrabany et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRheumatoid arthritis (RA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRA is an autoimmune inflammatory disease in which O\u0026amp;NS can play a role in its physiopathology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, placebo-controlled clinical trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;46\u003c/p\u003e \u003cp\u003e(20\u0026ndash;80/ Placebo: 44.29 Probiotic: 41.14; F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL. casei\u003c/em\u003e 01, for 8 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eThere was no significant difference between probiotic \u003cem\u003evs\u003c/em\u003e. placebo for markers of O\u0026amp;NS .\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKaramali et al\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePolycystic ovary syndrome (POC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInflammation and O\u0026amp;NS are players in POC pathogenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRandomized, double-blind, placebo-controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;60\u003c/p\u003e \u003cp\u003e(18\u0026ndash;40/ Placebo: 27.7 Probiotic: 27.2; F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL. acidophilus\u003c/em\u003e, \u003cem\u003eL. casei\u003c/em\u003e, and \u003cem\u003eB. bifidum\u003c/em\u003e, for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eProbiotic intervention \u0026uarr; TAC and \u0026darr; MDA hsCRP levels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eTotal of participants into both groups (probiotic and placebo) from all RCTs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e837\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cb\u003eCaption\u003c/b\u003e: GSH - glutathione, TAC - total antioxidant capacity, NO - nitric oxide, MDA - malondialdehyde, 8-OHdG \u0026minus;\u0026thinsp;8-hydroxy-2\u0026prime;-deoxyguanosine, hsCRP - high sensitivity C-reactive protein, IL-6 - interleukin-6, TNF-α \u0026ndash; tumor necrosis factor-α. \u003csup\u003ea\u003c/sup\u003e: Total of participants randomized into control (placebo) and treatment (probiotic intervention) groups (concluded the study). \u003csup\u003eb\u003c/sup\u003e: in most of the included studies, probiotics were administered in capsules, containing the probiotics plus adjuvant (lactose or dextrose anhydrous/filler, magnesium acetate or stearate/lubricant, oil; all of them with no interferences on outcomes). Placebo (non-containing probiotic) treatments were administered with equal conditions (formula and period of administration). \u003csup\u003ec\u003c/sup\u003e Two probiotic groups: 30 patients into each group; plus 30 patients into placebo group. \u0026uarr;: increase/high \u0026darr;: decrease/low. NI: Not informed.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStudy characteristics\u003c/h2\u003e \u003cp\u003eThe characteristics of the studies included in this SR\u0026amp;MA are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Non-communicable diseases varied among studies, with DM (or DM types or plus comorbid) being the most common. The most common country was Iran, and the publication period (from 2013 to 2023) spanned the last decade, demonstrating a current trend to explore this topic. Probiotic supplementation protocols were similar in terms of frequency of administration (daily) and time of intervention (wk, between 8 and 16, the most common being 12 wk - as seen in 9 studies), but varied considerably in terms of number of microorganisms (from 1 to 8 strains) and CFU, and when (two or more strains) combined to yield different supplements (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eImpact of probiotic intervention on primary and secondary outcomes in the included randomized placebo-controlled trials (RCTs), highlighting details of microbial load \u003cem\u003eversus\u003c/em\u003e effect size for each individual study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRCTs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c4\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eAmount (potency) of probiotic (Intervention)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c12\" namest=\"c5\"\u003e \u003cp\u003eStudy effect size (\u003csup\u003ek\u003c/sup\u003e) for impact of probiotic intervention on primary and secondary endpoints (\u0026uarr; or \u0026darr; markers) compared to placebo group.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c9\" namest=\"c5\"\u003e \u003cp\u003ePrimary outcomes: O\u0026amp;NS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eSecondary outcomes: inflammation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of microorganisms\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDosage of CFU and duration of intervention\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal CFU (wks\u003csup\u003ea\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGSH levels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMDA levels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8-OHdG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ehsCRP levels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDesirable (positive) outcome on marker levels\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026uarr;\u0026darr;\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChong et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8: \u003cem\u003eStreptococcus thermophilus, Bifidobacterium breve, B. longum, B. infantis, Lactobacillus acidophilus, L. plantarum, L. paracasei\u003c/em\u003e, and \u003cem\u003eL. bulgaricus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 sachets twice a day for 10 wk. At least 112.5 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU/sachet.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6 \u0026times;10\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.44 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.43 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.25 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHajifaraji et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4: \u003cem\u003eL. acidophilus\u003c/em\u003e LA- 5, \u003cem\u003eBifidobacterium\u003c/em\u003e BB-12, \u003cem\u003eS. thermophilus\u003c/em\u003e STY-31, and \u003cem\u003eL. delbrueckii bulgaricus\u003c/em\u003e LBY-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnce daily\u0026thinsp;\u0026gt;\u0026thinsp;4 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU each for 8 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.9 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.92 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.8 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.75 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.35 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.97 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.9 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoleimani et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3: \u003cem\u003eL. acidophilus, L. casei\u003c/em\u003e, and \u003cem\u003eB. bifidum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnce daily 2 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU\u003c/p\u003e \u003cp\u003eeach (totally 6 10\u003csup\u003e9\u003c/sup\u003e CFU per capsule) for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.07 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.28 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.23 (\u0026uarr;\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.97 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.28 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsemi et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7: \u003cem\u003eL. acidophilus\u003c/em\u003e, \u003cem\u003eL. casei\u003c/em\u003e, \u003cem\u003eL. rhamnosus\u003c/em\u003e, \u003cem\u003eL. bulgaricus\u003c/em\u003e, \u003cem\u003eB. breve\u003c/em\u003e, \u003cem\u003eB. longum\u003c/em\u003e, and \u003cem\u003eS. thermophilus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnce day, for 8 wk: 2 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU, 7 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU, 1.5 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU, 2 \u0026times; 10\u003csup\u003e8\u003c/sup\u003e CFU, 2 \u0026times; 10\u003csup\u003e10\u003c/sup\u003e CFU, 7 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU, 1.5 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU, respectively\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3 \u0026times;10\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.44 