Adjunctive treatment of sepsis with mesenchymal stem cell-derived extracellular vesicles: a systemic review and meta-analysis of pre-clinical studies

Adjunctive treatment of sepsis with mesenchymal stem cell-derived extracellular vesicles: a systemic review and meta-analysis of pre-clinical studies | 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 Adjunctive treatment of sepsis with mesenchymal stem cell-derived extracellular vesicles: a systemic review and meta-analysis of pre-clinical studies Awirut Charoensappakit, Kritsanawan Sae‑khow, Pongpera Rattanaliam, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4328001/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 Background: Multiple preclinical studies have reported a beneficial effect of extracellular vesicles (EVs), especially mesenchymal stem cell-derived EVs (MSC-EVs), in the treatment of sepsis. However, the therapeutic effect of MSC-EVs is still unclear. Therefore, we conducted this meta-analysis by summarizing data from all published studies that met the criteria for a systematic review on the association between EV treatment and mortality in animal models of sepsis. Methods: Systematic retrieval of all studies in PubMed, Scopus, and Web of Science that reported the effects of EVs on sepsis models up to December 2023 was performed. The targeted outcome was animal mortality. After screening the eligible articles according to inclusion and exclusion criteria, the inverse variance method of the fixed effect model was used to calculate the joint odds ratio (OR) and 95% confidence interval (CI). Results: A total of 53 studies met the inclusion criteria, indicating that EVs treatment was associated with reduced mortality in animal models of sepsis, with a RR of 0.53 and a 95%CI of 0.46 to 0.60 ( p < 0.001) and RD of -0.35 and 95%CI of -0.41 to -0.30 ( p < 0.001). Subsequent subgroup analysis revealed that several factors,such as sepsis models and EV administration (source, dose, time to injection, and route of administion), may significantly affect the therapeutic efficacy of EVs. Conclusion: This meta-analysis showed that MSC-EVs treatment may be associated with lower mortality in animal models of sepsis. Subsequent preclinical studies will need to address the standardization of dose, source, and timing of EVs to provide comparable data. In addition, the effectiveness of EVs in treating sepsis must be studied in large animal studies to provide important clues for human clinical trials. Mesenchymal stem cells derived extracellular vesicles sepsis meta-analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Sepsis, an abnormal host response toward infection, is a life-threatening syndrome with multi-organ dysfunction and high morbidity and mortality, despite the currently improved supportive care ( 1 , 2 ). Currently, antibiotics and supportive measures remain the only available treatments for patients with sepsis, but these measures have limited effects on reducing the mortality of sepsis ( 1 , 2 ), highlighting the urgent need to develop innovative and potent therapies. In pro-inflammatory sepsis, excessive secretion of inflammatory cytokines contributes to multi-organ dysfunction, and the severity and duration of inflammatory responses determine the prognosis of patients ( 3 ). Thus, the use of immune modulation therapy is still frequently mentioned in the research field ( 3 , 4 ), and several immune inhibitors might be beneficial in patients with severe sepsis. However, none of these substances can be used in real clinical situations because of the complex sepsis pathogenesis. Then, the ideal adjuvant therapy for sepsis might be a combination of multiple drug targets, including early immunomodulation, cell protection, and prevention of end-organ damage ( 1 – 3 ). In this context, an investigation into novel therapies to ameliorate sepsis would be urgently needed, especially for sepsis-induced hyper-inflammatory responses. Among several immune inhibitors, mesenchymal stem cells (MSCs) or multipotent mesenchymal stromal cells have attracted interest for use in sepsis. Indeed, injection of MSCs in cecal ligation and puncture (CLP) surgery-induced sepsis mice attenuates sepsis severity ( 5 ), partly through an interaction with monocytes/macrophages ( 6 ) and other immune cells ( 7 ). Additionally, the suppressive effects of MSCs are also demonstrated in other conditions, including organ transplantation, graft versus host disease, and some autoimmune diseases ( 6 ). Due to several stem cell properties (differentiation potential and self-renewal), MSCs have also been clinically studied as therapeutic agents for regenerative medicine in a variety of diseases, for example, diabetes, Alzheimer's disease, and osteoarthritis ( 8 ). However, there are some challenges with the use of MSCs, including the low survival rate of the cells after administration, the difficulty of stem cells reaching the injury sites, and cell preparation problems ( 9 ). On the other hand, it is well known that the mechanisms of MSC-induced immune suppression are mainly due to the soluble factors of MSCs, and the extraction methods of these factors have been extensively studied ( 5 ). Due to the difficulties in cell preparation and several limitations in the administration of viable cells ( 9 ), the use of soluble factors from MSCs, including MSC-derived extracellular vesicles (MSC-EVs), is currently being introduced. As such, extracellular vesicles (EVs) are cell-derived membrane surrounded vesicles from almost all cells, with prominently high production in stem cells, carrying bioactive molecules to distant sites in the body ( 10 ). In addition, EVs are characterized by the diameters of exosomes and microvesicles and the EV structures effectively protect their cargo components, including proteins, lipids, genetic material (miRNA, RNA, and DNA), and some metabolites, from the extracellular environment ( 11 ). Compared with cell therapy, EVs have several advantages; for example, non-immunogenicity, non-infusion toxicity, relatively higher stability in the blood circulation, easier access, uncomplicated preservation, and ethical issues ( 12 ). For clinical application, MSC-EVs attenuate patients suffering from steroid refractory graft-versus-host disease, ostheoarthitis, and grade III-IV chronic kidney disease ( 13 – 15 ). In sepsis, pre-clinical studies in animal models have demonstrated the beneficial efficacy of MSC-EVs in sepsis; however, the impacts of MSC-EV treatment are still inconclusive. Therefore, we conducted this meta-analysis by summarizing data from all published studies that met our criteria to explore the association between MSC-EV treatment and mortality in animal models of sepsis. Additionally, we also determine the potential effects of some specific microRNAs (miRNA) contained in MSC-EVs using data mining and a bioinformatic database for predicting the possible miRNA that might be responsible for the MSC-EV therapeutic effect. Materials and Methods Search strategies and eligibility criteria. The study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 guidelines. A systematic literature search of the Scopus, PubMed, Cochrane Library, and Clinicaltrial.gov databases published from 2000 until December 2023 was performed. The article was limited only to the English-reported studies. The retrieval query formulation used for the search was “mesenchymal stem cell-derived extracellular vesicles” OR “MSC-EVs” OR “mesenchymal stem cell-derived exosomes” OR “mesenchymal stem cell-derived microvesicles” AND “sepsis” OR “pneumonia” AND “animal models”. All the reference lists of the identified articles and relevant reviews were also manually screened. Two groups of reviewers independently screened the inclusion of the article’s eligibility. The disagreement on any topic during the review process was resolved through a consensus with the third group of reviewers. The inclusion criteria were full text studies investigating the effectiveness of MSC-EV treatment on sepsis animal models. The inclusion criteria were: i) evaluation of the therapeutic effect of MSC-EVs on sepsis animal models; ii) the studies involved an animal model of sepsis or endotoxemia; iii) the protective effect of MSC-EVs or EV-derived active molecules was the focus of the study; and iv) the studies reported mortality rates or reductions in inflammation. The exclusion criteria were: i) MSC-EVs were not directly used as therapy; ii) extracellular vesicles were genetically modified; iii) no sepsis occurred and a lack of end points of interest; and iv) none of in the vivo experiments. Only publications whose language is English are included. Risk of bias The risk of bias was assessed according to the Systematic Review Center for Laboratory Animal Experimentation (SYRCLE) ( 16 ), including selection bias, performance bias, detection bias, attrition bias, reporting bias, and others. The risk of bias was assessed carefully by two independent reviewers as low risk, high risk, or unclear risk based on the content of the article. Any disputes encountered during the evaluation process were resolved through discussion. Data extraction and statistical analysis Two authors extracted the relevant data from the included studies independently using a specific form (Microsoft Excel), and then, three of the authors re-checked and confirmed the obtained raw data. The differences encountered were resolved through discussion with the third expert reviewer. The following data were recorded: first author, country or region, year of publication, animal type, number, sepsis model type, origin of EVs, dose, injection method, injection time, observation time after EVs administration, and indicators related to the primary outcome. For gathering of the results, the effect size of this meta-analysis was mortality. The risk ratio (RR) and risk difference (RD) values of the EV treatment group and control group were calculated to determine the combined effect size. The mean with standard deviations (SD) values was used for the calculations, and the standard errors (SE) were calculated into SD using the Cochrane Collaboration formula (SD = SE x √N). For the values presented with median and range, or interquartile range (IQR), the mean values and SD were estimated by the statistical formula reported by Wan et al. ( 17 ). The effect model of meta-analysis was selected according to whether the heterogeneity was significant ( 18 ). Heterogeneity was measured using the among-study variance (τ2), chi-squared (χ2) test, and identify and interpret strategy (I2) statistical analyses. For the measurement with an I2 < 50%, the results were pooled using a fixed effects model, otherwise, a random effects model was used. All statistical analyses were performed using SPSS version 22 and visualized using Microsoft Excel. Then, the results of the analysis were presented as the forest plots of pooled RR and RD with a 95% confidence interval. Statistical significance was defined at the p-value < 0.05. Sensitivity analyses were performed by removing each study individually from the results of the meta-analysis. As a method for bioinformatics of miRNA prediction, an integrated platform linking miRNAs, their targets, and their functions named “miRNet 2.0 ( https://www.mirnet.ca/ )” was used to predict the downstream targeted genes of the expected miRNAs. As part of network creation and analysis, all expected miRNA entries are annotated according to the latest miRbase (miRTarBase). Gene set enrichment analysis was performed using validated miRNA gene targets from the miRNet database and their built-in software for Gene Ontology (GO) biological processes and reactome enrichment