Clinical Significance of MDSCs in Patients with Sepsis

Clinical Significance of MDSCs in Patients with Sepsis | 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 Article Clinical Significance of MDSCs in Patients with Sepsis FAN JIANG, MIN TU, JINGQUAN ZHAO, YINGHUA WAN, ZHAO LIU, MINGQIANG ZHANG, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9051683/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted 17 You are reading this latest preprint version Abstract Background Accumulating evidence has established a correlation between Myeloid-derived suppressor cell (MDSC)-mediated immunosuppression and the prognosis of sepsis and septic shock. However, the relationship between MDSCs and specific infection sites or pathogens remains largely unexplored. Therefore, this study aimed to further elucidate the role of MDSCs in peripheral blood. Methods This single-center, prospective, cross-sectional study enrolled patients according to predefined inclusion and exclusion criteria. Demographic characteristics, clinical data, and blood samples were collected from all participants. Flow cytometry was performed to detect the expression levels of MDSCs in different groups, and the results were subsequently compared and analyzed.sepsis by investigating their association with different infectious origins. Results The expression levels of both PMN-MDSCs and M-MDSCs were significantly higher in the sepsis group than in the healthy control group (4.92 ± 0.31 vs. 2.20 ± 0.14, t = 6.87, P < 0.01; 19.40 ± 1.31 vs. 7.93 ± 0.45, t = 6.80, P < 0.01, respectively). However, no significant differences were observed in the levels of these subsets between the general sepsis and septic shock groups (t = 0.56, P = 0.58; t = -1.43, P = 0.16). Patient mortality was significantly correlated with both PMN-MDSCs (Wald = 5.56, P = 0.01, 95% CI: 0.43–0.92) and M-MDSCs (Wald = 5.25, P = 0.02, 95% CI: 0.98–1.26). Regarding infection sites, M-MDSC expression was significantly lower in pulmonary infections compared to urinary tract infections (t = 2.77, P = 0.01). In contrast, no significant differences were found in either PMN-MDSC or M-MDSC expression between Gram-positive and Gram-negative bacterial infections (t = 0.99, P = 0.32; t = 0.71, P = 0.48, respectively). Conclusion MDSC-mediated immunosuppression correlates with patient prognosis and mortality risk. While no early-stage difference in MDSC expression was found between sepsis and septic shock—underscoring the need for dynamic monitoring—expression levels did vary by infection site. Specifically, M-MDSCs were significantly elevated in urinary tract infections and were more pronounced in Gram-negative than in Gram-positive bacterial infections. Health sciences/Biomarkers Health sciences/Diseases Biological sciences/Immunology Health sciences/Medical research Biological sciences/Microbiology spesis sepsis shock MDSCs Gram-positive bacterial Gram-negative bacterial 1. Introduction Sepsis is a common critical illness. In 2017, the World Health Organization described sepsis as a global health priority due to the substantial burden of high morbidity and mortality. The annual incidence of sepsis is approximately 40 million cases, with a case fatality rate of about one-fifth, accounting for 19.7% of global deaths. Sepsis is defined as a "life-threatening organ dysfunction caused by a dysregulated host response to infection" . 1–5 Even though advances in medical technology and accumulated clinical experience have led to the recovery of many patients, its increasing incidence and mortality continue to impose a significant economic burden worldwide. In the early stage, patients with sepsis primarily exhibit a hyperinflammatory response, which can lead to organ damage and even organ failure. As the disease progresses, the later stage is characterized by an immunosuppressive state. The immunosuppressive state in septic patients is mediated, on one hand, by the release of anti-inflammatory factors such as interleukin-10 (IL-10), IL-1 receptor antagonists, or transforming growth factor. On the other hand, it is achieved through the upregulation of regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) during sepsis. 2 – 7 Tregs can suppress the functions of effector T cells, monocytes, and neutrophils. MDSCs are a heterogeneous population of immature myeloid cells with immunosuppressive properties. Studies have shown that the expansion of MDSCs is correlated with the length of ICU stay and patient prognosis in sepsis. The immunosuppressive role played by MDSCs during the course of sepsis in patients is closely related to their prognosis. 5 , 6 , 8 MDSCs were initially identified in studies of tumor patients and first described as 'natural suppressor cells' generated by soluble factors; based on their ability to suppress the immune response, they were subsequently defined as myeloid suppressive cells. MDSCs can be classified into two main categories according to their surface characteristics: one is granulocytic or polymorphonuclear MDSCs (PMN-MDSCs), which are phenotypically and morphologically similar to neutrophils; the other is monocytic MDSCs (M-MDSCs), which are phenotypically and morphologically similar to monocytes. 5 – 9 In mice, PMN-MDSCs can be defined as CD11b+Ly6G+Ly6Clow cells, while M-MDSCs are characterized by a CD11b+Ly6G−Ly6Chigh phenotype. In humans, PMN-MDSCs are defined as CD33 + CD11b+CD14− (CD15 + or CD66+), and M-MDSCs as CD11b+CD14 + HLA-DR−/lowCD15−. Although three MDSC subsets (granulocytic, monocytic, and early MDSCs) have been identified, studies have proven that sepsis is associated with a greater relative expansion of PMN-MDSCs compared to M-MDSCs. 5 , 7 – 9 Studies have shown that the expression level of MDSCs in the peripheral blood of patients with sepsis is elevated, peaking in the later stage of sepsis, and that higher expression levels are associated with poorer patient prognosis. 8 – 13 MDSCs contribute to sepsis-induced immunosuppression through several mechanisms, including inducing shortages of essential amino acids, eliciting oxidative damage, releasing anti-inflammatory cytokines such as IL-10 and TGF-β, and inducing Tregs. 2,3,13 This study will focus on exploring the correlation between MDSCs and the severity of sepsis, and further investigate the relationship between different infection sites and pathogens and the expression levels of MDSCs, aiming to provide new insights for the clinical diagnosis and treatment of sepsis. 2. Materials and methods 2.1 Definitions Sepsis is a clinical syndrome and can be difined as an increase in the Sequential [Sepsis-related] Organ Failure Assessment (SOFA) score of 2 points or more from the baseline.Septic shock was defined as a subset of sepsis in which circulatory, cellular, and metabolic abnormalities are associated with a greater risk of mortality than sepsis alone. The clinical criteria representing this definition were: 1)meets the criteria for sepsis (infection + organ dysfunction); 2)persisting hypotension requiring vasopressors to maintain mean arterial pressure (MAP) ≥ 65 mmHg; 3)having a serum lactate level > 2 mmol/L (> 18 mg/dL) despite adequate fluid resuscitation. 2–4 ,11 Mortality was assessed as death from any cause within 28 days following enrollment. 2.2 Study Design 2.2.1 Enrollment strategy Inclusion Criteria: Patients aged over 18 years with a confirmed diagnosis of sepsis. Patients must have complete general demographic data, clinical data, and laboratory/imaging results required for the study. Patients with a confirmed and single primary focus of infection. Patients agree to participate in the study after providing informed consent. Exclusion Criteria: Patients under 18 years of age; pregnant patients; patients with immunodeficiency diseases (Such as HIV et al) or those taking immunosuppressive drugs; patients who have received hormone therapy within the last 3 months; patients with severe comorbidities, including heart disease (NYHA class > 2), kidney disease (CKD stage > 2), or active malignant tumors; patients in whom the primary infection focus was unclear or who had multifocal infections; patients with incomplete required data; patients who refuse to participate in the study after providing informed consent. 