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Sepsis is a potentially fatal condition arising from an abnormal immune response to an infection, which can result in organ failure and even death. To explore the mechanism underlying the dysregulated immune response during sepsis and identify potential therapeutic targets, single-cell RNA sequencing (scRNA-seq) and immune repertoire analysis were conducted to depict the cellular landscape of peripheral blood cells in septic mice. We observed significant alterations in the number and proportion of peripheral blood cell populations driven by sepsis. By combining single-cell gene expression profiles and B cell receptor (BCR) repertoire analysis, we discerned that infection inflicted serious damage on the antigen presentation ability of B cells and the diversity of BCR in a short time. In addition, we found that the cecal ligation and puncture procedure in mice inhibited the communication signals of CD4 + and CD8 + T cells and decreased the interactions between B cells and other cells. Our study provides detailed insights into the dynamic changes in the biological characteristics of peripheral blood cells driven by sepsis and provides important advances in our understanding of immune disorders during sepsis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments We gratefully acknowledge the participation of Shanghai OE Biotech Co., Ltd for the support of construction of single cell sequencing Library, and thanks Mr. Zhengshan Chen (Laboratory of Advanced Biotechnology) for the support of data analysis and visualization. This study was supported by grants from the National Natural Science Foundation of China (82170229)., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Sepsis is a severe condition characterized by multiple organ dysfunction resulting from an imbalanced host immune response to infections. miRNAs play a crucial role in regulating various biological processes. However, the precise role of miR-31 in the immunopathology of sepsis remains poorly understood., Methods: The concentration of hsa-miR-31-5p in patients with sepsis (both survivors and non-survivors) and healthy individuals was assayed. Using an experimental sepsis model of caecal ligation and puncture (CLP), the impact of mmu-miR-31-5p on survival, organ injury, and inflammation was evaluated. Additionally, the effect of mmu-miR-31-5p on macrophage polarization through Chi3l1 was investigated. Lastly, the therapeutic effects of miPEP31 on experimental sepsis were examined., Results: The results of miRNA sequencing (miRNA-seq) and quantitative polymerase chain reaction (q-PCR) analyses identified hsa-miR-31-5p as a potential biomarker for patients with sepsis, with non-survivors showing higher levels of hsa-miR-31-5p in peripheral blood mononuclear cells (PBMCs) compared to survivors. Functional studies conducted on peritoneal elucidated macrophages (PEMs) demonstrated that mmu-miR-31-5p inhibits M2 polarization in macrophages by downregulating Chi3l1. The utilization of miPEP31 as a therapeutic intervention had a substantial impact on reducing mortality rates, mitigating organ damage, inducing macrophage polarization towards the M2 phenotype, and suppressing the inflammatory response in murine models of severe sepsis., Conclusions: The suppression of miR-31 in sepsis plays a protective role in the host defense response by upregulating Chi3l1, highlighting the potential therapeutic efficacy of miPEP31 in sepsis treatment., Competing Interests: Declarations Ethics approval and consent to participate All procedures performed in studies involving human participants were approved by the Ethics Committee of Shanghai General Hospital under ethical approval number 2022SQ098. All animal experiments were conducted under the rules approved by the Experimental Animal Management Ethics Committee of Shanghai Jiao Tong University School of Medicine (ethical approval number: 2022AWS0160). Consent for publication All authors listed have provided their consent for submission, and all data utilized in this study have been obtained with the consent of the individuals responsible for generating the data. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Vitamin D deficiency has been proven to be associated with dyslipidemia. Additionally, the synthesis of vitamin D depends on cytochrome P450 2R1 (CYP2R1). However, the relationship between CYP2R1 polymorphisms and lipid metabolism has shown inconsistent results. A case-control study was conducted in a Han Chinese population, including 92 septic patients and 92 polytrauma patients. Based on serum lipid levels, 28 septic patients were further divided into a hyperlipidemia group, while 64 were placed in the control group; similarly, 34 polytrauma patients were categorized into a hyperlipidemia group and 58 into the control group. Genotyping of CYP2R1-rs10741657 was performed and serum lipid levels were measured. The Genotype-Tissue Expression project was used to assess expression quantitative trait loci for CYP2R1 mRNA expression and rs10741657. The genetic analyses revealed that the G-allele of CYP2R1-rs10741657 was significantly associated with an increased risk of hyperlipidemia in both sepsis (OR = 2.333, 95% CI: 1.227-4.436, P = .010) and polytrauma groups (OR = 4.000, 95% CI: 2.048-7.811, P < .001). Further analysis indicated that the rs10741657 mutation was mainly linked to higher serum high-density lipoprotein cholesterol levels in controls (P < .05). In functional analysis of rs10741657, the mutation was found to be associated with high CYP2R1 mRNA expression in whole blood from expression quantitative trait loci data (P = 3.53 × 10-9). In conclusion, the G-allele of CYP2R1-rs10741657 could elevate high-density lipoprotein cholesterol levels and protect against sepsis development., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Sepsis triggers severe inflammatory responses leading to organ dysfunction and demands early diagnostic and therapeutic intervention. This study identifies differentially expressed genes (DEGs) in sepsis patients using the Gene Expression Omnibus database to find potential diagnostic and therapeutic markers. We analyzed the dataset GSE123731 via GEO2R to detect DEGs, constructed protein-protein interaction networks, and performed transcription factor analyses using Cytoscape. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted using R and FunRich software. Key genes were validated by Quantitative Reverse Transcription Polymerase Chain and co-immunoprecipitation assays in granulocytes from sepsis patients. We identified 59 DEGs significantly involved in neutrophil degranulation and immune system activation. Cytokine signaling pathways were highlighted in Kyoto Encyclopedia of Genes and Genomes analysis. Co-immunoprecipitation assays confirmed interactions involving matrix metallopeptidase 8, matrix metallopeptidase 9, and arginase 1, supporting their roles as biomarkers. The identified DEGs and validated interactions reveal crucial molecular mechanisms in sepsis, offering new avenues for diagnostic and therapeutic strategies, potentially enhancing patient outcomes., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Septic Cardiomyopathy (SCM) is a syndrome of acute cardiac dysfunction in septic patients, unrelated to cardiac ischemia. Multiomics studies including transcriptomics and proteomics have provided new insights into the mechanisms of SCM. In here, a rat model of SCM was established by intraperitoneal injection of lipopolysaccharide (LPS). Biomarkers of SCM were characterized via a multi-omics analysis. The differentially expressed (DE) mRNAs predominantly appeared in pathways linked to the immune response, inflammatory response, and the complement and coagulation cascades, while DE proteins were mainly enriched in pathways associated with the complement and coagulation cascades. On this basis, the integrated analysis was performed between transcriptome and proteome. The potential biomarkers were further verified by RT-qPCR and WB. The current proteotranscriptomic research has furnished a valuable dataset and fresh perspectives that will enhance our comprehension of the development of SCM. This, in turn, is expected to expedite the formulation of novel approaches for the prevention and management of SCM in patients., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Cai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Previous studies have demonstrated the roles of both microglia homeostasis and RNA editing in sepsis-associated encephalopathy (SAE), yet their relationship remains to be elucidated. In this study, we analyzed bulk and single-cell RNA-seq (scRNA) datasets containing 107 brain tissue and microglia samples from mice with microglial depletion and repopulation to explore canonical RNA editing associated with microglia homeostasis and evaluate its role in SAE. Analysis of mouse brain RNA-Seq revealed hallmarks of microglial repopulation, including peak expressions of Apobec1 and Apobec3 at Day 5 of repopulation and dramatically altered B2m RNA editing. Significant time-dependent changes in brain RNA editing during microglial depletion and repopulation were primarily observed in synapse-related genes, such as Tbc1d24 and Slc1a2. ScRNA-Seq revealed heterogeneous RNA editing among microglia subpopulations and their distinct changes associated with microglia homeostasis. Moreover, repopulated microglia from lipopolysaccharide (LPS)-induced sepsis mice exhibited intensified up-regulation of Apobec1 and Apobec3, with distinct RNA editing responses to LPS, mainly involved in immune-related pathways. The hippocampus from sepsis mice induced by peritoneal contamination and infection showed upregulated Apobec1 and Apobec3 expression, and altered RNA editing in immune-related genes, such as B2m and Mier1, and nervous-related lncRNA Meg3 and Snhg11, both of which were repressed by microglial depletion. Furthermore, the expression of complement-related genes, such as C4b and Cd47, was substantially correlated with RNA editing activity in microglia homeostasis and SAE. Our study demonstrates canonical RNA editing associated with microglia homeostasis and provides new insights into its potential role in SAE., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 International Brain Research Organization (IBRO). Published by Elsevier Inc. All rights reserved.)

