Photobiomodulation Therapy Reduces Oxidative Stress and Modulates Postoperative Recovery in Abdominoplasty: A Pilot Study

Photobiomodulation Therapy Reduces Oxidative Stress and Modulates Postoperative Recovery in Abdominoplasty: A Pilot Study | 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 Research Article Photobiomodulation Therapy Reduces Oxidative Stress and Modulates Postoperative Recovery in Abdominoplasty: A Pilot Study Carmen Lucia Kretiska Araujo, Graziele Silveira Fardin, Ana Paula Bernardi, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7437378/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Photobiomodulation (PBM) has been proposed as a non-invasive therapeutic strategy to support wound healing and modulate oxidative and inflammatory responses. However, clinical data evaluating its effects in the postoperative period of abdominoplasty remain limited. This non-randomized clinical trial included 31 female patients undergoing abdominoplasty, divided into two groups: PBM intervention (n = 15) and control (n = 16). Salivary samples were collected at three time points: preoperative (T0), 48 hours postoperative (T1), and 7 days postoperative (T2). Inflammatory markers (TNF-α, IL-10), oxidative stress indicators (TBARS, nitrites), and pain scores were assessed. PBM was applied once using an 808 nm infrared laser (100 mW, 3 J/point) before hospital discharge. Statistical analyses included the Shapiro-Wilk test, Friedman test, Mann-Whitney U test, Spearman’s correlation, and multiple linear regression. PBM showed no significant changes in TNF-α, IL-10, nitrites, or pain scores compared to the control group. However, a statistically significant reduction in TBARS levels was observed at 48 hours postoperative in the PBM group (p = 0.040), suggesting a potential antioxidant effect. Physical activity was associated with lower nitrite concentrations (p = 0.047), indicating a modulatory interaction between exercise and nitric oxide metabolism. Although a single session of PBM did not significantly alter most inflammatory and oxidative markers, it appeared to reduce lipid peroxidation and was well tolerated. These preliminary results support the safety of PBM in the postoperative period of abdominoplasty. Further randomized studies with larger sample sizes and multiple applications are warranted to better elucidate its therapeutic potential. Photobiomodulation Therapy Abdominoplasty Oxidative Stress Cytokines Postoperative Pain Introduction Wound healing is a complex biological process involving the coordinated action of inflammatory cells, epidermal and dermal cells, extracellular matrix components, blood vessels, and plasma-derived proteins, all regulated by cytokines and growth factors (Dorantes et al., 2019). This physiological process is essential for tissue repair following injury or surgical procedures. However, wound healing becomes more challenging in the presence of inflammatory complications, especially after high-complexity procedures such as abdominoplasty. Photobiomodulation (PBM) has emerged as a promising, non-invasive therapeutic strategy that uses low-level light to modulate cellular processes and accelerate wound healing (Leyane et al., 2021 ). PBM interacts with mitochondrial components—primarily cytochrome c oxidase—increasing ATP synthesis, promoting tissue repair, and activating cellular signaling pathways involved in regeneration (Raja et al., 2024 ; Tang & Arany, 2016 ). It has been shown to stimulate fibroblast proliferation and migration, improve extracellular matrix deposition, and enhance collagen production, all of which are essential for effective healing. These effects are particularly relevant in pathological conditions such as diabetic wounds, where fibroblast function is often impaired (Jere & Houreld, 2024 ). Additionally, PBM can regulate gene expression during the healing process, downregulating matrix metalloproteinases (MMP2 and MMP9) and pro-inflammatory cytokines such as IL-6 and IL-10, while upregulating genes like DNMT3A and bFGF, which are associated with improved wound outcomes (Pilar et al., 2024 ). Clinical trials have also shown that PBM improves scar quality during the early stages of healing when compared to untreated scars, although its long-term effects appear to diminish after one year (Ramos et al., 2019 ). Despite encouraging findings, the efficacy of PBM is highly dependent on parameters such as light source, wavelength, energy density, pulse structure, and application duration (Leyane et al., 2021 ). The effects of PBM in the acute postoperative period, particularly on inflammatory and oxidative markers in surgical patients, remain poorly explored. Abdominoplasty provides a robust clinical model due to its extensive tissue manipulation and inflammatory response. Therefore, the present study aimed to evaluate the effect of a single PBM session during the acute healing phase following abdominoplasty by analyzing inflammatory biomarkers (TNF-α and IL-10) and oxidative stress markers (TBARS and nitrites) in saliva. Saliva offers a non-invasive, easily accessible matrix for monitoring inflammatory and oxidative biomarkers, complementing systemic assessments in surgical recovery These biomarkers were selected due to their relevance in tissue repair, systemic inflammation, and nitric oxide metabolism. Methods Study Design and Ethical Considerations This was a non-randomized clinical trial conducted at the Plastic Surgery Service of Irmandade Santa Casa de Misericórdia de Porto Alegre, Brazil. The study protocol was approved by the Institutional Ethics Committee (approval number 6.308.240) and conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants. . Participants and Group Allocation Eligible participants were women aged 18 years or older scheduled for elective abdominoplasty. Exclusion criteria included acute inflammatory or infectious conditions, use of photosensitizing medications, HIV positivity, pregnancy, lactation, and tattoos on the abdominal region. Participants were allocated into two groups: Intervention group (PBM group) : received photobiomodulation after surgery and Control group : received standard postoperative care with no PBM. All participants received the same postoperative physical therapy instructions, including posture adjustments and wound care. Photobiomodulation Protocol PBM was applied using an 808 nm infrared laser (Elight IRL, DMC, São Carlos, Brazil) in cluster mode, with 100 mW output power per diode, continuous emission mode, and perpendicular positioning at a distance of 1 cm from the abdominal skin. The total energy delivered was 3 J per point, applied for 30 seconds per site in a single session prior to hospital discharge. A custom template based on the anatomical vascular zones described by Huger (1979) was developed to standardize the irradiation area. The template covered 36 cm × 9 cm, marked with 144 points spaced 1 cm apart. Anatomical landmarks (e.g., iliac crests and costal margins) were used to align the template. All safety protocols were followed, including protective eyewear and equipment disinfection. Saliva Collection and Biomarker Analysis Saliva samples were collected at three time points: T0 : 1 to 6 hours before surgery (in-hospital); T1 : 48 hours postoperatively (home collection) and T2 : 7 days postoperatively (home collection) For T1 and T2, patients collected saliva in the morning while fasting, using Salivette® kits. Samples were stored in home freezers and later transported to the laboratory. A video call was conducted at each time point to verify correct sample collection and assess pain using the Visual Analog Scale (VAS). Samples were stored at − 80°C at the Cellular and Molecular Immunology Laboratory (UFCSPA). For deproteinization, 500 µL of saliva was mixed with 500 µL of absolute ethanol at room temperature and centrifuged at 3000 rpm for 10 minutes. Supernatants were collected and stored at − 80°C. Saliva Deproteinization To prepare samples for biochemical analysis, 500 µL of saliva were mixed with 500 µL of absolute ethanol at room temperature. The mixture was then centrifuged at 3,000 rpm for 10 minutes. Protein precipitation was achieved by centrifugation, and the resulting supernatant was collected and stored in microtubes at − 80°C for subsequent assays. Cytokines (TNF-α and IL-10) Analysis Quantified using ELISA kits (Peprotech/Thermo Fisher scientific) according to manufacturer instructions. Detection ranges were 23–3000 pg/mL. Nitrite Quantification (Griess Reaction) Nitrite levels were measured as an indicator of nitric oxide (NO) availability using the Griess reaction. For each well of a 96-well plate, 50 µL of deproteinized saliva were added along with 50 µL of Griess reagent, which consisted of 5% phosphoric acid (H₃PO₄), 2% sulfanilamide, 0.2% N-(1-naphthyl)ethylenediamine dihydrochloride (NEED), and ultrapure water. The plate was incubated for 1 hour at 37°C, and absorbance was read at 540 nm using a spectrophotometer. Concentrations were determined based on a standard curve. Lipid Peroxidation Assay (MDA-TBARS Test) Lipid peroxidation was assessed using the MDA-TBARS method as described by Ohkawa, Ohishi, and Yagi (1979). A total of 200 µL of deproteinized saliva were pipetted into separate test tubes. Each tube received 375 µL of acetic acid (2.5 M, pH 3.4), 375 µL of thiobarbituric acid (0.8%), and 500 µL of sodium dodecyl sulfate (8.1%). The reaction mixture was incubated in a water bath at 100°C for 1 hour, followed by centrifugation at 5,000 g for 15 minutes. The resulting supernatant was transferred to a 96-well plate and read at 532 nm using a microplate spectrophotometer. Final concentrations were calculated from absorbance values using a standard curve. Statistical Analysis Statistical analyses were performed using Python with appropriate statistical packages (e.g., scipy). Data were tested for normality using the Shapiro-Wilk test. For continuous variables, non-parametric comparisons between groups were performed using the Mann-Whitney U test. Repeated measures over time were analyzed using the Friedman test. Correlations were assessed using Spearman’s rank correlation coefficient. Multiple linear regression was used to assess predictors of biomarker levels (age, BMI, physical activity, surgical history). A significance level of 5% (p < 0.05) was adopted for all analyses. Results A total of 31 patients completed the study, with 15 in the PBM group and 16 in the control group.The PBM group had a mean age of 46.8 ± 9.3 years, while the control group presented a similar age profile, with a mean of 48.4 ± 8.5 years. The mean body mass index (BMI) was also comparable between groups, with 26.5 ± 2.5 kg/m² in the PBM group and 26.2 ± 2.0 kg/m² in the control group. Regarding ethnicity, 81.2% of participants in the PBM group and 86.7% in the control group self-identified as white. Tobacco exposure (current or former smoking) was reported by 18.8% of participants in the PBM group and 40.0% in the control group. The average length of follow-up with the surgical team was 25.3 ± 16.4 months in the PBM group and 27.3 ± 16.0 months in the control group. Pain perception was evaluated on postoperative days 2 and 7. On day 2 (T1), the PBM group reported a mean pain score of 2.7 ± 2.1, compared to 3.8 ± 2.7 in the control group. By day 7 (T2), mean pain levels had decreased in both groups, reaching 1.2 ± 1.3 in the PBM group and 1.4 ± 1.4 in the control group. Descriptive statistics for each biomarker are presented in Table 1 . Among the analyzed salivary biomarkers (TNF, IL-10, nitrite, and TBARS), no statistically significant changes were observed within groups over time for TNF, IL-10, or nitrite, nor between groups at any specific time point. However, a significant difference was detected for TBARS between the PBM and control groups at 48 hours postoperatively (T1) (p = 0.034). This suggests that photobiomodulation may exert an early modulatory effect on oxidative stress following abdominoplasty, as reflected by lower lipid peroxidation levels in the intervention group at this time point. Table 1 Descriptive statistics for salivary biomarkers at baseline (T0), 48 hours postoperatively (T1), and 7 days postoperatively (T2), for the photobiomodulation (PBM) and control groups. Biomarker Timepoint Group Mean ± SD Median [IQR] TNF T0 PBM (n = 15) 19.29 ± 8.35 14.35 [12.42–25.95] TNF T0 Control (n = 16) 20.45 ± 7.83 20.75 [12.74–22.79] TNF T1 PBM (n = 15) 18.10 ± 6.67 13.57 [12.65–23.12] TNF T1 Control (n = 16) 32.19 ± 54.66 19.09 [12.44–22.82] TNF T2 PBM (n = 15) 17.09 ± 6.48 12.58 [12.40–22.66] TNF T2 Control (n = 16) 18.26 ± 5.38 19.23 [12.61–21.53] IL10 T0 PBM (n = 15) 6.13 ± 8.77 4.00 [3.60–4.39] IL10 T0 Control (n = 16) 6.48 ± 10.07 3.77 [3.59–4.18] IL10 T1 PBM (n = 15) 6.06 ± 8.82 3.76 [3.63–4.29] IL10 T1 Control (n = 16) 7.22 ± 12.33 4.06 [3.54–4.69] IL10 T2 PBM (n = 15) 9.04 ± 13.47 3.88 [3.49–4.38] IL10 T2 Control (n = 16) 3.92 ± 0.67 3.68 [3.53–4.12] Nitrito T0 PBM (n = 15) 2.03 ± 1.77 1.67 [1.37–2.13] Nitrito T0 Control (n = 16) 2.99 ± 4.69 1.74 [1.31–2.54] Nitrito T1 PBM (n = 15) 2.36 ± 1.79 2.11 [1.81–2.28] Nitrito T1 Control (n = 16) 2.56 ± 1.77 2.30 [1.43–2.83] Nitrito T2 PBM (n = 15) 1.99 ± 0.77 2.08 [1.39–2.37] Nitrito T2 Control (n = 16) 2.05 ± 0.83 1.99 [1.37–2.45] TBARS T0 PBM (n = 15) 0.51 ± 0.45 0.23 [0.22–0.81] TBARS T0 Control (n = 16) 0.25 ± 0.11 0.22 [0.22–0.23] TBARS T1 PBM (n = 15) 0.50 ± 0.49 0.24 [0.22–0.61] TBARS T1 Control (n = 16) 0.24 ± 0.05 0.22 [0.22–0.23] TBARS T2 PBM (n = 15) 0.36 ± 0.40 0.22 [0.22–0.25] TBARS T2 Control (n = 16) 0.24 ± 0.07 0.22 [0.22–0.24] Data are presented as mean ± standard deviation and median [interquartile range]. TNF: tumor necrosis factor alpha; IL-10: interleukin-10; TBARS: thiobarbituric acid reactive substances. The Friedman test showed no significant temporal variation in TNF-α and IL-10 levels (p > 0.05). TBARS significantly decreased in the PBM group from T0 to T1 (p 0.05). Pain scores significantly decreased over time in both groups (p < 0.05). Correlation Analysis Spearman correlation analysis was conducted to explore potential associations between baseline salivary biomarkers (TNF, IL-10, and TBARS) and postoperative pain scores on days 2 and 7. No statistically significant correlations were identified (p < 0.05). However, some moderate, non-significant trends were observed: A moderate positive correlation between TNF and IL-10 (r = 0.34; p = 0.061); A weak-to-moderate positive correlation between TBARS and pain on postoperative day 2 (r = 0.24; p = 0.188); A weak-to-moderate positive correlation between TBARS and pain on day 7 (r = 0.26; p = 0.151). Pain scores on days 2 and 7 were significantly correlated with each other (r = 0.64; p < 0.001), suggesting consistency in individual pain perception throughout the postoperative recovery. Overall, these findings indicate that inflammatory and oxidative stress biomarkers at baseline are not strongly associated with short-term clinical outcomes such as postoperative pain. Multiple Linear Regression Analysis Multiple linear regression analyses were conducted to evaluate whether age, BMI, previous surgeries, bariatric surgery, and physical activity influenced salivary levels of TNF-α, IL-10, TBARS, and nitrites at baseline (T0). For TNF-α, the model had a low explanatory power (adjusted R² = -0.037), with no statistically significant predictors (p > 0.05). Although not significant, BMI (β = 0.89; p = 0.225) and physical activity (β = 3.30; p = 0.361) showed positive trends. The IL-10 model demonstrated an adjusted R² of -0.139, and none of the predictors reached statistical significance. Age showed a weak and non-significant negative association (β = -0.15; p = 0.493). For TBARS, the adjusted R² was − 0.043, again indicating limited explanatory value of the predictors. BMI (β = 0.05; p = 0.119) and age (β = -0.0067; p = 0.402) showed weak, non-significant trends. In contrast, the model for nitrites yielded a higher adjusted R² (0.045), and physical activity was a statistically significant negative predictor (β = -3.09; p = 0.047). Participants who reported engaging in physical activity within the past six months had significantly lower nitrite levels compared to sedentary individuals. Overall, the models suggest that demographic and clinical variables had limited ability to explain the variance in inflammatory and oxidative stress markers. However, physical activity may play a relevant role in modulating nitrite metabolism, potentially reflecting more efficient regulation of nitric oxide pathways. Discussion Despite the growing interest in the effects of photobiomodulation (PBM) on inflammatory and oxidative processes, studies that explore the association between salivary biomarkers and clinical outcomes in patients undergoing abdominal surgery remain scarce. Salivary biomarkers have emerged as a promising tool for monitoring postoperative recovery, as they allow for the simultaneous assessment of local and systemic inflammatory responses. While their application has been well documented in oral and maxillofacial surgery, where they provide insight into tissue healing and inflammatory modulation (Popa et al., 2024 ). Furthermore, the non-invasive nature of saliva collection makes this approach particularly advantageous in populations for whom blood sampling may be challenging, such as pediatric or post-surgical patients with limited venous access (Orzechowska-Wylegala et al., 2024). This underscores the novelty and clinical relevance of the present study, as one of the few investigations applying salivary biomarker analysis to monitor recovery in abdominal aesthetic surgery. TNF-α levels in both groups were within or slightly below the reference ranges reported for healthy adults in recent literature, rather than indicating a heightened inflammatory state as initially assumed. Reported reference values for salivary TNF-α vary considerably across studies, ranging approximately from 22 to 47 pg/mL (Rathinasamy et al., 2020 ; Chaudhuri et al., 2018 ). Such discrepancies likely reflect methodological and population differences, underscoring the need for standardization when interpreting salivary cytokine data in clinical research. In our study, values were at the lower end of the healthy range, suggesting that participants were not markedly pro-inflammatory at baseline. The greater variability observed in the PBM group suggests heterogeneous individual responses to treatment, while the slight reduction over time may reflect a normal postoperative resolution of inflammation. No significant between-group differences were detected. IL-10, a key anti-inflammatory cytokine, showed elevated mean values across both groups, with consistently higher levels in the PBM group. This pattern suggests a postoperative anti-inflammatory response, potentially enhanced by PBM. Previous studies in facial surgery have shown that PBM can modulate cytokine activity, including IL-10, thereby reducing inflammation and supporting tissue repair (Al-Thobaiti et al., 2023). These effects are attributed to PBM’s ability to regulate immune responses, stimulate mitochondrial activity, and promote tissue regeneration. Nevertheless, variability in PBM protocols and the absence of standardized guidelines may contribute to inconsistent clinical outcomes. The increased IL-10 expression observed postoperatively may also reflect a compensatory response to surgical trauma, as previously reported (Short et al., 2021 ; Short et al., 2022 ). Although some studies indicate that PBM may stimulate IL-10 release, our findings did not demonstrate significant between-group differences, which could be explained by individual variability, limited PBM exposure, or differences in baseline inflammatory status. The wide dispersion of IL-10 responses observed, particularly in the PBM group, reinforces the notion of heterogeneous effects potentially modulated by metabolic and immunological factors. TBARS concentrations, used as an indirect marker of oxidative stress and lipid peroxidation, showed a reduction in the PBM group compared to baseline, suggesting an acute antioxidant effect. This aligns with experimental evidence from animal models of diabetes, arthritis, and high-intensity exercise, where PBM decreased lipid peroxidation (Frigero et al., 2018 ; Santos et al., 2017 ) and enhanced antioxidant defenses, such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) activities. Variability in TBARS assay results and differences in PBM parameters (wavelength, dosage) may explain inconsistent findings across studies (Rupel et al., 2018 ; Ghani et al., 2005). Taken together, these results support a potential antioxidant role for PBM in surgical recovery, but standardized clinical protocols are needed to confirm its efficacy. Nitrite levels remained within reference ranges in both groups, with no significant temporal variation. However, participants reporting regular physical activity in the preceding six months showed lower baseline nitrite levels, supporting the hypothesis that exercise modulates nitric oxide (NO) metabolism by upregulating endothelial nitric oxide synthase (eNOS), enhancing vasodilation, and improving vascular health (Arefirad et al., 2022 ; Woo, 2022 ). Regular exercise also reduces oxidative stress, thereby preserving NO bioavailability (Nosarev et al., 2015 ; Cangemi et al., 2017 ). The lower nitrite levels in active participants may therefore reflect more efficient NO turnover and reduced nitrite accumulation, consistent with the cardiovascular benefits of physical activity. Pain intensity, assessed on days 2 (D2) and 7 (D7) postoperatively, decreased significantly in both groups over time. Although no statistically significant between-group differences were found, the PBM group consistently exhibited numerically lower pain scores, which may have clinical relevance. Pain scores at D2 and D7 were strongly correlated (r = 0.64; p < 0.001), indicating stable pain perception patterns during early recovery. The analgesic effects of PBM are likely mediated by multiple mechanisms, including modulation of inflammatory mediators, reduction of ROS, stimulation of mitochondrial ATP production, promotion of angiogenesis and lymphatic drainage, and modulation of nociceptive pathways with endogenous opioid release (Al-Thobaiti et al., 2023). Clinical studies in dental and surgical procedures have shown that PBM can reduce postoperative pain, swelling, and functional limitations (Ganguly et al., 2024 ; Cirisola et al., 2023 ; Angolkar et al., 2024 ). However, variability in PBM parameters remains a limitation for standardization (Pergolini et al., 2022 ; Hosseinpour et al., 2019 ; Collado-Murcia et al., 2024 ). The trend toward lower pain scores in the PBM group in our study is consistent with the literature, supporting PBM’s potential as an adjunct for postoperative analgesia. The relationship between inflammatory/oxidative markers and postoperative pain perception is complex and multifactorial, involving both peripheral and central nociceptive mechanisms. In our study, Spearman correlations between inflammatory/oxidative markers and pain scores revealed no statistically significant associations, although moderate trends were observed for TNF vs. IL-10 and TBARS vs. pain. These trends suggest that inflammatory markers alone may not fully explain perceived pain or recovery dynamics. TBARS levels showed a non-significant trend toward association with pain scores, consistent with the hypothesis that oxidative stress may contribute to postoperative discomfort. The absence of statistically significant correlations could be due to the relatively small sample size, interindividual variability in inflammatory responses, and potential confounders such as anesthetic regimen, analgesic protocols, and baseline health status. Overall, while inflammation and oxidative stress are biologically plausible contributors to postoperative pain, their impact is modulated by metabolic status, surgical technique, pharmacological management, and psychosocial factors. The lack of significant associations in this dataset highlights the multifactorial nature of postoperative pain and underscores the need for integrative approaches in future research. Studies with larger samples, multimodal biomarker panels, and standardized analgesic regimens will be essential to clarify mechanistic links between inflammation, oxidative stress, and pain in surgical recovery. Several methodological limitations must be acknowledged. The small sample size (n = 31) may have limited statistical power to detect subtle between-group differences or biomarker–pain associations. Biological variability, including age, comorbidities, and individual recovery responses, may have influenced biomarker levels and pain perception. The three assessment timepoints may not fully capture the dynamic fluctuations in inflammatory and oxidative markers following surgery. Furthermore, variability in PBM application parameters and the limited number of sessions could have influenced treatment effects. Future studies should employ larger cohorts, extended follow-up, and more frequent biomarker assessments (e.g., 24 h, 48 h, 72 h) to capture the temporal dynamics of recovery. Incorporating standardized PBM protocols and evaluating dose–response relationships will be crucial for optimizing clinical applicability. Declarations Clinical trial number not applicable Ethics approval and consent to participate The study protocol was approved by the institution’s Research Ethics Committee (approval number 6.308.240) and followed the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants. Competing interests The authors declare that they have no competing interests. Funding This study was supported