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.81 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMafi et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4: \u003cem\u003eL. acidophilus\u003c/em\u003e strain ZT-L1, \u003cem\u003eB. bifidum\u003c/em\u003e strain ZT-B1, \u003cem\u003eL. reuteri\u003c/em\u003e strain ZT-Lre, and \u003cem\u003eL. fermentum\u003c/em\u003e strain ZT-L3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEach 2 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU (totally 8 10\u003csup\u003e9\u003c/sup\u003e CFU per capsule), for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.7 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.14 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.43\u003c/p\u003e \u003cp\u003e(\u0026uarr;\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.1 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.87 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMohseni et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4: \u003cem\u003eL. acidophilus\u003c/em\u003e, \u003cem\u003eL. casei\u003c/em\u003e, \u003cem\u003eL. Fermentum\u003c/em\u003e, and \u003cem\u003eB. bifidum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU/g each, for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.7 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.88 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003cp\u003e(\u0026uarr;\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.49 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.13 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRaygan et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3: \u003cem\u003eB. bifidum\u003c/em\u003e, \u003cem\u003eL. casei\u003c/em\u003e, \u003cem\u003eL. acidophilus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026times;10\u003csup\u003e9\u003c/sup\u003e CFU each, once daily, for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.64 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003cp\u003e(\u0026uarr;\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.09 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.23 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTamtaji et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4: \u003cem\u003eL. acidophilus, B. bifidum, L.reuteri\u003c/em\u003e, and \u003cem\u003eL. fermentum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12-week supplementation with 2\u0026times;10\u003csup\u003e9\u003c/sup\u003e CFU once daily, each bacterial (8\u0026times;10\u003csup\u003e9\u003c/sup\u003e CFU, total)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.7 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.21 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.41 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgahi et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 capsules containing each 3 bacteria: \u003cem\u003eL.fermentum\u003c/em\u003e, \u003cem\u003eL.plantarum\u003c/em\u003e, and \u003cem\u003eB.lactis\u003c/em\u003e; or\u003c/p\u003e \u003cp\u003e\u003cem\u003eL.acidophilus\u003c/em\u003e, \u003cem\u003eB.bifidum\u003c/em\u003e, \u003cem\u003eB.longum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA total dosage of 3 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e (10\u003csup\u003e9\u003c/sup\u003e each strain) CFU/day, for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.1 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3.75\u003c/p\u003e \u003cp\u003e(\u0026uarr;\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.65 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.18 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.03 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.83 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.67 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAkhgarjand et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1: \u003cem\u003eLacticaseibacillus rhamnosus\u003c/em\u003e HA-114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnce daily 7.5 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e, for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.3 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.18 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.65 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.58 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.76 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAkhgarjand et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1: \u003cem\u003eBifidobacterium longum\u003c/em\u003e R0175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnce daily 7.5 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e, for 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.3 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.22 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.23 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.65 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.76 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsghari et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1: \u003cem\u003eSaccharomyces boulardii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnce daily 250 mg (10\u003csup\u003e10\u003c/sup\u003e CFU)/4 months (16 wk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1 \u0026times;10\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.8 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.34 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.03 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSabouri et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4: \u003cem\u003eB. bifidum\u003c/em\u003e, \u003cem\u003eB. lactis\u003c/em\u003e, \u003cem\u003eB. langum\u003c/em\u003e, and \u003cem\u003eL. acidophilus\u003c/em\u003e,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU of each bacterial strain, once daily for 8 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.27 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.03 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.2 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAkkasheh\u003c/p\u003e \u003cp\u003eet al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3: \u003cem\u003eL.acidophilus\u003c/em\u003e, \u003cem\u003eL.casei\u003c/em\u003e, and\u003c/p\u003e \u003cp\u003e\u003cem\u003eB.bifidum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU/day (2 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e each strain), for 8 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.4 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaghef-Mehrabany et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1: \u003cem\u003eL. casei\u003c/em\u003e 01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003csup\u003e8\u003c/sup\u003e CFU/day, for 8 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.6 \u0026times;10\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.34 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKaramali et al\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3: \u003cem\u003eL. acidophilus\u003c/em\u003e, \u003cem\u003eL. casei\u003c/em\u003e, and \u003cem\u003eB. bifidum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU/g each, 12 wk.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.4 (\u0026uarr;\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.47 (\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.48 (\u0026uarr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal of participants into both groups (probiotic and placebo) from all RCTs by outcome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e348 (\u0026uarr;\u0026darr;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e262\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003cb\u003eCaption\u003c/b\u003e: CFU: colony-forming units. GSH - glutathione, TAC - total antioxidant capacity, NO - nitric oxide, MDA - malondialdehyde, 8-OHdG \u0026minus;\u0026thinsp;8-hydroxy-2\u0026prime;-deoxyguanosine, hsCRP - high sensitivity C-reactive protein, IL-6 - interleukin-6, TNF-α \u0026ndash; tumor necrosis factor-α. Comparisons probiotic \u003cem\u003evs\u003c/em\u003e. placebo: + values of k (desirable), effect favors probiotic; - values of k, favors placebo. \u0026uarr;: increased levels \u0026darr;: decreased levels. \u003csup\u003ea\u003c/sup\u003eWithout considering possible differences among potencies of different microorganisms, just considering the total CFU amount from all microorganisms administered during whole period of study. \u003csup\u003eb\u003c/sup\u003eThis interpretation is factually contextual.