2.2.2 Data collection This prospective, cross-sectional study was approved by the Ethics Committee of Beijing Tsinghua Changguang Hospital (BTCH) (Ethics number: 18190-0-02; Date: September 7, 2021) and was conducted collaboratively by the Department of Emergency and the Infectious Disease Center at BTCH. All participants provided written informed consent prior to enrollment, and blood samples were collected for analysis. From September 2021 to September 2022,We screened 40 normal patients as the control group and 121 patients with sepsis. Ultimately, 71 patients with sepsis met the inclusion criteria and agreed to participate in the study. During the study, 4 patients withdrew from treatment, and 3 patients were transferred to other hospitals. Finally, 64 patients completed the study. 2.2.3 Laboratory methods Human peripheral blood mononuclear cells (PBMCs), freshly isolated, were stained for 30 minutes at 4°C with a panel of monoclonal antibodies conjugated to FITC, PE, PerCP-Cyanine5.5, or APC. The antibodies used were specific for the following human antigens: CD3, CD4, CD8, CD15, CD33, CD11b, CD14, CD127, HLA-DR, PD-1, PD-L1, and CTLA-4. All antibodies were purchased from eBioscience (Invitrogen, USA), and corresponding isotype controls were used in all experiments. Following staining, cells were washed with phosphate-buffered saline (PBS). Data were acquired immediately using a FACSCalibur™ flow cytometer and analyzed with FlowJo software. All flow cytometry results are presented as the percentage of cells within the indicated gated population. The gating strategies employed were as follows:T Cell Subpopulations: T cell subsets, including regulatory T cells (Tregs), were identified. Tregs were defined as the CD3 + CD4+ CD25 + CD127-/low population.Myeloid-Derived Suppressor Cells (MDSCs): MDSC subsets were identified based on the expression of specific markers. Monocytic MDSCs (M-MDSCs) were defined as CD14 + CD15- CD11b+ CD33 + HLA-DR-/low. Granulocytic MDSCs (G-MDSCs) were defined as CD15 + CD33+ CD11b+ CD14- HLA-DR-/low. 2.4 Statistical analysis Statistical analyses were performed using SPSS software (version 30.0) and GraphPad Prism (version 10). Continuous variables were tested for normality using appropriate methods. Normally distributed data are presented as mean ± standard deviation (x̄± s), and comparisons between two groups were conducted using the independent samples t-test, comparisons between two groups were conducted using the ANOVA. Non-normally distributed data are expressed as median with interquartile range [M (P 25 , P 75 )], and group comparisons were performed using the Mann-Whitney U test (rank sum test). Categorical variables are presented as frequencies and percentages (n, %), and comparisons among groups were analyzed using the chi-square test. The correlation between MDSCs expression and clinical variables was assessed using Pearson correlation analysis for normally distributed data; a positive correlation coefficient indicated a positive association, while a negative coefficient indicated a negative association. Regarding the exploration of risk factors, Logistic regression was employed.All statistical tests were two-tailed, and a P-value < 0.05 was considered statistically significant. 3. Results 3.1 Comparison of PMN-MDSCs and M-MDSCs Between Different Groups 3.1.1 Differential Expression of PMN-MDSCs and M-MDSCs Between the Control Group and the Sepsis Group In this study, there were 40 cases in the control group and 62 cases in the sepsis group (including the general sepsis group and the septic shock group). There were no significant differences between the two groups in terms of age, gender, or past medical history (history of cardiovascular disease, kidney disease, central nervous system disease, or pulmonary disease). Differences were observed in the levels of PMN-MDSCs and M-MDSCs between the two groups. Specifically, the expression level of PMN-MDSCs was significantly higher in the sepsis group than in the control group (4.92 ± 0.31 vs. 2.20 ± 0.14, t = 6.87, P < 0.01). Similarly, the expression level of M-MDSCs was significantly higher in the sepsis group than in the control group (19.40 ± 1.31 vs. 7.93 ± 0.45, t = 6.80, P < 0.01). The expression levels of both PMN-MDSCs and M-MDSCs were significantly higher in the sepsis group compared to the normal control group.（Table 1） 3.1.2 Differential Expression of PMN-MDSCs and M-MDSCs Between the Genaral Sepsis Group and the Septic Shock Group The sepsis group was further divided into the general sepsis group (35 cases) and the septic shock group (27 cases). There were no significant differences between the two groups in terms of age, gender, or past medical history (history of cardiovascular disease, kidney disease, central nervous system disease, or pulmonary disease). No significant differences were observed between the two groups in white blood cell (WBC) count, red blood cell (RBC) count, platelet (PLT) count, C-reactive protein (CRP) levels, procalcitonin (PCT) or SOFA scores. There were no significant differences in the expression levels of PMN-MDSCs and M-MDSCs between the two groups (t = 0.56, P = 0.58; t = -1.43, P =0.16). Additionally, no significant difference was observed in days of hospitalization and mortality between the two groups.（Table 2） 3.2 Correlation Between the Expression of PMN-MDSCs and M-MDSCs and PCT, SOFA Scores, and Prognosis Correlation analysis revealed no significant correlation between PCT levels and the expression levels of PMN-MDSCs (correlation coefficient = 0.22, P = 0.09). Similarly, no significant correlation was found between PCT levels and the expression levels of M-MDSCs (correlation coefficient = 0.09, P = 0.49). Correlation analysis between SOFA scores and the two cell subsets showed that SOFA scores were not significantly correlated with PMN-MDSC expression levels (correlation coefficient = 0.66, P = 0.61) but were significantly correlated with M-MDSC expression levels (correlation coefficient = 0.28, P = 0.04). To evaluate patient prognosis, we assessed three indicators: length of hospital stay, incidence of shock, and mortality. There was no significant correlation between length of hospital stay and the expression levels of either PMN-MDSCs (t = -1.15, P = 0.26, 95% CI: -6.18 to 1.67) or M-MDSCs (t = -0.48, P = 0.65, 95% CI: -1.12 to 0.69). The incidence of shock was not significantly correlated with PMN-MDSCs (Wald = 1.31, P = 0.25, 95% CI: 0.91 to 1.46) or with M-MDSCs (Wald = 2.80, P = 0.09, 95% CI: 0.89 to 1.00). However, patient mortality was significantly correlated with both PMN-MDSCs (Wald = 5.56, P = 0.01, 95% CI: 0.43 to 0.92) and M-MDSCs (Wald = 5.25, P = 0.02, 95% CI: 0.98 to 1.26). 3.3 Differential Expression of PMN-MDSCs and M-MDSCs at Different Infection Sites In this study, the infection sites were classified as pulmonary infection(Group A) , abdominal infection (Group B) , and urinary tract infection (Group C) (30 vs. 16 vs. 16 cases, respectively). No significant differences were observed in PMN-MDSC expression across different infection sites (F = 0.342, P = 0.71). However, M-MDSC expression differed significantly among infection sites (F = 3.72, P = 0.03). Specifically, the expression level of M-MDSCs was significantly lower in pulmonary infections than in urinary tract infections (t = 2.77, P = 0.01).In pulmonary infections, the mean SOFA score was 4.63±0.52, while in urinary tract infections, the mean SOFA score was 8.88±0.98, showing a statistically significant difference between the two groups (t = -4.20, P < 0.01) 3. 4 Differential Expression of PMN-MDSCs and M-MDSCs in Infections Caused by Different Pathogens In this study, a definitive pathogen diagnosis was established in 38 cases. Among these, 24 cases were infected with Gram-negative bacteria (G- bacteria), including 6 cases of pulmonary infection, 7 cases of abdominal infection, and 11 cases of urinary tract infection. Ten cases were infected with Gram-positive bacteria (G+ bacteria), comprising 7 cases of pulmonary infection, 2 cases of abdominal infection, and 1 case of urinary tract infection. Four cases were fungal infections, including 3 cases of pulmonary infection and 1 case of abdominal infection. The incidence of G- bacilli was significantly higher in urinary tract infections than in pulmonary infections (χ² = 10.46, P = 0.03).(Table 3) No significant differences were observed in the expression levels of PMN-MDSCs between G+ and G- bacterial infections (t = 0.99, P = 0.32). Similarly, there were no significant differences in M-MDSC expression levels between G+ and G- bacterial infections (t = 0.71, P = 0.48). 4. Discussion Sepsis is a common critical illness. In previous studies, most research has indicated that immune activation plays a significant role in the pathogenesis of sepsis. With the continuous progression of research, recent studies have pointed out that an immunosuppressive state also plays an indispensable role in the onset and progression of sepsis. 