by grants from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Finance Code 001) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). Alessandra Peres is grateful to CNPq for the research productivity scholarship. Author Contribution Conceptualization: Alessandra Peres, Carmen Lucia Kretiska Araujo, Patricia Viana da Rosa. Data curation: Alessandra Peres, Carmen Lucia Kretiska Araujo, Graziele Silveira Fardin. Formal analysis: Carmen Lucia Kretiska Araujo, Ana Paula Bernardi, Ricardo Vitiello Schramm, Isadora Frois Ourique, Maria Luiza Santos, Betina Vescovi, Tássio Fernando Crusius, Flávia Marafon, Denis Valente e Níveo Steffen. Funding acquisition: Alessandra Peres, Investigation: Alessandra Peres, Carmen Lucia Kretiska Araujo, Patricia Viana da Rosa, Graziele Silveira Fardin, Joane Severo Ribeiro. Methodology: Alessandra Peres, Carmen Lucia Kretiska Araujo, Graziele Fardin Project administration: Alessandra Peres. Resources: Alessandra Peres. Supervision and Validation: Alessandra Peres. Visualization: Joane Severo Ribeiro. Writing – original draft: Alessandra Peres, Carmen Lucia Kretiska Araujo, Graziele Silveira Fardin, Joane Severo Ribeiro Writing – review & editing: all authors. Data Availability The datasets generated and/or analyzed during the current study are not publicly available due to privacy and ethical restrictions involving patient data. 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Aesthetic Plast Surg 43(1):147–154. 10.1007/s00266-018-1271-2 Rathinasamy K, Ulaganathan A, Ramamurthy S, Ganesan R, Saket P, Alamelu S (2020) Estimation of TNF-α levels in saliva and serum of patients with periodontal health and chronic periodontitis: a case-control study. J Contemp Dent Pract 21(2):148–151 PMID: 32381818 Rupel K, Zupin L, Colliva A, Kamada AJ, Poropat A, Ottaviani G, Gobbo M, Fanfoni L, Gratton R, Santoro MM, Di Lenarda R, Biasotto M, Zacchigna S (2018) Photobiomodulation at multiple wavelengths differentially modulates oxidative stress in vitro and in vivo. Oxid Med Cell Longev 2018:6510159. 10.1155/2018/6510159 Short WD, Wang X, Li H, Yu L, Kaul A, Calderon GA, Gilley J, Bollyky PL, Balaji S, Keswani SG (2021) Interleukin-10 producing T lymphocytes attenuate dermal scarring. Ann Surg 274(4):627–636. 10.1097/SLA.0000000000004984 Short WD, Rae MM, Lu T, Padon BW, Prajapati TJ, Faruk F, Olutoye OO, Yu L, Bollyky PL, Keswani SG, Balaji S (2022) Endogenous IL-10 contributes to wound healing and regulates tissue repair. bioRxiv. 10.1101/2022.03.15.484452 Tang BSGE, Arany RP (2016) Tissue regeneration with photobiomodulation. Proc SPIE. 10.1117/12.2019284 Woo J (2022) Exercise and function of nitric oxide. Korean Int Res Found 1(2):55–64. 10.56336/kirf.2022.1.2.55 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-7437378","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":513808808,"identity":"d66c4feb-2eea-4955-a8f3-136d2d8c72d6","order_by":0,"name":"Carmen Lucia Kretiska Araujo","email":"","orcid":"","institution":"Universidade Federal de Ciências da Saúde de Porto Alegre","correspondingAuthor":false,"prefix":"","firstName":"Carmen","middleName":"Lucia Kretiska","lastName":"Araujo","suffix":""},{"id":513808809,"identity":"8b43885e-c73d-42e0-a13f-d5840bd5b4ae","order_by":1,"name":"Graziele Silveira Fardin","email":"","orcid":"","institution":"Universidade Federal de Ciências da Saúde de Porto Alegre","correspondingAuthor":false,"prefix":"","firstName":"Graziele","middleName":"Silveira","lastName":"Fardin","suffix":""},{"id":513808810,"identity":"ec487a66-7413-4a00-94d1-337bf3b0e5f7","order_by":2,"name":"Ana Paula Bernardi","email":"","orcid":"","institution":"Universidade Federal de Ciências da Saúde de Porto Alegre","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Paula","lastName":"Bernardi","suffix":""},{"id":513808811,"identity":"fa45e9a8-b131-444d-9808-6bbbce5572d6","order_by":3,"name":"Joane Severo Ribeiro","email":"","orcid":"","institution":"Universidade Federal de Jataí","correspondingAuthor":false,"prefix":"","firstName":"Joane","middleName":"Severo","lastName":"Ribeiro","suffix":""},{"id":513808812,"identity":"51929967-1694-4bd7-9d93-0d2028ca299a","order_by":4,"name":"Ricardo Vitiello Schramm","email":"","orcid":"","institution":"Universidade Federal de Ciências da Saúde de Porto Alegre","correspondingAuthor":false,"prefix":"","firstName":"Ricardo","middleName":"Vitiello","lastName":"Schramm","suffix":""},{"id":513808813,"identity":"419ad588-5bfa-4ad5-9433-cf11cae27c62","order_by":5,"name":"Isadora Frois Ourique","email":"","orcid":"","institution":"Universidade Federal de Ciências da Saúde de Porto Alegre","correspondingAuthor":false,"prefix":"","firstName":"Isadora","middleName":"Frois","lastName":"Ourique","suffix":""},{"id":513808814,"identity":"edbd79bc-704f-4c78-9739-fe1ccd26c2b6","order_by":6,"name":"Maria Luiza Santos","email":"","orcid":"","institution":"Universidade Federal de Ciências da Saúde de Porto Alegre","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Luiza","lastName":"Santos","suffix":""},{"id":513808815,"identity":"cc634639-c69c-4108-8aef-af1131b24823","order_by":7,"name":"Betina Vescovi","email":"","orcid":"","institution":"Universidade Federal de Ciências da Saúde de Porto 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Alegre","correspondingAuthor":false,"prefix":"","firstName":"Denis","middleName":"","lastName":"Valente","suffix":""},{"id":513808819,"identity":"424bca4e-5a18-4074-9361-ad268500c0db","order_by":11,"name":"Níveo Steffen","email":"","orcid":"","institution":"Universidade Federal de Ciências da Saúde de Porto Alegre","correspondingAuthor":false,"prefix":"","firstName":"Níveo","middleName":"","lastName":"Steffen","suffix":""},{"id":513808821,"identity":"b2a5b978-2073-4d82-9a12-a5a189ad5d49","order_by":12,"name":"Patrícia Viana da Rosa","email":"","orcid":"","institution":"Universidade Federal de Ciências da Saúde de Porto Alegre","correspondingAuthor":false,"prefix":"","firstName":"Patrícia","middleName":"Viana da","lastName":"Rosa","suffix":""},{"id":513808823,"identity":"e69b4e91-f32f-4723-9e39-32e7f8571a9f","order_by":13,"name":"Alessandra Peres","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIie3QMQuCQBTA8XcIuiiuL7TvcCBk4ZdJAl2i2UHiJifFLxB9jPY4sMV2t3Jptk2XqCAIIi7dGu6/vLf84N0ByGR/WwTma1MAsBcpYcSGEZIMIa6W1XW35Wjmx30DkeczKzsLySw9OI6x44jVaoFQhj6zD1RIaBWoFtnxNUWdIkm4zzAQH0ZPF63rNhypWTotufUhlaqCwR4ElhMkrAeZpYFi6UX4fEswnRehk9iFmLhaQa5t7D1/jFdN7I1zK/lx2HvVAeaPoYrBJ5HJZDLZt+6Lw0EJhniD9QAAAABJRU5ErkJggg==","orcid":"","institution":"Universidade Federal de Ciências da Saúde de Porto Alegre","correspondingAuthor":true,"prefix":"","firstName":"Alessandra","middleName":"","lastName":"Peres","suffix":""}],"badges":[],"createdAt":"2025-08-22 21:09:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7437378/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7437378/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93439576,"identity":"4f93ca96-8219-4991-8b73-6b4d20e374f1","added_by":"auto","created_at":"2025-10-13 22:01:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":736946,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7437378/v1/6e326b4a-d9ff-48b6-b05a-9899b5c08d79.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Photobiomodulation Therapy Reduces Oxidative Stress and Modulates Postoperative Recovery in Abdominoplasty: A Pilot Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWound healing is a complex biological process involving the coordinated action of inflammatory cells, epidermal and dermal cells, extracellular matrix components, blood vessels, and plasma-derived proteins, all regulated by cytokines and growth factors (Dorantes et al., 2019). This physiological process is essential for tissue repair following injury or surgical procedures. However, wound healing becomes more challenging in the presence of inflammatory complications, especially after high-complexity procedures such as abdominoplasty.