Objective: Compelling evidence has shown that aggressive resuscitation bundles are one of the cornerstones of the successful treatment of patients with sepsis. Recent studies suggest that lactate normalization during resuscitation is a more powerful indicator of resuscitative adequacy; however, early lactate clearance-guided therapy is still not recommended. We performed this meta-analysis to evaluate the effect of early lactate clearance-directed therapy as a potentially more effective resuscitation target. Methods: Studies were identified using PubMed, Embase, and the Cochrane Library without region, publication type, or language restrictions. Randomized trials were included when they compared the efficacy and safety of lactate clearance-guided resuscitation versus central venous oxygen saturation (ScvO₂)-guided therapy. The primary outcome was mortality, and the secondary outcomes were intensive care unit (ICU) stay, length of hospital stay, mechanical ventilation time, Acute Physiology and Chronic Health Evaluation-II (APACHE-II) score, and Sepsis-related Organ Failure Assessment (SOFA) score. Results: Seven randomized controlled trials encompassing 1301 cases were reviewed. Compared with guided ScvO₂ therapy, early lactate clearance-directed therapy was associated with decreased in-hospital mortality (relative ratio [RR] 0.68, 95% confidence interval [CI] 0.56 to 0.82), shorter ICU stay (mean difference [MD] −1.64 days, 95% CI −3.23 to −0.05), shorter mechanical ventilation time (MD −10.22 hours, 95% CI −15.94 to −4.5), and lower APACHE-II scores (MD −4.47, 95% CI −7.25 to −1.69). However, patients undergoing early lactate clearance-guided therapy had similar lengths of hospital stay and similar SOFA scores. Conclusions: As a specific indicator of resuscitation outcome, lactate clearance alone is superior to ScvO₂ alone during a standard resuscitation paradigm. The optimal or desired rate of lactate clearance is still a contentious area. To guide resuscitation and normalize lactate levels in patients, repeating lactate measurements every 2 hours until the patient has met a lactate clearance of 10% or greater may be helpful. Trial registration number: PROSPERO CRD42018100515.

Sepsis-related mortality rates are high among elderly patients, especially those in intensive care units (ICUs). Early prediction of the prognosis of sepsis is critical, as prompt and effective treatment can improve prognosis. Researchers have predicted mortality and the development of sepsis using machine learning algorithms; however, few studies specifically focus on elderly patients with sepsis. This paper proposes a viable model for early prediction of in-hospital mortality among elderly patients diagnosed with sepsis. We extracted patient information from the Medical Information Mart for Intensive Care IV database. We employed several machine learning algorithms to predict the in-hospital mortality of elderly ICU patients with sepsis. The performance of the model was evaluated by using the AUROC and score. Furthermore, the SHAP algorithm was used to explain the model, analyze how the individual features affect the model output, and visualize the Shapley value for a single individual. Our study included 18522 elderly patients, with a mortality of 15.4%. After screening, 59 clinical variables were extracted to develop models. Feature importance analysis showed that age, PO2, RDW, SPO2, WBC, and urine output were significantly related to the in-hospital mortality. According to the results of AUROC (0.871 (95% CI: 0.854–0.888)) and score (0.547 (95% CI: 0.539–0.661)) analyses, the extreme gradient boosting (XGBoost) model outperformed the other models (i.e., LGBM, LR, RF, DT, and KNN). Furthermore, SHAP force analysis illustrated how the constructed model visualized the individualized prediction of death. XGBoost machine learning framework gives good in-hospital mortality prediction of elderly patients with sepsis and can maximize prediction model accuracy. The XGBoost model could be an effective tool to assist doctors in identifying high-risk cases of in-hospital mortality among elderly patients with sepsis. This could be used to create a clinical decision support system in the future.

Ambient fine particulate matter (PM) exposure associates with an increased risk of cardiovascular diseases (CVDs). Major sex differences between males and females exist in epidemiology, pathophysiology, and outcome of CVDs. Endothelial progenitor cells (EPCs) play a vital role in the development and progression of CVDs. PM exposure-induced reduction of EPCs is observed in male, not female, mice with increased reactive oxygen species (ROS) production and oxidative stress. The lung is considered an important source of ROS in mice with PM exposure. The aim of the present study was to investigate the sex differences in pulmonary superoxide dismutase (SOD) expression and ROS production, and to test the effect of SOD mimic Tempol on the populations of EPCs in mice with PM exposure. Both male and female C57BL/6 mice (8–10 weeks) were exposed to intranasal PM or vehicle for 6 weeks. Flow cytometry analysis demonstrated that PM exposure significantly decreased the levels of EPCs (CD34⁺/CD133⁺) in both blood and bone marrow with increased ROS production in males, but not in females. ELISA analysis showed higher levels of serum IL-6 and IL-1βin males than in females. Pulmonary expression of the antioxidant enzyme SOD1 was significantly decreased in males after PM exposure, but not in females. Administration of the SOD mimic Tempol in male mice with PM exposure attenuated the production of ROS and inflammatory cytokines, and preserved EPC levels. These data indicated that PM exposure-induced reduction of EPC population in male mice may be due to decreased expression of pulmonary SOD1 in male mice.