Background: Sepsis survivors exhibit immune dysregulation that contributes to poor long-term outcomes. Phenotypic and functional alterations within the myeloid compartment are believed to be a contributing factor. Here we dissect the cellular and transcriptional heterogeneity of splenic CD11b + Ly6C high myeloid cells that are expanded in mice that survive the cecal ligation and puncture (CLP) murine model of polymicrobial sepsis to better understand the basis of immune dysregulation in sepsis survivors., Methods: Sham or CLP surgeries were performed on C57BL/6J and BALB/c mice. Four weeks later splenic CD11b + Ly6C high cells from both groups were isolated for phenotypic (flow cytometry) and functional (phagocytosis and glycolysis) characterization and RNA was obtained for single-cell RNA-seq (scRNA-seq) and subsequent analysis., Results: CD11b + Ly6C high cells from sham and CLP surviving mice exhibit phenotypic and functional differences that relate to immune function, some of which are observed in both C57BL/6J and BALB/c strains and others that are not. To dissect disease-specific and strain-specific distinctions within the myeloid compartment, scRNA-seq analysis was performed on CD11b + Ly6C high cells from C57BL/6J and BALB/c sham and CLP mice. Uniform Manifold Approximation and Projection from both strains identified 13 distinct clusters of sorted CD11b + Ly6C high cells demonstrating significant transcriptional heterogeneity and expressing gene signatures corresponding to classical-monocytes, non-classical monocytes, M1- or M2-like macrophages, dendritic-like cells, monocyte-derived dendritic-like cells, and proliferating monocytic myeloid-derived suppressor cells (M-MDSCs). Frequency plots showed that the percentages of proliferating M-MDSCs (clusters 8, 11 and 12) were increased in CLP mice compared to sham mice in both strains. Pathway and UCell score analysis in CLP mice revealed that cell cycle and glycolytic pathways were upregulated in proliferating M-MDSCs in both strains. Notably, granule protease genes were upregulated in M-MDSCs from CLP mice. ScRNA-seq analyses also showed that phagocytic pathways were upregulated in multiple clusters including the classical monocyte cluster, confirming the increased phagocytic capacity in CD11b + Ly6C high cells from CLP mice observed in ex vivo functional assays in C57BL/6J mice., Conclusion: The splenic CD11b + Ly6C high myeloid populations expanded in survivors of CLP sepsis correspond to proliferating cells that have an increased metabolic demand and gene signatures consistent with M-MDSCs, a population known to have immunosuppressive capacity., (© 2024. The Author(s).)

Septic cardiomyopathy (SCM), a complication initiated by sepsis, presents a significant clinical challenge, leading to increased mortality rates. However, the mechanisms of SCM have not been fully uncovered. Our study involved analyzing RNA sequencing (RNA-seq) data from rat heart tissue, along with utilizing molecular docking and molecular dynamics (MD) simulations, to discover key targets and potential pharmacological actions of the calcitonin gene-related peptide (CGRP) against SCM. A lipopolysaccharide-induced SCM model was established in rats (LPS 10 mg/kg, intraperitoneal (i.p.)). Thereafter, the myocardial tissues from the three groups of rats (Ctrl group, LPS group, and CGRP group) (n = 5) were extracted and underwent RNA-seq, followed by bioinformatics analyses. The qPCR-validated hub targets potentially interacting with CGRP were identified. Following this, homology modeling was utilized to obtain the 3D structure of hub targets, and molecular docking was conducted to evaluate the interaction between CGRP and hub targets. MD simulations (300 ns) were performed to confirm the findings further. Our findings demonstrated that CGRP significantly lowered mortality in SCM rats. 633 DEGs were affected by LPS, contrasted with the Ctrl group. 96 DEGs were affected by CGRP compared to the LPS group. In total, ten fully annotated CGRP-triggered hub genes were obtained. The molecular docking and MD simulations indicate that the relationship between CGRP and eight hub genes is extremely strong. This research offers a thorough examination of the possible objectives and fundamental molecular processes of CGRP in combating SCM, laying the groundwork for investigating the potential protective mechanisms of CGRP against SCM., (© 2024. The Author(s).)