\u003c/p\u003e\u003cp\u003ePhotobiomodulation (PBM) has emerged as a promising, non-invasive therapeutic strategy that uses low-level light to modulate cellular processes and accelerate wound healing (Leyane et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). PBM interacts with mitochondrial components\u0026mdash;primarily cytochrome c oxidase\u0026mdash;increasing ATP synthesis, promoting tissue repair, and activating cellular signaling pathways involved in regeneration (Raja et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Tang \u0026amp; Arany, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). It has been shown to stimulate fibroblast proliferation and migration, improve extracellular matrix deposition, and enhance collagen production, all of which are essential for effective healing. These effects are particularly relevant in pathological conditions such as diabetic wounds, where fibroblast function is often impaired (Jere \u0026amp; Houreld, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAdditionally, PBM can regulate gene expression during the healing process, downregulating matrix metalloproteinases (MMP2 and MMP9) and pro-inflammatory cytokines such as IL-6 and IL-10, while upregulating genes like DNMT3A and bFGF, which are associated with improved wound outcomes (Pilar et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Clinical trials have also shown that PBM improves scar quality during the early stages of healing when compared to untreated scars, although its long-term effects appear to diminish after one year (Ramos et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite encouraging findings, the efficacy of PBM is highly dependent on parameters such as light source, wavelength, energy density, pulse structure, and application duration (Leyane et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The effects of PBM in the acute postoperative period, particularly on inflammatory and oxidative markers in surgical patients, remain poorly explored. Abdominoplasty provides a robust clinical model due to its extensive tissue manipulation and inflammatory response.\u003c/p\u003e\u003cp\u003eTherefore, the present study aimed to evaluate the effect of a single PBM session during the acute healing phase following abdominoplasty by analyzing inflammatory biomarkers (TNF-α and IL-10) and oxidative stress markers (TBARS and nitrites) in saliva. Saliva offers a non-invasive, easily accessible matrix for monitoring inflammatory and oxidative biomarkers, complementing systemic assessments in surgical recovery These biomarkers were selected due to their relevance in tissue repair, systemic inflammation, and nitric oxide metabolism.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Ethical Considerations\u003c/h2\u003e\u003cp\u003eThis was a non-randomized clinical trial conducted at the Plastic Surgery Service of Irmandade Santa Casa de Miseric\u0026oacute;rdia de Porto Alegre, Brazil. The study protocol was approved by the Institutional Ethics Committee (approval number 6.308.240) and conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants. .\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParticipants and Group Allocation\u003c/h3\u003e\n\u003cp\u003eEligible participants were women aged 18 years or older scheduled for elective abdominoplasty. Exclusion criteria included acute inflammatory or infectious conditions, use of photosensitizing medications, HIV positivity, pregnancy, lactation, and tattoos on the abdominal region.\u003c/p\u003e\u003cp\u003eParticipants were allocated into two groups: \u003cb\u003eIntervention group (PBM group)\u003c/b\u003e: received photobiomodulation after surgery and \u003cb\u003eControl group\u003c/b\u003e: received standard postoperative care with no PBM.\u003c/p\u003e\u003cp\u003eAll participants received the same postoperative physical therapy instructions, including posture adjustments and wound care.\u003c/p\u003e\n\u003ch3\u003ePhotobiomodulation Protocol\u003c/h3\u003e\n\u003cp\u003ePBM was applied using an 808 nm infrared laser (Elight IRL, DMC, S\u0026atilde;o Carlos, Brazil) in cluster mode, with 100 mW output power per diode, continuous emission mode, and perpendicular positioning at a distance of 1 cm from the abdominal skin. The total energy delivered was 3 J per point, applied for 30 seconds per site in a single session prior to hospital discharge.\u003c/p\u003e\u003cp\u003eA custom template based on the anatomical vascular zones described by Huger (1979) was developed to standardize the irradiation area. The template covered 36 cm \u0026times; 9 cm, marked with 144 points spaced 1 cm apart. Anatomical landmarks (e.g., iliac crests and costal margins) were used to align the template. All safety protocols were followed, including protective eyewear and equipment disinfection.\u003c/p\u003e\n\u003ch3\u003eSaliva Collection and Biomarker Analysis\u003c/h3\u003e\n\u003cp\u003eSaliva samples were collected at three time points: \u003cb\u003eT0\u003c/b\u003e: 1 to 6 hours before surgery (in-hospital); \u003cb\u003eT1\u003c/b\u003e: 48 hours postoperatively (home collection) and \u003cb\u003eT2\u003c/b\u003e: 7 days postoperatively (home collection)\u003c/p\u003e\u003cp\u003eFor T1 and T2, patients collected saliva in the morning while fasting, using Salivette\u0026reg; kits. Samples were stored in home freezers and later transported to the laboratory. A video call was conducted at each time point to verify correct sample collection and assess pain using the Visual Analog Scale (VAS).\u003c/p\u003e\u003cp\u003eSamples were stored at \u0026minus;\u0026thinsp;80\u0026deg;C at the Cellular and Molecular Immunology Laboratory (UFCSPA). For deproteinization, 500 \u0026micro;L of saliva was mixed with 500 \u0026micro;L of absolute ethanol at room temperature and centrifuged at 3000 rpm for 10 minutes. Supernatants were collected and stored at \u0026minus;\u0026thinsp;80\u0026deg;C.\u003c/p\u003e\n\u003ch3\u003eSaliva Deproteinization\u003c/h3\u003e\n\u003cp\u003eTo prepare samples for biochemical analysis, 500 \u0026micro;L of saliva were mixed with 500 \u0026micro;L of absolute ethanol at room temperature. The mixture was then centrifuged at 3,000 rpm for 10 minutes. Protein precipitation was achieved by centrifugation, and the resulting supernatant was collected and stored in microtubes at \u0026minus;\u0026thinsp;80\u0026deg;C for subsequent assays.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eCytokines (TNF-α and IL-10) Analysis\u003c/h2\u003e\u003cp\u003eQuantified using ELISA kits (Peprotech/Thermo Fisher scientific) according to manufacturer instructions. Detection ranges were 23\u0026ndash;3000 pg/mL.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eNitrite Quantification (Griess Reaction)\u003c/h3\u003e\n\u003cp\u003eNitrite levels were measured as an indicator of nitric oxide (NO) availability using the Griess reaction. For each well of a 96-well plate, 50 \u0026micro;L of deproteinized saliva were added along with 50 \u0026micro;L of Griess reagent, which consisted of 5% phosphoric acid (H₃PO₄), 2% sulfanilamide, 0.2% N-(1-naphthyl)ethylenediamine dihydrochloride (NEED), and ultrapure water. The plate was incubated for 1 hour at 37\u0026deg;C, and absorbance was read at 540 nm using a spectrophotometer. Concentrations were determined based on a standard curve.\u003c/p\u003e\n\u003ch3\u003eLipid Peroxidation Assay (MDA-TBARS Test)\u003c/h3\u003e\n\u003cp\u003eLipid peroxidation was assessed using the MDA-TBARS method as described by Ohkawa, Ohishi, and Yagi (1979). A total of 200 \u0026micro;L of deproteinized saliva were pipetted into separate test tubes. Each tube received 375 \u0026micro;L of acetic acid (2.5 M, pH 3.4), 375 \u0026micro;L of thiobarbituric acid (0.8%), and 500 \u0026micro;L of sodium dodecyl sulfate (8.1%). The reaction mixture was incubated in a water bath at 100\u0026deg;C for 1 hour, followed by centrifugation at 5,000 g for 15 minutes. The resulting supernatant was transferred to a 96-well plate and read at 532 nm using a microplate spectrophotometer. Final concentrations were calculated from absorbance values using a standard curve.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were performed using Python with appropriate statistical packages (e.g., scipy). Data were tested for normality using the Shapiro-Wilk test. For continuous variables, non-parametric comparisons between groups were performed using the Mann-Whitney U test. Repeated measures over time were analyzed using the Friedman test. Correlations were assessed using Spearman\u0026rsquo;s rank correlation coefficient. Multiple linear regression was used to assess predictors of biomarker levels (age, BMI, physical activity, surgical history). A significance level of 5% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was adopted for all analyses.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 31 patients completed the study, with 15 in the PBM group and 16 in the control group.The PBM group had a mean age of 46.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.3 years, while the control group presented a similar age profile, with a mean of 48.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.5 years. The mean body mass index (BMI) was also comparable between groups, with 26.