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eQuality assessment: risk of bias\u003c/h2\u003e \u003cp\u003eThe risk of bias is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. All studies were based on the intention-to-treat principle. In general, for the five domains considered, most studies had a complete overall low risk of bias, although two of these studies had some concerns. Among some concerns and high risk of bias, those related to randomization and related intervention were the most common, in which some studies did not report in the paper an adequate method of concealment of allocation and investigators. Thus, some studies are actually randomized single-blind (or non-blind) placebo-controlled trials (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Other areas of concern include the conditions of the probiotic intervention and the appropriate analysis used to estimate the effect of assigning participants to it.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eForest plots of effect sizes: the effects of probiotic intervention on markers of O\u0026amp;NS and inflammation\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFigures\u003c/b\u003e from \u003cb\u003e3\u003c/b\u003e to \u003cb\u003e5\u003c/b\u003e show the individual Forest plots for each outcome measure. Effect sizes for probiotic intervention on O\u0026amp;NS markers (GSH, NO levels, and TAC) and O\u0026amp;NS-related biomolecule damage (MDA and 8-OHdG levels) and markers of inflammation (hsCRP, IL-6, and TNF-α levels) were considered. Study weights (blue circle size) in forest plots were similar for all outcomes. Overall effect (pooled result, green) in Forest plots for almost all outcomes (except NO) show the positive effects of probiotic intervention (positive values on the right side of each Forest plot), with \u003cem\u003ep\u003c/em\u003e-values and IC lower and upper bounds showing that increases in GSH levels and TAC and decreases in MDA and hsCRP levels favor probiotic intervention. There was high heterogeneity (\u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;75%) for all outcome measures evaluated. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the Forest plots and shows significant positive effects (effect size) of probiotic intervention (\u003cem\u003evs\u003c/em\u003e. placebo). Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows that the exclusion of studies with a high risk of bias did not have a significant effect on the parameters (outcomes) evaluated here. There was no significant number of included studies (\u0026gt;\u0026thinsp;3) reporting other O\u0026amp;NS markers (e.g.., SOD, Cat, GPx, etc.; or biomolecule damage markers: protein oxidation among others).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKey findings from the meta-analysis based on Forest plots interpretations highlighting the impact of probiotic intervention on markers of oxidative/nitrosative stress and inflammation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMeasures and Interpretations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003eOutcomes/endpoints\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eOxidative stress markers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c9\" namest=\"c7\" rowspan=\"2\"\u003e \u003cp\u003eInflammation markers\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAntioxidant defense\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRNS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eBiomolecule damage (reflects oxidants attack)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSpecific\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePrecursor of potent RNS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eLipid\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ePeroxidation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eOxidative\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eDNA damage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eGeneral acute phase\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003eGeneral acute phase/Immune mediators\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGSH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eTAC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eNO\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMDA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e8-OHdG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ehsCRP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eIL-6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eTNF-α\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpact of probiotic intervention\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive: \u0026uarr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive: \u0026uarr; capacity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----:\u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive: \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePositive: \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive: \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePositive: \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePositive: \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePooled effect size (SE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89 (0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75 (0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;0.47 (0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03 (0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75 (0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.74 (0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.67 (0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.06 (0.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.23 to 2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28 to 1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.22 to 1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37 to 1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.24 to 2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.07 to 1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.66 to 2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.25 to 2.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot significant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNot significant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot significant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEffect size interpretation\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% placebo group below mean probiotic group\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79\u0026ndash;91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u0026ndash;78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79\u0026ndash;91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59\u0026ndash;78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59\u0026ndash;78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e59\u0026ndash;78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e79\u0026ndash;91%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterogeneity (I\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cb\u003eCaption\u003c/b\u003e: GSH - glutathione, TAC - total antioxidant capacity, NO - nitric oxide, MDA - malondialdehyde, 8-OHdG \u0026minus;\u0026thinsp;8-hydroxy-2\u0026prime;-deoxyguanosine, hsCRP - high sensitivity C-reactive protein, IL-6 - interleukin-6, TNF-α \u0026ndash; tumor necrosis factor-α, RNS \u0026ndash; Reactive nitrogen species. \u0026uarr; high or increase; \u0026darr; low or decrease. \u003csup\u003ea\u003c/sup\u003e based on overall (pooled) effect size (SMD). \u003csup\u003eb\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05: effects those are statistically significant. \u003csup\u003ec\u003c/sup\u003eInterpretation of relative size (Cohen\u0026rsquo;s d): 0 to 0.49 \u0026ndash; small (\u003csup\u003ed\u003c/sup\u003e 0\u0026ndash;58%); 0.5 to 0.79 \u0026ndash; medium (\u003csup\u003ed\u003c/sup\u003e 59\u0026ndash;78%); \u0026ge;0.8 \u0026ndash; large (\u003csup\u003ed\u003c/sup\u003e 0.8 to 1.39\u0026thinsp;=\u0026thinsp;79\u0026ndash;91%; \u0026ge;1.4\u0026thinsp;=\u0026thinsp;\u0026ge;\u0026thinsp;92%) (Lakens, 2013).