Sepsis‑induced cardiac dysfunction is one of the most common types of organ dysfunction in sepsis; its pathogenesis is highly complex and not yet fully understood. Cardiomyocytes serve a key role in the pathophysiology of cardiac function; due to the limited ability of cardiomyocytes to regenerate, their loss contributes to decreased cardiac function. The activation of inflammatory signalling pathways affects cardiomyocyte function and modes of cardiomyocyte death in sepsis. Prevention of cardiomyocyte death is an important therapeutic strategy for sepsis‑induced cardiac dysfunction. Thus, understanding the signalling pathways that activate cardiomyocyte death and cross‑regulation between death modes are key to finding therapeutic targets. The present review focused on advances in understanding of sepsis‑induced cardiomyocyte death pathways, including apoptosis, necroptosis, mitochondria‑mediated necrosis, pyroptosis, ferroptosis and autophagy. The present review summarizes the effect of inflammatory activation on cardiomyocyte death mechanisms, the diversity of regulatory mechanisms and cross‑regulation between death modes and the effect on cardiac function in sepsis to provide a theoretical basis for treatment of sepsis‑induced cardiac dysfunction.

There is a lack of large-scale epidemiological data on the clinical practice of enteral nutrition (EN) feeding in China. This study aimed to provide such data on Chinese hospitals and to investigate factors associated with EN delivery. This cross-sectional study was launched in 118 intensive care units (ICUs) of 116 mainland hospitals and conducted on April 26, 2017. At 00:00 on April 26, all patients in these ICUs were included. Demographic and clinical variables of patients on April 25 were obtained. The dates of hospitalization, ICU admission and nutrition initiation were reviewed. The outcome status 28 days after the day of investigation was obtained. A total of 1953 patients were included for analysis, including 1483 survivors and 312 nonsurvivors. The median study day was day 7 (IQR 2–19 days) after ICU entry. The proportions of subjects starting EN within 24, 48 and 72 h after ICU entry was 24.8% (84/352), 32.7% (150/459) and 40.0% (200/541), respectively. The proportion of subjects receiving > 80% estimated energy target within 24, 48, 72 h and 7 days after ICU entry was 10.5% (37/352), 10.9% (50/459), 11.8% (64/541) and 17.8% (162/910), respectively. Using acute gastrointestinal injury (AGI) 1 as the reference in a Cox model, patients with AGI 2–3 were associated with reduced likelihood of EN initiation (HR 0.46, 95% CI 0.353–0.599; p < 0.001). AGI 4 was significantly associated with lower hazard of EN administration (HR 0.056; 95% CI 0.008–0.398; p = 0.004). In a linear regression model, greater Sequential Organ Failure Assessment scores (coefficient – 0.002, 95% CI – 0.008 to − 0.001; p = 0.024) and male gender (coefficient – 0.144, 95% CI – 0.203 to − 0.085; p < 0.001) were found to be associated with lower EN proportion. As compared with AGI 1, AGI 2–3 was associated with lower EN proportion (coefficient – 0.206, 95% CI – 0.273 to − 0.139; p < 0.001). The study showed that EN delivery was suboptimal in Chinese ICUs. More attention should be paid to EN use in the early days after ICU admission.

Background: Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are life-threatening disorders with a high risk of mortality. Astaxanthin (AST) is a supernatural antioxidant that has been extensively studied due to its role in immunomodulation, oxidative stress, and lipid peroxidation. However, the association between ferroptosis and AST is not well understood. The purpose of this study is to explore the regulatory role of AST on ferroptosis in lipopolysaccharide (LPS)-induced ALI. Methods: We established an MLE-12 cell injury model and a mouse ALI model by treating with LPS. The levels of IL-6, TNF-α, and IL-1β in the mouse serum were measured using an enzyme-linked immunosorbent assay. Moreover, immunohistochemical, immunofluorescence, western blot, and quantitative real-time polymerase chain reaction analyses were conducted to examine the effects of AST and ferrostatin-1. Results: We discovered that AST pretreatment greatly alleviated LPS-induced lung injury and inhibited ferroptosis, which was demonstrated by a decrease in the accumulation of malondialdehyde and Fe²⁺ and an increase in the levels of glutathione and glutathione peroxidase 4 in the lung tissues of ALI mice and MLE-12 cells. Additionally, we found that AST also evidently suppressed ferritinophagy by upregulation of ferritin and downregulation of nuclear receptor co-activator 4 (NCOA4) in MLE-12 cells. Conclusions: AST pretreatment could lead to a relief of LPS-induced ALI, perhaps via suppressing ferroptosis, and could also reduce unstable iron accumulation by inhibiting NCOA4-mediated ferritin phagocytosis from mitigating lipid peroxidation and ferroptosis in lung epithelial cells.