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5 kg/m\u0026sup2; in the PBM group and 26.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0 kg/m\u0026sup2; in the control group. Regarding ethnicity, 81.2% of participants in the PBM group and 86.7% in the control group self-identified as white. Tobacco exposure (current or former smoking) was reported by 18.8% of participants in the PBM group and 40.0% in the control group. The average length of follow-up with the surgical team was 25.3\u0026thinsp;\u0026plusmn;\u0026thinsp;16.4 months in the PBM group and 27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;16.0 months in the control group.\u003c/p\u003e\u003cp\u003ePain perception was evaluated on postoperative days 2 and 7. On day 2 (T1), the PBM group reported a mean pain score of 2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1, compared to 3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 in the control group. By day 7 (T2), mean pain levels had decreased in both groups, reaching 1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 in the PBM group and 1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 in the control group.\u003c/p\u003e\u003cp\u003eDescriptive statistics for each biomarker are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Among the analyzed salivary biomarkers (TNF, IL-10, nitrite, and TBARS), no statistically significant changes were observed within groups over time for TNF, IL-10, or nitrite, nor between groups at any specific time point. However, a significant difference was detected for TBARS between the PBM and control groups at 48 hours postoperatively (T1) (p\u0026thinsp;=\u0026thinsp;0.034). This suggests that photobiomodulation may exert an early modulatory effect on oxidative stress following abdominoplasty, as reflected by lower lipid peroxidation levels in the intervention group at this time point.\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\u003eDescriptive statistics for salivary biomarkers at baseline (T0), 48 hours postoperatively (T1), and 7 days postoperatively (T2), for the photobiomodulation (PBM) and control groups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiomarker\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTimepoint\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMedian [IQR]\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e19.29\u0026thinsp;\u0026plusmn;\u0026thinsp;8.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.35 [12.42\u0026ndash;25.95]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e20.45\u0026thinsp;\u0026plusmn;\u0026thinsp;7.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20.75 [12.74\u0026ndash;22.79]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e18.10\u0026thinsp;\u0026plusmn;\u0026thinsp;6.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e13.57 [12.65\u0026ndash;23.12]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e32.19\u0026thinsp;\u0026plusmn;\u0026thinsp;54.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.09 [12.44\u0026ndash;22.82]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e17.09\u0026thinsp;\u0026plusmn;\u0026thinsp;6.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12.58 [12.40\u0026ndash;22.66]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e18.26\u0026thinsp;\u0026plusmn;\u0026thinsp;5.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.23 [12.61\u0026ndash;21.53]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e6.13\u0026thinsp;\u0026plusmn;\u0026thinsp;8.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.00 [3.60\u0026ndash;4.39]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e6.48\u0026thinsp;\u0026plusmn;\u0026thinsp;10.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.77 [3.59\u0026ndash;4.18]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e6.06\u0026thinsp;\u0026plusmn;\u0026thinsp;8.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.76 [3.63\u0026ndash;4.29]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e7.22\u0026thinsp;\u0026plusmn;\u0026thinsp;12.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.06 [3.54\u0026ndash;4.69]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e9.04\u0026thinsp;\u0026plusmn;\u0026thinsp;13.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.88 [3.49\u0026ndash;4.38]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e3.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.68 [3.53\u0026ndash;4.12]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNitrito\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.67 [1.37\u0026ndash;2.13]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNitrito\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;4.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.74 [1.31\u0026ndash;2.54]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNitrito\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.11 [1.81\u0026ndash;2.28]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNitrito\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.30 [1.43\u0026ndash;2.83]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNitrito\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.08 [1.39\u0026ndash;2.37]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNitrito\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.99 [1.37\u0026ndash;2.45]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBARS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.23 [0.22\u0026ndash;0.81]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBARS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.22 [0.22\u0026ndash;0.23]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBARS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.24 [0.22\u0026ndash;0.61]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBARS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.22 [0.22\u0026ndash;0.23]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBARS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePBM (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.22 [0.22\u0026ndash;0.25]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBARS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.22 [0.22\u0026ndash;0.24]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and median [interquartile range]. TNF: tumor necrosis factor alpha; IL-10: interleukin-10; TBARS: thiobarbituric acid reactive substances.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe Friedman test showed no significant temporal variation in TNF-α and IL-10 levels (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). TBARS significantly decreased in the PBM group from T0 to T1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while nitrite levels did not change over time (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Pain scores significantly decreased over time in both groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eCorrelation Analysis\u003c/h2\u003e\u003cp\u003eSpearman correlation analysis was conducted to explore potential associations between baseline salivary biomarkers (TNF, IL-10, and TBARS) and postoperative pain scores on days 2 and 7. No statistically significant correlations were identified (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, some moderate, non-significant trends were observed:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eA moderate positive correlation between TNF and IL-10 (r\u0026thinsp;=\u0026thinsp;0.34; p\u0026thinsp;=\u0026thinsp;0.061);\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eA weak-to-moderate positive correlation between TBARS and pain on postoperative day 2 (r\u0026thinsp;=\u0026thinsp;0.24; p\u0026thinsp;=\u0026thinsp;0.188);\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eA weak-to-moderate positive correlation between TBARS and pain on day 7 (r\u0026thinsp;=\u0026thinsp;0.26; p\u0026thinsp;=\u0026thinsp;0.151).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003ePain scores on days 2 and 7 were significantly correlated with each other (r\u0026thinsp;=\u0026thinsp;0.64; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting consistency in individual pain perception throughout the postoperative recovery. Overall, these findings indicate that inflammatory and oxidative stress biomarkers at baseline are not strongly associated with short-term clinical outcomes such as postoperative pain.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eMultiple Linear Regression Analysis\u003c/h2\u003e\u003cp\u003eMultiple linear regression analyses were conducted to evaluate whether age, BMI, previous surgeries, bariatric surgery, and physical activity influenced salivary levels of TNF-α, IL-10, TBARS, and nitrites at baseline (T0).