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKey findings of the meta-analysis based on Forest plots interpretations highlighting the impact of probiotic intervention on markers of oxidative/nitrosative stress and inflammation, excluding studies with high risk of bias\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMeasures and Interpretations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003eOutcomes/endpoints\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eOxidative stress markers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c9\" namest=\"c7\" rowspan=\"2\"\u003e \u003cp\u003eInflammation markers\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAntioxidant defense\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRNS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eBiomolecule damage (reflects oxidants attack)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSpecific\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePrecursor of potent RNS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eLipid\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ePeroxidation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eOxidative\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eDNA damage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eGeneral acute phase\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003eGeneral acute phase/Immune mediators\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGSH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eTAC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eNO\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMDA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e8-OHdG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ehsCRP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eIL-6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eTNF-α\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemaining studies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpact of probiotic intervention\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive: \u0026uarr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive: \u0026uarr; capacity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----: \u0026uarr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive: \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePositive: \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive: \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePositive: \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePositive: \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePooled effect size (SE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.51 (0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64 (0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33 (0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97 (0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.22 (0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.59 (0.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.06 (0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.16 (0.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.24 to 1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15 to 1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.38 to 1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17 to 1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02 to 1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.42 to 1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.17 to 2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.74 to 3.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot significant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot significant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNot significant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEffect size interpretation\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSmall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% placebo group below mean probiotic group\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59\u0026ndash;78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u0026ndash;78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79\u0026ndash;91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79\u0026ndash;91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59\u0026ndash;78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e79\u0026ndash;91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e79\u0026ndash;91%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterogeneity (I\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026uarr; (88.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026uarr; (83.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003cp\u003e(65.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026uarr; (94.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026darr; (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026uarr; (95.01%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026uarr; (85.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026uarr; (94.71%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cb\u003eCaption\u003c/b\u003e: GSH - glutathione, TAC - total antioxidant capacity, NO - nitric oxide, MDA - malondialdehyde, 8-OHdG \u0026minus;\u0026thinsp;8-hydroxy-2\u0026prime;-deoxyguanosine, hsCRP - high sensitivity C-reactive protein, IL-6 - interleukin-6, TNF-α \u0026ndash; tumor necrosis factor-α, RNS \u0026ndash; Reactive nitrogen species. \u0026uarr; high or increase; \u0026darr; low or decrease. \u003csup\u003ea\u003c/sup\u003e based on overall (pooled) effect size (SMD). \u003csup\u003eb\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05: effects those are statistically significant. \u003csup\u003ec\u003c/sup\u003eInterpretation of relative size (Cohen\u0026rsquo;s d): 0 to 0.49 \u0026ndash; small (\u003csup\u003ed\u003c/sup\u003e 0\u0026ndash;58%); 0.5 to 0.79 \u0026ndash; medium (\u003csup\u003ed\u003c/sup\u003e 59\u0026ndash;78%); \u0026ge;0.8 \u0026ndash; large (\u003csup\u003ed\u003c/sup\u003e 0.8 to 1.39\u0026thinsp;=\u0026thinsp;79\u0026ndash;91%; \u0026ge;1.4\u0026thinsp;=\u0026thinsp;\u0026ge;\u0026thinsp;92%) (Lakens, 2013).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eExcluded studies with high risk of bias: Asemi et al., Mafi et al., Agahi et al.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003cp\u003eSince \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e was large, we proceeded with subgroup analysis to investigate the source of variation: dosage of CFU/quantity of strains; age (mean years); and type of NCDs. As interpretation of the pooled effect size (and its intervals) is not recommended, only heterogeneity was considered in the subgroup analysis, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Factors related to intervention (dose and number of strains) and population (age and NCDs) were adjusted for.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSubgroup analysis on variables of interest\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSUBGROUP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNUMBER OF STUDIES\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eT\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eGSH\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTotal CFU\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e and \u0026le;\u0026thinsp;10\u003csup\u003e12\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10\u003csup\u003e12\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eNumber of strains\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2\u0026thinsp;\u0026le;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0..60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eMean age (yr)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eDisease group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndocrine \u0026amp; metabolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e123.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNS/ND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTAC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTotal CFU\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e and \u0026le;\u0026thinsp;10\u003csup\u003e12\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10\u003csup\u003e12\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eNumber of strains\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2\u0026thinsp;\u0026le;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eMean age (yr)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eDisease group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndocrine \u0026amp; metabolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNS/ND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMDA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTotal CFU\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e and \u0026le;\u0026thinsp;10\u003csup\u003e12\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10\u003csup\u003e12\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eNumber of strains\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2\u0026thinsp;\u0026le;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eMean age (yr)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eDisease group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndocrine \u0026amp; metabolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e124.