Background: Sepsis-induced myocardial injury (SIMI) is a severe complication of sepsis, contributing significantly to mortality. Mitochondrial dysfunction and dysregulated autophagy are implicated in SIMI pathogenesis. Long non-coding RNA MALAT1 has been associated with various diseases, including sepsis, but its role in SIMI remains unclear., Objective: This study aimed to investigate the role of lncRNA MALAT1 in SIMI, specifically in the regulation of mitochondrial autophagy., Methods: A sepsis-induced cardiomyopathy model was established in mice, and the cardiac tissues were analyzed. The expression of lncRNA MALAT1 was modulated and its effects on mitochondrial autophagy, myocardial injury, inflammation, and apoptosis were assessed. Furthermore, the interaction between MALAT1 and miR-146a was explored, as well as the involvement of the TLR4/NF-kB/MAPK signaling pathway., Results: Activation of mitochondrial autophagy by urolithin A (UA) alleviated SIMI, inflammation, and cardiac dysfunction. Downregulation of MALAT1 enhanced mitochondrial autophagy, stabilized the mitochondrial membrane potential, and inhibited mitochondrial reactive oxygen species (ROS) production, leading to improved cell viability and reduced myocardial injury. Furthermore, MALAT1 interacted with miR-146a, and their modulation influenced mitochondrial autophagy, myocardial injury, and inflammation. The TLR4/NF-kB/MAPK signaling pathway was implicated in these processes., Conclusion: Our findings suggest that lncRNA MALAT1 plays a crucial role in SIMI by modulating miR-146a-mediated mitochondrial autophagy and the TLR4/NF-kB/MAPK signaling pathway. These results provide new insights into the pathogenesis of SIMI and potential therapeutic targets., (© 2024. The Author(s).)

As global aging accelerates, the super-elderly population is at higher risk of infectious diseases, especially sepsis, a condition that may be associated with declining immune system function and abnormal inflammatory responses. The aim of this study was to investigate the role of CARD16 protein in sepsis susceptibility in the elderly population and its potential mechanism, and to reveal the expression characteristics of CARD16-related genes through blood transcriptomic analysis. Transcriptome sequencing was conducted on peripheral blood samples obtained from patients suffering from senile sepsis, along with samples from a healthy elderly control group. To examine the differences in gene expression, bioinformatics techniques were employed to compare the expression levels of CARD16-related genes between the two groups. Additionally, a comprehensive analysis was performed on the downstream inflammatory pathways and cytokines that are regulated by CARD16.The findings from the transcriptome analysis indicated that the expression of CARD16 was markedly upregulated in the cohort of patients experiencing hypersenile sepsis. This upregulation was associated with an increase in a variety of pro-inflammatory factors. Further network analysis suggested that CARD16 may potentiate the inflammatory response by modulating the NF-κB signaling pathway, which could consequently heighten the patients' vulnerability to sepsis.In comparison to the healthy elderly control group, the levels of anti-inflammatory genes in the super-elderly cohort were found to be significantly diminished. This observation points to a notable imbalance in immune regulation, further emphasizing the altered immune response in individuals with senile sepsis., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Septic acute kidney injury (AKI) is a fatal disease in the intensive care unit, with ferroptosis playing a crucial role in its pathogenesis. Long non-coding RNA (LncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) has been implicated in septic-induced AKI inflammation and apoptosis. However, its regulatory role in ferroptosis and underlying mechanisms remain unclear. In vivo and in vitro models of septic AKI were established using cecal ligation and puncture (CLP) and lipopolysaccharide (LPS) challenge, respectively. Serum levels of creatinine (Cr), blood urea nitrogen (BUN), kidney injury molecule-1 (Kim-1), neutrophil gelatinase-associated lipocalin (NGAL), and inflammatory cytokine in kidney tissues were determined by ELISA kits. Histopathological alterations and apoptosis were evaluated by HE staining and TUNEL. Ferroptosis was accessed by measuring MDA, GSH, Fe 2+ , total and lipid ROS levels, and mitochondrial ultrastructure changes. Target molecular levels were determined using RT-qPCR, Western blotting, and immunofluorescence. Interactions among MALAT1, acyl-CoA synthetase family member 2 (ACSF2) and FUS RNA binding protein (FUS) were validated by RIP and RNA-pull down. MALAT1 level was significantly elevated in both in vivo and in vitro septic AKI models, of which knockdown impeded ferroptosis to alleviate septic AKI. Mechanistically, high MALAT1 expression increased ACSF2 mRNA stability via interaction with FUS. Rescue experiments showed that ACSF2 overexpression partially reversed the ferroptosis inhibition mediated by MALAT1 silencing. MALAT1 induces ferroptosis and exacerbates septic AKI by stabilizing ACSF2 mRNA with the assistance of FUS. These findings provide theoretical evidence for MALAT1 as a potential therapeutic target for septic AKI., (© 2024 The Author(s). The Kaohsiung Journal of Medical Sciences published by John Wiley & Sons Australia, Ltd on behalf of Kaohsiung Medical University.)