\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eFor TNF-α, the model had a low explanatory power (adjusted R\u0026sup2; = -0.037), with no statistically significant predictors (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Although not significant, BMI (β\u0026thinsp;=\u0026thinsp;0.89; p\u0026thinsp;=\u0026thinsp;0.225) and physical activity (β\u0026thinsp;=\u0026thinsp;3.30; p\u0026thinsp;=\u0026thinsp;0.361) showed positive trends.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eThe IL-10 model demonstrated an adjusted R\u0026sup2; of -0.139, and none of the predictors reached statistical significance. Age showed a weak and non-significant negative association (β = -0.15; p\u0026thinsp;=\u0026thinsp;0.493).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eFor TBARS, the adjusted R\u0026sup2; was \u0026minus;\u0026thinsp;0.043, again indicating limited explanatory value of the predictors. BMI (β\u0026thinsp;=\u0026thinsp;0.05; p\u0026thinsp;=\u0026thinsp;0.119) and age (β = -0.0067; p\u0026thinsp;=\u0026thinsp;0.402) showed weak, non-significant trends.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eIn contrast, the model for nitrites yielded a higher adjusted R\u0026sup2; (0.045), and physical activity was a statistically significant negative predictor (β = -3.09; p\u0026thinsp;=\u0026thinsp;0.047). Participants who reported engaging in physical activity within the past six months had significantly lower nitrite levels compared to sedentary individuals.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eOverall, the models suggest that demographic and clinical variables had limited ability to explain the variance in inflammatory and oxidative stress markers. However, physical activity may play a relevant role in modulating nitrite metabolism, potentially reflecting more efficient regulation of nitric oxide pathways.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDespite the growing interest in the effects of photobiomodulation (PBM) on inflammatory and oxidative processes, studies that explore the association between salivary biomarkers and clinical outcomes in patients undergoing abdominal surgery remain scarce. Salivary biomarkers have emerged as a promising tool for monitoring postoperative recovery, as they allow for the simultaneous assessment of local and systemic inflammatory responses. While their application has been well documented in oral and maxillofacial surgery, where they provide insight into tissue healing and inflammatory modulation (Popa et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, the non-invasive nature of saliva collection makes this approach particularly advantageous in populations for whom blood sampling may be challenging, such as pediatric or post-surgical patients with limited venous access (Orzechowska-Wylegala et al., 2024). This underscores the novelty and clinical relevance of the present study, as one of the few investigations applying salivary biomarker analysis to monitor recovery in abdominal aesthetic surgery.\u003c/p\u003e\u003cp\u003eTNF-α levels in both groups were within or slightly below the reference ranges reported for healthy adults in recent literature, rather than indicating a heightened inflammatory state as initially assumed. Reported reference values for salivary TNF-α vary considerably across studies, ranging approximately from 22 to 47 pg/mL (Rathinasamy et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chaudhuri et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Such discrepancies likely reflect methodological and population differences, underscoring the need for standardization when interpreting salivary cytokine data in clinical research. In our study, values were at the lower end of the healthy range, suggesting that participants were not markedly pro-inflammatory at baseline. The greater variability observed in the PBM group suggests heterogeneous individual responses to treatment, while the slight reduction over time may reflect a normal postoperative resolution of inflammation. No significant between-group differences were detected.\u003c/p\u003e\u003cp\u003eIL-10, a key anti-inflammatory cytokine, showed elevated mean values across both groups, with consistently higher levels in the PBM group. This pattern suggests a postoperative anti-inflammatory response, potentially enhanced by PBM. Previous studies in facial surgery have shown that PBM can modulate cytokine activity, including IL-10, thereby reducing inflammation and supporting tissue repair (Al-Thobaiti et al., 2023). These effects are attributed to PBM\u0026rsquo;s ability to regulate immune responses, stimulate mitochondrial activity, and promote tissue regeneration. Nevertheless, variability in PBM protocols and the absence of standardized guidelines may contribute to inconsistent clinical outcomes. The increased IL-10 expression observed postoperatively may also reflect a compensatory response to surgical trauma, as previously reported (Short et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Short et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although some studies indicate that PBM may stimulate IL-10 release, our findings did not demonstrate significant between-group differences, which could be explained by individual variability, limited PBM exposure, or differences in baseline inflammatory status. The wide dispersion of IL-10 responses observed, particularly in the PBM group, reinforces the notion of heterogeneous effects potentially modulated by metabolic and immunological factors.\u003c/p\u003e\u003cp\u003eTBARS concentrations, used as an indirect marker of oxidative stress and lipid peroxidation, showed a reduction in the PBM group compared to baseline, suggesting an acute antioxidant effect. This aligns with experimental evidence from animal models of diabetes, arthritis, and high-intensity exercise, where PBM decreased lipid peroxidation (Frigero et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Santos et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and enhanced antioxidant defenses, such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) activities. Variability in TBARS assay results and differences in PBM parameters (wavelength, dosage) may explain inconsistent findings across studies (Rupel et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ghani et al., 2005). Taken together, these results support a potential antioxidant role for PBM in surgical recovery, but standardized clinical protocols are needed to confirm its efficacy.\u003c/p\u003e\u003cp\u003eNitrite levels remained within reference ranges in both groups, with no significant temporal variation. However, participants reporting regular physical activity in the preceding six months showed lower baseline nitrite levels, supporting the hypothesis that exercise modulates nitric oxide (NO) metabolism by upregulating endothelial nitric oxide synthase (eNOS), enhancing vasodilation, and improving vascular health (Arefirad et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Woo, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Regular exercise also reduces oxidative stress, thereby preserving NO bioavailability (Nosarev et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Cangemi et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The lower nitrite levels in active participants may therefore reflect more efficient NO turnover and reduced nitrite accumulation, consistent with the cardiovascular benefits of physical activity.\u003c/p\u003e\u003cp\u003ePain intensity, assessed on days 2 (D2) and 7 (D7) postoperatively, decreased significantly in both groups over time. Although no statistically significant between-group differences were found, the PBM group consistently exhibited numerically lower pain scores, which may have clinical relevance. Pain scores at D2 and D7 were strongly correlated (r\u0026thinsp;=\u0026thinsp;0.64; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating stable pain perception patterns during early recovery. The analgesic effects of PBM are likely mediated by multiple mechanisms, including modulation of inflammatory mediators, reduction of ROS, stimulation of mitochondrial ATP production, promotion of angiogenesis and lymphatic drainage, and modulation of nociceptive pathways with endogenous opioid release (Al-Thobaiti et al., 2023). Clinical studies in dental and surgical procedures have shown that PBM can reduce postoperative pain, swelling, and functional limitations (Ganguly et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Cirisola et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Angolkar et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, variability in PBM parameters remains a limitation for standardization (Pergolini et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hosseinpour et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Collado-Murcia et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The trend toward lower pain scores in the PBM group in our study is consistent with the literature, supporting PBM\u0026rsquo;s potential as an adjunct for postoperative analgesia.