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNS/ND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ehsCRP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTotal CFU\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 \u0026times;10\u003csup\u003e11\u003c/sup\u003e and \u0026le;\u0026thinsp;10\u003csup\u003e12\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10\u003csup\u003e12\u003c/sup\u003e CFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eNumber of strains\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2\u0026thinsp;\u0026le;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eMean age (yr)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eDisease group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndocrine \u0026amp; metabolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e129.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNS/ND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eCaption\u003c/b\u003e: [\u0026darr; Heterogeneity (\u0026lt;\u0026thinsp;50% or \u0026lt;\u0026thinsp;75%)]. CFU - colony-forming units. GSH - glutathione, hsCRP - high sensitivity C-reactive protein, MDA - malondialdehyde, NDs - neurodegenerative diseases, NS - Nervous system, Others: Rheumatoid arthritis and polycystic ovary syndrome, TAC - total antioxidant capacity.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003ePublication Bias\u003c/h2\u003e \u003cp\u003eThe results of Egger's test (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) showed no evidence of significant publication bias for TAC (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.722), MDA (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.201), hsCRP (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.659), IL-6 (0.220), and TNF-α (0.389). There was evidence of publication bias (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for GSH, NO and 8-OHdG.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePublication bias analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of studies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value (Egger\u0026rsquo;s test)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eOxidative \u0026amp; nitrosative stress\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGSH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8-OHdG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eInflammation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.389\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eGrading of evidence\u003c/h2\u003e \u003cp\u003eThe results of the GRADE analysis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, with key findings highlighted. Finally, complementing the evidence based on the pooled effect size (and its intervals), the GRADE profiles confirm the positive effects of the probiotic intervention (\u003cem\u003evs\u003c/em\u003e. placebo) on markers of O\u0026amp;NS (GSH, TAC, and MDA) and inflammation (hsCRP). Qualities of evidence were: high () for the effectiveness of probiotic in decreasing MDA levels in patients with NCDs; and moderate () for the impact of probiotic in increasing GSH levels and TAC and decreasing hsCRP levels in patients with NCDs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGrading the quality of evidence in this systematic review and meta-analysis for the effects of probiotic interventions on various markers of oxidative/nitrosative stress and inflammation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e \u003cp\u003ePatients with non-communicable diseases that have an inflammatory process and oxidative stress.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e \u003cp\u003eProbiotic (one strain) and/or probiotic supplementation containing a mix (more than one strain) of microorganisms.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e \u003cp\u003ePlacebo.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eO\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e \u003cp\u003ePrimary: GSH, TAC, NO, MDA, and 8-OHdG. Secondary: hsCRP, IL-6, and TNF-α\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e \u003cp\u003eRandomized placebo-controlled trials\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSTUDY DESIGN: STARTS AS HIGH QUALITY\u003c/b\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eOutcome measure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eN. studies/N. Partic.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eDowngrading\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(levels, -1 or -2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003eUpgrading\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(levels\u0026thinsp;+\u0026thinsp;1 or +\u0026thinsp;2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003eKey findings\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRisk of bias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInconsistency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIndirectness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eImprecision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePublication bias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMagnitude/effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDose-response gradient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOthers\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eQuality of evidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGSH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12/\u003c/p\u003e \u003cp\u003e673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo serious risk of bias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVery Serious \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;75%\u003c/p\u003e \u003cp\u003e(-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStrongly suspected\u003c/p\u003e \u003cp\u003e(-1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLarge effect size (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo Plausible confounding (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eThe use of probiotics in patients with NCD probably increases GSH levels\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTAC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12/\u003c/p\u003e \u003cp\u003e679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo serious risk of bias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVery Serious \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;75%\u003c/p\u003e \u003cp\u003e(-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUndetected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo Plausible confounding (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eThe use of probiotics in patients with NCD probably increases TAC levels\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNO\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6/\u003c/p\u003e \u003cp\u003e348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSerious risk of bias (-1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVery Serious \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;75%\u003c/p\u003e \u003cp\u003e(-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVery Serious (-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStrongly suspected\u003c/p\u003e \u003cp\u003e(-1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo Plausible confounding (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eThere was no evidence of the effect estimate.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMDA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13/\u003c/p\u003e \u003cp\u003e708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo serious risk of bias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVery Serious \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;75%\u003c/p\u003e \u003cp\u003e(-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUndetected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLarge effect size (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo Plausible confounding (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eThe use of probiotics in patients with NCD does decrease MDA levels\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e8-OHdG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3/\u003c/p\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSerious risk of bias (-1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVery Serious \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;75%\u003c/p\u003e \u003cp\u003e(-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVery Serious (-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStrongly suspected\u003c/p\u003e \u003cp\u003e(-1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo Plausible confounding (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eThere was no evidence of the effect estimate.