Sepsis remains a critical challenge in the field of medicine, claiming countless lives each year. Despite significant advances in medical science, the molecular mechanisms underlying sepsis pathogenesis remain elusive. Understanding molecular sequelae is gaining deeper insights into the roles played by various damage-associated molecular patterns (DAMPs) and pathogen-associated molecular patterns (PAMPs) in disease pathogenesis. Among the known DAMPs, circulating cell-free mitochondrial DNA (mtDNA) garners increasing attention as a key player in the immune response during sepsis and other diseases. Mounting evidence highlights numerous connections between circulating cell-free mtDNA and inflammation, a pivotal state of sepsis, characterized by heightened inflammatory activity. In this review, we aim to provide an overview of the molecular basis of sepsis, particularly emphasizing the role of circulating cell-free mtDNA as a DAMP. We discuss the mechanisms of mtDNA release, its interaction with pattern recognition receptors (PRRs), and the subsequent immunological responses that contribute to sepsis progression. Furthermore, we discuss the forms of cell-free mtDNA; detection techniques of circulating cell-free mtDNA in various biological fluids; and the diagnostic, prognostic, and therapeutic implications offering insights into the potential for innovative interventions in sepsis management., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The study was supported by the Intramural Research Grant from the Central Laboratory for Stem Cell Research and Translational Medicine, Deccan College of Medical Sciences, Hyderabad 500 058, Telangana, India., (Published by Elsevier B.V.)

Sepsis-induced acute lung injury (SI-ALI) leads to significant deaths in critically ill patients worldwide. This study explores the mechanism of EZH2 regulating ferroptosis of alveolar epithelial cells (AECs) in SI-ALI. In vitro cell model and in vivo mouse lung injury model of sepsis were established. EZH2 expression in lung tissues was intervened by sh-EZH2, followed by H&E staining observation of lung tissue pathological changes. EZH2, H3K27me3, USP10, GPX4, and ACSL4 expressions were determined by qRT-PCR or Western blot. ROS, GSH, and iron ion levels were detected using fluorescent labeling and reagent kits, respectively. ChIP analyzed the enrichment of EZH2 and H3K27me3 on USP10 promoter. The binding between USP10 and GPX4, and the ubiquitination level of GPX4 were detected using Co-IP. EZH2 was highly expressed in lung tissues of SI-ALI mice. EZH2 silencing alleviated ALI and ferroptosis of AECs; EZH2 increased the H3K27me3 level on USP10 promoter through histone methylation. USP10 stabilized GPX4 protein expression through ubiquitination; inhibition of USP10 partially reversed the inhibitory effect of EZH2 silencing on ferroptosis of AECs. In conclusion, EZH2 depresses USP10 expression by promoting histone H3K27me3 modification on USP10 promoter, thereby enhancing ubiquitination degradation of GPX4 and ultimately facilitating ferroptosis of AECs in sepsis., (© 2024 Wiley Periodicals LLC.)

This study explored the mechanism by which the m6A demethylase ALKBH5 mediates epithelial-mesenchymal transition (EMT) in sepsis-associated acute kidney injury (SA-AKI) and AKI-chronic kidney disease (CKD) transition. HK-2 cells were stimulated with lipopolysaccharide (LPS) to establish an in vitro model of SA-AKI. ALKBH5 expression was reduced through the transfection of si-ALKBH5. Cell viability, apoptosis, and migration were detected by CCK-8 assay, TUNEL staining, and Transwell. The levels of TNF-α, IL-1β, and IL-6 were measured by enzyme-linked immunosorbent assay. Quantitative real-time polymerase chain reaction or Western blotting was performed to determine the expressions of ALKBH5, miR-205-5p, DDX5, E-cadherin, and α-SMA. The m6A level was quantitatively analyzed. The expression of pri-miR-205 bound to DGCR8 and m6A-modified pri-miR-205 after intervention with ALKBH5 expression was detected by RNA immunoprecipitation. A dual-luciferase assay confirmed the binding between miR-205-5p and DDX5. ALKBH5 was highly expressed in LPS-induced HK-2 cells. Inhibition of ALKBH5 increased cell viability, repressed apoptosis, and reduced EMT. Inhibition of ALKBH5 increased the m6A modification level, thereby promoting DGCR8 binding to pri-miR-205 to increase miR-205-5p expression and eventually targeting DDX5 expression. Low expression of miR-205-5p or overexpression of DDX5 partially abolished the inhibitory effect of ALKBH5 silencing on EMT. In conclusion, ALKBH5 represses miR-205-5p expression by removing m6A modification to upregulate DDX5 expression, thereby promoting EMT and AKI-CKD transition after SA-AKI., (© 2024 The Author(s). The Kaohsiung Journal of Medical Sciences published by John Wiley & Sons Australia, Ltd on behalf of Kaohsiung Medical University.)

Abstract: Background: Sepsis-associated brain injury is associated with deterioration of mental status, persistent cognitive impairment, and morbidity. The SUR1/TRPM4 channel is a nonselective cation channel that is transcriptionally upregulated in the central nervous system with injury, allowing sodium influx, depolarization, cellular swelling, and secondary injury. We hypothesized that genetic variation in ABCC8 (SUR1 gene) and TRPM4 would associate with central nervous system dysfunction in severe pediatric sepsis. Methods: 326 children with severe sepsis underwent whole exome sequencing in an observational cohort. We compared children with and without central nervous system dysfunction (Glasgow Coma Scale <12) to assess for associations with clinical characteristics and pooled rare variants in ABCC8 and TRPM4. Sites of variation were mapped onto protein structure and assessed for phenotypic impact. Results: Pooled rare variants in either ABCC8 or TRPM4 associated with decreased odds of central nervous system dysfunction in severe pediatric sepsis (OR 0.14, 95% CI 0.003-0.87), P = 0.025). This association persisted following adjustment for race, organ failure, viral infection, and continuous renal replacement therapy (aOR 0.11, 95% CI 0.01-0.59, P = 0.038). Structural mapping showed that rare variants concentrated in the nucleotide-binding domains of ABCC8 and N-terminal melastatin homology region of TRPM4 . Conclusion : This study suggests a role for the ABCC8/TRPM4 channel in central nervous system dysfunction in severe pediatric sepsis. Although exploratory, the lack of therapies to prevent or mitigate central nervous system dysfunction in pediatric sepsis warrants further studies to clarify the mechanism and confirm the potential protective effect of these rare ABCC8/TRPM4 variants., Competing Interests: The remaining authors report no conflicts of interest., (Copyright © 2024 by the Shock Society.)

