Candida infections are among the most common fungal diseases worldwide and are associated with notable morbidity and mortality, particularly in immunocompromised and critically ill patients. Moreover, the emergence and spread of antifungal resistance pose an increasing threat to global public health. Therefore, evidence-based recommendations are urgently needed to guide the surveillance and control of Candida infections. A multidisciplinary guidance development group comprising experts of infectious diseases, clinical microbiology, pharmacology, infection control, and guideline methodology jointly developed the present clinical practice guidance. The process followed internationally recognized grading of recommendations, assessment, development and evaluation (GRADE) framework. Clinical questions were formulated based on priority issues or areas of uncertainty in current practice, and corresponding recommendations were developed after systematic review and synthesis of the best available evidence. The strength of recommendations was classified as strong or conditional (weak), and the certainty of evidence was graded from high to low. The guidance provides recommendations on diagnostic strategies, antifungal therapy, and infection prevention and control measures for Candida infections, integrating both global evidence and national clinical experience. The target users include clinicians, microbiologists, infection control practitioners, and policymakers involved in the management of fungal diseases. The guidance aims to support optimized clinical decision-making, improve antifungal stewardship, and strengthen infection control strategies to address the growing challenge posed by Candida infections.

Background:Sepsis-associated acute kidney injury (SA-AKI) is a frequent and high-mortality complication in critically ill patients. Current diagnostic criteria rely on functional markers that often lag behind the onset of renal injury. While immune dysregulation is central to SA-AKI pathogenesis, few prediction models systematically integrate multidimensional immune phenotypes. Methods:The present analysis was based on a multicenter prospective cohort study involving 1,551 septic patients. The study was carried out across five tertiary hospitals in Beijing. Clinical data and immuno-inflammatory biomarkers (including humoral, complement, and T lymphocyte subsets) were collected within 24 hours of sepsis diagnosis. An Extreme Gradient Boosting (XGBoost) model was then developed to predict SA-AKI. Results:New-onset SA-AKI occurred in 44.8% of the cohort and was associated with increased mortality. We identified a distinct high-risk immuno-inflammatory endotype characterized by elevated immunoglobulin A and procalcitonin (PCT), consumptive complement component 3 depletion, and a "complex and divergent cellular immune pattern"-manifested as depleted naïve CD4+ T cells coexisting with expanded CD28+CD4+ T cells. Integrating these immune features with routine clinical variables (Acute Physiology and Chronic Health Evaluation II (APACHE II), the Sequential Organ Failure Assessment [SOFA], PCT, prothrombin time [PT], sex) yielded an XGBoost-based clinical-immune model with superior discrimination (area under the curve [AUC], 0.914), significantly outperforming the clinical model (AUC, 0.788). Decision curve analysis further confirmed greater net clinical benefit for the integrated model. Conclusion:Immune dysregulation plays an important role in developing AKI in sepsis patients. Immune biomarkers could significantly improve early identification of high SA-AKI risk patients.

BACKGROUND:Sepsis-associated acute kidney injury (SA-AKI) is a severe complication of sepsis characterized by high mortality and limited early immune-related biomarkers. Increasing evidence suggests that immune dysregulation contributes substantially to the pathogenesis of SA-AKI; however, the immunological characteristics underlying bacterial intra-abdominal infection (IAI)-associated SA-AKI remain incompletely understood. METHODS:In this study, we investigated alterations in lymphocyte subsets and immune mediators in patients with bacterial IAI-associated sepsis. Clinical and immunological data were collected to identify independent risk factors for SA-AKI, and an immuno-nomogram was established. Public transcriptomic datasets from the Gene Expression Omnibus (GEO) database were analyzed to evaluate immune cell infiltration and immunosuppressive gene expression. Experimental validation was performed using murine LPS and CLP models with flow cytometry and immunofluorescence. RESULTS:A total of 408 patients with bacterial IAI-associated sepsis were enrolled, among whom 120 patients (29.4%) developed SA-AKI. Patients with SA-AKI exhibited significantly lower peripheral CD8+ T-cell percentages compared with those without SA-AKI. Integrated immuno-inflammatory profiling identified peripheral CD8+ T cell reduction as a prominent immune feature and an independent risk factor for SA-AKI. Incorporation of CD8+ T cell percentage into the immuno-nomogram significantly improved predictive performance compared with the clinical model alone. Transcriptomic analysis and experimental validation consistently demonstrated reduced renal CD8+ T cell infiltration accompanied by enhanced immunosuppressive signaling and elevated immunosuppressive scores. Moreover, renal CD8+ T cell abundance was inversely associated with immunosuppressive signaling. CONCLUSIONS:Collectively, these findings identify CD8+ T cell reduction as a key immunological feature of SA-AKI. Integrated clinical, transcriptomic, and experimental data support a consistent association between systemic immune alterations and kidney immune-related signatures in SA-AKI. These findings support the potential utility of CD8+ T cells as an immune-associated biomarker for risk stratification in SA-AKI.