Background: Urosepsis is a subset of sepsis with a high mortality rate. Currently, the ranking of urosepsis in sepsis etiology is on the rise. Our goal is to use machine learning (ML) methods to construct and validate an interpretable prognosis prediction model for patients with urosepsis.Method: Data were collected from the Intensive Care Medical Information Mart IV database version 3.1 and divided into a training cohort and a validation cohort in a 7:3 ratio. Random Forest (RF), Lasso, Boruta, and eXtreme Gradient Boosting (XGBoost) were used to identify the most influential variables in the model development dataset, and the optimal variables were selected based on achieving the λ_1se value. Model development includes seven machine learning methods and ten cross validations. Accuracy and Decision Curve Analysis (DCA) were used to evaluate the performance of the model in order to select the optimal model. Internal validation of the model included area under the ROC curve (AUC), sensitivity, specificity, Matthews correlation coefficient, and F1-score. Finally, SHapley Additive exPlans (SHAP) was used to explain ML models.Result: A total of 1389 patients with urosepsis were included. Optimal predictors were selected through statistical regularization, yielding a parsimonious set of 9 variables for model development. The performance of XGBoost model is the best and the accuracy of XGBoost was 0.818, with an AUC of 0.904 (95% CI: 0.886-0.923). The internal validation accuracy was 0.797, AUC was 0.869 (95% CI: 0.834-0.904), sensitivity was 0.797, specificity was 0.752, Matthews correlation coefficient was 0.597, and F1-score was 0.791. This indicates that the predictive model performs well in internal validation. SHAP-based summary graphs and diagrams were used to globally explain the XGBoost model.Conclusion: ML demonstrates strong prognostic capability in urosepsis, with the SHAP method providing clinically intuitive explanations of model predictions. This enables clinicians to identify critical prognostic factors and personalize treatments. While our model achieved high predictive accuracy, its retrospective derivation from a single-center database necessitates external validation in diverse populations, which should be addressed through future prospective multicenter studies to establish clinical generalizability.

Background: Activating transcription factor 3 (ATF3) is a nuclear protein that is widely expressed in a variety of cells. It is a stress‐inducible transcription gene and a member of the activating transcription factor/cAMP responsive element‐binding protein (ATF/CREB) family.Methods: The comprehensive literature review was conducted by searching PubMed and Google Scholar. Search terms used were “ATF3”, “ATF3 and (ALI or ARDS)”, “ATF3 and COPD”, “ATF3 and PF”, and “ATF3 and Posttranslational modifications”.Results: Recent studies have shown that ATF3 plays a critical role in many inflammatory pulmonary diseases, including acute lung injury (ALI)/acute respiratory distress syndrome (ARDS), chronic obstructive pulmonary disease (COPD), and pulmonary fibrosis (PF). ATF3 participates in many signaling pathways and complex pathophysiological processes, such as inflammation, immunity, endoplasmic reticulum stress, and cell proliferation. However, the role of ATF3 in current studies is controversial, and there are reports showing that ATF3 plays different roles in different pulmonary diseases.Conclusions: In this review, we first summarized the structure, function, and mechanism of ATF3 in various inflammatory pulmonary diseases. The impact of ATF3 on disease pathogenesis and the clinical implications was particularly focused on, with an overall aim to identify new targets for treating inflammatory pulmonary diseases.