Several investigations have been carried out to explore the genetic association of TLR4 codon variants, specifically Asp299Gly and Thr399Ile, and susceptibility to sepsis, but the results have been contradictory. The present study aimed to conduct a meta-analysis to draw a definitive conclusion regarding the role of TLR4 genetic variants (Asp299Gly and Thr399Ile) in sepsis. A thorough literature search was conducted using the PubMed, Scopus, and Science Direct databases. The inclusion and exclusion criteria were established to ensure the accuracy of the data. The Comprehensive Meta-Analysis Software v4 was utilized to perform the meta-analysis and related analyses. A total of 13 studies were analyzed, including 2328 sepsis cases and 2495 healthy controls for the TLR4 Asp299Gly variant. Eight studies provided genotype data for the rs4986791 polymorphism. The Asp299Gly variant showed a marginal protective effect in the allele (p = 0.08, odds ratio = 0.71) and dominant (p = 0.09, odds ratio = 0.71) genetic models, although it was not statistically significant. The trial sequential analysis indicated that further case-control studies are necessary to draw definitive conclusions about the TLR4 polymorphisms in sepsis. The TLR4 Asp299Gly variant may have a protective effect against sepsis. However, additional research with larger sample sizes across diverse populations is required to validate this finding., (© 2024 Scandinavian Societies for Pathology, Medical Microbiology and Immunology.)

During a sepsis infection, the lung is extremely susceptible to damage. A condition known as acute respiratory distress syndrome (ARDS) may develop in extreme circumstances. The primary objective of this research is to identify important genes that are related with both sepsis and lung injury. These genes have the potential to act as novel biomarkers in the investigation of sepsis-induced lung injury prevention strategies. It was possible to download from GEO data both the sepsis-related dataset (GSE64457) and the lung injury-related dataset (GSE40839). In the GSE64457 dataset, using the "limma" package in R revealed 429 differentially expressed genes (DEGs) with logFC values more than or equal to -1 and p values <0.05. There were 266 genes that were up-regulated and 163 genes that were down-regulated. Through the use of Gene Ontology (GO), it was discovered that the majority of the DEGs were associated with the inflammatory response (BP terms), a particular granule lumen (CC terms), and protein binding (MF terms). By doing a pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG), researchers were able to identify DEGs that were mostly associated with the NOD-like receptor signalling pathway, the TNF signalling pathway, and Epstein-Barr virus infection. Within the GSE40839 dataset, Weighted Gene Co-Expression Network Analysis (WGCNA) yielded a total of 7 modules, from which it was possible to screen out 2 critical modules and 693 key genes. The important genes and DEGs were both subjected to a Venn analysis. Finally, 14 genes that overlapped (ARL4A, LAIR1, MTHFD2, TSPAN13, DUSP6, PECR, CBS, TES, ASNS, SYNE1, FGF13, LCN2, KLF10, BCAT1) were closely associated to the incidence and development of sepsis-induced lung injury. This indicates that these genes are the essential genes to avoid the occurrence of sepsis-induced lung injury. This study provides novel strategies for preventing lung harm brought on by sepsis., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Abstract: Background: Recent observational studies have suggested that osteoporosis may be a risk factor for sepsis. To mitigate confounding factors and establish the causal relationship between sepsis and osteoporosis, we conducted a two-sample Mendelian randomization analysis using publicly available summary statistics. Methods: Utilizing summary data from FinnGen Biobank, we employed a two-sample Mendelian randomization (MR) analysis to predict the causal relationship between osteoporosis and sepsis. The MR analysis primarily utilized the inverse variance weighted (IVW) method, supplemented by MR-Egger, weighted median, weighted mode, and simple mode analyses, with Bayesian weighted MR (BWMR) analysis employed for result validation. Sensitivity analyses included MR-PRESSO, "leave-one-out" analysis, MR-Egger regression, and Cochran Q test. Results: In the European population, an increase of one standard deviation in osteoporosis was associated with an 11% increased risk of sepsis, with an odds ratio (OR) of 1.11 (95% CI, 1.06-1.16; P = 3.75E-06). BWMR yielded an OR of 1.11 (95% CI, 1.06-1.67; P = 1.21E-05), suggesting osteoporosis as a risk factor for sepsis. Conversely, an increase of one standard deviation in sepsis was associated with a 26% increased risk of osteoporosis, with an OR of 1.26 (95% CI, 1.11-1.16; P = 0.45E-03). BWMR yielded an OR of 1.26 (95% CI, 1.09-1.45; P = 1.45E-03), supporting sepsis as a risk factor for osteoporosis. Conclusion: There is an association between osteoporosis and sepsis, with osteoporosis serving as a risk factor for the development of sepsis, while sepsis may also promote the progression of osteoporosis., Competing Interests: Conflicts of interest: The authors declare no conflicts of interest in this work., (Copyright © 2024 by the Shock Society.)

Sepsis is a systemic inflammatory reaction caused by infection, and severe sepsis can develop into septic shock, eventually leading to multiorgan dysfunction and even death. In recent years, studies have shown that mitochondrial damage is closely related to the occurrence and development of sepsis. Recent years have seen a surge in concern over mitochondrial DNA (mtDNA), as anomalies in this material can lead to cellular dysfunction, disruption of aerobic respiration, and even death of the cell. In this review, we discuss the latest findings on the mechanisms of mitochondrial damage and the molecular mechanisms controlling mitochondrial mtDNA release. We also explored the connection between mtDNA misplacement and inflammatory activation. Additionally, we propose potential therapeutic targets of mtDNA for sepsis treatment., (© 2024 The Author(s). Journal of Cellular Physiology published by Wiley Periodicals LLC.)

The pathogenesis of sepsis, with a high mortality rate and often poor prognosis, has not been fully elucidated. Therefore, an in-depth study on the pathogenesis of sepsis at the molecular level is essential to identify key sepsis-related genes. The aim of this study was to explore the key genes and potential molecular mechanisms of sepsis using a bioinformatics approach. In addition, key genes with miRNA network correlation analysis and immune infiltration correlation analysis were investigated. The scRNA dataset (GSE167363) and RNA-seq dataset (GSE65682, GSE134347) from GEO database were used for screening out differentially expressed genes using single-cell sequencing and transcriptome sequencing. The analysis of immune infiltration was evaluated by the CIBERSORT method. Key genes and possible mechanisms were identified by WGCNA analysis, GSVA analysis, GSEA enrichment analysis and regulatory network analysis, and miRNA networks associated with key genes were constructed. Nine key genes associated with the development of sepsis, namely IL7R, CD3D, IL32, GPR183, HLA-DPB1, CD81, PEBP1, NCL, and ETS1 were screened, and the specific signaling mechanisms associated with the key genes causing sepsis were predicted. Immune profiling showed immune heterogeneity between control and sepsis samples. A regulatory network of 82 miRNAs, 266 pairs of mRNA-miRNA relationship pairs was also constructed. These nine key genes have the potential to become biomarkers for the diagnosis of sepsis and provide new targets and research directions for the treatment of sepsis.