Immune dysregulation is central to sepsis-related organ injury, yet standard clinical indicators show limited predictive value for sepsis-associated acute kidney injury (SA-AKI) in older adults(aged ≥ 65 years). This study evaluated whether immuno-inflammatory biomarkers improve early prediction of SA-AKI. In this prospective multicenter cohort of 627 older adults with sepsis admitted to ICUs in five Beijing tertiary hospitals, the overall incidence of SA-AKI was 43.1

OBJECTIVES:Sepsis-induced coagulopathy (SIC) is a critical complication of sepsis that profoundly affects the severity of organ dysfunction and clinical prognosis. The current study aimed to construct and compare multiple individualized machine learning (ML) prediction models for predicting severe acute kidney injury (AKI) in patients with SIC, with the goal of identifying the most robust model to improve the accuracy of clinical decision-making. METHODS:The retrospective analysis was conducted based on the MIMIC‑IV database and a Chinese cohort. Eligible patients with sepsis and SIC were included. Both LASSO regression and the Boruta algorithm were used to select predictive variables. Eight ML models were constructed to predict the individual probability for severe AKI development. The receiver operating characteristic (ROC) curve, area under the precision-recall curve (PR-AUC) value, calibration indicators, and net benefit were used to assess the predictive model performance. Subgroup analyses were performed to evaluate the stability of model performance. Model predictions and feature importance were estimated using SHapley additive explanations (SHAP). RESULTS:Among the 14,155 patients with sepsis, 5,207 developed SIC and were randomly divided into training and internal validation cohorts. The severe AKI incidence rate was 24.7% (1288/5207). The Chinese external validation cohort enrolled 525 patients with SIC, with a severe AKI incidence rate of 28.1% (148/525). Six key predictive variables were identified to construct the ML models. The XGBoost prediction model demonstrated the most robust performance and best discrimination, achieving an area under the ROC curve of 0.875 (0.862-0.888) in the training cohort, 0.831 (0.807-0.854) in the internal cohort, and 0.843 (0.806-0.879) in the external validation cohort. Serum creatinine on the day of SIC diagnosis was identified as the most influential feature in the SHAP analysis. Subgroup analyses demonstrated that the model maintained predictive efficacy when stratified by age, sex, chronic kidney disease, and liver disease. CONCLUSIONS:The XGBoost machine learning model performed well in predicting the risk of severe AKI in patients with SIC, exhibiting satisfactory generalizability and interpretability. This prediction model provides a valuable and evidence-based tool for early identification and facilitates personalized targeted management in critical care settings.