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ehsCRP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10/\u003c/p\u003e \u003cp\u003e545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo serious risk of bias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVery Serious \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;75%\u003c/p\u003e \u003cp\u003e(-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUndetected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo Plausible confounding (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eThe use of probiotics in patients with NCD probably decreases hsCRP levels\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIL-6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5/\u003c/p\u003e \u003cp\u003e262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo serious risk of bias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVery Serious \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;75%\u003c/p\u003e \u003cp\u003e(-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVery Serious (-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUndetected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo Plausible confounding (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eThere was no evidence of the effect estimate.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTNF-α\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5/\u003c/p\u003e \u003cp\u003e262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo serious risk of bias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVery Serious \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;75%\u003c/p\u003e \u003cp\u003e(-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSerious (-1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUndetected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLarge effect size (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo Plausible confounding (+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eThere was no evidence of the effect estimate.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eQuality of this RS\u0026amp;MA\u003c/h2\u003e \u003cp\u003eAccording to the AMSTAR 2, this RS\u0026amp;MA is a High Quality Review.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eBased on the review question highlighting the effects of probiotic consumption in improving conditions (O\u0026amp;NS markers and inflammatory process) associated with NCDs, we conducted this SR\u0026amp;MA. Fifteen studies (16 trials) were included, generally with patients between 18\u0026ndash;90 years of age and both biological sexes included, with few exceptions.\u003c/p\u003e \u003cp\u003eFirst, the quality of the studies included in this SR\u0026amp;MA was assessed. A low risk of bias was observed in most of the studies. In most them, there was an ideal randomization process (1:1 ratio of treatment to placebo arms) using a computer-generated code with randomly permuted blocks of randomly varying size. In most trials, the investigators and participants were also blinded throughout the trial, supporting the term \"double-blind\". However, some trials did not report whether there were measures to conceal allocation (participants and investigators). Other domains of risk of bias were in most cases in line with good practice for conducting RCTs. In general, it is important to note that the inclusion of three trials with high risk of bias [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] in this RS\u0026amp;MA did not have a relevant impact on the effect sizes or other parameters reported here, justifying such inclusions, which ultimately did not affect the quality of the present work.\u003c/p\u003e \u003cp\u003eRegarding the population, among the NCDs, endocrine \u0026amp; metabolic, with DM or DM plus comorbid, and one study with NAFLD were most commonly reported. Neurodegenerative diseases (PD and AD) were also frequently reported. The number of different NCDs may be reflected in different degrees of outcomes (O\u0026amp;NS and inflammation) and different need for formulations of probiotics. Although, for example, MS is a disease in which women are three times more likely to develop it, protocols among all trails provided that the mean age was matched, as well as biological sex when studies involved both sexes. In terms of intensity, the degree of O\u0026amp;NS and inflammation may vary according to the reported NCDs. For example, O\u0026amp;NS seems to be intense in different types of uncontrolled DM [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], while inflammation is a chronic complication that is relatively more pronounced in RA [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Current evidence suggests a relevant role for inflammation and O\u0026amp;NS in NAFLD and MS [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], as well as AD, PD and other psychiatric disorders [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Thus, in addition to probiotic formulation and dosage, disease severity and timing of administration have a profound impact on intervention outcomes.\u003c/p\u003e \u003cp\u003eRegarding the markers employed here, (hs)CRP, IL-6 and TNF-α are commonly used as appropriate inflammatory markers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The overall effect size showed a positive effect of probiotic intervention to reduce hsCRP levels, with evidence for its indication. In contrast, there was no evidence of probiotic effectiveness to decrease IL-6 and TNF-α levels.\u003c/p\u003e \u003cp\u003eAn optimum redox steady state (i.e. equilibrium of oxidants and antioxidants tone) is a physiological condition in healthy people. Oxidative/nitrosative stress represents a disruption in redox homeostasis when the generation of ROS/RNS exceeds the body's detoxification capacity, resulting in damage if not controlled by antioxidant defenses (i.e., measured by individual antioxidants from the human body, such as SOD, catalase, and GSH; or ultimately TAC) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Total antioxidant capacity (TAC) represents the amount of oxidants scavenged in an appropriate assay, so it reflects the total antioxidant defense of the body. An established framework of O\u0026amp;NS leads to biomolecule damage, e.g. lipid peroxidation upon hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) attack; this is tracked by plasma MDA levels as a by-product of such peroxidation, as it is a widely used marker of OS-mediated lipid damage [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Studies have pointed out that peroxidative tissue damage correlates with some NCDs severity, and also the significant impact of probiotics in preventing it [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In relation to nitrosative stress, this condition is caused only when a joint reaction of NO and O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026bull;\u0026minus;\u003c/sup\u003e occurs in the body (commonly when OS has already occurred), producing ONOO\u003csup\u003e\u0026minus;\u003c/sup\u003e [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This last RNS can nitrate biomolecules, including proteins, lipids, and DNA, for example, yielding 3-nitrotyrosine (3-NT) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In this sense, interpretation of nitrosative stress in health and disease conditions is complex and contextual.