This study aimed to explore the underlying mechanism of neddylation in macrophage polarization during sepsis. A mouse model of sepsis was established by cecal ligation and puncture (CLP). ELISA and Flow cytometry were performed to analyze the generation of pro-inflammatory factors and M1/M2 macrophage polarization, respectively. Western blotting was applied to detect NEDD8-mediated neddylation and glycolysis-related proteins. ECAR method was used to analyze the glycolysis level. HE staining was applied to detect the lung injury. The bacterial load in peritoneal cavity and peripheral blood was determined by counting the colony-forming units. The results showed the upregulated neddylation, M1 polarization and glycolysis of macrophage in patients with sepsis and CLP-challenged mice. NEDD8-mediated Cullin1 neddylation promoted M1 polarization and glycolysis to accelerate inflammation via NF-κB p65 pathway in E.coli-treated Raw264.7 cells. MLN4924 treatment alleviated sepsis by inhibiting neddylation to prevent M1 polarization in CLP-challenged mice. In summary, this study demonstrated that upregulation of NEDD8-mediated Cullin1 neddylation promotes glycolysis and M1 polarization of macrophage via NF-κB p65 pathway, accelerating inflammation in sepsis., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This research investigated the intricate relationship between ferroptosis and sepsis by utilizing advanced genomic and pharmacological methodologies. Specifically, we obtained expression quantitative trait loci (eQTLs) for 435 genes associated with ferroptosis from the eQTLGen Consortium and detected notable cis-eQTLs for 281 of these genes. Next, we conducted a detailed analysis to assess the impact of these eQTLs on susceptibility to sepsis using Mendelian randomization (MR) with data from a cohort of 10,154 sepsis patients and 452,764 controls sourced from the UK Biobank. MR analysis revealed 16 ferroptosis-related genes that exhibited significant associations with sepsis outcomes. To bolster the robustness of these findings, sensitivity analyses were performed to assess pleiotropy and heterogeneity, thus confirming the reliability of the causal inferences. Furthermore, single-cell RNA sequencing data from sepsis patients offered a detailed examination of gene expression profiles, demonstrating varying levels of ferroptosis marker expression across different cell types. Pathway enrichment analysis utilizing gene set enrichment analysis (GSEA) further revealed the key biological pathways involved in the progression of sepsis. Additionally, the use of computational molecular docking facilitated the prediction of interactions between identified genes and potential therapeutic compounds, highlighting novel drug targets. In conclusion, our integrated approach combining genomics and pharmacology offers valuable insights into the involvement of ferroptosis in sepsis, laying the groundwork for potential therapeutic strategies targeting this cell death pathway to enhance sepsis management., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Sepsis is a life-threatening condition caused by an excessive inflammatory response to an infection. However, the precise regulatory mechanism of sepsis remains unclear. Using a strand-specific RNA-sequencing, we identified 115 hub differentially expressed long noncoding RNAs (lncRNAs) and 443 mRNAs in septic patients, primarily participated in crucial pathways including neutrophil extracellular trap (NET) formation and toll-like receptor signaling. Notably, NETs related gene aquaporin-9 (AQP9) and its associated lncRNAs exhibited significant upregulation in septic neutrophils. Functional experiments revealed AQP9 interacts with its lncRNAs to augment the formation of neutrophil NETs. In murine sepsis models, AQP9 inhibition with phloretin reduced proinflammatory cytokine production and lung damage. These findings provide crucial insights into the regulatory role of AQP9 in sepsis, unraveling its interaction with associated lncRNAs in transmitting downstream signals, holding promise in informing the development of novel therapeutic strategies aimed at ameliorating the debilitating effects of sepsis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Sepsis-induced myopathy is one of the serious complications of sepsis, which severely affects the respiratory and peripheral motor systems of patients, reduces their quality of life, and jeopardizes their lives, as evidenced by muscle atrophy, loss of strength, and impaired regeneration after injury. The pathogenesis of sepsis-induced myopathy is complex, mainly including cytokine action, enhances free radical production in muscle, increases muscle protein hydrolysis, and decreases skeletal muscle protein synthesis, etc. The above mechanisms have been demonstrated in existing studies. However, it is still unclear how the overall pattern of gene co-expression affects the pathological process of sepsis-induced myopathy. Therefore, we intend to identify hub genes and signaling pathways. Weighted gene co-expression network analysis was our main approach to study gene expression profiles: skeletal muscle transcriptome in ICU patients with sepsis-induced multi-organ failure (GSE13205). After data pre-processing, about 15,181 genes were used to identify 13 co-expression modules. Then, 16 genes (FEM1B, KLHDC3, GPX3, NIFK, GNL2, EBNA1BP2, PES1, FBP2, PFKP, BYSL, HEATR1, WDR75, TBL3, and WDR43) were selected as the hub genes including 3 up-regulated genes and 13 down-regulated genes. Then, Gene Set Enrichment Analysis was performed to show that the hub genes were closely associated with skeletal muscle dysfunction, necrotic and apoptotic skeletal myoblasts, and apoptosis in sepsis-induced myopathy. Overall, 16 candidate biomarkers were certified as reliable features for more in-depth exploration of sepsis-induced myopathy in basic and clinical studies., (© 2024. The Author(s).)