Severe sepsis-associated acute kidney injury (severe SA-AKI) is clinically important in older adults with sepsis, but early identification remains challenging. This study aimed to characterize clinical and immuno-inflammatory features of severe SA-AKI and develop an interpretable prediction model for older ICU patients with sepsis. This prospective multicenter cohort study enrolled older adults with sepsis admitted to five tertiary ICUs between June 2023 and December 2025. Patients were temporally assigned to a training cohort and an internal temporal validation cohort. Severe SA-AKI was defined as KDIGO acute kidney injury stage 2 or 3 within 7 days after sepsis time zero or during ICU stay. Candidate predictors collected within 24 h after time zero were evaluated in the training cohort, and a logistic regression nomogram was developed and validated. Among 1,236 included patients, the minimum age was 65 years, and the mean age was 74.6 ± 7.5 years; 258 patients developed severe SA-AKI. The final 7-variable model included non-renal SOFA score, chronic kidney disease, log(Lactate + 1), log(IL-6 + 1), NK-cell percentage, CD4 + T-cell percentage, and C3. The model achieved AUCs of 0.917 and 0.904 in the training and validation cohorts, respectively. Brier scores were 0.086 and 0.096. Severe SA-AKI incidence increased across low-, intermediate-, and high-risk groups: 0.5

CD4 + T cells are major reactive subpopulation for cellular and humoral immune responses following sepsis. The apoptosis of CD4 + T cells may contribute to sepsis-induced immunosuppression, and preventing the induction of endoplasmic reticulum stress (ERS) can ameliorate apoptosis of CD4 + T cells in sepsis. The mechanistic target of rapamycin (mTOR) pathway performs an essential regulatory role on ERS-apoptosis of CD4 + T cells. This study aims to elucidate the underlying mechanisms of mTOR regulation of ERS-apoptosis of CD4 + T cells. In this study, based on the cecal ligation and puncture (CLP) model, 4-phenylbutyric acid (4-PBA), we firstly detected the percentage of ERS-apoptosis of CD4 + T cells with flow cytometry, Western blotting. Next, we observed the autophagy process and related makers with transmission electron microscopy (TEM) and Western blotting. Furthermore, we created CLP models with T cell-specific mTOR and TSC1 genetic knockout mice, and bafilomycin A1(Baf-A1), a selective inhibitor of autophagy to explore the regulatory role and underlying mechanism of mTOR on ERS-apoptosis of CD4 + T cells. With rapamycin, we proved the clinical potential of mTOR. Here we observed a considerably higher percentage of apoptotic CD4 + T cells in sepsis, and 4-PBA (an inhibitor of ERS) could alleviate not only ERS, but also the apoptosis of CD4 + T cells. As our previous work proved, deletion of mTOR decreased ERS-apoptosis of CD4 + T cells in sepsis. Furthermore, deficient autophagy, especially impaired autophagic flux was observed in sepsis. Mechanistically, we found knockdown of mTOR erased impaired autophagic flux, decreased ER stress-induced apoptosis, which could be reversed by Baf-A1. More importantly, rapamycin (inhibitor of mTOR) showed great clinical potential. we proved that mTOR deletion could alleviate CD4 + T cells ERS-apoptosis by rescuing autophagy involving autophagosome –lysosome fusion. For the first time, we demonstrate the mTOR-autophagy-ERS-apoptosis axis in sepsis, enriching the targets for future discovery of new sepsis therapies.