analysis. Results Study inclusion and characteristics. A total of 1,078 articles were retrieved from the three databases according to the search strategies. After the elimination of duplicate articles, 1,013 of 1,078 articles were initially screened and excluded according to the title and abstract. The full text of the remaining 68 articles was reviewed. Fifty-three articles were selected to be included in this systematic review according to the inclusion and exclusion criteria, and 30 articles were selected to be included in the meta-analysis due to mortality reports in the studies (Fig. 1 ). Details of the included studies are demonstrated in Table 1 . The risk of bias among the studies was assessed by SYRCLE's RoB tool (Table 2 ). All studies were considered to have RoB risks. Although 11 studies (36.7%) reported randomization of animals, none of them showed the method for generating the random sequences or the assignments were inadequately reported. Therefore, the RoB scores in the selection bias component were "unclear" for these studies. Six studies might have had a problem with the experimental design, which resulted in a RoB score of "high risk" due to a possible contamination of substances in the stimulated MSCs. Table 2 SYRCLE tool risk of bias Authors year Selection bias Performance bias Detection bias Attrition bias Reporting bias Other bias Random sequence generation? Groups similar at baseline? Allocation concealed? Animals randomly housed? Blinding of caregivers and/or examiners? Random selection for outcome assessment? Blinding of outcome assessor? Incomplete outcome data addressed? Free from selective outcome reporting? Free from other bias? Xiaohong Wang et al. 2015 U U U U U U L L L L Haojie Yuan et al. 2015 L U U U U U L L L L Antoine Monsel et al. 2015 U U U U U U L U L U Yuxian song et al. 2017 L U U U U U L L L H Chia-Lo Chang et al. 2018 U U U U U U L L L L Amir K. Varkouhi et al. 2019 L U U U U U L L L H Rongxue Zhang et al. 2020 U U U U U U L L L L Fang Gao et al. 2020 U U U U U U L L L L Huimin Deng et al. 2020 L U U U U U L L L L Danyang Zheng et al. 2021 U U U U U U L L L L Jia Sun et al. 2021 U U U U U U L H L L Qin Zhou et al. 2021 L U U U U U L L L L Jie Chen et al. 2021 L U U U U U L L L L Yuan Su et al. 2021 U U U U U U L L L L Mahshid Akhavan Rahnama et al. 2021 U U U U U U L L L L Mengying Yao et al. 2021 U U U U U U L L L L Liangjun Xia et al. 2021 U U U U U U L L L H Xiaoyan et al. 2022 U U U U U U L L L H Huimin Deng et al. 2022 L U U U U U L L L L Ruichao Niu et al. 2022 U U U U U U L L L H Huimin Deng et al. 2022 L U U U U U L L L L Shan Cao et al. 2022 L U U U U U L L L L Wen Zhang et al. 2022 L U U U U U L L L L Xiaoxia Wang et al. 2022 U U U U U U L L L L Wei Peng et al. 2023 U U U U U U L L L H Jizhen Cai et al. 2023 U U U U U U L L L L Cui Jin et al. 2023 L U U U U U L L L L Paulius Valiukevicius et al. 2023 U U U U U U L L L L Natália G. Blanco et al. 2023 U U U U U U L L L L Kento Homma et al. 2023 U U U U U U L L L L Effects of mesenchymal stem cell-derived extracellular vesicles on sepsis mortality A total of 30 published articles related to MSC-EV treatment and mortality from sepsis were included in the meta-analysis (pooled analysis), all of which mentioned mortality rates in the publication. Mortality at the end point (observed time) was 148 of 648 (22.8%) in the MSC-EV-treated experiments, whereas 258 of 381 (67.7%) were in the control group. As the forest plot of pooled analysis of relative risk (RR) and risk difference (RD) showed high certain results (very low heterogeneity; I 2 = 0%) that MSC-EVs treatment significantly attenuated sepsis mortality in both RR and RD values (the fixed effect model: RR = 0.53, 95% CI: 0.46–0.60, p < 0.001 and RD= -0.35, 95% CI: -0.41 - -0.30, p < 0.001) (Fig. 2 ). Sensitivity analysis was conducted by excluding each study from the results of the meta-analysis. Subgroup analysis Subgroup analyses were performed to evaluate the efficacy of MSC-EVs in the treatment of sepsis using the fixed effect model, considering the generality and reproducibility of treatment outcomes across different experimental conditions (Fig. 3 A, B). Importantly, heterogeneity was also low in each subgroup. As such, in the animal model, all subgroups showed statistical significance in both RR and RD, except for the use of MSC-EVs in non-rodent animals (sheep) (Fig. 3 A). The use of MSC-EVs in rats (RR = 0.33, 95% CI: 0.22–0.50, p < 0.001 and RD = -0.42, 95% CI: -0.54 – -0.29, p < 0.001) was more effective than in mice (RR = 0.55, 95% CI: 0.48–0.64, p < 0.001 and RD = -0.34, 95% CI: -0.41 – -0.28, p < 0.001) (Fig. 3 A). In comparison with the cecal ligation and puncture (CLP) model (RR = 0.56, 95% CI: 0.48–0.66, p < 0.001 and RD = -0.32, 95% CI: -0.40 – -0.25, p < 0.001), MSC-EVs demonstrated better therapeutic outcomes than the non-CLP sepsis models, including lipopolysaccharide (LPS) and bacteria injection models. As such, the parameters for “LPS/ Bacteria-induced sepsis” were: RR = 0.45, 95% CI: 0.30–0.65 ( p < 0.001) and RD = -0.48, 95% CI: -0.65 – -0.30 ( p < 0.001). On the other hand, the data for MSC-EVs impacts in LPS and bacterial pneumonia model from “LPS/Bacteria-induced pneumonia” were: RR = 0.45, 95% CI: 0.33–0.60 ( p < 0.001) and RD = -0.37, 95% CI: -0.47 – -0.26 ( p < 0.001), when compared with the CLP model (Fig. 3 A). There was a more prominent survival with the dosage of MSC-EVs at equal or greater than 100 ug per mouse (RR = 0.36, 95% CI: 0.23–0.59, p < 0.001 and RD = -0.45, 95% CI: -0.55 – -0.34, p < 0.001) than with the dosage lower than 100 ug (RR = 0.52, 95% CI: 0.44–0.62, p < 0.001 and RD = -0.39, 95% CI: -0.48 – -0.31, p < 0.001) (Fig. 3 A). In comparison with the MSC-EV treatment for more than 2 days (RR = 0.56, 95% CI: 0.48–0.64, p < 0.001 and RD = -0.38, 95% CI: -0.45 – -0.31, p < 0.001), the EV treatment for less than 2 days (RR = 0.37, 95% CI: 0.26–0.35, p < 0.001 and RD = -0.30, 95% CI: -0.39 – -0.21, p < 0.001) also improved sepsis survival rate (Fig. 3 A). To estimate the potential to use MSC-EVs in real clinical situations, a subgroup analysis of the MSC-EVs that were derived from human MSC was determined (Fig. 3 B). In the human MSC data, all subgroups also presented low heterogeneity, and human umbilical cord MSC-EVs (huUCMSCs) (RR = 0.72, 95% CI: 0.57–0.89, p = 0.003 and RD = -0.09, 95% CI: -0.19–0.01, p = 0.078) exhibited a significant lower effectiveness than bone marrow-isolated MSC-EVs (huBMMSCs) (RR = 0.44, 95% CI: 0.27–0.74, p = 0.002 and RD = -0.37, 95% CI: -0.53 – -0.22, p < 0.001) or adipose tissue-derived MSC-EVs (huADMSCs) (RR = 0.35, 95% CI: 0.21–0.58, p < 0.001 and RD = -0.36, 95% CI: -0.48 – -0.23, p < 0.001) (Fig. 3 B). With human MSC-EVs, the treatment before sepsis induction did improve survival (RR = 0.71, 95% CI: 0.47–1.09, p = 0.12 and RD = -0.27, 95% CI: -0.54–0.03, p = 0.076) (Fig. 3 B), while the treatment after sepsis induction for less or more than 2 days (RR = 0.26, 95% CI: 0.11–0.62, p < 0.001 and RD = -0.22, 95% CI: -0.35 – -0.10, p < 0.001) could attenuate sepsis mortality (Fig. 3 B). Parallelly, the higher doses of MSC-EVs (RR = 0.30, 95% CI: 0.12–0.75, p = 0.005 and RD = -0.45, 95% CI: -0.59 – -0.31, p < 0.001) had a trend of improved survival than the lower dosages (RR = 0.53, 95% CI: 0.41–0.68, p < 0.001 and RD = -0.43, 95% CI: -0.56 – -0.29, p < 0.001) could (Fig. 3 B). Bioinformatic analysis of miRNA containing in human MSC-EVs Then, the possibility of using a MSC-EV treatment in real clinical situation was simulated through data mining and bioinformatic prediction (Fig. 4 ). With the Venn diagram, the sphere shapes with orange and grey colors represent MSC-EV studies with improved inflammatory responses and mortality, respectively, while the ellipse shapes represent studies mentioning organ injuries (Fig. 4 A). There were only 3 studies that demonstrated all outcomes (inflammation, mortality, kidney injury, lung lesion, and liver damage), while most of the studies (8 studies) demonstrated survival, inflammatory responses, and lung complications (Fig. 4 A). Because microRNAs (miRNAs) contained in EVs are possible molecules responsible for sepsis attenuation, for example, through epigenetic regulation ( 19 ), subgroup analysis following the miRNAs, mentioned in the human MSC-EV sepsis studies, was performed using the miRNA-target interaction networks (miRnet; www.mirnet.ca ). From the list of miRNAs in human MSC-EVs (hsa-miR223, hsa-miR146a, hsa-miR145, hsa-miR377, and hsa-miR150), there were 1,693 genes that were targeted by these miRNAs (Fig. 4 B). Among the top 10 enrichment functional pathways regulated by all miRNAs, innate immunity was the first enrichment, followed by oncology genes (Onco-MiRNAs) (Fig. 4 C). Moreover, enrichment pathways for the targeted genes, referred to as target gene Gene Ontology (GO), were generated. With the GO term in biological processes, the majority of enrichment pathways were those that were related to the immune system and immune cell development (Fig. 4 D). Consisting of the enrichment of Reactome (the pathway database providing the intuitive bioinformatics tools for visualization), the results also showed that the first rank of the enrichment was the cell responses to stress, followed by cellular senescence (Fig. 4 E). Discussion Immune modulation is an interesting strategy against sepsis, especially sepsis hyper inflammation, and anti-inflammation with effective anti-biotics might attenuate sepsis-induced organ injury ( 3 , 20 ). Currently, there are several biomarkers that can be used for identifying hyper-inflammatory responses in sepsis and exhibit correlation with severity and mortality; for example, serum cytokines, endotoxemia, cell-free DNA, and immune cell activities ( 21 – 24 ). Then, some immune inhibitors might be beneficial in patients with severe sepsis identified by these biomarkers. Although there are several inflammatory inhibitors and immune stimulators that might be useful in sepsis, especially from pre-clinical studies ( 1 , 24 ) none of these substances can be used in real clinical situations. Therefore, new therapeutic strategies to attenuate sepsis-induced hyper-inflammatory responses might improve the clinical outcome of these patients. Among several anti-inflammatory strategies in sepsis, MSC-EV treatment is one of the most interesting candidates compared with MSC therapy, with several advantages, including safety, stability, good permeability, immunogenicity, and cytotoxicity ( 12 ). The effective anti-inflammation in sepsis of MSC-EVs might be due to the delivery of miRNAs or long non-coding RNA (lncRNA) to several immune cells, especially macrophages ( 25 ). Meanwhile, the EVs from other cells; for example, erythrocytes and platelets, might aggravate inflammation, which may be a potential risk factor for transfusion-related immune regulation ( 26 , 27 ). The possibilities of using MSC-EVs in patients have been demonstrated in many clinical trials of MSC-EV-related therapies, including the potential to treat severe COVID-19 ( 28 , 29 ). Unfortunately, the studies of MSC-EVs in human sepsis have never been demonstrated. Although immune regulation and differentiation capabilities of MSCs are beneficial for immune modulation and repair in sepsis, several limitations of cell therapy, including uncontrolled cell proliferation, malignant cell differentiation, and low engraftment ( 9 ), are mentioned. Here, there are two included studies comparing the effectiveness between MSC cell-based therapy and MSC-EVs on sepsis that demonstrated the greater efficacy of MSC-EVs, possibly through the better biodistribution of MSC-EVs throughout the body and