Background Programmed death-1 (PD-1) checkpoint blockade has revolutionized cancer therapy, yet its clinical success is confined to a subset of patients, underscoring the urgent need to understand the molecular underpinnings of programmed cell death ligand 1 (PD-L1) expression to combat immunotherapy resistance. Methods Employing CRISPR/Cas9 screening, we identified key regulators of PD-L1 in non-small cell lung cancer (NSCLC) cells, focusing on the transcription factor CEBPB and its isoform liver-enriched inhibitory protein (LIP). Through chromatin immunoprecipitation (ChIP) and luciferase reporter assays, we explored the interaction between LIP and basic-helix-loop-helix E22 (BHLHE22) in controlling PD-L1 transcription. We also used immunofluorescence and NBD-CI assays to examine how N-terminal acetylation affects LIP’s subcellular localization. The impact of LIP on tumor growth was assessed via subcutaneous tumorigenicity assays, while immunohistochemistry and immunofluorescence were used to analyze LIP-induced alterations in the tumor immune microenvironment. Results Our research indicates that CEBPB, particularly its LIP isoform, significantly suppresses PD-L1 expression in NSCLC cells. This suppression is contingent on LIP’s N-terminal acetylation by the N-terminal acetyltransferase A complex, which facilitates LIP’s nuclear entry and interaction with BHLHE22. This interaction leads to the formation of a co-repressor complex at the PD-L1 promoter, effectively reducing PD-L1 expression and enhancing the tumor immune response. Conclusions Identifying CEBPB, especially the LIP isoform, as a pivotal regulator of PD-L1 expression sheds light on the mechanisms behind PD-1 blockade resistance in NSCLC. Our findings suggest that modulating LIP’s function or its molecular interactions might offer a novel approach to boosting the efficacy of immunotherapies.

Background: Virtual reality (VR) technology has gained much traction related to mental health owing to its interactive features and immersive nature. A systematic bibliometric evaluation is necessary to guide researchers in identifying emerging trends and research priorities in VR technology applications for mental health, highlighting evolving challenges and research needs. Objective: This study aimed to analyze the bibliometric characteristics and scope of evidence on the application of virtual reality in mental health care, synthesizing findings and exploring potential innovations. Methods: We conducted a bibliometric analysis using CiteSpace to examine 1333 articles from the Web of Science Core Collection (from January 1, 1999, to February 14, 2025), retrieved via the search query TS=(“Mental health” AND “Virtual reality”). The study mapped key research trends, including international and institutional collaboration networks, author co-citation networks, and the evolution of keyword co-occurrence to identify influential contributors, thematic clusters, and emerging developments in VR-based mental health research. Results: The analysis revealed three key findings: (1) Exponential publication growth starting in 2020 with over 110 annual publications; (2) Robust collaboration networks featuring 3587 authors with Riva, G. as a central figure and the University of London as the most prominent institutional hub; (3) Virtual reality, exposure therapy, skin conductance, mild cognitive impairment, psychosis, augmented reality, and serious game are the main research clusters. Emergent word analysis of keywords from 2014 to early 2025 yielded 34 words/terms with the strongest citation bursts. Conclusion: This study demonstrates VR’s integration with traditional therapy and its expanding role in treating diverse mental health conditions, from anxiety to schizophrenia. Future research should focus on standardizing treatments and validating their efficacy.

Purpose: To determine the clinical manifestations and results of adult hemophagocytic lymphohistiocytosis (HLH) patients in our emergency department. Methods: We retrospectively evaluated patients with HLH from 1 April 2018 to 31 December 2020. The clinical data of these patients (basic information, symptoms, vital signs, laboratory results, HLH diagnostic criteria, H Score, main treatments, outcomes) were collected. Results: Thirty-three patients (23 males and 10 females; 40.55± 18.78 years) with 34 clinical episodes (one male had two clinical episodes and died during the second episode) were enrolled. Twenty-five patients were placed in a “survivor” group, and nine patients were categorized into a “deceased” group. Fever, splenomegaly, hemoglobin < 90 g/L and platelet count < 100× 10⁹/L most commonly met the diagnostic standard for HLH. The H Score results in the survival group and deceased group was 212.4± 37.18 and 252.1± 40.95, respectively. Viral infection was the most common reason for HLH, followed by immune-system disease and cancer. Laboratory tests showed that deceased-group patients had multiple-organ dysfunction. Multivariate logistic regression showed that the lactate dehydrogenase (lactate dehydrogenase) level (P = 0.039; odds ratio, 0.999) was significantly related to death. Conclusion: In the emergency department, HLH should be considered for critically ill patients with fever, splenomegaly, low hemoglobin and low platelet count. The H Score might be useful to diagnose HLH quickly. In our study, 26.47% of HLH patients died in the emergency department, and patients with a significantly increased lactate dehydrogenase level had a markedly increased risk of death.