Older adults are at high risk of sepsis, but the immune-inflammatory features distinguishing sepsis from nonsevere infection and their prognostic relevance remain incompletely defined. We aimed to characterize immune-inflammatory profiles across the older adult infection spectrum and evaluate their longitudinal association with in-hospital mortality. In this multicentre prospective observational cohort, 1,851 participants aged ≥ 60 years were enrolled, including healthy controls, patients with nonsevere infection, and patients with sepsis. Immune-cell subsets, cytokines, complement components, and routine laboratory indices were assessed. Adjusted cross-sectional comparisons were performed using multivariable linear regression. Among patients with sepsis, model-estimated longitudinal profiles from intensive care unit (ICU) day 1 to day 7 were analysed using linear mixed-effects models among available scheduled measurements, and day-1 biomarkers associated with in-hospital mortality were evaluated using Cox regression. The cohort included 524 healthy controls, 511 patients with nonsevere infection, and 816 patients with sepsis. Across the infection spectrum, sepsis was characterized by progressively lower circulating lymphocyte, T-cell, cluster of differentiation 8 (CD8+) T-cell, and natural killer (NK)-cell counts, together with higher interleukin (IL)-6, IL-8, and IL-10 levels. These differences remained after adjustment for age, sex, and major comorbidities. Among patients with available follow-up measurements, non-survivors had consistently higher Sequential Organ Failure Assessment (SOFA) scores, IL-6, and IL-10 and lower lymphocyte, T-cell, CD8⁺ T-cell, NK-cell, and complement component 3 (C3) levels. No time-by-outcome interaction remained significant after false-discovery-rate correction. In multivariable Cox models, higher day-1 SOFA score and IL-10 were associated with increased in-hospital mortality, whereas higher NK-cell count was associated with lower mortality. In older adults, sepsis was associated with an adjusted circulating immune-inflammatory pattern characterized by lower cellular immune markers and higher cytokine levels. This separation was evident on ICU day 1 and remained observable among patients with available follow-up measurements. Given the observational design, these associations should not be interpreted as causal.

Patients with severe community-acquired pneumonia (SCAP) are at significantly increased risk for venous thromboembolism (VTE). Traditional VTE risk assessment tools like the Caprini and Padua prediction scores are often underutilized in acute care settings due to their complexity. The CURB-65 score, a routine severity assessment tool for pneumonia, may offer a simplified and integrated approach for VTE risk stratification, but its predictive value for deep vein thrombosis (DVT) in SCAP patients requires validation. We retrospectively enrolled 766 adults with SCAP admitted to Beijing Chao-Yang Hospital between January 1, 2015 and August 31, 2024. Baseline characteristics, CURB-65, Caprini, and Padua prediction scores, VTE prophylaxis details, and the occurrence of ultrasound confirmed in-hospital DVT were collected. Multivariable logistic regression was employed to identify independent risk factors for DVT. We further performed a sensitivity analysis restricted to proximal DVT. The predictive performance of the scores was compared using the area under the receiver operating characteristic curve (AUC). Patients were stratified into low-risk (CURB-65 < 3) and high-risk (CURB-65 ≥ 3) groups for further analysis, including Kaplan-Meier survival analysis to compare cumulative DVT incidence. A separate multivariable analysis was conducted in the subgroup of patients who received VTE prophylaxis. The overall incidence of DVT was 30.3

Background:Sepsis-associated acute kidney injury (SA-AKI) is a frequent and life-threatening complication of sepsis. While the static lactate-to-albumin ratio (LAR) has prognostic value, its dynamic temporal evolution during early resuscitation and its utility for guiding clinical risk stratification remain underexplored. Objective:The aim of the study is to identify distinct dynamic trajectories of LAR, evaluate their independent associations with adverse clinical outcomes, and construct a practical prognostic nomogram for patients with SA-AKI. Methods:Data were extracted from the Medical Information Mart for Intensive Care IV database, including adult patients with SA-AKI and ≥ 3 lactate and albumin measurements within the first 72 hours of intensive care unit admission. A multicenter external validation cohort was assembled from 5 tertiary hospitals in Beijing, China. Group-based trajectory modeling identified distinct LAR trajectories. The primary outcome was 28-day mortality; secondary outcomes included 90-day mortality and continuous renal replacement therapy initiation. Trajectory-outcome associations were assessed using multivariable Cox and logistic regression models. Robustness was examined using restricted cubic splines, inverse probability of treatment weighting, weight truncation, doubly robust estimation, and subgroup analyses. Incremental predictive value beyond single baseline LAR was quantified, and a trajectory-integrated nomogram was developed and externally validated. Results:Among the 615 patients in the primary cohort, 3 LAR trajectories were identified: trajectory 1 (low-stable type), trajectory 2 (rapid-clearance type), and trajectory 3 (delayed-clearance type). In adjusted multivariable models, trajectory 3 (vs trajectory 1) was independently associated with increased 28-day mortality risk (hazard ratio 1.63, 95% CI 1.00-2.64; P=.0496), 90-day mortality (hazard ratio 1.72, 95% CI 1.14-2.60; P=.01), and continuous renal replacement therapy initiation (odds ratio 3.40, 95% CI 1.64-7.15; P=.001). Conversely, the mortality risk for trajectory 2 did not differ significantly from trajectory 1. Sensitivity analyses supported these findings, although trajectory 3 associations attenuated in inverse probability of treatment weighting-weighted analyses. Incorporating trajectories improved predictive accuracy over single baseline LAR (continuous net reclassification improvement 0.170, integrated discrimination improvement 0.023; both P=.01). In the external validation cohort (n=508), 3 analogous trajectories were identified. Trajectory 3 consistently conferred a higher mortality risk across both cohorts, whereas trajectory 2 was significantly associated with 28-day mortality only in validation. The nomogram exhibited modest discrimination in the external cohort (concordance index=0.612), acceptable calibration, and potential utility as a supplementary bedside risk stratification tool. Conclusions:Dynamic LAR trajectories are independently associated with 28- and 90-day mortality in SA-AKI. The delayed-clearance trajectory identifies a specific high-risk phenotype, suggesting that longitudinal LAR monitoring and the constructed nomogram may support early risk stratification and inform clinical decision-making.