\u003c/p\u003e\u003cp\u003eThe relationship between inflammatory/oxidative markers and postoperative pain perception is complex and multifactorial, involving both peripheral and central nociceptive mechanisms. In our study, Spearman correlations between inflammatory/oxidative markers and pain scores revealed no statistically significant associations, although moderate trends were observed for TNF vs. IL-10 and TBARS vs. pain. These trends suggest that inflammatory markers alone may not fully explain perceived pain or recovery dynamics. TBARS levels showed a non-significant trend toward association with pain scores, consistent with the hypothesis that oxidative stress may contribute to postoperative discomfort. The absence of statistically significant correlations could be due to the relatively small sample size, interindividual variability in inflammatory responses, and potential confounders such as anesthetic regimen, analgesic protocols, and baseline health status.\u003c/p\u003e\u003cp\u003eOverall, while inflammation and oxidative stress are biologically plausible contributors to postoperative pain, their impact is modulated by metabolic status, surgical technique, pharmacological management, and psychosocial factors. The lack of significant associations in this dataset highlights the multifactorial nature of postoperative pain and underscores the need for integrative approaches in future research. Studies with larger samples, multimodal biomarker panels, and standardized analgesic regimens will be essential to clarify mechanistic links between inflammation, oxidative stress, and pain in surgical recovery.\u003c/p\u003e\u003cp\u003eSeveral methodological limitations must be acknowledged. The small sample size (n\u0026thinsp;=\u0026thinsp;31) may have limited statistical power to detect subtle between-group differences or biomarker\u0026ndash;pain associations. Biological variability, including age, comorbidities, and individual recovery responses, may have influenced biomarker levels and pain perception. The three assessment timepoints may not fully capture the dynamic fluctuations in inflammatory and oxidative markers following surgery. Furthermore, variability in PBM application parameters and the limited number of sessions could have influenced treatment effects.\u003c/p\u003e\u003cp\u003eFuture studies should employ larger cohorts, extended follow-up, and more frequent biomarker assessments (e.g., 24 h, 48 h, 72 h) to capture the temporal dynamics of recovery. Incorporating standardized PBM protocols and evaluating dose\u0026ndash;response relationships will be crucial for optimizing clinical applicability.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eClinical trial number\u003c/h2\u003e\n\u003cp\u003enot applicable\u003c/p\u003e\n\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe study protocol was approved by the institution\u0026rsquo;s Research Ethics Committee (approval number 6.308.240) and followed the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was supported by grants from Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior (CAPES, Finance Code 001) and Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq). Alessandra Peres is grateful to CNPq for the research productivity scholarship.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eConceptualization: Alessandra Peres, Carmen Lucia Kretiska Araujo, Patricia Viana da Rosa. Data curation: Alessandra Peres, Carmen Lucia Kretiska Araujo, Graziele Silveira Fardin. Formal analysis: Carmen Lucia Kretiska Araujo, Ana Paula Bernardi, Ricardo Vitiello Schramm, Isadora Frois Ourique, Maria Luiza Santos, Betina Vescovi, T\u0026aacute;ssio Fernando Crusius, Fl\u0026aacute;via Marafon, Denis Valente e N\u0026iacute;veo Steffen. Funding acquisition: Alessandra Peres, Investigation: Alessandra Peres, Carmen Lucia Kretiska Araujo, Patricia Viana da Rosa, Graziele Silveira Fardin, Joane Severo Ribeiro. Methodology: Alessandra Peres, Carmen Lucia Kretiska Araujo, Graziele Fardin Project administration: Alessandra Peres. Resources: Alessandra Peres. Supervision and Validation: Alessandra Peres. Visualization: Joane Severo Ribeiro. Writing \u0026ndash; original draft: Alessandra Peres, Carmen Lucia Kretiska Araujo, Graziele Silveira Fardin, Joane Severo Ribeiro Writing \u0026ndash; review \u0026amp; editing: all authors.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to privacy and ethical restrictions involving patient data. However, they are available from the corresponding author upon reasonable request and with appropriate institutional approvals.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAl-Thobaiti YE, Batwa MA, Alghawi JA, Aljamaan RF, Alkhowaiter FA, Alhejaili MA, Alshammari SZ (2024) The role of photobiomodulation in postoperative recovery of facial procedures. 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Korean Int Res Found 1(2):55\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.56336/kirf.2022.1.2.55\u003c/span\u003e\u003cspan address=\"10.56336/kirf.2022.1.2.55\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Photobiomodulation Therapy, Abdominoplasty, Oxidative Stress, Cytokines, Postoperative Pain","lastPublishedDoi":"10.21203/rs.3.rs-7437378/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7437378/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePhotobiomodulation (PBM) has been proposed as a non-invasive therapeutic strategy to support wound healing and modulate oxidative and inflammatory responses. However, clinical data evaluating its effects in the postoperative period of abdominoplasty remain limited. This non-randomized clinical trial included 31 female patients undergoing abdominoplasty, divided into two groups: PBM intervention (n\u0026thinsp;=\u0026thinsp;15) and control (n\u0026thinsp;=\u0026thinsp;16). Salivary samples were collected at three time points: preoperative (T0), 48 hours postoperative (T1), and 7 days postoperative (T2). Inflammatory markers (TNF-α, IL-10), oxidative stress indicators (TBARS, nitrites), and pain scores were assessed. PBM was applied once using an 808 nm infrared laser (100 mW, 3 J/point) before hospital discharge. Statistical analyses included the Shapiro-Wilk test, Friedman test, Mann-Whitney U test, Spearman\u0026rsquo;s correlation, and multiple linear regression. PBM showed no significant changes in TNF-α, IL-10, nitrites, or pain scores compared to the control group. However, a statistically significant reduction in TBARS levels was observed at 48 hours postoperative in the PBM group (p\u0026thinsp;=\u0026thinsp;0.040), suggesting a potential antioxidant effect. Physical activity was associated with lower nitrite concentrations (p\u0026thinsp;=\u0026thinsp;0.047), indicating a modulatory interaction between exercise and nitric oxide metabolism. Although a single session of PBM did not significantly alter most inflammatory and oxidative markers, it appeared to reduce lipid peroxidation and was well tolerated. These preliminary results support the safety of PBM in the postoperative period of abdominoplasty. Further randomized studies with larger sample sizes and multiple applications are warranted to better elucidate its therapeutic potential.\u003c/p\u003e","manuscriptTitle":"Photobiomodulation Therapy Reduces Oxidative Stress and Modulates Postoperative Recovery in Abdominoplasty: A Pilot Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-15 16:30:21","doi":"10.21203/rs.3.rs-7437378/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9544cbc3-f428-4d5f-a4c0-f1cff6b09fbf","owner":[],"postedDate":"September 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-08T23:23:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-15 16:30:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7437378","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7437378","identity":"rs-7437378","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}