\u003c/p\u003e \u003cp\u003eIn terms of O\u0026amp;NS, the probiotic intervention promoted an overall effect (pooled result) with positive effects, i.e. increasing GSH levels and TAC, and decreasing MDA levels, with proven evidence of its effectiveness. Of clinical relevance, the extraction and presentation of O\u0026amp;NS markers from separate Forest plots was ideal because, as observed, there was evidence for a proven positive effect of the probiotic only to increase GSH levels and TAC and decrease MDA levels (and not for NO and 8-OHdG levels), so it is not recommended to generalize all of the markers (they are different from each other) in a single forest plot as for \"O\u0026amp;NS\". Also, it is biologically plausible as an interpretation, whereas a high total antioxidant defense (TAC, non-specific) does not necessarily increase a specific antioxidant defense, but was attested by an apparent effectiveness of probiotic in decreasing the levels of MDA, a lipid peroxidation product that appears when there is inefficiency of the specific defense against hydrogen peroxide, i.e. increased levels of the antioxidant enzyme catalase that detoxifies this oxidant, preventing attack on lipids. For example, SOD (not evaluated, it acts on O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026bull;\u0026minus;\u003c/sup\u003e) and GSH itself, associated with other type of antioxidant protection. This fact is confirmed, for example, by individual findings of Soleimani et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and Karamali et al. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], who showed that probiotic interventions significantly increased plasma TAC compared to placebo, but did not affect plasma NO and GSH levels.\u003c/p\u003e \u003cp\u003eThe Forest plots show that individual research results may in some cases have \"conflicting\" or \"ambiguous\" results regarding effect size measures. Most studies have shown significant positive effects (in favor of probiotics). In contrast, some other studies have shown negative effects. In health sciences, since physicians and policy makers (public health measures, for a decision on implementing a specific intervention) is not only interested in whether there is only a positive effect of supplemental probiotics on healthy biomarkers, but mainly in how large such effect is, as subgroup analysis can specify interventions to particular subgroups (as discussed below). To explain the possible positive effect of probiotics according to the effect size analysis, heterogeneity highlights that the results among studies can be different and this inconsistency within a single meta-analysis can be quantified with a statistical test (e.g. \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e) to assess whether the variation among studies is due to real differences (true heterogeneity) and not to chance. In terms of heterogeneity, there was a high degree of heterogeneity for all outcomes analyzed, with differences among studies mainly due to design, population (individual biology: age, genetic specificity, health and disease states; among others; or sample size), and mainly different treatment protocols with probiotic [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. For this purpose, the sample size of each trial was relatively small and there was considerable evidence of heterogeneity among trials. Frequency and duration of intervention were similar, but the number of microorganisms and CFUs varied considerably among trials. Due to the lack of evidence on an appropriate dosage of probiotics for patients with NCDs, different protocols were seen in the meta-analyzed trials.\u003c/p\u003e \u003cp\u003eOther meta-analyses on this topic corroborate our findings [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], and the comparisons regarding the results for the outcome measures are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. As clinical and methodological heterogeneity is common in the biomedical sciences, statistical heterogeneity is inevitable, as usually observed in a meta-analysis [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of comparisons among systematic reviews and meta-analyses (SR\u0026amp;MAs) for the effects of probiotic interventions on markers of oxidative and nitrosative stress (O\u0026amp;NS) and inflammation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSR\u0026amp;MA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDisease\u003c/p\u003e \u003cp\u003emodel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eMarkers of O\u0026amp;NS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eMarkers of inflammation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGSH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMDA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8-OHdG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ehsCRP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e \u003cp\u003eMain findings for the impact of probiotic on markers\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePresent\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNCD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEvidence\u003csup\u003ea\u003c/sup\u003e to \u0026uarr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEvidence to \u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo evidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEvidence to \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo evidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEvidence to \u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo evidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo evidence\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBohlouli et al. (2021)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetic\u003c/p\u003e \u003cp\u003enephropathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026uarr; levels\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo evidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDai\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eet al. (2022)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026uarr; levels\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026uarr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDeng\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eet al. (2020)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlzheimer\u0026rsquo;s disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo evidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo evidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo evidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026darr; levels\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTabrizi et al. (2019)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolycystic ovary syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026uarr; levels\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026uarr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr; levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFurthermore, most of the included studies, when analyzed individually, reported that after weeks of probiotic consumption (baseline/pre-treatment \u003cem\u003evs\u003c/em\u003e. intervention/post-treatment, as well as probiotic \u003cem\u003evs\u003c/em\u003e. placebo), significant effects of probiotic supplementation were observed (improvement in markers of inflammation, O\u0026amp;NS, and biomolecule damage), even reinforcing the fact that the pooled effect size (SMD) is sovereign over the statistical individualities and \u003cem\u003ep\u003c/em\u003e-values from isolated studies. However, the high heterogeneity means that the effect size of the meta-analysis for the variables analyzed may be related to the large variation in effect size among studies. Thus, it is considered likely that the studies in the meta-analysis are not estimating the exact same effect size, which added to other parameters, i.e. imprecision (CI, number of participants), must be taken into account to interpret evidence of the true impact of probiotic intervention, or lead to uncertainty of the evidence toward the effects in favor of placebo or probiotic. Exception for the outcomes GSH, TAC, MDA, and hsCRP, for which, despite heterogeneity, consistent evidence confirmed by the GRADE system supports the effectiveness of probiotic intervention on these markers of O\u0026amp;NS and inflammation in patients with NCDs.\u003c/p\u003e \u003cp\u003eIn that way, also aiming to better guide public health measures, i.e. decision on implementing a specific intervention, subgroup analysis was performed to solve the heterogeneity, in some subgroups it indicated specificity of probiotic effectiveness on some markers of O\u0026amp;NS and inflammation, particularly, for age bracket between 41\u0026ndash;60 (\u0026darr;MDA levels) and \u0026gt;\u0026thinsp;61 years (\u0026darr;hsCRP levels) and type of NCDs (NS/NDs, \u0026uarr;GSH and \u0026darr;hsCRP, respectively) or RA and POS (both with \u0026uarr;TAC); and strain number (in this case, only one strain) promotes an increase in GSH levels.