Septic lung injury is strongly associated with polarization of M1 macrophages and excessive cytokine release. Fibroblast growth factor (FGF) signaling plays a role in both processes. However, the impact of FGF2 deficiency on macrophage polarization and septic acute lung injury remains unclear. To investigate this, we obtained macrophages from FGF2 knockout mice and examined their polarization and inflammatory cytokine expression. We also eliminated endogenous macrophages using clodronate liposomes and administered FGF2 knockout or WT macrophages intravenously in conjunction with cecal ligation and puncture (CLP) surgery to induce sepsis. In vitro analysis by flow cytometry and real-time PCR analysis demonstrated that FGF2 deficiency resulted in increased expression of M1 markers (iNOS and CD86) and inflammatory cytokines (CXCL1, IL1β, and IL6), especially after LPS stimulation. Additionally, immunofluorescence demonstrated increased nuclear translocation of p65 NF-κB in FGF2 knockout macrophages and RNA-seq analysis showed enrichment of differentially expressed genes in the IL17 and TNFα inflammatory signaling pathways. Furthermore, in vivo experiments revealed that depletion of FGF2 in macrophages worsened sepsis-induced lung inflammation, lung vascular leak, and lung histological injury, accompanied by an increase in CD86-positive cells and apoptosis. Our study suggests that FGF2 deficiency in macrophages plays a critical role in the pathogenesis of septic ALI, possibly because of the enhanced M1 macrophage polarization and production of proinflammatory cytokines. These findings provide empirical evidence for potential therapeutic interventions targeting FGF2 signaling to modulate the polarization of M1 and M2 macrophages in the management of sepsis-induced acute lung injury., (© 2024. The Author(s).)

Sepsis-induced acute lung injury (ALI), characterized by severe hypoxemia and pulmonary leakage, remains a leading cause of mortality in intensive care units. The exacerbation of ALI during sepsis is largely attributed to uncontrolled inflammatory responses and endothelial dysfunction. Emerging evidence suggests an important role of Z-DNA binding protein 1 (ZBP1) as a sensor in innate immune to drive inflammatory signaling and cell death during infections. However, the role of ZBP1 in sepsis-induced ALI has yet to be defined. We utilized ZBP1 knockout mice and combined single-cell RNA sequencing with experimental validation to investigate ZBP1's roles in the regulation of macrophages and lung endothelial cells during sepsis. We demonstrate that in sepsis, ZBP1 deficiency in macrophages reduces mitochondrial damage and inhibits glycolysis, thereby altering the metabolic status of macrophages. Consequently, this metabolic shift leads to a reduction in the differentiation of macrophages into pro-inflammatory states and decreases macrophage pyroptosis triggered by activation of the NLRP3 inflammasome. These changes significantly weaken the inflammatory signaling pathways between macrophages and endothelial cells and alleviate endothelial dysfunction and cellular damage. These findings reveal important roles for ZBP1 in mediating multiple pathological processes involved in sepsis-induced ALI by modulating the functional states of macrophages and endothelial cells, thereby highlighting its potential as a promising therapeutic target., (© 2024. The Author(s).)

Sepsis is a life-threatening condition characterized by an exaggerated immune response to pathogens, leading to organ damage and high mortality rates in the intensive care unit. Although deep learning has achieved impressive performance on prediction and classification tasks in medicine, it requires large amounts of data and lacks explainability, which hinder its application to sepsis diagnosis. We introduce a deep learning framework, called scCaT, which blends the capsulating architecture with Transformer to develop a sepsis diagnostic model using single-cell RNA sequencing data and transfers it to bulk RNA data. The capsulating architecture effectively groups genes into capsules based on biological functions, which provides explainability in encoding gene expressions. The Transformer serves as a decoder to classify sepsis patients and controls. Our model achieves high accuracy with an AUROC of 0.93 on the single-cell test set and an average AUROC of 0.98 on seven bulk RNA cohorts. Additionally, the capsules can recognize different cell types and distinguish sepsis from control samples based on their biological pathways. This study presents a novel approach for learning gene modules and transferring the model to other data types, offering potential benefits in diagnosing rare diseases with limited subjects., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Zheng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: The objective was to use bioinformatics to analyze the potential key genes involved in the mechanism of sulforaphane's protective effects in  sepsis-associated acute kidney injury (SA-AKI) and to identify potential intervention targets., Methods: Gene Expression Omnibus (GEO) gene chip datasets containing gene expression profiles from kidney tissues of SA-AKI patients and normal controls were selected. Upregulated differentially expressed genes (DEGs) were identified using GEO2R. Protein-protein interaction (PPI), GO, and KEGG enrichment analyses were performed. Allyl isothiocyanate's target genes were analyzed in the ChEMBL database, and intersections with the above DEGs were presented in Venn diagrams. Rat tissues were examined for FKBP1A expression using qRT-PCR., Results: A total of 17 DEGs related to SA-AKI were obtained (|log fold change| > 0 and P < .05). KEGG pathway analysis indicated that the primary pathways linked to the elevated DEGs were glycogen breakdown, leukocyte trans-endothelial migration, and T-cell receptor, TNF, and NF-κB signaling. The module and PPI network analysis of common DEGs revealed one cluster and four candidate genes, including OASL, TRRAP, FKBP1A, and BANF. ChEMBL database analysis identified 339 target genes for allyl isothiocyanate, and the intersection with upregulated DEGs related to SA-AKI injury yielded two co-expressed genes, FKBP1A and TRRAP. According to the findings of the qRT-PCR assay, the kidney tissues of the model cohort showed significantly higher expression levels of FKBP1A mRNA than the control cohort (P = .0142)., Conclusion: Allyl isothiocyanate may alleviate SA-AKI injury by targeting FKBP1/NF-κB.