tissue-specific localization ( 10 ), or alternatively via secondary effects on activated host cells in tissue upon EV uptake ( 30 ). Due to the larger sizes of MSCs than MSC-EVs, the distribution of MSCs after intravenous injection is limited to some organs (livers and lungs) ( 31 ), while MSC-EVs rapidly spread throughout the whole body and might also be delivered through the EV-uptake cells. Included studies using vital tracking found that MSC-EVs spread to the whole mouse body within an early time and were localized in the lung, liver, and a little bit in the kidney after 2–6 h after administration ( 32 ). These data suggest that when MSC-EVs are administered, they may easily move to reach other tissues to induce anti-inflammatory effects elsewhere. Here, our meta-analytic results supported the high effectiveness of MSC-EVs on sepsis attenuation with homogeneity results. From the subgroup analysis, EVs of the same species are more effective than the EV xenografts (the use of human MSC-EVs in animals), which possibly relates to the well-known acute rejection caused by natural antibodies and complements in xenografts ( 33 ). Additionally, the EVs that were derived from primary MSCs of bone marrow show superior efficacy to EVs extracted from other cell types, which may be related to the lower immunogenicity and higher immunomodulatory capacities of MSCs. Previous studies also demonstrated the benefits of EVs from bone marrow (BM)-derived MSCs in other disease models, including cardiovascular, liver, and lung diseases ( 34 ). However, the BM requires an invasive biopsy to obtain the MSCs to extract EVs, and the yield is relatively limited as the high numbers of MSCs might be required for the treatment in humans ( 35 ). Although the umbilical cord is possibly a more suitable source of MSC-EVs for clinical translation than the BM isolation as determined by the feasibility and the greater self-renewal capacity ( 36 ), our analysis showed a significant lower effectiveness of MSC-EVs from the umbilical cord compared with the MSCs from BM. On the other hand, demonstrating the effect of EVs from adipose tissue-derived MSCs (ADMSCs) was an important advance in this regard, with nearly the same capacity as BMMSC-EVs. Among the advantages of ADMSCs, the easier extraction with more prominent adipocytes through subcutaneous lipoaspiration compared with BM stem cell harvesting through BM biopsy is mentioned ( 34 ). Although our meta-analysis suggested that MSC-EVs at the dose of 100 µg might have a better therapeutic effect in a dose-dependent manner, further studies for the determination of proper doses of MSC-EVs for sepsis treatment are urgently required. Some insights on the therapeutic potential of MSC-EVs, particularly clinical applications, EV induction, and isolation, are also interesting. For the content delivery of EVs, an important mechanism of immunomodulation in sepsis, several included studies have proposed that MSC-EVs transfer a variety of bioactive molecules, particularly miRNAs, to the recipient cells and induce some beneficial outcomes ( 37 ). Indeed, miRNAs function as guides by base-pairing with target mRNA, mostly for negative regulation of the targeted mRNA (marked mRNA), which might be either denatured or preserved and translated later instead of being quickly translated into a protein. Here, the enrichment analysis of the recorded miRNAs contained in human MSC-EVs using human miRdatabase bioinformatic tools revealed impacts of miRNAs in many mechanisms, including innate immunity control, hematopoiesis, and stress responses (Fig. 3 C-F). However, the difference in miRNA content in EVs derived from different conditions; for example, EVs from different sources of MSCs was not determined. Then, more studies on the miRNAs in MSC-EVs from various conditions are interesting. The synthetic EVs that contain single, combined or engineered miRNAs are an interesting idea for developing a new anti-inflammatory strategy against sepsis. Here, we provid a list of the interesting miRNAs for sepsis in MSC-EVs. Several miRNAs in the list were previously mentioned. For example, miR-150 associates with several cancers, especially during metastasis ( 38 ), and also acts as an inhibitor against some immune cells, including dendritic cells and T-helper cells ( 39 , 40 ). In parallel, miR-145, miR-146, and miR-377 are anti-inflammation and antiproliferation ( 41 , 42 ), while miR-223 is correlated with infectious diseases ( 43 ). Conclusions In conclusion, our meta-analysis provided important clues about the use of MSC-EVs for sepsis as a guide for basic research for further clinical endeavors. To the best of our knowledge, this is the first meta-analysis of MSC-EVs in pre-clinical sepsis experiments, which provides a summary of the efficacy of MSC-EVs on sepsis attenuation. Future research on MSC-EVs for sepsis in patients is needed. Declarations Acknowledgements All authors approved the submission of the final article. The authors have disclosed that they do not have any potential conflicts of interest. Author contributions A.C., K.s-k. and A.L. performed the literature search, data extraction, analysis and wrote the manuscript. A.C. and P.R. extracted the data and performed assessment of bias and certainty of evidence, independently. M.P., N.V., P.M., T.S. and A.L. conceived the study, analyzed the data, and corrected the manuscript. All authors read and approved the final manuscript. Fundings This research was funded by Chulalongkorn University, the National Research Council of Thailand (NRCT) (N41A640076, N34A660583), and the Program Management Unit for Human Resources, Institutional Development, Research, and Innovation (B16F640175). A.C. was funded by Second Century Fund (C2F) from Chulalongkorn University. Ethics approval and consent to participate Not applicable. Consent for publication All authors have read and approved the submission of the manuscript. Competing interests The authors declare no competing interests. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References Sae-khow K, Charoensappakit A, Chiewchengchol D, Leelahavanichkul A. High-Dose Intravenous Ascorbate in Sepsis, a Pro-Oxidant Enhanced Microbicidal Activity and the Effect on Neutrophil Functions. Biomedicines [Internet]. 2023; 11(1). Chen AX, Simpson SQ, Pallin DJ. Sepsis Guidelines. New England Journal of Medicine. 2019;380(14):1369-71. Leligdowicz A, Harhay Michael O, Calfee Carolyn S. Immune Modulation in Sepsis, ARDS, and Covid-19 — The Road Traveled and the Road Ahead. NEJM Evidence. 2022;1(11):EVIDra2200118. Cao M, Wang G, Xie J. Immune dysregulation in sepsis: experiences, lessons and perspectives. Cell Death Discovery. 2023;9(1):465. Németh K, Leelahavanichkul A, Yuen PS, Mayer B, Parmelee A, Doi K, et al. Bone marrow stromal cells attenuate sepsis via prostaglandin E(2)-dependent reprogramming of host macrophages to increase their interleukin-10 production. Nat Med. 2009;15(1):42-9. Ghannam S, Bouffi C, Djouad F, Jorgensen C, Noël D. Immunosuppression by mesenchymal stem cells: mechanisms and clinical applications. Stem Cell Res Ther. 2010;1(1):2. Monsel A, Zhu YG, Gennai S, Hao Q, Liu J, Lee JW. Cell-based therapy for acute organ injury: preclinical evidence and ongoing clinical trials using mesenchymal stem cells. Anesthesiology. 2014;121(5):1099-121. Maldonado VV, Patel NH, Smith EE, Barnes CL, Gustafson MP, Rao RR, et al. Clinical utility of mesenchymal stem/stromal cells in regenerative medicine and cellular therapy. Journal of Biological Engineering. 2023;17(1):44. Musiał-Wysocka A, Kot M, Majka M. The Pros and Cons of Mesenchymal Stem Cell-Based Therapies. Cell Transplant. 2019;28(7):801-12. Park KS, Svennerholm K, Shelke GV, Bandeira E, Lasser C, Jang SC, et al. Mesenchymal stromal cell-derived nanovesicles ameliorate bacterial outer membrane vesicle-induced sepsis via IL-10. Stem Cell Res Ther. 2019;10(1):231. Verweij FJ, Balaj L, Boulanger CM, Carter DRF, Compeer EB, D’Angelo G, et al. The power of imaging to understand extracellular vesicle biology in vivo. Nature Methods. 2021;18(9):1013-26. Khosrojerdi A, Soudi S, Hosseini AZ, Eshghi F, Shafiee A, Hashemi SM. Immunomodulatory and Therapeutic Effects of Mesenchymal Stem Cells on Organ Dysfunction in Sepsis. Shock. 2021;55(4):423-40. Kordelas L, Rebmann V, Ludwig AK, Radtke S, Ruesing J, Doeppner TR, et al. MSC-derived exosomes: a novel tool to treat therapy-refractory graft-versus-host disease. Leukemia. 2014;28(4):970-3. Nassar W, El-Ansary M, Sabry D, Mostafa MA, Fayad T, Kotb E, et al. Umbilical cord mesenchymal stem cells derived extracellular vesicles can safely ameliorate the progression of chronic kidney diseases. Biomaterials Research. 2016;20(1):21. Warmink K, Rios JL, Varderidou-Minasian S, Torres-Torrillas M, van Valkengoed DR, Versteeg S, et al. Mesenchymal stem/stromal cells-derived extracellular vesicles as a potentially more beneficial therapeutic strategy than MSC-based treatment in a mild metabolic osteoarthritis model. Stem Cell Research & Therapy. 2023;14(1):137. Hooijmans CR, Rovers MM, de Vries RB, Leenaars M, Ritskes-Hoitinga M, Langendam MW. SYRCLE's risk of bias tool for animal studies. BMC Med Res Methodol. 2014;14:43. Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014;14:135. Borenstein M, Hedges LV, Higgins JP, Rothstein HR. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods. 2010;1(2):97-111. Qiu G, Zheng G, Ge M, Wang J, Huang R, Shu Q, et al. Mesenchymal stem cell-derived extracellular vesicles affect disease outcomes via transfer of microRNAs. Stem Cell Res Ther. 2018;9(1):320. Dang CP, Issara-Amphorn J, Charoensappakit A, Udompornpitak K, Bhunyakarnjanarat T, Saisorn W, et al. BAM15, a Mitochondrial Uncoupling Agent, Attenuates Inflammation in the LPS Injection Mouse Model: An Adjunctive Anti-Inflammation on Macrophages and Hepatocytes. J Innate Immun. 2021;13(6):359-75. Barichello T, Generoso JS, Singer M, Dal-Pizzol F. Biomarkers for sepsis: more than just fever and leukocytosis—a narrative review. Critical Care. 2022;26(1):14. Charoensappakit A, Sae-khow K, Rattanaliam P, Vutthikraivit N, Pecheenbuvan M, Udomkarnjananun S, et al. Cell-free DNA as diagnostic and prognostic biomarkers for adult sepsis: a systematic review and meta-analysis. Scientific Reports. 2023;13(1):19624. Visitchanakun P, Kaewduangduen W, Chareonsappakit A, Susantitaphong P, Pisitkun P, Ritprajak P, et al. Interference on Cytosolic DNA Activation Attenuates Sepsis Severity: Experiments on Cyclic GMP–AMP Synthase (cGAS) Deficient Mice. International Journal of Molecular Sciences [Internet]. 2021; 22(21). Sae-khow K, Tachaboon S, Wright HL, Edwards SW, Srisawat N, Leelahavanichkul A, et al. Defective Neutrophil Function in Patients with Sepsis Is Mostly Restored by ex vivo Ascorbate Incubation. Journal of Inflammation Research. 2020;13(null):263-74. Wang J, Xia J, Huang R, Hu Y, Fan J, Shu Q, et al. Mesenchymal stem cell-derived extracellular vesicles alter disease outcomes via endorsement of macrophage polarization. Stem Cell Res Ther. 2020;11(1):424. Gao Y, Jin H, Tan H, Cai X, Sun Y. Erythrocyte-derived extracellular vesicles aggravate inflammation by promoting the proinflammatory macrophage phenotype through TLR4–MyD88–NF-κB–MAPK pathway. Journal of Leukocyte Biology. 2022;112(4):693-706. Lu X, Jiang G, Gao Y, Chen Q, Sun S, Mao W, et al. Platelet-derived extracellular vesicles aggravate septic acute kidney injury via delivering ARF6. Int J Biol Sci. 2023;19(16):5055-73. Krishnan A, Muthusamy S, Fernandez FB, Kasoju N. Mesenchymal Stem Cell-Derived Extracellular Vesicles in the Management of COVID19-Associated Lung Injury: A Review on Publications, Clinical Trials and Patent Landscape. Tissue Eng Regen Med. 2022;19(4):659-73. Zarrabi M, Shahrbaf MA, Nouri M, Shekari F, Hosseini S-E, Hashemian S-MR, et al. Allogenic mesenchymal stromal cells and their extracellular vesicles in COVID-19 induced ARDS: a randomized controlled trial. Stem Cell Research & Therapy. 