Sepsis is a life-threatening syndrome characterized by organ dysfunction caused by a dysregulated host response to infection. Sepsis-associated acute liver injury (SA-ALI) is a frequent and serious complication of sepsis that considerably impacts both short-term and long-term survival outcomes. In intensive care units (ICUs), the mortality rate of patients with SA-ALI remains high, mostly due to the absence of effective early diagnostic markers and suitable therapeutic strategies. Recent studies have demonstrated the importance of non-coding RNAs (ncRNAs) in the development and progression of SA-ALI. This review focuses on the critical roles of ncRNAs, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), in regulating "cytokine storms", oxidative stress, mitochondrial dysfunction, and programmed cell death in SA-ALI, and summarizes the current state and limitations of existing studies on lncRNAs and circRNAs in SA-ALI. By integrating advancements in high-throughput sequencing technologies, this review provides novel insights into the dual potential of ncRNAs as diagnostic biomarkers and therapeutic targets, offers new ideas for SA-ALI diagnosis and treatment research and highlights potential challenges in clinical translation.

Sepsis is a life-threatening disease that affects 30 million people worldwide each year. Despite the rapid advances in medical technology and organ support systems, it is still difficult to reduce the mortality rate. Early and rapid diagnosis is crucial to improve the treatment outcome. The aim of this study was to investigate the prediction efficiency of lymphopenia and other clinical markers, such as white blood cell (WBC), neutrophil count (N#), procalcitonin (PCT), and arterial lactic acid (Lac) in the diagnosis and prognosis assessment for adult patients with nonviral infection-related sepsis. A total of 77 sepsis- and 23 non-sepsis adult patients were enrolled in this study from September 2016 to September 2018. Daily lymphocyte count (Lym) of the patients was calculated until discharge or death. The diagnostic performance of the Lym and other biomarkers were compared using the area under the receiver operating characteristic curve (ROC) value. The level of Lym was decreased significantly in the sepsis group. Lym had a high diagnostic performance for sepsis, with an area under the curve (AUC) value of 0.971 (95% CI = 0.916–0.994). The diagnostic efficacy of Lym was more significant than WBC, N#, and PCT (P < .001). The results showed that the 28-day mortality rate of patients with continuous Lym <0.76 × 10⁹/L was 39.66%, which significantly higher than patients without persistent lymphocytopenia. Lym is a promising, low cost, fast, and easily available biomarker for the diagnosis of sepsis. When nonviral infection is suspected and lymphocytopenia level is lower than the optimal cut-off (0.76 × 10⁹/L) value, high vigilance is required for sepsis. The persistence with the lymphocytopenia cut-off value (3 days indicates a higher 28-day mortality rate.

Introduction: Adipose-derived mesenchymal stem cells (ADSCs) are promising candidates for mesenchymal stem cell (MSC) therapy due to their ease of isolation from the stromal vascular fraction (SVF) of adipose tissue. However, traditional isolation methods often result in mouse ADSCs with low purity and significant heterogeneity contributing to inconsistencies in results from preclinical and clinical studies. This is partly attributed to the lack of consensus on their surface markers.Methods: This study compared three purification methods for isolating mouse ADSCs based on Sca-1 positivity—direct adherence (ADSC-A), magnetic cell sorting followed by adherence (ADSC-M), and adherence to the third generation followed by magnetic cell sorting (ADSC-AM). Third-generation ADSCs were evaluated for proliferative activity, differentiation potential, and functional enrichment using proliferation assays, trilineage differentiation assays, and RNA sequencing. Flow cytometry was employed to assess Sca-1 positivity and the expression of positive (CD44, CD90, CD29) and negative markers (CD31, CD45) in the fourth-generation ADSCs.Results: Among the three methods, ADSC-AM exhibited superior properties, including uniform morphology, enhanced proliferation, and over 95% expression of Sca-1 and CD29. While all methods supported trilineage differentiation, ADSC-AM demonstrated enhanced adipogenesis. Furthermore, RNA sequencing and pathway enrichment analysis revealed that ADSC-AM possessed unique potential in angiogenesis and immune regulation.Discussion: These findings suggest that the ADSC-AM method offers a simple and reproducible approach for obtaining high-purity mouse ADSCs with better functional properties and provide a fundamental reference for understanding mouse ADSCs surface marker profiles.