Sepsis-induced immunosuppression contributes to poor outcomes in sepsis patients, yet the mechanisms underlying T cell dysfunction remain incompletely understood. We integrated single-cell RNA sequencing (scRNA-seq), paired single-cell T cell receptor sequencing (scTCR-seq), bulk RNA sequencing (RNA-seq), and flow cytometry to characterize CD8+ and CD4+ T cells in septic shock-associated immunosuppression. Patients showed reduced T cell receptor (TCR) clonotype diversity in CD4+ T cells but not CD8+ T cells, with restricted clonality correlating with disease severity and lymphopenia. Integrative analyses revealed the expansion of two disease-associated subsets: (1) CD177+CD8+ T cells, enriched for interleukin-17 (IL-17) signaling with hyperexpanded clonotypes, and (2) TLR4+CD4+ T cells, enriched for phagocytosis- and lysosome-related programs with restricted clonality. Both subsets expressed high levels of S100A8, S100A9, and S100A12, correlating positively with severity scores and systemic inflammation. These findings provided single-cell resolution evidence that clonal restriction of CD4+ T cells is a hallmark of septic immunosuppression. Our study depicted a single-cell atlas linking CD4+ clonal restriction and the expansion of pathogenic T cell subsets to outcome, highlighting TCR clonality as a biomarker of immune competence and CD177+CD8+ and TLR4+CD4+ T cells as candidate therapeutic targets in septic shock-associated immunosuppression.

Background:Sepsis is defined as a life-threatening organ dysfunction caused by dysregulated host responses to infections. This study aimed to investigate the early and dynamic changes in peripheral lymphocyte subsets following sepsis in octogenarian and elder patients and whether these changes were related to 28-day mortality. Methods:A prospective cohort study of 3601 consecutive patients admitted to the intensive care unit (ICU) was performed between March 2017 and January 2023. Peripheral blood samples were collected on admission, Day 3, and Day 7 for patients with sepsis and on enrollment for patients without sepsis. Lymphocyte subsets were detected by flow cytometry. The 28-day mortality was determined using Kaplan-Meier analysis, while Cox regression identified prognostic factors. Results:All enrolled patients were divided into three groups: adult (18-64 years), elder (65-79 years), and octogenarian (≥80 years). Sepsis induced a numerical reduction in lymphocytes (median=0.653 [IQR: 0.500-1.038] vs. median=0.840 [IQR: 0.579-1.142] × 109/L, P=0.043) and CD3+ T-cell counts (median=0.461 [IQR: 0.312-0.759] vs. median=0.590 [IQR: 0.417-0.789] × 109/L, P=0.021) in octogenarian patients. Kaplan-Meier survival curves showed that in the elder (P [log-rank test] < 0.001) and octogenarian (P [log-rank test]=0.02) groups, patients with CD3+ T-cell nonrecovery on Day 3 and Day 7 had the highest mortality, followed by those with late recovery, and the lowest mortality was observed in the early recovery group. Multivariate Cox regression analysis demonstrated that age (hazard ratio [HR]=1.217, 95% confidence interval [CI]: 1.050 to 1.410, P=0.009) and CD3+T-cell counts (HR=0.999, 95% CI: 0.999 to 1.000, P < 0.001) were independent risk factors associated with 28-day mortality in patients with sepsis. Conclusions:Sepsis induced a numerical reduction in lymphocytes and CD3+ T-cell counts in octogenarian patients (≥80 years). The persistent decrease of CD3+ T-cell counts on Day 3 and Day 7 following sepsis was associated with higher mortality in elder and octogenarian patients.Trial registration Chinese Clinical Trial Registry identifier: ChiCTR-ROC-17010750.