2-6,11 In the early stages of sepsis, an excessive immune response is primarily involved, while the later stages are mainly characterized by an immunosuppressive state. MDSCs are a group of cells with potent immunosuppressive functions and can exert immunosuppressive effects in various diseases. Genes associated with MDSC recruitment, phenotype, and suppressive functions, including MMP8,MMP9, ARG1, S100A8, S100A9, S100A12,CD274 (programmed death-ligand 1[PD-L1]), IL4R, and IL10 were upregulated, whereas genes associated with adaptive immunity and inflammation, including CD4, MS4A1 (CD20), CD8B,CD3G, IL8, and IL6 were down-regulated in patients with sepsis . 5-10 At present, numerous animal models have shown that the expression level of MDSCs is upregulated in sepsis, further validating the role of immunosuppression in the process of sepsis. 2,11-15 In our study, the level of MDSCs in the sepsis group was significantly increased compared with that in the normal group, thus also confirming that in the human model, MDSCs can still exhibit an upregulation pattern in sepsis patients. Therefore, we can infer that the immunosuppressive state mediated by MDSCs is correlated with the occurrence and development of sepsis. In our study, a further comparison between general sepsis and septic shock revealed no significant difference in MDSCs levels between the two groups. Existing research has indicated that the level of MDSCs is correlated with the length of ICU stay and survival period, which is consistent with our findings. 5,7-9 In our study, logistic regression analysis concluded that MDSCs levels are correlated with patient mortality and serve as a risk factor for patient death. Although our study suggested a positive correlation between SOFA scores and MDSCs levels, when sepsis was divided into the general sepsis group and the septic shock group, no significant difference was found between them in the early stage of onset. In Brittany's study, 8 an analysis of changes in MDSCs levels at different time points and patients' ICU stay and survival period revealed that patients with longer ICU stays or shorter survival times exhibited an upward trend in MDSCs levels, while patients with shorter ICU stays or longer survival times showed a downward trend in MDSCs levels. Therefore, we can also infer that it is not rigorous to judge the severity of sepsis based on MDSCs levels in the early stage of the disease, and dynamic monitoring of changes in their levels may be more useful for assessing disease prognosis. Currently, most studies are dedicated to exploring the correlation between MDSCs and prognosis, with very few studies focusing on the relationship between different infection sites or pathogens and MDSCs. At present, most animal models of sepsis are induced by Gram-negative bacteria, making it difficult to provide a detailed explanation of the immunosuppressive effects of different bacterial flora. In this study, a comparison between Gram-negative bacteria (G⁻ bacteria) and Gram-positive bacteria (G⁺ bacteria) revealed a certain difference in MDSCs levels between the two groups. The level of M-MDSCs in the G⁻ bacteria group was significantly higher than that in the G⁺ cocci group, and concurrently, the SOFA score in the G⁻ bacteria group was also higher than that in the G⁺ bacteria group. We previously believed that G⁻ bacteria are generally more invasive than G⁺ bacteria, leading to more severe infections. In this study, the SOFA score of the G⁻ bacteria group was higher than that of the G⁺ bacteria group, which is consistent with the findings of most studies. Furthermore, the M-MDSC level in the G⁻ bacteria group was also higher than that in the G⁺ bacteria group. From this, we can infer that G⁻ bacteria may induce a stronger immunosuppressive effect compared to G⁺ bacteria, which could be one of the reasons for the greater severity of G⁻ bacterial infections. However, limited by the small sample size and sampling bias of this study, this argument still needs to be validated by more clinical trials. Literature reports indicate that M-MDSCs possess stronger immunosuppressive capacity than PMN-MDSCs, and this difference may be attributed to differences in gene expression. The high expression of Arg1 in M-MDSCs is an important factor contributing to their stronger immunosuppressive function, whereas PMN-MDSCs do not express this gene. 2,6-9 This finding may help explain why, in our study, the upregulation of M-MDSCs was more significant in infections caused by Gram-negative bacteria compared to Gram-positive bacteria, while the upregulation of PMN-MDSCs was not as pronounced.Furthermore, our investigation into the relationship between different infection sites and MDSCs levels revealed that M-MDSC expression levels vary depending on the infection site. A more significant increase in M-MDSCs was observed in urinary tract infections, whereas PMN-MDSC levels showed no significant difference across different infection sites. Consistently, SOFA scores were also higher in the urinary tract infection group compared to other groups. The reasons for this difference may be, on one hand, the predominance of Gram-negative bacteria in urinary tract infections, and on the other hand, it may be related to the stronger immunosuppressive capacity inherently associated with M-MDSCs. 5. Conclusion The expression level of MDSCs is significantly increased in patients with sepsis. The immunosuppressive state mediated by MDSCs is correlated with patient prognosis and serves as a risk factor for patient mortality. There is no significant difference in the expression levels of MDSCs between sepsis and septic shock in the early stage, suggesting that dynamic monitoring of their levels is necessary. MDSC expression varies across different infection sites, with M-MDSC levels being notably elevated in urinary tract infections. Furthermore, M-MDSC upregulation is more pronounced in Gram-negative bacterial infections compared to Gram-positive bacterial infections. Declarations Authors’ contributions Fan Jiang: Research conceptualization, data synthesis, manuscript writing. Min Tu& Zhao Liu: Statistical analysis. Jingquan Zhao & Yinghua Wan: Data collection and cytological monitoring. Mingqiang Zhang : Flow cytometry monitoring and data interpretation. Chenguang Zhang : Study design, manuscript writing, and proofreading. Funding Not applicable. Ethics approval and consent to participate This study was conducted in accordance with the International Ethical Guidelines for Biomedical Research Involving Human Subjects (2002) and the Declaration of Helsinki (2013). The research protocol was approved by the Ethics Committee of Beijing Tsinghua Changgung Hospital (Approval No. 18190-0-02; Date: September 7, 2021). All patients provided written informed consent prior to participation and agreed to the use of their samples and data for research purposes. Competing interests The authors declare that they have no competing interests. Data availability statement The datasets generated and/or analyzed during the current study are not publicly available due to their intended use in ongoing and future research. However, they may be made available by the corresponding author upon reasonable request. References Chiu C, Legrand M. Epidemiology of sepsis and septic shock. Curr Opin Anaesthesiol. 2021 Apr 1;34(2):71-76. doi: 10.1097/ACO.0000000000000958. PMID: 33492864. Esposito S, De Simone G, Boccia G, De Caro F, Pagliano P. Sepsis and septic shock: New definitions, new diagnostic and therapeutic approaches. 