Sepsis is a multisystem disease characterized by dysregulation of the host immune response to infection. Immune response kinetics play a crucial role in the pathogenesis and progression of sepsis. Macrophages, which are known for their heterogeneity and plasticity, actively participate in the immune response during sepsis. These cells are influenced by the ever-changing immune microenvironment and exhibit two-sided immune regulation. Recently, the immunomodulatory function of mesenchymal stem cells (MSCs) in sepsis has garnered significant attention. The immune microenvironment can profoundly impact MSCs, prompting them to exhibit dual immunomodulatory functions akin to a double-edged sword. This discovery holds great importance for understanding sepsis progression and devising effective treatment strategies. Importantly, there is a close interrelationship between macrophages and MSCs, characterized by the fact that during sepsis, these two cell types interact and cooperate to regulate inflammatory processes. This review summarizes the plasticity of macrophages and MSCs within the immune microenvironment during sepsis, as well as the intricate crosstalk between them. This remains an important concern for the future use of these cells for immunomodulatory treatments in the clinic.

Sepsis is a leading cause of hospital mortality, and its significant heterogeneity complicates prognosis and stratification. To address this challenge, we developed an explainable artificial intelligence prognostic model (SepsisFormer, a transformer-based neural network) and an automated risk-stratification tool (SMART) for sepsis. In a multi-center retrospective study of 12,408 sepsis patients, SepsisFormer achieved high predictive accuracy (AUC: 0.9301, sensitivity: 0.9346, and specificity: 0.8312). SMART (AUC: 0.7360) surpassed most established scoring systems. Seven coagulation-inflammatory routine laboratory measurements and patient age were identified to classify patients’ four risk levels (mild, moderate, severe, dangerous) and two subphenotypes (CIS1 and CIS2), each with distinct clinical characteristics and mortality rates. Notably, patients with moderate/severe levels or CIS2 derive more significant benefits from anticoagulant treatment. Our work, therefore, offers a set of simple, real-time executable tools for sepsis heterogeneity, demonstrating the potential to enhance sepsis clinical practice globally, particularly in resource-constrained healthcare settings.

Currently, there is a lack of sepsis screening tools that can be widely used worldwide. Pulmonary sepsis can be of sufficient concern to physicians due to their noticeable symptoms, which usually rely less on screening tools. To investigate the efficiency of the international normalized ratio (INR) for the early rapid recognition of adult nonpulmonary infectious sepsis. This is a prospective observational study. A total of 108 sepsis patients and 106 nonsepsis patients were enrolled according to relevant inclusion and exclusion criteria. Commonly used clinical indicators, such as white blood cell, neutrophil count, lymphocyte count, neutrophil-lymphocyte count ratio (NLCR), platelets (PLT), prothrombin time, INR, activated partial thromboplastin time, and quick Sequential “Sepsis-related” Organ Failure Assessment (qSOFA) scores were recorded within 24 h after admission. The diagnostic performances of these clinical indicators were analyzed and compared through multivariate logistic regression analysis, Spearman correlation, and receiver operating characteristic curve analysis. The INR value of the sepsis group was significantly higher than that of the nonsepsis group. INR has superior diagnostic efficacy for sepsis, with an area under the curve value of 0.918, when those preexisting diseases which significantly affect coagulation function were excluded. The diagnostic efficacy of the INR was more significant than that of NLCR, PLT, and qSOFA (P < 0.05). Moreover, INR levels of 1.17, 1.20, and 1.22 could be used to categorize the relative risk of nonpulmonary infections sepsis into three categories: low, medium and high risk, respectively. The INR is a promising and easily available biomarker for diagnosis, and it can be used as one of the indicators for early screening of adult nonpulmonary infectious sepsis. When its value is higher than the optimal cutoff value (1.22), high vigilance is required for adult nonpulmonary infectious sepsis.