This case report highlights cutaneous mucormycosis in a 99-year-old patient who was effectively treated with intravenous isavuconazole and local amphotericin B after wound debridement. The patient showed significant improvement within two weeks, highlighting the importance of diagnosis and treatment for this rare fungal infection. It underscores the need for early recognition and suggests that combining antifungal treatments with surgical intervention may be an optimal strategy, even in patients lacking typical risk factors.

Background:Neutrophil acts as a double-edged sword in the immune system. We hypothesized that an elevated neutrophil granule protein level is associated with sepsis-associated lymphopenia (SAL). Methods:We enrolled 61 patients with sepsis admitted to the Department of Critical Care Medicine of Peking Union Medical College Hospital between May 2022 and October 2023 in this study. Clinical and immunological parameters were recorded. Levels of neutrophil granule proteins, including myeloperoxidase (MPO) and neutrophil elastase (NE), and pyroptosis factors were examined. Results:Levels of neutrophil granule proteins (MPO, 82.9 vs. 175.3, p < 0 <.0001; NE, 56.3 vs. 144.2, p < 0.0001) were significantly higher in patients with sepsis with lymphopenia. Neutrophil granule protein levels were independently associated with SAL risk (MPO: OR = 1.0841, 95% CI, 1.0020-1.1730; NE: OR = 1.0540, 95% CI, 1.0040-1.1065). The area under the curve of MPO levels predicting SAL occurrence was 0.939 (95% CI, 0.846-0.984), and that of NE was 0.950 (95% CI, 0.862-0.989). Furthermore, neutrophil granule proteins were significantly correlated with CD4+ T cell and its pyroptosis [MPO and CD4+ T cells (r = -0.4039, p < 0.0001), CD4+NLRP3 (r = 0.4868, p < 0.0001), NE and CD4+ T cells (r = -0.5140, p < 0.0001), and CD4+NLRP3 (r = 0.6513, p < 0.0001)]. Conclusion:Increased levels of neutrophil granule proteins were significantly associated with SAL incidence, and a significant relationship between neutrophil granule proteins and the pyroptosis pathway of CD4+ T cells was revealed. Clinical trial registration:chictr.org.cn identifier ChiCTR-ROC-17010750.