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Differences in MDSCs Between the Sepsis Group and the Control Group Control Group Sepsis Group Value P Number 40 62 - - Age（years old） 63.50+2.57 67.58+2.33 1.15 0.34 Male 17（42.5） 30（48.4） 0.34 0.56 Cardiovascular disease 1 13（12.7） 16（15.7） 0.54 0.46 Kidney disease 1 7（17.5） 9（14.5） 0.16 0.69 Central nervous system disease 1 6（15.0） 9（14.5） 0.01 0.95 Pulmonary disease 1 6（15.0） 9（14.5） 0.01 0.95 PMN-MDSCs 2.20+0.14 4.92+0.31 6.87 <0.01 M-MDSCs 7.93+0.45 19.40+1.31 6.80 <0.01 Patients with a positive history of the disease Table 2. The levels of MDSCs were compared between the general sepsis group and the septic shock group Genaral Sepsis Group Septic Shock Group Value P Number 35 27 - - Male 16（45.7） 14（51.9） 0.23 0.63 Age（years old） 67.20+2.68 67.23+4.20 0.18 0.85 Cardiovascular disease 1 8（22.9） 8（29.6） 0.36 0.54 Kidney disease 1 5（14.3） 4（14.8） 0.36 0.54 Central nervous system disease 1 3（8.6） 6（22.2） 0.01 0.95 Pulmonary disease 1 5（14.3） 4（14.8） 2.29 0.13 WBC(×10 9 /L) 9.97+0.97 9.64+0.88 -0.25 0.80 RBC(×10 12 /L) 4.14+0.13 4.20+0.13 0.49 0.63 PLT(×10 9 /L) 218.39+17.64 244.65+18.57 0.55 1.03 CRP(mg/L) （10.44,116.30） （9.50,75.12） 1.06 0.31 PCT(ng/mL) 5.52+0.99 13.97+2.47 -0.42 0.16 SOFA scores 4.71+0.43 7.46+0.84 3.21 0.01 PMN-MDSCs 4.77+0.41 5.20+0.48 0.56 0.58 M-MDSCs 17.59+1.48 21.02+1.99 -1.43 0.16 Length of hospotal-stay (day) (11.00,24.00) (9.00,29.25) 1.58 0.21 Death 2（5.7） 5（18.50） 2.49 0.11 1. Patients with a positive history of the disease Table 3. Expression levels of MDSCs in response to G - and G + bacteria G- bacteria G+ bacteria t P Number 24 10 - - PMN-MDSCs 5.36+0.51 4.39+0.87 0.99 0.32 M-MDSCs 18.74+8.42 10.32+3.34 2.97 0.02 SOFA 8.00+0.80 4.90+0.92 2.23 0.03 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 21 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 02 Apr, 2026 Reviews received at journal 30 Mar, 2026 Reviewers agreed at journal 29 Mar, 2026 Reviews received at journal 29 Mar, 2026 Reviewers agreed at journal 29 Mar, 2026 Reviewers agreed at journal 28 Mar, 2026 Reviews received at journal 28 Mar, 2026 Reviews received at journal 27 Mar, 2026 Reviewers agreed at journal 27 Mar, 2026 Reviewers agreed at journal 27 Mar, 2026 Reviewers agreed at journal 27 Mar, 2026 Reviewers agreed at journal 27 Mar, 2026 Reviewers invited by journal 26 Mar, 2026 Editor invited by journal 17 Mar, 2026 Editor assigned by journal 17 Mar, 2026 Submission checks completed at journal 12 Mar, 2026 First submitted to journal 12 Mar, 2026 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. 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Introduction","content":"\u003cp\u003eSepsis is a common critical illness. In 2017, the World Health Organization described sepsis as a global health priority due to the substantial burden of high morbidity and mortality. The annual incidence of sepsis is approximately 40\u0026nbsp;million cases, with a case fatality rate of about one-fifth, accounting for 19.7% of global deaths. Sepsis is defined as a \"life-threatening organ dysfunction caused by a dysregulated host response to infection\" .\u003csup\u003e1\u0026ndash;5\u003c/sup\u003e Even though advances in medical technology and accumulated clinical experience have led to the recovery of many patients, its increasing incidence and mortality continue to impose a significant economic burden worldwide.\u003c/p\u003e \u003cp\u003eIn the early stage, patients with sepsis primarily exhibit a hyperinflammatory response, which can lead to organ damage and even organ failure. As the disease progresses, the later stage is characterized by an immunosuppressive state. The immunosuppressive state in septic patients is mediated, on one hand, by the release of anti-inflammatory factors such as interleukin-10 (IL-10), IL-1 receptor antagonists, or transforming growth factor. On the other hand, it is achieved through the upregulation of regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) during sepsis.\u003csup\u003e\u003cspan additionalcitationids=\"CR3 CR4 CR5 CR6\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Tregs can suppress the functions of effector T cells, monocytes, and neutrophils. MDSCs are a heterogeneous population of immature myeloid cells with immunosuppressive properties. Studies have shown that the expansion of MDSCs is correlated with the length of ICU stay and patient prognosis in sepsis. The immunosuppressive role played by MDSCs during the course of sepsis in patients is closely related to their prognosis.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMDSCs were initially identified in studies of tumor patients and first described as 'natural suppressor cells' generated by soluble factors; based on their ability to suppress the immune response, they were subsequently defined as myeloid suppressive cells. MDSCs can be classified into two main categories according to their surface characteristics: one is granulocytic or polymorphonuclear MDSCs (PMN-MDSCs), which are phenotypically and morphologically similar to neutrophils; the other is monocytic MDSCs (M-MDSCs), which are phenotypically and morphologically similar to monocytes.\u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e In mice, PMN-MDSCs can be defined as CD11b+Ly6G+Ly6Clow cells, while M-MDSCs are characterized by a CD11b+Ly6G\u0026minus;Ly6Chigh phenotype. In humans, PMN-MDSCs are defined as CD33\u0026thinsp;+\u0026thinsp;CD11b+CD14\u0026minus; (CD15\u0026thinsp;+\u0026thinsp;or CD66+), and M-MDSCs as CD11b+CD14\u0026thinsp;+\u0026thinsp;HLA-DR\u0026minus;/lowCD15\u0026minus;. Although three MDSC subsets (granulocytic, monocytic, and early MDSCs) have been identified, studies have proven that sepsis is associated with a greater relative expansion of PMN-MDSCs compared to M-MDSCs.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eStudies have shown that the expression level of MDSCs in the peripheral blood of patients with sepsis is elevated, peaking in the later stage of sepsis, and that higher expression levels are associated with poorer patient prognosis.\u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e MDSCs contribute to sepsis-induced immunosuppression through several mechanisms, including inducing shortages of essential amino acids, eliciting oxidative damage, releasing anti-inflammatory cytokines such as IL-10 and TGF-β, and inducing Tregs. \u003csup\u003e2,3,13\u003c/sup\u003e This study will focus on exploring the correlation between MDSCs and the severity of sepsis, and further investigate the relationship between different infection sites and pathogens and the expression levels of MDSCs, aiming to provide new insights for the clinical diagnosis and treatment of sepsis.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Definitions\u003c/h2\u003e \u003cp\u003eSepsis is a clinical syndrome and can be difined as an increase in the Sequential [Sepsis-related] Organ Failure Assessment (SOFA) score of 2 points or more from the baseline.Septic shock was defined as a subset of sepsis in which circulatory, cellular, and metabolic abnormalities are associated with a greater risk of mortality than sepsis alone. The clinical criteria representing this definition were: 1)meets the criteria for sepsis (infection\u0026thinsp;+\u0026thinsp;organ dysfunction); 2)persisting hypotension requiring vasopressors to maintain mean arterial pressure (MAP)\u0026thinsp;\u0026ge;\u0026thinsp;65 mmHg; 3)having a serum lactate level\u0026thinsp;\u0026gt;\u0026thinsp;2 mmol/L (\u0026gt;\u0026thinsp;18 mg/dL) despite adequate fluid resuscitation. \u003csup\u003e2\u0026ndash;4 ,11\u003c/sup\u003e Mortality was assessed as death from any cause within 28 days following enrollment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Design\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Enrollment strategy\u003c/h2\u003e \u003cp\u003eInclusion Criteria: Patients aged over 18 years with a confirmed diagnosis of sepsis. Patients must have complete general demographic data, clinical data, and laboratory/imaging results required for the study. Patients with a confirmed and single primary focus of infection. Patients agree to participate in the study after providing informed consent.\u003c/p\u003e \u003cp\u003eExclusion Criteria: Patients under 18 years of age; pregnant patients; patients with immunodeficiency diseases (Such as HIV et al) or those taking immunosuppressive drugs; patients who have received hormone therapy within the last 3 months; patients with severe comorbidities, including heart disease (NYHA class\u0026thinsp;\u0026gt;\u0026thinsp;2), kidney disease (CKD stage\u0026thinsp;\u0026gt;\u0026thinsp;2), or active malignant tumors; patients in whom the primary infection focus was unclear or who had multifocal infections; patients with incomplete required data; patients who refuse to participate in the study after providing informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Data collection\u003c/h2\u003e \u003cp\u003e This prospective, cross-sectional study was approved by the Ethics Committee of Beijing Tsinghua Changguang Hospital (BTCH) (Ethics number: 18190-0-02; Date: September 7, 2021) and was conducted collaboratively by the Department of Emergency and the Infectious Disease Center at BTCH. All participants provided written informed consent prior to enrollment, and blood samples were collected for analysis.