2023;14(1):169. Tolomeo AM, Zuccolotto G, Malvicini R, De Lazzari G, Penna A, Franco C, et al. Biodistribution of Intratracheal, Intranasal, and Intravenous Injections of Human Mesenchymal Stromal Cell-Derived Extracellular Vesicles in a Mouse Model for Drug Delivery Studies. Pharmaceutics. 2023;15(2):548. Sanchez-Diaz M, Quiñones-Vico MI, Sanabria de la Torre R, Montero-Vílchez T, Sierra-Sánchez A, Molina-Leyva A, et al. Biodistribution of Mesenchymal Stromal Cells after Administration in Animal Models and Humans: A Systematic Review. J Clin Med. 2021;10(13). Tieu A, Stewart DJ, Chwastek D, Lansdell C, Burger D, Lalu MM. Biodistribution of mesenchymal stromal cell-derived extracellular vesicles administered during acute lung injury. Stem Cell Res Ther. 2023;14(1):250. Jin X, Lin T, Xu Y. Stem Cell Therapy and Immunological Rejection in Animal Models. Curr Mol Pharmacol. 2016;9(4):284-8. Mohamed-Ahmed S, Fristad I, Lie SA, Suliman S, Mustafa K, Vindenes H, et al. Adipose-derived and bone marrow mesenchymal stem cells: a donor-matched comparison. Stem Cell Res Ther. 2018;9(1):168. Mastrolia I, Foppiani EM, Murgia A, Candini O, Samarelli AV, Grisendi G, et al. Challenges in Clinical Development of Mesenchymal Stromal/Stem Cells: Concise Review. Stem Cells Transl Med. 2019;8(11):1135-48. Malgieri A, Kantzari E, Patrizi MP, Gambardella S. Bone marrow and umbilical cord blood human mesenchymal stem cells: state of the art. Int J Clin Exp Med. 2010;3(4):248-69. Varderidou-Minasian S, Lorenowicz MJ. Mesenchymal stromal/stem cell-derived extracellular vesicles in tissue repair: challenges and opportunities. Theranostics. 2020;10(13):5979-97. Ameri A, Ahmed HM, Pecho RDC, Arabnozari H, Sarabadani H, Esbati R, et al. Diverse activity of miR-150 in Tumor development: shedding light on the potential mechanisms. Cancer Cell Int. 2023;23(1):261. Oshi M, Gandhi S, Wu R, Yan L, Yamada A, Ishikawa T, et al. Abstract P3-10-01: Mir-150 expression is associated with immune cell infiltration and immune response in breast cancer. Cancer Research. 2022;82(4_Supplement):P3-10-01-P3-10-01. Xiao C, Rajewsky K. MicroRNA control in the immune system: basic principles. Cell. 2009;136(1):26-36. Wang H, Li X, Li T, Wang L, Wu X, Liu J, et al. Multiple roles of microRNA-146a in immune responses and hepatocellular carcinoma. Oncol Lett. 2019;18(5):5033-42. Li B, Xu WW, Han L, Chan KT, Tsao SW, Lee NPY, et al. MicroRNA-377 suppresses initiation and progression of esophageal cancer by inhibiting CD133 and VEGF. Oncogene. 2017;36(28):3986-4000. Yuan S, Wu Q, Wang Z, Che Y, Zheng S, Chen Y, et al. miR-223: An Immune Regulator in Infectious Disorders. Front Immunol. 2021;12:781815. Table Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4328001","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":300316596,"identity":"7f09db39-ff8d-44a1-99dc-17d1462991f8","order_by":0,"name":"Awirut Charoensappakit","email":"","orcid":"","institution":"Center of Excellence on Translational Research in Inflammation and Immunology (CETRII), Department of Microbiology, Faculty of Medicine, Chulalongkorn University","correspondingAuthor":false,"prefix":"","firstName":"Awirut","middleName":"","lastName":"Charoensappakit","suffix":""},{"id":300316598,"identity":"ea459132-eefe-4496-9bbb-1f37d6540321","order_by":1,"name":"Kritsanawan Sae‑khow","email":"","orcid":"","institution":"Center of Excellence on Translational Research in Inflammation and Immunology (CETRII), Department of Microbiology, Faculty of Medicine, Chulalongkorn University","correspondingAuthor":false,"prefix":"","firstName":"Kritsanawan","middleName":"","lastName":"Sae‑khow","suffix":""},{"id":300316600,"identity":"6495882c-fa12-4c5b-a10e-1bcc4a0e9cc5","order_by":2,"name":"Pongpera Rattanaliam","email":"","orcid":"","institution":"Department of Clinical Microscopy, Faculty of Allied Health Sciences, Chulalongkorn University","correspondingAuthor":false,"prefix":"","firstName":"Pongpera","middleName":"","lastName":"Rattanaliam","suffix":""},{"id":300316602,"identity":"bac12663-86ff-47c2-bea2-7afc95e0dfdb","order_by":3,"name":"Nuntanuj Vutthikraivit","email":"","orcid":"","institution":"Division of Critical Care Medicine, Department of Internal Medicine, Chulalongkorn University","correspondingAuthor":false,"prefix":"","firstName":"Nuntanuj","middleName":"","lastName":"Vutthikraivit","suffix":""},{"id":300316604,"identity":"1012b90f-22a9-43db-a53a-ab5e9537726e","order_by":4,"name":"Patinya Maneesow","email":"","orcid":"","institution":"Division of Critical Care Medicine, Department of Internal Medicine, Chulalongkorn University","correspondingAuthor":false,"prefix":"","firstName":"Patinya","middleName":"","lastName":"Maneesow","suffix":""},{"id":300316606,"identity":"caef55d1-7bfa-44a2-b42c-8d66bb9e1e77","order_by":5,"name":"Thitiwat Sriprasart","email":"","orcid":"","institution":"Division of Critical Care Medicine, Department of Internal Medicine, Chulalongkorn University","correspondingAuthor":false,"prefix":"","firstName":"Thitiwat","middleName":"","lastName":"Sriprasart","suffix":""},{"id":300316608,"identity":"9ade7aed-a409-4f90-b543-b66a1caf462c","order_by":6,"name":"Monvasi Pecheenbuvan","email":"","orcid":"","institution":"Division of Critical Care Medicine, Department of Internal Medicine, Chulalongkorn University","correspondingAuthor":false,"prefix":"","firstName":"Monvasi","middleName":"","lastName":"Pecheenbuvan","suffix":""},{"id":300316610,"identity":"502f01ef-d0ae-4bc9-bee7-b0ccc0826d89","order_by":7,"name":"Asada Leelahavanichkul","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYDACdiB+wHAAzD7AUAEkmZkb8GthBuIEmJYDZ0AijCRoYTjYBiIJaOFvZj74IKHmjrzB8bMHD3+cVxvN3w7U8qNiG04tEofZkg0Sjj0z3HAmL+HAwW3Hc2ccZmxg7DlzG7c1h3nMJBLYDjPObMgxAGo5ltsA1MLM2IZbi/xh/u8/Ev4dtp/Z/waoZc6x3PmEtBgc5mFjSGw7nNgvAbKloSZ3AyEthofZjCUS+w4n90sAbTlz7EDuRqCWg/j8Ine8+eGHD98O27bx5xh/qKipy513/vDBBz8q8HgfDRwGkweIVg8EdaQoHgWjYBSMghECADdzZ7hXxl/WAAAAAElFTkSuQmCC","orcid":"","institution":"Center of Excellence on Translational Research in Inflammation and Immunology (CETRII), Department of Microbiology, Faculty of Medicine, Chulalongkorn University","correspondingAuthor":true,"prefix":"","firstName":"Asada","middleName":"","lastName":"Leelahavanichkul","suffix":""}],"badges":[],"createdAt":"2024-04-26 07:40:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4328001/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4328001/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56188368,"identity":"6280bb6c-78b7-43d1-a846-78e23b8b768d","added_by":"auto","created_at":"2024-05-09 16:01:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":457624,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA guideline for systematic searching\u003c/p\u003e","description":"","filename":"image1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4328001/v1/09000d20ec1ecee613fb4366.jpg"},{"id":56188375,"identity":"a6e4515d-52d6-44a0-915d-55d3e447eba6","added_by":"auto","created_at":"2024-05-09 16:01:13","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":599669,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots of relative risk (RR) and risk difference (RD) in mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) treatment in sepsis models are demonstrated.\u003c/p\u003e","description":"","filename":"image2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4328001/v1/f721b87024f33aa42d428905.jpg"},{"id":56188712,"identity":"de40d7d5-cc5d-4f0f-a20a-6ab8edbe01fa","added_by":"auto","created_at":"2024-05-09 16:09:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":695716,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots of the relative risk (RR) and risk difference (RD) of sepsis treatment by mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) with subgroup analysis in the publications using MSC-EVs from humans and animals (A) or MCS-EVs from humans alone (B) are demonstrated.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4328001/v1/f5fcdacc2a8d34cc9ce66bb4.png"},{"id":56188371,"identity":"8a5a5646-5e60-4857-9c0a-aff4b226261b","added_by":"auto","created_at":"2024-05-09 16:01:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":632542,"visible":true,"origin":"","legend":"\u003cp\u003eThe bio-informatics from the studies using human mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) (25 studies) with the differences and similarities in the endpoint of the studies in several aspects, including inflammation, mortality rate, and organ injury (lungs, kidneys, and livers), are demonstrated through the Ven-diagram (A). The correlation of different human micro-RNAs (hsa-miRs) mentioned in the studies with human MSC-EVs using miRnet software with miRDatabase ver 8.0 as indicated by the connection of the possible target genes (B), miR function (C), biological process (target gene GO) (D), and target gene Reactome (E) is shown.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4328001/v1/4fb2a1fa2ef4d6cf097f05ae.png"},{"id":57535087,"identity":"704abd3f-5f67-438b-9e05-7d1d83676236","added_by":"auto","created_at":"2024-06-01 07:32:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3137298,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4328001/v1/e32e145e-9564-408b-95c0-5430bcb7ab21.pdf"},{"id":56188711,"identity":"6bea6142-f57b-4f96-9b80-b79d8a7b0989","added_by":"auto","created_at":"2024-05-09 16:09:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":132497,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4328001/v1/82c38cf8e5a75e603b26b5e2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Adjunctive treatment of sepsis with mesenchymal stem cell-derived extracellular vesicles: a systemic review and meta-analysis of pre-clinical studies","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSepsis, an abnormal host response toward infection, is a life-threatening syndrome with multi-organ dysfunction and high morbidity and mortality, despite the currently improved supportive care (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Currently, antibiotics and supportive measures remain the only available treatments for patients with sepsis, but these measures have limited effects on reducing the mortality of sepsis (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), highlighting the urgent need to develop innovative and potent therapies. In pro-inflammatory sepsis, excessive secretion of inflammatory cytokines contributes to multi-organ dysfunction, and the severity and duration of inflammatory responses determine the prognosis of patients (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Thus, the use of immune modulation therapy is still frequently mentioned in the research field (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), and several immune inhibitors might be beneficial in patients with severe sepsis. However, none of these substances can be used in real clinical situations because of the complex sepsis pathogenesis. Then, the ideal adjuvant therapy for sepsis might be a combination of multiple drug targets, including early immunomodulation, cell protection, and prevention of end-organ damage (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In this context, an investigation into novel therapies to ameliorate sepsis would be urgently needed, especially for sepsis-induced hyper-inflammatory responses.