BackgroundSepsis induces profound derangements in the immune system, including lymphopenia, which correlates with immunosuppression and poor prognosis. However, most evaluations of immunosuppression in sepsis patients rely on static, sporadic lymphocyte counts, lacking dynamic modeling over the disease course. This study aimed to apply latent class mixed modeling on longitudinal lymphocyte counts to uncover heterogeneous trajectory phenotypes in sepsis patients and assess their predictive value for clinical outcomes.ResultsFour lymphocyte trajectory phenotypes were identified in the retrospective cohort (n=2,149) and externally validated (n=2,388): high–declining (α, 3.8%), stable–medium (β, 69.3%), high–increasing (γ, 3.2%), and stable–low (δ, 23.8%). The α phenotype exhibited the highest disease severity and mortality (25.9%) compared with other phenotypes in both cohorts. In the prospective cohort (n=1,056), all lymphocyte subset counts differed among phenotypes on admission (P <.001) and were lower in non-survivors (P<.05). Multivariable regression demonstrated that age, Acute Physiology and Chronic Health Evaluation-II score, heart rate, natural killer cell count, infection source, and lymphocyte trajectory phenotype were independent predictors of 28-day mortality. A nomogram combining these variables provided individualized risk estimations.ConclusionsThe lymphocyte trajectories delineated novel dynamic phenotypes associated with divergent sepsis outcomes. Incorporating longitudinal trajectory modeling and lymphocyte subsets may improve prognostic risk assessment and guide the selection of immunotherapies tailored to specific immune phenotypes in sepsis patients.Clinical trial registrationhttps://www.chictr.org.cn/showproj.aspx?proj=18277, identifier ChiCTR-40 ROC-17010750.

INTRODUCTION:Intra-abdominal candidiasis (IAC) still has a high mortality rate despite prompt antifungal therapy due to immunosuppression. T cell exhaustion is an important manifestation of immunosuppression. This study aimed to explore the expression pattern of exhaustion-related molecules in patients with IAC and determine the possible association between dynamic trends and prognosis. METHODS:Patients with IAC were enrolled, and non-IAC critically ill patients were included as controls. Peripheral blood mononuclear cells (PBMCs) were analysed by flow cytometry to determine the expression levels of T cell exhaustion-related markers. T cells isolated from PBMCs were stimulated by IL-2 in α-CD3/α-CD28 medium to compare intracellular cytokine production and proliferative capacity. RESULTS:A total of 34 patients with IAC and 35 controls were enrolled in this study. Patients with IAC had a significant decrease in lymphocytes. CD4+ and CD8+ T cells from patients with IAC had a significantly higher level of immune checkpoint molecules, such as programmed cell death protein 1 (PD-1), cytotoxic T-lymphocyte antigen 4 (CTLA4), and B and T lymphocyte attenuator (BTLA), and exhibited a consistently impaired cytokine-secreting function. Increased exhaustion-associated molecules and deteriorating dysfunction were detected in non-survivors, while survivors demonstrated the opposite tendency. Patients with impaired granzyme B (GZMB) production function who died from IAC over the course of the disease had higher levels of PD-1 expression in CD8+ T cells. CONCLUSIONS:T cells from patients with IAC displayed an immunosuppressive phenotype of T cell exhaustion. Sustaining exhaustion status and deteriorated dysfunction were associated with poor prognosis. Persistently increased PD-1 expression and impaired GZMB secretion in CD8+ T cells were linked to worse outcomes. Immunoadjuvants reversing T cell exhaustion have promising prospects in treating IAC and improving prognosis.

Infections, particularly sepsis, are a global health threat and a leading cause of mortality among elderly patients (≥ 60 years) in intensive care units (ICUs). The variable immune responses in this vulnerable population warrant deeper investigation. This multicenter prospective study included elderly patients with infections admitted to the ICUs of four hospitals between May 2023 and October 2024. Patients were classified into sepsis and non-sepsis infection groups based on a ≥2-point increase in Sequential Organ Failure Assessment (SOFA) score. Baseline immune and inflammatory markers were compared between groups. Logistic regression analyses were used to assess associations with mortality. Subgroup analyses were conducted by sex, age, infection site, and pathogen type. Among 1,152 elderly patients with infections in the ICUs, 640 with sepsis were older (70.0 vs.72.0 years), were predominantly male (55.3