\u003c/p\u003e \u003cp\u003eFrom September 2021 to September 2022,We screened 40 normal patients as the control group and 121 patients with sepsis. Ultimately, 71 patients with sepsis met the inclusion criteria and agreed to participate in the study. During the study, 4 patients withdrew from treatment, and 3 patients were transferred to other hospitals. Finally, 64 patients completed the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Laboratory methods\u003c/h2\u003e \u003cp\u003eHuman peripheral blood mononuclear cells (PBMCs), freshly isolated, were stained for 30 minutes at 4\u0026deg;C with a panel of monoclonal antibodies conjugated to FITC, PE, PerCP-Cyanine5.5, or APC. The antibodies used were specific for the following human antigens: CD3, CD4, CD8, CD15, CD33, CD11b, CD14, CD127, HLA-DR, PD-1, PD-L1, and CTLA-4. All antibodies were purchased from eBioscience (Invitrogen, USA), and corresponding isotype controls were used in all experiments.\u003c/p\u003e \u003cp\u003eFollowing staining, cells were washed with phosphate-buffered saline (PBS). Data were acquired immediately using a FACSCalibur\u0026trade; flow cytometer and analyzed with FlowJo software. All flow cytometry results are presented as the percentage of cells within the indicated gated population.\u003c/p\u003e \u003cp\u003eThe gating strategies employed were as follows:T Cell Subpopulations: T cell subsets, including regulatory T cells (Tregs), were identified. Tregs were defined as the CD3\u0026thinsp;+\u0026thinsp;CD4+ CD25\u0026thinsp;+\u0026thinsp;CD127-/low population.Myeloid-Derived Suppressor Cells (MDSCs): MDSC subsets were identified based on the expression of specific markers. Monocytic MDSCs (M-MDSCs) were defined as CD14\u0026thinsp;+\u0026thinsp;CD15- CD11b+ CD33\u0026thinsp;+\u0026thinsp;HLA-DR-/low. Granulocytic MDSCs (G-MDSCs) were defined as CD15\u0026thinsp;+\u0026thinsp;CD33+ CD11b+ CD14- HLA-DR-/low.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS software (version 30.0) and GraphPad Prism (version 10). Continuous variables were tested for normality using appropriate methods. Normally distributed data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (x̄\u0026plusmn; s), and comparisons between two groups were conducted using the independent samples t-test, comparisons between two groups were conducted using the ANOVA. Non-normally distributed data are expressed as median with interquartile range [M (P\u003csub\u003e25\u003c/sub\u003e, P\u003csub\u003e75\u003c/sub\u003e)], and group comparisons were performed using the Mann-Whitney U test (rank sum test). Categorical variables are presented as frequencies and percentages (n, %), and comparisons among groups were analyzed using the chi-square test.\u003c/p\u003e \u003cp\u003eThe correlation between MDSCs expression and clinical variables was assessed using Pearson correlation analysis for normally distributed data; a positive correlation coefficient indicated a positive association, while a negative coefficient indicated a negative association. Regarding the exploration of risk factors, Logistic regression was employed.All statistical tests were two-tailed, and a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Comparison of PMN-MDSCs and M-MDSCs Between Different Groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.1 Differential Expression of PMN-MDSCs and M-MDSCs Between the Control Group and the Sepsis Group\u003cbr\u003e\u003c/strong\u003e\u0026nbsp; In this study, there were 40 cases in the control group and 62 cases in the sepsis group (including the general sepsis group and the septic shock group). There were no significant differences between the two groups in terms of age, gender, or past medical history (history of cardiovascular disease, kidney disease, central nervous system disease, or pulmonary disease). Differences were observed in the levels of PMN-MDSCs and M-MDSCs between the two groups. Specifically, the expression level of PMN-MDSCs was significantly higher in the sepsis group than in the control group (4.92 \u0026plusmn; 0.31 vs. 2.20 \u0026plusmn; 0.14, t = 6.87, P \u0026lt; 0.01). Similarly, the expression level of M-MDSCs was significantly higher in the sepsis group than in the control group (19.40 \u0026plusmn; 1.31 vs. 7.93 \u0026plusmn; 0.45, t = 6.80, P \u0026lt; 0.01). The expression levels of both PMN-MDSCs and M-MDSCs were significantly higher in the sepsis group compared to the normal control group.（Table 1）\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.2 Differential Expression of PMN-MDSCs and M-MDSCs Between the\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eGenaral\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSepsis Group and the Septic Shock Group\u003c/strong\u003e\u003cbr\u003e\u0026nbsp; \u0026nbsp;The sepsis group was further divided into the general sepsis group (35 cases) and the septic shock group (27 cases). There were no significant differences between the two groups in terms of age, gender, or past medical history (history of cardiovascular disease, kidney disease, central nervous system disease, or pulmonary disease). No significant differences were observed between the two groups in white blood cell (WBC) count, red blood cell (RBC) count, platelet (PLT) count, C-reactive protein (CRP) levels, procalcitonin (PCT) or SOFA scores. There were no significant differences in the expression levels of PMN-MDSCs and M-MDSCs between the two groups (t = 0.56, P = 0.58; t = -1.43, P =0.16). Additionally, no significant difference was observed in days of hospitalization and mortality between the two groups.（Table 2）\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCorrelation Between the Expression of PMN-MDSCs and M-MDSCs and PCT, SOFA Scores, and Prognosis\u003c/strong\u003e\u003cbr\u003e\u0026nbsp; \u0026nbsp;Correlation analysis revealed no significant correlation between PCT levels and the expression levels of PMN-MDSCs (correlation coefficient = 0.22, P = 0.09). Similarly, no significant correlation was found between PCT levels and the expression levels of M-MDSCs (correlation coefficient = 0.09, P = 0.49). Correlation analysis between SOFA scores and the two cell subsets showed that SOFA scores were not significantly correlated with PMN-MDSC expression levels (correlation coefficient = 0.66, P = 0.61) but were significantly correlated with M-MDSC expression levels (correlation coefficient = 0.28, P = 0.04).\u003c/p\u003e\n\u003cp\u003eTo evaluate patient prognosis, we assessed three indicators: length of hospital stay, incidence of shock, and mortality. There was no significant correlation between length of hospital stay and the expression levels of either PMN-MDSCs (t = -1.15, P = 0.26, 95% CI: -6.18 to 1.67) or M-MDSCs (t = -0.48, P = 0.65, 95% CI: -1.12 to 0.69). The incidence of shock was not significantly correlated with PMN-MDSCs (Wald = 1.31, P = 0.25, 95% CI: 0.91 to 1.46) or with M-MDSCs (Wald = 2.80, P = 0.09, 95% CI: 0.89 to 1.00). However, patient mortality was significantly correlated with both PMN-MDSCs (Wald = 5.56, P = 0.01, 95% CI: 0.43 to 0.92) and M-MDSCs (Wald = 5.25, P = 0.02, 95% CI: 0.98 to 1.26).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDifferential Expression of PMN-MDSCs and M-MDSCs at Different Infection Sites\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the infection sites were classified as pulmonary infection(Group A) , abdominal infection (Group B) , and urinary tract infection (Group C) (30 vs. 16 vs. 16 cases, respectively). No significant differences were observed in PMN-MDSC expression across different infection sites (F = 0.342, P = 0.71). However, M-MDSC expression differed significantly among infection sites (F = 3.72, P = 0.03). Specifically, the expression level of M-MDSCs was significantly lower in pulmonary infections than in urinary tract infections (t = 2.77, P = 0.01).In pulmonary infections, the mean SOFA score was 4.63\u0026plusmn;0.52, while in urinary tract infections, the mean SOFA score was 8.88\u0026plusmn;0.98, showing a statistically significant difference between the two groups (t = -4.20, P \u0026lt; 0.01)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.\u003c/strong\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Differential Expression of PMN-MDSCs and M-MDSCs in Infections Caused by Different Pathogens\u003c/strong\u003e\u003cbr\u003e\u0026nbsp; In this study, a definitive pathogen diagnosis was established in 38 cases. Among these, 24 cases were infected with Gram-negative bacteria (G- bacteria), including 6 cases of pulmonary infection, 7 cases of abdominal infection, and 11 cases of urinary tract infection. Ten cases were infected with Gram-positive bacteria (G+ bacteria), comprising 7 cases of pulmonary infection, 2 cases of abdominal infection, and 1 case of urinary tract infection. Four cases were fungal infections, including 3 cases of pulmonary infection and 1 case of abdominal infection. The incidence of G- bacilli was significantly higher in urinary tract infections than in pulmonary infections (\u0026chi;\u0026sup2; = 10.46, P = 0.03).