\u003c/p\u003e \u003cp\u003eAs a limitation, the number of publications found in this study may be related to the fact that this is an emerging field/area of study that is still under construction, which is also confirmed by other studies [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], which reported \u0026sim; 4\u0026ndash;15 trials on this topic, supporting our findings. Moreover, not all included studies evaluated the same outcome variables selected in this SR\u0026amp;MA. In fact, with respect to the variables of O\u0026amp;NS, they showed a large variation among the studies.\u003c/p\u003e \u003cp\u003eSuggestions to strengthen the association between probiotic treatment and outcomes include the evaluation of gut microbiota. Most of the included RCTs did not measure such characteristics (e.g., fecal microbial load) before and after probiotic treatment, as well as characterization of the microbiome at baseline and after interventions. Strains of probiotic microorganisms for human consumption are usually derived from the human intestinal tract and are able to survive the rigors of the gastrointestinal tract and possibly colonize it, being biologically active against the target [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In this sense, most of the studies included in this SR\u0026amp;MA used them (mainly \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eStreptococcus\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, this is a high quality SR\u0026amp;MA of RCTs that provide evidence of the positive effects (effectiveness) of probiotics in increasing GSH levels and TAC, and decreasing MDA and hsCRP levels (4 out of 8 analyzed markers of O\u0026amp;NS and inflammation) in NCDs. Nevertheless, what is the most effective species and amount (dosage of CFUs, which reflects potency) are still unclear. Most of the information in this SR\u0026amp;MA comes from trials with a low risk of bias. To address questions about heterogeneity, subgroup analyses indicated some variables that may be related to heterogeneity, such as number of strains, age group, and type of NCD. In addition, the GRADE profiles indicated the certainty of evidence for the effectiveness of probiotic intervention on these markers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN.S.S. participated in development, searching for trials, eligibility screening, quality assessment, data extraction, data analysis, comment on drafts and review and is the guarantor of this SR\u0026amp;MA. C.D.C. conceived the concept and designed the study,\u0026nbsp;data curation,\u0026nbsp;searching for trials, eligibility screening, quality assessment of studies, data extraction, data analysis, writing and update of the text, comment on drafts and review,\u0026nbsp;Writing - Review \u0026amp; Editing\u0026nbsp;(final version), and is the guarantor of this SR\u0026amp;MA. T.M.R. participated in protocol development, comment on drafts and review; update of the text. M.R.R. participated in development, comment on drafts and review; update of the text, and supervision/advice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo datasets were generated during the current study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRaygan F, Rezavandi Z, Bahmani F, Ostadmohammadi V, Ali Mansournia M, TajabadiEbrahimi M, Borzabadi S, Asemi Z (2018) The effects of probiotic supplementation on metabolic status in type 2 diabetic patients with coronary heart disease. 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Gut 59:325e332 [CrossRef]\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"probiotics-and-antimicrobial-proteins","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"paap","sideBox":"Learn more about [Probiotics and Antimicrobial Proteins](http://link.springer.com/journal/12601)","snPcode":"12602","submissionUrl":"https://submission.nature.com/new-submission/12602/3","title":"Probiotics and Antimicrobial Proteins","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Total antioxidant capacity. GSH. CRP. Lactobacillus. Bifidobacterium. Dysbiosis","lastPublishedDoi":"10.21203/rs.3.rs-5791482/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5791482/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInflammation and oxidative/nitrosative stress (O\u0026amp;NS) are serious complications in non-communicable diseases (NCDs), including endocrine \u0026amp; metabolic and neurodegenerative diseases. The beneficial probiotic microbes, such as \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eStreptococcus\u003c/em\u003e, can decrease O\u0026amp;NS and inflammation. We conducted this systematic review and meta-analysis of randomized controlled trials (RCTs) to elucidate the effects of probiotics on O\u0026amp;NS and inflammation in NCDs. A systematic search of PubMed, Scopus and EMBASE resulted in the inclusion of studies if they met the eligibility criteria. Methodological quality was assessed using the Cochrane Risk of Bias 2 tool. Data (combined effect size) were analyzed using Meta Essentials software. Fifteen studies/16 trials with a total of 837 participants were reviewed. There was high and moderate certainty of evidence (GRADE) for the effectiveness of probiotic intervention (\u003cem\u003evs\u003c/em\u003e. placebo) in increasing (\u0026uarr;) glutathione (GSH) levels [SMD(SE)\u0026thinsp;=\u0026thinsp;0.89 (0.51)/\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, 95%CI -0.23 to 2.1, \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;92.77%] and total antioxidant capacity (TAC) [SMD(SE)\u0026thinsp;=\u0026thinsp;0. 75 (0.22)/\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, 95%CI 0.28 to 1.23, \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;87.50%] as well as decreased (\u0026darr;) malondialdehyde (MDA) (SMD(SE)\u0026thinsp;=\u0026thinsp;1.03 (0.31)/\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0. 01, 95%CI 0.37 to 1.7, \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;93.88%) and C-reactive protein (hsCRP) (SMD(SE)\u0026thinsp;=\u0026thinsp;0.74 (0.36)/\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, 95%CI -0.07 to 1.55, \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;94.32%). There was no effects on nitric oxide, 8-hydroxy-2\u0026prime;-deoxyguanosine, interleukin-6, and tumor necrosis factor-α. Subgroup analysis to reduce heterogeneity indicated probiotic effectiveness on strain number (one/\u0026uarr;GSH), age bracket (41\u0026ndash;60\u0026nbsp;year./\u0026darr;MDA or \u0026gt;\u0026thinsp;61\u0026nbsp;year./\u0026darr;hsCRP) and NCD (nervous system/neurodegenerative diseases/\u0026uarr;GSH and \u0026darr;hsCRP or rheumatoid arthritis/polycystic ovary syndrome/\u0026uarr;TAC). An overall low risk of bias was observed. In conclusion, probiotics may have beneficial effects on markers of O\u0026amp;NS and inflammation in patients with NCDs.\u003c/p\u003e","manuscriptTitle":"Effects of Probiotics on Markers of Oxidative/Nitrosative Stress and Damage Associated with Inflammation in Non-Communicable Diseases: a Systematic Review and Meta-Analysis of Randomized Placebo-Controlled Trials","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-15 11:53:41","doi":"10.21203/rs.3.rs-5791482/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-05T05:58:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-04T17:31:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-30T10:38:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"291432128397243336999172591813517127476","date":"2025-01-11T14:31:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172177085649295455613533330722062665473","date":"2025-01-11T08:05:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-11T07:20:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-10T09:20:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-10T09:18:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Probiotics and Antimicrobial Proteins","date":"2025-01-08T19:14:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"probiotics-and-antimicrobial-proteins","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"paap","sideBox":"Learn more about [Probiotics and Antimicrobial Proteins](http://link.springer.com/journal/12601)","snPcode":"12602","submissionUrl":"https://submission.nature.com/new-submission/12602/3","title":"Probiotics and Antimicrobial Proteins","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f0aa9e24-dc7a-4ff0-98d9-b6507cc6bc5a","owner":[],"postedDate":"January 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-01T06:23:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-15 11:53:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5791482","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5791482","identity":"rs-5791482","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}