Aimsto clarify the endoplasmic reticulum stress (ERS) status of CD4+ T lymphocytes in sepsis patients, particularly elderly individuals aged over 65 years, and to elucidate its association with mTOR-mediated autophagic-lysosomal disorder.Methods62 sepsis patients were enrolled from January 1 to July 31, 2024. Peripheral blood mononuclear cells (PBMCs) were isolated within 24 hours post-enrollment. flow cytometry was used to quantify the expression levels of ERS markers (CHOP and GRP78) and mTOR-mediated autophagic-lysosomal fusion markers (mTOR, LC3II and P62) on CD4+ T lymphocytes. These markers were compared between sepsis and non-sepsis patients, elderly and non-elderly sepsis patients, survivors and non-survivors based on in-hospital mortality. The correlations between CHOP mean fluorescence intensity (MFI) and CD4+ T lymphocyte count, LC3II MFI, and P62 MFI were also analyzed.ResultsCompared to non-septic controls, sepsis patients exhibited significantly higher CHOP and GRP78 MFIs (210.9 versus 142.9, P<0.001 and 279.1 versus 223.7, P=0.045). Within the sepsis group, elderly patients and non-survivors showed significantly higher CHOP and GRP78 MFIs (334.4 versus 164.2, P<0.001 and 374.3 versus 218.6, P<0.001; 390.8 versus 177.6, P<0.001 and 389.1 versus 227.0, P<0.001). CHOP MFI on CD4+ T lymphocytes showed significant correlations with LC3II and P62 MFIs in sepsis patients (Pearson’s correlation r=0.657, p<0.001 and r=0.811, P<0.001), elderly sepsis patients (r=0.644, P<0.001 and r=0.710, P<0.001), and non-survived elderly sepsis patients (r=0.897, P<0.001 and r=0.772, P=0.009).ConclusionERS in CD4+ T cells was enhanced in sepsis patients, particularly in elderly and non-survived individuals; ERS is strongly associated with mTOR-mediated autophagic-lysosomal disorder.Clinical trial registrationchictr.org.cn, identifier ChiCTR2300074175.

INTRODUCTION:There is a lack of evidence on the efficacy of extracorporeal blood purification (EBP) to reduce the mortality rate in septic shock. We have designed the EABPSS (Efficacy of Adaptive Blood Purification for Septic Shock) study to confirm whether adaptive blood purification (ABP) intervention could confer a clinical benefit. METHODS AND ANALYSIS:In this multicentre, open-label, randomised controlled trial, we are recruiting a total of 276 patients with septic shock. Eligible patients who provide informed consent will be randomly assigned in a 1:1 ratio to either the control group or the intervention group. Patients in the control group will receive standard care according to the Surviving Sepsis Guidelines. Patients in the intervention group will receive two 6-hour sessions of ABP treatment within 24 hours of enrolment, based on standard care. ABP is a novel, adaptive EBP strategy proposed by our research team. Specifically, for patients with septic shock who do not require renal replacement therapy (RRT), plasmafiltration-adsorption (PFAD) will be used alone, and for patients with septic shock and acute kidney injury meeting RRT indications, a combination of PFAD-RRT will be employed. The primary endpoint of this study is all-cause mortality at 90 days after enrolment. Secondary endpoints of the study include the declining proportion of serum cytokines such as tumour necrosis factor-α (TNF-α), IL-4, IL-6, IL-8, IL-10 and high-mobility group box 1 within 24 hours after enrolment. Additionally, the study will evaluate the improvement of the Sequential Organ Failure Assessment score on day 7 postenrolment, as well as the 30-day mortality rate. ETHICS AND DISSEMINATION:The study was approved by the respective ethical committees of the participant centres, including: Ethics Committee of Beijing Chaoyang Hospital, Capital Medical University (2024-KE-348); Ethics Committee of PLA General Hospital (S2024-716-01); Ethics Committee of China-Japan Friendship Hospital (2024-KY181); Clinical Research Ethics Committee of Peking University First Hospital (2024YAN258-001); Ethics Committee of Beijing Hospital (2024BJYYEC-KY106-02); Ethics Committee of Air Force Medical Center, PLA (KONGTE2024-29-PJ01); Ethics Committee of Beijing Jishuitan Hospital, Capital Medical University (JILUN(K2023)(370)-00). The findings of the study will be disseminated in peer-reviewed journals and presented at national and international conference presentations. TRIAL REGISTRATION NUMBER:NCT06692036.