\u003c/p\u003e \u003cp\u003eAmong several immune inhibitors, mesenchymal stem cells (MSCs) or multipotent mesenchymal stromal cells have attracted interest for use in sepsis. Indeed, injection of MSCs in cecal ligation and puncture (CLP) surgery-induced sepsis mice attenuates sepsis severity (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), partly through an interaction with monocytes/macrophages (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) and other immune cells (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Additionally, the suppressive effects of MSCs are also demonstrated in other conditions, including organ transplantation, graft versus host disease, and some autoimmune diseases (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Due to several stem cell properties (differentiation potential and self-renewal), MSCs have also been clinically studied as therapeutic agents for regenerative medicine in a variety of diseases, for example, diabetes, Alzheimer's disease, and osteoarthritis (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). However, there are some challenges with the use of MSCs, including the low survival rate of the cells after administration, the difficulty of stem cells reaching the injury sites, and cell preparation problems (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). On the other hand, it is well known that the mechanisms of MSC-induced immune suppression are mainly due to the soluble factors of MSCs, and the extraction methods of these factors have been extensively studied (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Due to the difficulties in cell preparation and several limitations in the administration of viable cells (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), the use of soluble factors from MSCs, including MSC-derived extracellular vesicles (MSC-EVs), is currently being introduced. As such, extracellular vesicles (EVs) are cell-derived membrane surrounded vesicles from almost all cells, with prominently high production in stem cells, carrying bioactive molecules to distant sites in the body (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). In addition, EVs are characterized by the diameters of exosomes and microvesicles and the EV structures effectively protect their cargo components, including proteins, lipids, genetic material (miRNA, RNA, and DNA), and some metabolites, from the extracellular environment (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Compared with cell therapy, EVs have several advantages; for example, non-immunogenicity, non-infusion toxicity, relatively higher stability in the blood circulation, easier access, uncomplicated preservation, and ethical issues (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). For clinical application, MSC-EVs attenuate patients suffering from steroid refractory graft-versus-host disease, ostheoarthitis, and grade III-IV chronic kidney disease (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). In sepsis, pre-clinical studies in animal models have demonstrated the beneficial efficacy of MSC-EVs in sepsis; however, the impacts of MSC-EV treatment are still inconclusive. Therefore, we conducted this meta-analysis by summarizing data from all published studies that met our criteria to explore the association between MSC-EV treatment and mortality in animal models of sepsis. Additionally, we also determine the potential effects of some specific microRNAs (miRNA) contained in MSC-EVs using data mining and a bioinformatic database for predicting the possible miRNA that might be responsible for the MSC-EV therapeutic effect.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e \u003cem\u003eSearch strategies and eligibility criteria.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 guidelines. A systematic literature search of the Scopus, PubMed, Cochrane Library, and Clinicaltrial.gov databases published from 2000 until December 2023 was performed. The article was limited only to the English-reported studies. The retrieval query formulation used for the search was \u0026ldquo;mesenchymal stem cell-derived extracellular vesicles\u0026rdquo; OR \u0026ldquo;MSC-EVs\u0026rdquo; OR \u0026ldquo;mesenchymal stem cell-derived exosomes\u0026rdquo; OR \u0026ldquo;mesenchymal stem cell-derived microvesicles\u0026rdquo; AND \u0026ldquo;sepsis\u0026rdquo; OR \u0026ldquo;pneumonia\u0026rdquo; AND \u0026ldquo;animal models\u0026rdquo;. All the reference lists of the identified articles and relevant reviews were also manually screened. Two groups of reviewers independently screened the inclusion of the article\u0026rsquo;s eligibility. The disagreement on any topic during the review process was resolved through a consensus with the third group of reviewers. The inclusion criteria were full text studies investigating the effectiveness of MSC-EV treatment on sepsis animal models. The inclusion criteria were: i) evaluation of the therapeutic effect of MSC-EVs on sepsis animal models; ii) the studies involved an animal model of sepsis or endotoxemia; iii) the protective effect of MSC-EVs or EV-derived active molecules was the focus of the study; and iv) the studies reported mortality rates or reductions in inflammation. The exclusion criteria were: i) MSC-EVs were not directly used as therapy; ii) extracellular vesicles were genetically modified; iii) no sepsis occurred and a lack of end points of interest; and iv) none of in the vivo experiments. Only publications whose language is English are included.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eRisk of bias\u003c/h2\u003e \u003cp\u003eThe risk of bias was assessed according to the Systematic Review Center for Laboratory Animal Experimentation (SYRCLE) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), including selection bias, performance bias, detection bias, attrition bias, reporting bias, and others. The risk of bias was assessed carefully by two independent reviewers as low risk, high risk, or unclear risk based on the content of the article. Any disputes encountered during the evaluation process were resolved through discussion.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData extraction and statistical analysis\u003c/h2\u003e \u003cp\u003eTwo authors extracted the relevant data from the included studies independently using a specific form (Microsoft Excel), and then, three of the authors re-checked and confirmed the obtained raw data. The differences encountered were resolved through discussion with the third expert reviewer. The following data were recorded: first author, country or region, year of publication, animal type, number, sepsis model type, origin of EVs, dose, injection method, injection time, observation time after EVs administration, and indicators related to the primary outcome. For gathering of the results, the effect size of this meta-analysis was mortality. The risk ratio (RR) and risk difference (RD) values of the EV treatment group and control group were calculated to determine the combined effect size. The mean with standard deviations (SD) values was used for the calculations, and the standard errors (SE) were calculated into SD using the Cochrane Collaboration formula (SD\u0026thinsp;=\u0026thinsp;SE x \u0026radic;N). For the values presented with median and range, or interquartile range (IQR), the mean values and SD were estimated by the statistical formula reported by Wan et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The effect model of meta-analysis was selected according to whether the heterogeneity was significant (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Heterogeneity was measured using the among-study variance (τ2), chi-squared (χ2) test, and identify and interpret strategy (I2) statistical analyses. For the measurement with an I2\u0026thinsp;\u0026lt;\u0026thinsp;50%, the results were pooled using a fixed effects model, otherwise, a random effects model was used. All statistical analyses were performed using SPSS version 22 and visualized using Microsoft Excel. Then, the results of the analysis were presented as the forest plots of pooled RR and RD with a 95% confidence interval. Statistical significance was defined at the p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Sensitivity analyses were performed by removing each study individually from the results of the meta-analysis. As a method for bioinformatics of miRNA prediction, an integrated platform linking miRNAs, their targets, and their functions named \u0026ldquo;miRNet 2.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mirnet.ca/\u003c/span\u003e\u003cspan address=\"https://www.mirnet.ca/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u0026rdquo; was used to predict the downstream targeted genes of the expected miRNAs. As part of network creation and analysis, all expected miRNA entries are annotated according to the latest miRbase (miRTarBase). Gene set enrichment analysis was performed using validated miRNA gene targets from the miRNet database and their built-in software for Gene Ontology (GO) biological processes and reactome enrichment analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eStudy inclusion and characteristics.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA total of 1,078 articles were retrieved from the three databases according to the search strategies. After the elimination of duplicate articles, 1,013 of 1,078 articles were initially screened and excluded according to the title and abstract. The full text of the remaining 68 articles was reviewed. Fifty-three articles were selected to be included in this systematic review according to the inclusion and exclusion criteria, and 30 articles were selected to be included in the meta-analysis due to mortality reports in the studies (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Details of the included studies are demonstrated in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The risk of bias among the studies was assessed by SYRCLE's RoB tool (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). All studies were considered to have RoB risks. Although 11 studies (36.7%) reported randomization of animals, none of them showed the method for generating the random sequences or the assignments were inadequately reported. Therefore, the RoB scores in the selection bias component were \"unclear\" for these studies. Six studies might have had a problem with the experimental design, which resulted in a RoB score of \"high risk\" due to a possible contamination of substances in the stimulated MSCs.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSYRCLE tool risk of bias\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAuthors\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eyear\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eSelection bias\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003ePerformance bias\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDetection bias\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAttrition bias\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eReporting bias\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOther bias\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRandom sequence generation?\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGroups similar at baseline?\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAllocation concealed?\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAnimals randomly housed?\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBlinding of caregivers and/or examiners?\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRandom selection for outcome assessment?\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBlinding of outcome assessor?