(Table 3)\u003c/p\u003e\n\u003cp\u003eNo significant differences were observed in the expression levels of PMN-MDSCs between G+ and G- bacterial infections (t = 0.99, P = 0.32). Similarly, there were no significant differences in M-MDSC expression levels between G+ and G- bacterial infections (t = 0.71, P = 0.48).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eSepsis is a common critical illness. In previous studies, most research has indicated that immune activation plays a significant role in the pathogenesis of sepsis. With the continuous progression of research, recent studies have pointed out that an immunosuppressive state also plays an indispensable role in the onset and progression of sepsis. \u003csup\u003e2-6,11\u0026nbsp;\u003c/sup\u003eIn the early stages of sepsis, an excessive immune response is primarily involved, while the later stages are mainly characterized by an immunosuppressive state. MDSCs are a group of cells with potent immunosuppressive functions and can exert immunosuppressive effects in various diseases. Genes associated with MDSC recruitment, phenotype, and suppressive functions, including MMP8,MMP9, ARG1, S100A8, S100A9, S100A12,CD274 (programmed death-ligand 1[PD-L1]), IL4R, and IL10 were upregulated, whereas genes associated with adaptive immunity and inflammation, including CD4, MS4A1 (CD20), CD8B,CD3G, IL8, and IL6 were down-regulated in patients with sepsis .\u003csup\u003e5-10\u003c/sup\u003e At present, numerous animal models have shown that the expression level of MDSCs is upregulated in sepsis, further validating the role of immunosuppression in the process of sepsis.\u003csup\u003e2,11-15\u003c/sup\u003e In our study, the level of MDSCs in the sepsis group was significantly increased compared with that in the normal group, thus also confirming that in the human model, MDSCs can still exhibit an upregulation pattern in sepsis patients. Therefore, we can infer that the immunosuppressive state mediated by MDSCs is correlated with the occurrence and development of sepsis.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In our study, a further comparison between general sepsis and septic shock revealed no significant difference in MDSCs levels between the two groups. Existing research has indicated that the level of MDSCs is correlated with the length of ICU stay and survival period, which is consistent with our findings.\u003csup\u003e5,7-9\u003c/sup\u003e In our study, logistic regression analysis concluded that MDSCs levels are correlated with patient mortality and serve as a risk factor for patient death. Although our study suggested a positive correlation between SOFA scores and MDSCs levels, when sepsis was divided into the general sepsis group and the septic shock group, no significant difference was found between them in the early stage of onset. In Brittany's study,\u003csup\u003e8\u003c/sup\u003e an analysis of changes in MDSCs levels at different time points and patients' ICU stay and survival period revealed that patients with longer ICU stays or shorter survival times exhibited an upward trend in MDSCs levels, while patients with shorter ICU stays or longer survival times showed a downward trend in MDSCs levels. Therefore, we can also infer that it is not rigorous to judge the severity of sepsis based on MDSCs levels in the early stage of the disease, and dynamic monitoring of changes in their levels may be more useful for assessing disease prognosis.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Currently, most studies are dedicated to exploring the correlation between MDSCs and prognosis, with very few studies focusing on the relationship between different infection sites or pathogens and MDSCs. At present, most animal models of sepsis are induced by Gram-negative bacteria, making it difficult to provide a detailed explanation of the immunosuppressive effects of different bacterial flora. In this study, a comparison between Gram-negative bacteria (G⁻ bacteria) and Gram-positive bacteria (G⁺ bacteria) revealed a certain difference in MDSCs levels between the two groups. The level of M-MDSCs in the G⁻ bacteria group was significantly higher than that in the G⁺ cocci group, and concurrently, the SOFA score in the G⁻ bacteria group was also higher than that in the G⁺ bacteria group. We previously believed that G⁻ bacteria are generally more invasive than G⁺ bacteria, leading to more severe infections. In this study, the SOFA score of the G⁻ bacteria group was higher than that of the G⁺ bacteria group, which is consistent with the findings of most studies. Furthermore, the M-MDSC level in the G⁻ bacteria group was also higher than that in the G⁺ bacteria group. From this, we can infer that G⁻ bacteria may induce a stronger immunosuppressive effect compared to G⁺ bacteria, which could be one of the reasons for the greater severity of G⁻ bacterial infections. However, limited by the small sample size and sampling bias of this study, this argument still needs to be validated by more clinical trials.\u003c/p\u003e\n\u003cp\u003eLiterature reports indicate that M-MDSCs possess stronger immunosuppressive capacity than PMN-MDSCs, and this difference may be attributed to differences in gene expression. The high expression of Arg1 in M-MDSCs is an important factor contributing to their stronger immunosuppressive function, whereas PMN-MDSCs do not express this gene.\u003csup\u003e2,6-9\u003c/sup\u003e This finding may help explain why, in our study, the upregulation of M-MDSCs was more significant in infections caused by Gram-negative bacteria compared to Gram-positive bacteria, while the upregulation of PMN-MDSCs was not as pronounced.Furthermore, our investigation into the relationship between different infection sites and MDSCs levels revealed that M-MDSC expression levels vary depending on the infection site. A more significant increase in M-MDSCs was observed in urinary tract infections, whereas PMN-MDSC levels showed no significant difference across different infection sites. Consistently, SOFA scores were also higher in the urinary tract infection group compared to other groups. The reasons for this difference may be, on one hand, the predominance of Gram-negative bacteria in urinary tract infections, and on the other hand, it may be related to the stronger immunosuppressive capacity inherently associated with M-MDSCs.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe expression level of MDSCs is significantly increased in patients with sepsis. The immunosuppressive state mediated by MDSCs is correlated with patient prognosis and serves as a risk factor for patient mortality. There is no significant difference in the expression levels of MDSCs between sepsis and septic shock in the early stage, suggesting that dynamic monitoring of their levels is necessary. MDSC expression varies across different infection sites, with M-MDSC levels being notably elevated in urinary tract infections. Furthermore, M-MDSC upregulation is more pronounced in Gram-negative bacterial infections compared to Gram-positive bacterial infections.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFan Jiang: Research conceptualization, data synthesis, manuscript writing.\u003c/p\u003e\n\u003cp\u003eMin Tu\u0026amp; Zhao Liu: Statistical analysis.\u003c/p\u003e\n\u003cp\u003eJingquan Zhao \u0026amp; Yinghua Wan: Data collection and cytological monitoring.\u003c/p\u003e\n\u003cp\u003eMingqiang Zhang : Flow cytometry monitoring and data interpretation.\u003c/p\u003e\n\u003cp\u003eChenguang Zhang : Study design, manuscript writing, and proofreading.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the International Ethical Guidelines for Biomedical Research Involving Human Subjects (2002) and the Declaration of Helsinki (2013). The research protocol was approved by the Ethics Committee of Beijing Tsinghua Changgung Hospital (Approval No. 18190-0-02; Date: September 7, 2021). All patients provided written informed consent prior to participation and agreed to the use of their samples and data for research purposes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to their intended use in ongoing and future research. However, they may be made available by the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eChiu C, Legrand M. Epidemiology of sepsis and septic shock. Curr Opin Anaesthesiol. 2021 Apr 1;34(2):71-76. doi: 10.1097/ACO.0000000000000958. PMID: 33492864.\u003c/li\u003e\n \u003cli\u003eEsposito S, De Simone G, Boccia G, De Caro F, Pagliano P. Sepsis and septic shock: New definitions, new diagnostic and therapeutic approaches. J Glob Antimicrob Resist. 2017 Sep;10:204-212. doi: 10.1016/j.jgar.2017.06.013. Epub 2017 Jul 22. PMID: 28743646.\u003c/li\u003e\n \u003cli\u003eShankar-Hari M, Phillips GS, Levy ML, et al. Developing a New Definition and Assessing New Clinical Criteria for Septic Shock: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):775\u0026ndash;787. doi:10.1001/jama.2016.0289\u003c/li\u003e\n \u003cli\u003ePurcarea A, Sovaila S. Sepsis, a 2020 review for the internist. Rom J Intern Med. 2020 Sep 1;58(3):129-137. doi: 10.2478/rjim-2020-0012. PMID: 32396142.\u003c/li\u003e\n \u003cli\u003eZhang W, Fang X, Gao C, Song C, He Y, Zhou T, Yang X, Shang Y, Xu J. MDSCs in sepsis-induced immunosuppression and its potential therapeutic targets. Cytokine Growth Factor Rev. 2023 Feb;69:90-103. doi: 10.1016/j.cytogfr.2022.07.007. Epub 2022 Jul 21. PMID: 35927154.\u003c/li\u003e\n \u003cli\u003eSchrijver IT, Th\u0026eacute;roude C and Roger T (2019) Myeloid-Derived Suppressor Cells in Sepsis. Front. Immunol. 10:327. doi: 10.3389/fimmu.2019.00327\u003c/li\u003e\n \u003cli\u003eZhang X, Zhang Y, Yuan S, Zhang J. The potential immunological mechanisms of sepsis. Front Immunol. 2024 Jul 8;15:1434688. doi: 10.3389/fimmu.2024.1434688. PMID: 39040114; PMCID: PMC11260823.\u003c/li\u003e\n \u003cli\u003eMathias B, Delmas AL, Ozrazgat-Baslanti T, Vanzant EL, Szpila BE, Mohr AM, Moore FA, Brakenridge SC, Brumback BA, Moldawer LL, Efron PA; the Sepsis, Critical Illness Research Center Investigators. Human Myeloid-derived Suppressor Cells are Associated With Chronic Immune Suppression After Severe Sepsis/Septic Shock. Ann Surg. 2017 Apr;265(4):827-834. doi: 10.1097/SLA.0000000000001783. PMID: 27163951; PMCID: PMC5102824.\u003c/li\u003e\n \u003cli\u003eUhel F, Azzaoui I, Gr\u0026eacute;goire M, Pangault C, Dulong J, Tadi\u0026eacute;\u0026nbsp;JM, Gacouin A, Camus C, Cynober L, Fest T, Le Tulzo Y, Roussel M, Tarte K. Early Expansion of Circulating Granulocytic Myeloid-derived Suppressor Cells Predicts Development of Nosocomial Infections in Patients with Sepsis. Am J Respir Crit Care Med. 2017 Aug 1;196(3):315-327. doi: 10.1164/rccm.201606-1143OC. PMID: 28146645.\u003c/li\u003e\n \u003cli\u003eHollen MK, Stortz JA, Darden D, Dirain ML, Nacionales DC, Hawkins RB, Cox MC, Lopez MC, Rincon JC, Ungaro R, Wang Z, Wu Q, Brumback B, Gauthier ML, Kladde M, Leeuwenburgh C, Segal M, Bihorac A, Brakenridge S, Moore FA, Baker HV, Mohr AM, Moldawer LL, Efron PA. Myeloid-derived suppressor cell function and epigenetic expression evolves over time after surgical sepsis. Crit Care. 2019 Nov 13;23(1):355. doi: 10.1186/s13054-019-2628-x. PMID: 31722736; PMCID: PMC6854728.\u003c/li\u003e\n \u003cli\u003eGong H, Zhao J, Xu W, Wan Y, Mu X, Zhang M. The distribution of myeloid-derived suppressor cells subsets and up-regulation of programmed death-1/PD-L1 axis in peripheral blood of adult CAP patients. PLoS One. 2023 Sep 27;18(9):e0291455. doi: 10.1371/journal.pone.0291455. PMID: 37756307; PMCID: PMC10529571.\u003c/li\u003e\n \u003cli\u003eHawkins RB, Raymond SL, Stortz JA, Horiguchi H, Brakenridge SC, Gardner A, Efron PA, Bihorac A, Segal M, Moore FA, Moldawer LL. Chronic Critical Illness and the Persistent Inflammation, Immunosuppression, and Catabolism Syndrome. Front Immunol. 2018 Jul 2;9:1511. doi: 10.3389/fimmu.2018.01511. PMID: 30013565; PMCID: PMC6036179.\u003c/li\u003e\n \u003cli\u003eGabrilovich DI. Myeloid-Derived Suppressor Cells. Cancer Immunol Res. 2017 Jan;5(1):3-8. doi: 10.1158/2326-6066.CIR-16-0297. PMID: 28052991; PMCID: PMC5426480.\u003c/li\u003e\n \u003cli\u003eOchoa Gautier JB. Dietary modification of myeloid-derived suppressor cells (MDSC) activity in sepsis. Proc Natl Acad Sci U S A. 2022 Mar 22;119(12):e2201396119. doi: 10.1073/pnas.2201396119. Epub 2022 Mar 15. PMID: 35290112; PMCID: PMC8944247.\u003c/li\u003e\n \u003cli\u003eHegde S, Leader AM, Merad M. MDSC: Markers, development, states, and unaddressed complexity. Immunity. 2021 May 11;54(5):875-884. doi: 10.1016/j.immuni.2021.04.004. PMID: 33979585; PMCID: PMC8709560.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e\u003cstrong\u003eDifferences in MDSCs Between the Sepsis Group and the Control Group\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"473\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eControl Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eSepsis Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eAge（years old）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e63.50+2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e67.58+2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e17（42.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e30（48.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eCardiovascular disease\u003csup\u003e1\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e13（12.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e16（15.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eKidney disease\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e7（17.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e9（14.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eCentral nervous system disease\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e6（15.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e9（14.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003ePulmonary disease\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e6（15.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e9（14.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003ePMN-MDSCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.20+0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e4.92+0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e6.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eM-MDSCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e7.93+0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e19.40+1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e6.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003ePatients with a positive history of the disease\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e\u003cstrong\u003eThe levels of MDSCs were compared between the\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;general\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;sepsis group and the septic shock group\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"551\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;Genaral Sepsis Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eSeptic Shock Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e16（45.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e14（51.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eAge（years old）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e67.20+2.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e67.23+4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eCardiovascular disease\u003csup\u003e1\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e8（22.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e8（29.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eKidney disease\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e5（14.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e4（14.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eCentral nervous system disease\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e3（8.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e6（22.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003ePulmonary disease\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e5（14.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e4（14.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eWBC(\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e9.97+0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e9.64+0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e-0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eRBC(\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e4.14+0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e4.20+0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003ePLT(\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e218.39+17.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e244.65+18.