\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eIncomplete outcome data addressed?\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFree from selective outcome reporting?\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFree from other bias?\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eXiaohong Wang et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHaojie Yuan et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAntoine Monsel et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYuxian song et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2017\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eH\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChia-Lo Chang et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2018\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAmir K. Varkouhi et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2019\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eH\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRongxue Zhang et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFang Gao et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHuimin Deng et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDanyang Zheng et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eJia Sun et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eH\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eQin Zhou et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eJie Chen et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYuan Su et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMahshid Akhavan Rahnama et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMengying Yao et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLiangjun Xia et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eH\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eXiaoyan et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eH\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHuimin Deng et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRuichao Niu et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eH\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHuimin Deng et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eShan Cao et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWen Zhang et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eXiaoxia Wang et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWei Peng et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eH\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eJizhen Cai et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCui Jin et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePaulius Valiukevicius et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNat\u0026aacute;lia G. Blanco et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKento Homma et al.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eL\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003eEffects of mesenchymal stem cell-derived extracellular vesicles on sepsis mortality\u003c/h2\u003e\n\u003cp\u003eA total of 30 published articles related to MSC-EV treatment and mortality from sepsis were included in the meta-analysis (pooled analysis), all of which mentioned mortality rates in the publication. Mortality at the end point (observed time) was 148 of 648 (22.8%) in the MSC-EV-treated experiments, whereas 258 of 381 (67.7%) were in the control group. As the forest plot of pooled analysis of relative risk (RR) and risk difference (RD) showed high certain results (very low heterogeneity; I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%) that MSC-EVs treatment significantly attenuated sepsis mortality in both RR and RD values (the fixed effect model: RR\u0026thinsp;=\u0026thinsp;0.53, 95% CI: 0.46\u0026ndash;0.60, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD= -0.35, 95% CI: -0.41 - -0.30, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Sensitivity analysis was conducted by excluding each study from the results of the meta-analysis.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003eSubgroup analysis\u003c/h2\u003e\n\u003cp\u003eSubgroup analyses were performed to evaluate the efficacy of MSC-EVs in the treatment of sepsis using the fixed effect model, considering the generality and reproducibility of treatment outcomes across different experimental conditions (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA, B). Importantly, heterogeneity was also low in each subgroup. As such, in the animal model, all subgroups showed statistical significance in both RR and RD, except for the use of MSC-EVs in non-rodent animals (sheep) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA). The use of MSC-EVs in rats (RR\u0026thinsp;=\u0026thinsp;0.33, 95% CI: 0.22\u0026ndash;0.50, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD = -0.42, 95% CI: -0.54 \u0026ndash; -0.29, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was more effective than in mice (RR\u0026thinsp;=\u0026thinsp;0.55, 95% CI: 0.48\u0026ndash;0.64, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD = -0.34, 95% CI: -0.41 \u0026ndash; -0.28, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA). In comparison with the cecal ligation and puncture (CLP) model (RR\u0026thinsp;=\u0026thinsp;0.56, 95% CI: 0.48\u0026ndash;0.66, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD = -0.32, 95% CI: -0.40 \u0026ndash; -0.25, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), MSC-EVs demonstrated better therapeutic outcomes than the non-CLP sepsis models, including lipopolysaccharide (LPS) and bacteria injection models. As such, the parameters for \u0026ldquo;LPS/ Bacteria-induced sepsis\u0026rdquo; were: RR\u0026thinsp;=\u0026thinsp;0.45, 95% CI: 0.30\u0026ndash;0.65 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and RD = -0.48, 95% CI: -0.65 \u0026ndash; -0.30 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). On the other hand, the data for MSC-EVs impacts in LPS and bacterial pneumonia model from \u0026ldquo;LPS/Bacteria-induced pneumonia\u0026rdquo; were: RR\u0026thinsp;=\u0026thinsp;0.45, 95% CI: 0.33\u0026ndash;0.60 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and RD = -0.37, 95% CI: -0.47 \u0026ndash; -0.26 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), when compared with the CLP model (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA). There was a more prominent survival with the dosage of MSC-EVs at equal or greater than 100 ug per mouse (RR\u0026thinsp;=\u0026thinsp;0.36, 95% CI: 0.23\u0026ndash;0.59, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD = -0.45, 95% CI: -0.55 \u0026ndash; -0.34, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than with the dosage lower than 100 ug (RR\u0026thinsp;=\u0026thinsp;0.52, 95% CI: 0.44\u0026ndash;0.62, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD = -0.39, 95% CI: -0.48 \u0026ndash; -0.31, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA). In comparison with the MSC-EV treatment for more than 2 days (RR\u0026thinsp;=\u0026thinsp;0.56, 95% CI: 0.48\u0026ndash;0.64, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD = -0.38, 95% CI: -0.45 \u0026ndash; -0.31, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the EV treatment for less than 2 days (RR\u0026thinsp;=\u0026thinsp;0.37, 95% CI: 0.26\u0026ndash;0.35, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD = -0.30, 95% CI: -0.39 \u0026ndash; -0.21, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) also improved sepsis survival rate (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e\n\u003cp\u003eTo estimate the potential to use MSC-EVs in real clinical situations, a subgroup analysis of the MSC-EVs that were derived from human MSC was determined (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB). In the human MSC data, all subgroups also presented low heterogeneity, and human umbilical cord MSC-EVs (huUCMSCs) (RR\u0026thinsp;=\u0026thinsp;0.72, 95% CI: 0.57\u0026ndash;0.89, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003 and RD = -0.09, 95% CI: -0.19\u0026ndash;0.01, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.078) exhibited a significant lower effectiveness than bone marrow-isolated MSC-EVs (huBMMSCs) (RR\u0026thinsp;=\u0026thinsp;0.44, 95% CI: 0.27\u0026ndash;0.74, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002 and RD = -0.37, 95% CI: -0.53 \u0026ndash; -0.22, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or adipose tissue-derived MSC-EVs (huADMSCs) (RR\u0026thinsp;=\u0026thinsp;0.35, 95% CI: 0.21\u0026ndash;0.58, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD = -0.36, 95% CI: -0.48 \u0026ndash; -0.23, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB). With human MSC-EVs, the treatment before sepsis induction did improve survival (RR\u0026thinsp;=\u0026thinsp;0.71, 95% CI: 0.47\u0026ndash;1.09, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12 and RD = -0.27, 95% CI: -0.54\u0026ndash;0.03, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.076) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB), while the treatment after sepsis induction for less or more than 2 days (RR\u0026thinsp;=\u0026thinsp;0.26, 95% CI: 0.11\u0026ndash;0.62, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD = -0.22, 95% CI: -0.35 \u0026ndash; -0.10, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) could attenuate sepsis mortality (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB). Parallelly, the higher doses of MSC-EVs (RR\u0026thinsp;=\u0026thinsp;0.30, 95% CI: 0.12\u0026ndash;0.75, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005 and RD = -0.45, 95% CI: -0.59 \u0026ndash; -0.31, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) had a trend of improved survival than the lower dosages (RR\u0026thinsp;=\u0026thinsp;0.53, 95% CI: 0.41\u0026ndash;0.68, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and RD = -0.43, 95% CI: -0.56 \u0026ndash; -0.29, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) could (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eBioinformatic analysis of miRNA containing in human MSC-EVs\u003c/h2\u003e\n\u003cp\u003eThen, the possibility of using a MSC-EV treatment in real clinical situation was simulated through data mining and bioinformatic prediction (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). With the Venn diagram, the sphere shapes with orange and grey colors represent MSC-EV studies with improved inflammatory responses and mortality, respectively, while the ellipse shapes represent studies mentioning organ injuries (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA). There were only 3 studies that demonstrated all outcomes (inflammation, mortality, kidney injury, lung lesion, and liver damage), while most of the studies (8 studies) demonstrated survival, inflammatory responses, and lung complications (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA). Because microRNAs (miRNAs) contained in EVs are possible molecules responsible for sepsis attenuation, for example, through epigenetic regulation (\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e), subgroup analysis following the miRNAs, mentioned in the human MSC-EV sepsis studies, was performed using the miRNA-target interaction networks (miRnet; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"https://www.mirnet.ca/\" target=\"_blank\"\u003ewww.mirnet.ca\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e). From the list of miRNAs in human MSC-EVs (hsa-miR223, hsa-miR146a, hsa-miR145, hsa-miR377, and hsa-miR150), there were 1,693 genes that were targeted by these miRNAs (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB). Among the top 10 enrichment functional pathways regulated by all miRNAs, innate immunity was the first enrichment, followed by oncology genes (Onco-MiRNAs) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC). Moreover, enrichment pathways for the targeted genes, referred to as target gene Gene Ontology (GO), were generated. With the GO term in biological processes, the majority of enrichment pathways were those that were related to the immune system and immune cell development (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD). Consisting of the enrichment of Reactome (the pathway database providing the intuitive bioinformatics tools for visualization), the results also showed that the first rank of the enrichment was the cell responses to stress, followed by cellular senescence (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eE).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eImmune modulation is an interesting strategy against sepsis, especially sepsis hyper inflammation, and anti-inflammation with effective anti-biotics might attenuate sepsis-induced organ injury (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Currently, there are several biomarkers that can be used for identifying hyper-inflammatory responses in sepsis and exhibit correlation with severity and mortality; for example, serum cytokines, endotoxemia, cell-free DNA, and immune cell activities (\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Then, some immune inhibitors might be beneficial in patients with severe sepsis identified by these biomarkers. Although there are several inflammatory inhibitors and immune stimulators that might be useful in sepsis, especially from pre-clinical studies (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) none of these substances can be used in real clinical situations. Therefore, new therapeutic strategies to attenuate sepsis-induced hyper-inflammatory responses might improve the clinical outcome of these patients. Among several anti-inflammatory strategies in sepsis, MSC-EV treatment is one of the most interesting candidates compared with MSC therapy, with several advantages, including safety, stability, good permeability, immunogenicity, and cytotoxicity (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The effective anti-inflammation in sepsis of MSC-EVs might be due to the delivery of miRNAs or long non-coding RNA (lncRNA) to several immune cells, especially macrophages (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Meanwhile, the EVs from other cells; for example, erythrocytes and platelets, might aggravate inflammation, which may be a potential risk factor for transfusion-related immune regulation (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). The possibilities of using MSC-EVs in patients have been demonstrated in many clinical trials of MSC-EV-related therapies, including the potential to treat severe COVID-19 (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Unfortunately, the studies of MSC-EVs in human sepsis have never been demonstrated.\u003c/p\u003e \u003cp\u003eAlthough immune regulation and differentiation capabilities of MSCs are beneficial for immune modulation and repair in sepsis, several limitations of cell therapy, including uncontrolled cell proliferation, malignant cell differentiation, and low engraftment (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), are mentioned. Here, there are two included studies comparing the effectiveness between MSC cell-based therapy and MSC-EVs on sepsis that demonstrated the greater efficacy of MSC-EVs, possibly through the better biodistribution of MSC-EVs throughout the body and tissue-specific localization (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), or alternatively via secondary effects on activated host cells in tissue upon EV uptake (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Due to the larger sizes of MSCs than MSC-EVs, the distribution of MSCs after intravenous injection is limited to some organs (livers and lungs) (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), while MSC-EVs rapidly spread throughout the whole body and might also be delivered through the EV-uptake cells. Included studies using vital tracking found that MSC-EVs spread to the whole mouse body within an early time and were localized in the lung, liver, and a little bit in the kidney after 2\u0026ndash;6 h after administration (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). These data suggest that when MSC-EVs are administered, they may easily move to reach other tissues to induce anti-inflammatory effects elsewhere.\u003c/p\u003e \u003cp\u003eHere, our meta-analytic results supported the high effectiveness of MSC-EVs on sepsis attenuation with homogeneity results. From the subgroup analysis, EVs of the same species are more effective than the EV xenografts (the use of human MSC-EVs in animals), which possibly relates to the well-known acute rejection caused by natural antibodies and complements in xenografts (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Additionally, the EVs that were derived from primary MSCs of bone marrow show superior efficacy to EVs extracted from other cell types, which may be related to the lower immunogenicity and higher immunomodulatory capacities of MSCs. Previous studies also demonstrated the benefits of EVs from bone marrow (BM)-derived MSCs in other disease models, including cardiovascular, liver, and lung diseases (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). However, the BM requires an invasive biopsy to obtain the MSCs to extract EVs, and the yield is relatively limited as the high numbers of MSCs might be required for the treatment in humans (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Although the umbilical cord is possibly a more suitable source of MSC-EVs for clinical translation than the BM isolation as determined by the feasibility and the greater self-renewal capacity (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), our analysis showed a significant lower effectiveness of MSC-EVs from the umbilical cord compared with the MSCs from BM. On the other hand, demonstrating the effect of EVs from adipose tissue-derived MSCs (ADMSCs) was an important advance in this regard, with nearly the same capacity as BMMSC-EVs. Among the advantages of ADMSCs, the easier extraction with more prominent adipocytes through subcutaneous lipoaspiration compared with BM stem cell harvesting through BM biopsy is mentioned (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Although our meta-analysis suggested that MSC-EVs at the dose of 100 \u0026micro;g might have a better therapeutic effect in a dose-dependent manner, further studies for the determination of proper doses of MSC-EVs for sepsis treatment are urgently required. Some insights on the therapeutic potential of MSC-EVs, particularly clinical applications, EV induction, and isolation, are also interesting.\u003c/p\u003e \u003cp\u003eFor the content delivery of EVs, an important mechanism of immunomodulation in sepsis, several included studies have proposed that MSC-EVs transfer a variety of bioactive molecules, particularly miRNAs, to the recipient cells and induce some beneficial outcomes (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Indeed, miRNAs function as guides by base-pairing with target mRNA, mostly for negative regulation of the targeted mRNA (marked mRNA), which might be either denatured or preserved and translated later instead of being quickly translated into a protein. Here, the enrichment analysis of the recorded miRNAs contained in human MSC-EVs using human miRdatabase bioinformatic tools revealed impacts of miRNAs in many mechanisms, including innate immunity control, hematopoiesis, and stress responses (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-F). However, the difference in miRNA content in EVs derived from different conditions; for example, EVs from different sources of MSCs was not determined. Then, more studies on the miRNAs in MSC-EVs from various conditions are interesting. The synthetic EVs that contain single, combined or engineered miRNAs are an interesting idea for developing a new anti-inflammatory strategy against sepsis. Here, we provid a list of the interesting miRNAs for sepsis in MSC-EVs. Several miRNAs in the list were previously mentioned. For example, miR-150 associates with several cancers, especially during metastasis (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), and also acts as an inhibitor against some immune cells, including dendritic cells and T-helper cells (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). In parallel, miR-145, miR-146, and miR-377 are anti-inflammation and antiproliferation (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), while miR-223 is correlated with infectious diseases (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, our meta-analysis provided important clues about the use of MSC-EVs for sepsis as a guide for basic research for further clinical endeavors. To the best of our knowledge, this is the first meta-analysis of MSC-EVs in pre-clinical sepsis experiments, which provides a summary of the efficacy of MSC-EVs on sepsis attenuation. Future research on MSC-EVs for sepsis in patients is needed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors approved the submission of the final article. The authors have disclosed that they do not have any potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.C., K.s-k. and A.L. performed the literature search, data extraction, analysis and wrote the manuscript. A.C. and P.R. extracted the data and performed assessment of bias and certainty of evidence, independently. M.P., N.V., P.M., T.S. and A.L. conceived the study, analyzed the data, and corrected the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFundings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by Chulalongkorn University, the National Research Council of Thailand (NRCT) (N41A640076, N34A660583), and the Program Management Unit for Human Resources, Institutional Development, Research, and Innovation (B16F640175). A.C. was funded by Second Century Fund (C2F) from Chulalongkorn University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the submission of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSae-khow K, Charoensappakit A, Chiewchengchol D, Leelahavanichkul A. High-Dose Intravenous Ascorbate in Sepsis, a Pro-Oxidant Enhanced Microbicidal Activity and the Effect on Neutrophil Functions. Biomedicines [Internet]. 2023; 11(1).\u003c/li\u003e\n\u003cli\u003eChen AX, Simpson SQ, Pallin DJ. Sepsis Guidelines. New England Journal of Medicine. 2019;380(14):1369-71.\u003c/li\u003e\n\u003cli\u003eLeligdowicz A, Harhay Michael O, Calfee Carolyn S. Immune Modulation in Sepsis, ARDS, and Covid-19 \u0026mdash; The Road Traveled and the Road Ahead. NEJM Evidence. 2022;1(11):EVIDra2200118.\u003c/li\u003e\n\u003cli\u003eCao M, Wang G, Xie J. Immune dysregulation in sepsis: experiences, lessons and perspectives. Cell Death Discovery. 2023;9(1):465.\u003c/li\u003e\n\u003cli\u003eN\u0026eacute;meth K, Leelahavanichkul A, Yuen PS, Mayer B, Parmelee A, Doi K, et al. Bone marrow stromal cells attenuate sepsis via prostaglandin E(2)-dependent reprogramming of host macrophages to increase their interleukin-10 production. Nat Med. 2009;15(1):42-9.\u003c/li\u003e\n\u003cli\u003eGhannam S, Bouffi C, Djouad F, Jorgensen C, No\u0026euml;l D. Immunosuppression by mesenchymal stem cells: mechanisms and clinical applications. Stem Cell Res Ther. 2010;1(1):2.\u003c/li\u003e\n\u003cli\u003eMonsel A, Zhu YG, Gennai S, Hao Q, Liu J, Lee JW. Cell-based therapy for acute organ injury: preclinical evidence and ongoing clinical trials using mesenchymal stem cells. Anesthesiology. 