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eCRP(mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e（10.44,116.30）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e（9.50,75.12）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003ePCT(ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e5.52+0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e13.97+2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e-0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eSOFA scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e4.71+0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e7.46+0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e3.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003ePMN-MDSCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e4.77+0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e5.20+0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eM-MDSCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e17.59+1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e21.02+1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e-1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eLength of hospotal-stay (day)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e(11.00,24.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e(9.00,29.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eDeath\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e2（5.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e5（18.50）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e1.\u003cstrong\u003ePatients with a positive history of the disease\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eExpression levels of MDSCs in response to G\u003c/strong\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and G\u003c/strong\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;bacteria\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"407\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eG- bacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eG+ bacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003ePMN-MDSCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e5.36+0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e4.39+0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eM-MDSCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e18.74+8.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e10.32+3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eSOFA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e8.00+0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e4.90+0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"spesis, sepsis shock, MDSCs, Gram-positive bacterial, Gram-negative bacterial","lastPublishedDoi":"10.21203/rs.3.rs-9051683/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9051683/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eBackground\u003c/b\u003e Accumulating evidence has established a correlation between Myeloid-derived suppressor cell (MDSC)-mediated immunosuppression and the prognosis of sepsis and septic shock. However, the relationship between MDSCs and specific infection sites or pathogens remains largely unexplored. Therefore, this study aimed to further elucidate the role of MDSCs in peripheral blood.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods\u003c/b\u003e This single-center, prospective, cross-sectional study enrolled patients according to predefined inclusion and exclusion criteria. Demographic characteristics, clinical data, and blood samples were collected from all participants. Flow cytometry was performed to detect the expression levels of MDSCs in different groups, and the results were subsequently compared and analyzed.sepsis by investigating their association with different infectious origins.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e The expression levels of both PMN-MDSCs and M-MDSCs were significantly higher in the sepsis group than in the healthy control group (4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31 vs. 2.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14, t\u0026thinsp;=\u0026thinsp;6.87, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; 19.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31 vs. 7.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45, t\u0026thinsp;=\u0026thinsp;6.80, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, respectively). However, no significant differences were observed in the levels of these subsets between the general sepsis and septic shock groups (t\u0026thinsp;=\u0026thinsp;0.56, P\u0026thinsp;=\u0026thinsp;0.58; t = -1.43, P\u0026thinsp;=\u0026thinsp;0.16). Patient mortality was significantly correlated with both PMN-MDSCs (Wald\u0026thinsp;=\u0026thinsp;5.56, P\u0026thinsp;=\u0026thinsp;0.01, 95% CI: 0.43\u0026ndash;0.92) and M-MDSCs (Wald\u0026thinsp;=\u0026thinsp;5.25, P\u0026thinsp;=\u0026thinsp;0.02, 95% CI: 0.98\u0026ndash;1.26). Regarding infection sites, M-MDSC expression was significantly lower in pulmonary infections compared to urinary tract infections (t\u0026thinsp;=\u0026thinsp;2.77, P\u0026thinsp;=\u0026thinsp;0.01). In contrast, no significant differences were found in either PMN-MDSC or M-MDSC expression between Gram-positive and Gram-negative bacterial infections (t\u0026thinsp;=\u0026thinsp;0.99, P\u0026thinsp;=\u0026thinsp;0.32; t\u0026thinsp;=\u0026thinsp;0.71, P\u0026thinsp;=\u0026thinsp;0.48, respectively).\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e MDSC-mediated immunosuppression correlates with patient prognosis and mortality risk. While no early-stage difference in MDSC expression was found between sepsis and septic shock\u0026mdash;underscoring the need for dynamic monitoring\u0026mdash;expression levels did vary by infection site. Specifically, M-MDSCs were significantly elevated in urinary tract infections and were more pronounced in Gram-negative than in Gram-positive bacterial infections.\u003c/p\u003e","manuscriptTitle":"Clinical Significance of MDSCs in Patients with Sepsis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-30 15:16:05","doi":"10.21203/rs.3.rs-9051683/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-02T05:46:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-31T03:26:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333404206518153500626766692712309309233","date":"2026-03-29T17:22:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-29T05:52:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"62223848174922618842939051688839792087","date":"2026-03-29T05:38:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286049644142017768648297589766347610945","date":"2026-03-28T08:06:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-28T07:12:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-28T02:37:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"296062443553231447341098789300428108438","date":"2026-03-28T00:39:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"39994933216775045251021405597504895881","date":"2026-03-27T13:33:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"114183354989131655023259096354846455911","date":"2026-03-27T09:49:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"16097438812807434551684983976102454314","date":"2026-03-27T06:47:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-27T00:10:36+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-17T15:10:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-17T06:34:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-12T11:55:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-03-12T06:51:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9973a3d6-b789-47b8-b891-688eaa996bda","owner":[],"postedDate":"March 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":65328971,"name":"Health sciences/Biomarkers"},{"id":65328972,"name":"Health sciences/Diseases"},{"id":65328973,"name":"Biological sciences/Immunology"},{"id":65328974,"name":"Health sciences/Medical research"},{"id":65328975,"name":"Biological sciences/Microbiology"}],"tags":[],"updatedAt":"2026-04-27T16:02:22+00:00","versionOfRecord":{"articleIdentity":"rs-9051683","link":"https://doi.org/10.1038/s41598-026-49604-x","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-04-21 15:58:48","publishedOnDateReadable":"April 21st, 2026"},"versionCreatedAt":"2026-03-30 15:16:05","video":"","vorDoi":"10.1038/s41598-026-49604-x","vorDoiUrl":"https://doi.org/10.1038/s41598-026-49604-x","workflowStages":[]},"version":"v1","identity":"rs-9051683","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9051683","identity":"rs-9051683","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}