2014;121(5):1099-121.\u003c/li\u003e\n\u003cli\u003eMaldonado VV, Patel NH, Smith EE, Barnes CL, Gustafson MP, Rao RR, et al. Clinical utility of mesenchymal stem/stromal cells in regenerative medicine and cellular therapy. Journal of Biological Engineering. 2023;17(1):44.\u003c/li\u003e\n\u003cli\u003eMusiał-Wysocka A, Kot M, Majka M. The Pros and Cons of Mesenchymal Stem Cell-Based Therapies. Cell Transplant. 2019;28(7):801-12.\u003c/li\u003e\n\u003cli\u003ePark KS, Svennerholm K, Shelke GV, Bandeira E, Lasser C, Jang SC, et al. Mesenchymal stromal cell-derived nanovesicles ameliorate bacterial outer membrane vesicle-induced sepsis via IL-10. Stem Cell Res Ther. 2019;10(1):231.\u003c/li\u003e\n\u003cli\u003eVerweij FJ, Balaj L, Boulanger CM, Carter DRF, Compeer EB, D\u0026rsquo;Angelo G, et al. The power of imaging to understand extracellular vesicle biology in vivo. Nature Methods. 2021;18(9):1013-26.\u003c/li\u003e\n\u003cli\u003eKhosrojerdi A, Soudi S, Hosseini AZ, Eshghi F, Shafiee A, Hashemi SM. Immunomodulatory and Therapeutic Effects of Mesenchymal Stem Cells on Organ Dysfunction in Sepsis. Shock. 2021;55(4):423-40.\u003c/li\u003e\n\u003cli\u003eKordelas L, Rebmann V, Ludwig AK, Radtke S, Ruesing J, Doeppner TR, et al. MSC-derived exosomes: a novel tool to treat therapy-refractory graft-versus-host disease. Leukemia. 2014;28(4):970-3.\u003c/li\u003e\n\u003cli\u003eNassar W, El-Ansary M, Sabry D, Mostafa MA, Fayad T, Kotb E, et al. Umbilical cord mesenchymal stem cells derived extracellular vesicles can safely ameliorate the progression of chronic kidney diseases. Biomaterials Research. 2016;20(1):21.\u003c/li\u003e\n\u003cli\u003eWarmink K, Rios JL, Varderidou-Minasian S, Torres-Torrillas M, van Valkengoed DR, Versteeg S, et al. Mesenchymal stem/stromal cells-derived extracellular vesicles as a potentially more beneficial therapeutic strategy than MSC-based treatment in a mild metabolic osteoarthritis model. Stem Cell Research \u0026amp; Therapy. 2023;14(1):137.\u003c/li\u003e\n\u003cli\u003eHooijmans CR, Rovers MM, de Vries RB, Leenaars M, Ritskes-Hoitinga M, Langendam MW. SYRCLE\u0026apos;s risk of bias tool for animal studies. BMC Med Res Methodol. 2014;14:43.\u003c/li\u003e\n\u003cli\u003eWan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014;14:135.\u003c/li\u003e\n\u003cli\u003eBorenstein M, Hedges LV, Higgins JP, Rothstein HR. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods. 2010;1(2):97-111.\u003c/li\u003e\n\u003cli\u003eQiu G, Zheng G, Ge M, Wang J, Huang R, Shu Q, et al. Mesenchymal stem cell-derived extracellular vesicles affect disease outcomes via transfer of microRNAs. Stem Cell Res Ther. 2018;9(1):320.\u003c/li\u003e\n\u003cli\u003eDang CP, Issara-Amphorn J, Charoensappakit A, Udompornpitak K, Bhunyakarnjanarat T, Saisorn W, et al. BAM15, a Mitochondrial Uncoupling Agent, Attenuates Inflammation in the LPS Injection Mouse Model: An Adjunctive Anti-Inflammation on Macrophages and Hepatocytes. J Innate Immun. 2021;13(6):359-75.\u003c/li\u003e\n\u003cli\u003eBarichello T, Generoso JS, Singer M, Dal-Pizzol F. Biomarkers for sepsis: more than just fever and leukocytosis\u0026mdash;a narrative review. Critical Care. 2022;26(1):14.\u003c/li\u003e\n\u003cli\u003eCharoensappakit A, Sae-khow K, Rattanaliam P, Vutthikraivit N, Pecheenbuvan M, Udomkarnjananun S, et al. Cell-free DNA as diagnostic and prognostic biomarkers for adult sepsis: a systematic review and meta-analysis. Scientific Reports. 2023;13(1):19624.\u003c/li\u003e\n\u003cli\u003eVisitchanakun P, Kaewduangduen W, Chareonsappakit A, Susantitaphong P, Pisitkun P, Ritprajak P, et al. Interference on Cytosolic DNA Activation Attenuates Sepsis Severity: Experiments on Cyclic GMP\u0026ndash;AMP Synthase (cGAS) Deficient Mice. International Journal of Molecular Sciences [Internet]. 2021; 22(21).\u003c/li\u003e\n\u003cli\u003eSae-khow K, Tachaboon S, Wright HL, Edwards SW, Srisawat N, Leelahavanichkul A, et al. Defective Neutrophil Function in Patients with Sepsis Is Mostly Restored by ex vivo Ascorbate Incubation. Journal of Inflammation Research. 2020;13(null):263-74.\u003c/li\u003e\n\u003cli\u003eWang J, Xia J, Huang R, Hu Y, Fan J, Shu Q, et al. Mesenchymal stem cell-derived extracellular vesicles alter disease outcomes via endorsement of macrophage polarization. Stem Cell Res Ther. 2020;11(1):424.\u003c/li\u003e\n\u003cli\u003eGao Y, Jin H, Tan H, Cai X, Sun Y. Erythrocyte-derived extracellular vesicles aggravate inflammation by promoting the proinflammatory macrophage phenotype through TLR4\u0026ndash;MyD88\u0026ndash;NF-\u0026kappa;B\u0026ndash;MAPK pathway. Journal of Leukocyte Biology. 2022;112(4):693-706.\u003c/li\u003e\n\u003cli\u003eLu X, Jiang G, Gao Y, Chen Q, Sun S, Mao W, et al. Platelet-derived extracellular vesicles aggravate septic acute kidney injury via delivering ARF6. Int J Biol Sci. 2023;19(16):5055-73.\u003c/li\u003e\n\u003cli\u003eKrishnan A, Muthusamy S, Fernandez FB, Kasoju N. Mesenchymal Stem Cell-Derived Extracellular Vesicles in the Management of COVID19-Associated Lung Injury: A Review on Publications, Clinical Trials and Patent Landscape. Tissue Eng Regen Med. 2022;19(4):659-73.\u003c/li\u003e\n\u003cli\u003eZarrabi M, Shahrbaf MA, Nouri M, Shekari F, Hosseini S-E, Hashemian S-MR, et al. Allogenic mesenchymal stromal cells and their extracellular vesicles in COVID-19 induced ARDS: a randomized controlled trial. Stem Cell Research \u0026amp; Therapy. 2023;14(1):169.\u003c/li\u003e\n\u003cli\u003eTolomeo AM, Zuccolotto G, Malvicini R, De Lazzari G, Penna A, Franco C, et al. Biodistribution of Intratracheal, Intranasal, and Intravenous Injections of Human Mesenchymal Stromal Cell-Derived Extracellular Vesicles in a Mouse Model for Drug Delivery Studies. Pharmaceutics. 2023;15(2):548.\u003c/li\u003e\n\u003cli\u003eSanchez-Diaz M, Qui\u0026ntilde;ones-Vico MI, Sanabria de la Torre R, Montero-V\u0026iacute;lchez T, Sierra-S\u0026aacute;nchez A, Molina-Leyva A, et al. Biodistribution of Mesenchymal Stromal Cells after Administration in Animal Models and Humans: A Systematic Review. J Clin Med. 2021;10(13).\u003c/li\u003e\n\u003cli\u003eTieu A, Stewart DJ, Chwastek D, Lansdell C, Burger D, Lalu MM. Biodistribution of mesenchymal stromal cell-derived extracellular vesicles administered during acute lung injury. Stem Cell Res Ther. 2023;14(1):250.\u003c/li\u003e\n\u003cli\u003eJin X, Lin T, Xu Y. Stem Cell Therapy and Immunological Rejection in Animal Models. Curr Mol Pharmacol. 2016;9(4):284-8.\u003c/li\u003e\n\u003cli\u003eMohamed-Ahmed S, Fristad I, Lie SA, Suliman S, Mustafa K, Vindenes H, et al. Adipose-derived and bone marrow mesenchymal stem cells: a donor-matched comparison. Stem Cell Res Ther. 2018;9(1):168.\u003c/li\u003e\n\u003cli\u003eMastrolia I, Foppiani EM, Murgia A, Candini O, Samarelli AV, Grisendi G, et al. Challenges in Clinical Development of Mesenchymal Stromal/Stem Cells: Concise Review. Stem Cells Transl Med. 2019;8(11):1135-48.\u003c/li\u003e\n\u003cli\u003eMalgieri A, Kantzari E, Patrizi MP, Gambardella S. Bone marrow and umbilical cord blood human mesenchymal stem cells: state of the art. Int J Clin Exp Med. 2010;3(4):248-69.\u003c/li\u003e\n\u003cli\u003eVarderidou-Minasian S, Lorenowicz MJ. Mesenchymal stromal/stem cell-derived extracellular vesicles in tissue repair: challenges and opportunities. Theranostics. 2020;10(13):5979-97.\u003c/li\u003e\n\u003cli\u003eAmeri A, Ahmed HM, Pecho RDC, Arabnozari H, Sarabadani H, Esbati R, et al. Diverse activity of miR-150 in Tumor development: shedding light on the potential mechanisms. Cancer Cell Int. 2023;23(1):261.\u003c/li\u003e\n\u003cli\u003eOshi M, Gandhi S, Wu R, Yan L, Yamada A, Ishikawa T, et al. Abstract P3-10-01: Mir-150 expression is associated with immune cell infiltration and immune response in breast cancer. Cancer Research. 2022;82(4_Supplement):P3-10-01-P3-10-01.\u003c/li\u003e\n\u003cli\u003eXiao C, Rajewsky K. MicroRNA control in the immune system: basic principles. Cell. 2009;136(1):26-36.\u003c/li\u003e\n\u003cli\u003eWang H, Li X, Li T, Wang L, Wu X, Liu J, et al. Multiple roles of microRNA-146a in immune responses and hepatocellular carcinoma. Oncol Lett. 2019;18(5):5033-42.\u003c/li\u003e\n\u003cli\u003eLi B, Xu WW, Han L, Chan KT, Tsao SW, Lee NPY, et al. MicroRNA-377 suppresses initiation and progression of esophageal cancer by inhibiting CD133 and VEGF. Oncogene. 2017;36(28):3986-4000.\u003c/li\u003e\n\u003cli\u003eYuan S, Wu Q, Wang Z, Che Y, Zheng S, Chen Y, et al. miR-223: An Immune Regulator in Infectious Disorders. Front Immunol. 2021;12:781815.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\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":"Mesenchymal stem cells derived extracellular vesicles, sepsis, meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-4328001/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4328001/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Multiple preclinical studies have reported a beneficial effect of extracellular vesicles (EVs), especially mesenchymal stem cell-derived EVs (MSC-EVs), in the treatment of sepsis. However, the therapeutic effect of MSC-EVs is still unclear. Therefore, we conducted this meta-analysis by summarizing data from all published studies that met the criteria for a systematic review on the association between EV treatment and mortality in animal models of sepsis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Systematic retrieval of all studies in PubMed, Scopus, and Web of Science that reported the effects of EVs on sepsis models up to December 2023 was performed. The targeted outcome was animal mortality. After screening the eligible articles according to inclusion and exclusion criteria, the inverse variance method of the fixed effect model was used to calculate the joint odds ratio (OR) and 95% confidence interval (CI).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 53 studies met the inclusion criteria, indicating that EVs treatment was associated with reduced mortality in animal models of sepsis, with a RR of 0.53 and a 95%CI of 0.46 to 0.60 (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) and RD of -0.35 and 95%CI of -0.41 to -0.30 (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Subsequent subgroup analysis revealed that several factors,such as sepsis models and EV administration (source, dose, time to injection, and route of administion), may significantly affect the therapeutic efficacy of EVs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e This meta-analysis showed that MSC-EVs treatment may be associated with lower mortality in animal models of sepsis. Subsequent preclinical studies will need to address the standardization of dose, source, and timing of EVs to provide comparable data. In addition, the effectiveness of EVs in treating sepsis must be studied in large animal studies to provide important clues for human clinical trials.\u003c/p\u003e","manuscriptTitle":"Adjunctive treatment of sepsis with mesenchymal stem cell-derived extracellular vesicles: a systemic review and meta-analysis of pre-clinical studies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-09 16:00:52","doi":"10.21203/rs.3.rs-4328001/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":"af269df2-142f-4c10-a2d1-4324fa4c114e","owner":[],"postedDate":"May 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-01T07:23:56+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-09 16:00:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4328001","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4328001","identity":"rs-4328001","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}