Sepsis remains a huge unmet medical need for which no approved drugs, besides antibiotics, are on the market. Despite the clinical impact of sepsis, its molecular mechanism remains inadequately understood. Recent insights have shown that profound hepatic transcriptional reprogramming, leading to fatal metabolic abnormalities, might open a new avenue to treat sepsis. Translation of experimental results from rodents to larger animal models of higher relevance for human physiology, such as pigs, is critical and needs exploration. We performed a comparative analysis of the transcriptome profiles in murine and porcine livers using the following sepsis models: cecal ligation and puncture (CLP) in mice and fecal instillation (FI) in pigs, both of which induce polymicrobial septic peritonitis, and lipopolysaccharide (LPS)-induced endotoxemia in pigs, inducing sterile inflammation. Using bulk RNA sequencing, Metascape pathway analysis, and HOMER transcription factor motif analysis, we were able to identify key genes and pathways affected in septic livers. Conserved upregulated pathways in murine CLP and porcine LPS and FI generally comprise typical inflammatory pathways, except for ER stress, which was only found in the murine CLP model. Conserved pathways downregulated in sepsis comprise almost exclusively metabolic pathways such as monocarboxylic acid, steroid, biological oxidation, and small-molecule catabolism. Even though the upregulated inflammatory pathways were equally induced in the two porcine models, the porcine FI model more closely resembles the metabolic dysfunction observed in the CLP liver compared to the porcine LPS model. This comprehensive comparison focusing on the hepatic responses in mouse CLP versus LPS or FI in pigs shows that the two porcine sepsis models generally resemble quite well the mouse CLP model, with a typical inflammatory signature amongst the upregulated genes and metabolic dysfunction amongst the downregulated genes. The hepatic ER stress observed in the murine model could not be replicated in the porcine models. When studying metabolic dysfunction in the liver upon sepsis, the porcine FI model more closely resembles the mouse CLP model compared to the porcine LPS model.

Septic patients with T2DM were prone to prolonged recovery and unfavorable prognoses. Thus, this study aimed to pinpoint potential genes related to sepsis with T2DM and develop a predictive model for the disease. The candidate genes were screened using protein-protein interaction networks (PPI) and machine learning algorithms. The nomogram and receiver operating characteristic curve were developed to assess the diagnostic efficiency of the biomarkers. The relationship between sepsis and immune cells was analyzed using the CIBERSORT algorithm. The biomarkers were validated by qPCR and western blotting in basic experiments, and differences in organ damage in mice were studied. Three genes (MMP8, CD177, and S100A12) were identified using PPI and machine learning algorithms, demonstrating strong predictive capabilities. These biomarkers presented significant differences in gene expression patterns between diseased and healthy conditions. Additionally, the expression levels of biomarkers in mouse models and blood samples were consistent with the findings of the bioinformatics analysis. The study elucidated the common molecular mechanisms associated with the pathogenesis of T2DM and sepsis and developed a gene signature-based prediction model for sepsis. These findings provide new targets for the diagnosis and intervention of sepsis complicated with T2DM., (© 2024 Federation of American Societies for Experimental Biology.)

Sepsis is a life-threatening organ malfunction induced by an imbalanced immunological reaction to infection in the host. Many studies have utilized traditional RNA sequencing (RNA-seq) data to identify important biological targets to predict sepsis prognosis. However, alterations in core cells and functional status cannot be effectively detected in sepsis patients. The goal of this study was to identify key cells through single-cell RNA-seq (scRNA-seq), and combine bulk RNA-seq data and multiple algorithm analysis to construct a stable prognostic model for sepsis. The scRNA-seq and bulk RNA-seq data from sepsis patients were collected from the Gene Expression Omnibus (GEO) database. The R package "Seurat" was used to process the scRNA-seq data. Cell communication was investigated using the R package "CellChat". The pseudo-time of the cells was calculated using the R package "monocle". The R package "limma" was used to identify differentially expressed genes (DEGs) between the sepsis group and the control group. Weighted gene correlation network analysis (WGCNA) was used to identify critical modules. Eight kinds of machine learning and 90 algorithm combinations were used to construct the prognostic model for sepsis. Quantitative real-time PCR (qRT‒PCR) was performed to determine the expression of key genes in the cecal ligation and puncture (CLP)-induced sepsis mouse model. The immunological status and related properties of DEGs were then investigated in the high- and low-risk groups delineated by the model. By combining the scRNA-seq data from nine samples, 13 clusters and 9 cell types were identified. CellChat analysis revealed that the number and strength of interactions between platelets and a variety of cells increased. We identified key platelet genes from the scRNA-seq data and combined these genes and the results of differential analysis and WGCNA of the bulk RNA-seq data. After univariate Cox regression analysis, we calculated the Cindex of the model constructed by the combination of 90 algorithms, and we finally determined the "CoxBoost + Lasso" combination. Multivariate Cox regression was used to construct the final prognostic model. The qRT-PCR results revealed significant differences in five key prognostic genes between the CLP and sham groups. The data was classified into high- and low-risk groups based on the model score. The high-risk group had a poorer survival rate and less immune infiltration. We identified the importance of platelets in sepsis patients through scRNA-seq, and established prognostic models with key genes that were identified via scRNA-seq combined with bulk RNA-seq analysis. The results of this model were closely associated with patient survival rates and immunological status and this model is useful for the prognostic management of sepsis., (© 2024. The Author(s).)

Damage-associated molecular patterns (DAMPs) and pathogen-associated molecular patterns (PAMPs) are key triggers of inflammation in sepsis. However, they have rarely been studied simultaneously. Thus, in the present study of patients with bacteraemic infection, we aimed to study how DAMP dynamics are linked to disease severity and outcome and to compare diagnostic and prognostic properties of a DAMP and a previously analysed PAMP (16S rDNA). In a prospective study of adult patients hospitalized with culture-proven community-onset bacteraemic infection, caused by Streptococcus pneumonia (n = 30), Staphylococcus aureus (n = 27), or Escherichia coli (n = 26), dynamics of a PAMP, i.e. 16S rDNA, have previously been presented. For the present study, blood samples obtained on hospital days 1-2 (when blood culture was positive), 3-4, 7 ± 1, 14 ± 2, and 28 ± 4 were analysed for four different DAMPs, i.e., nuclear DNA (nDNA), mitochondrial DNA (mtDNA), heat shock protein 90 alpha (HSP90α), and extracellular high mobility group box 1 (HMGB1). Sepsis was defined according to the Sepsis-3 criteria. The study outcomes were sepsis at admission and negative outcome, defined as intensive care unit (ICU) admission and/or death within 60 days. Of 83 study patients, sepsis was noted in 41 patients (49%) and a negative outcome was noted in 17 patients (20%). nDNA had areas under the receiver operating characteristic (ROC) curves of 0.78 for sepsis and 0.76 for negative outcome, which were higher than those of the other DAMPs and additional biomarkers (CRP, IL-6, IL-8, and IL-10). The nDNA and positive 16S rDNA results on day 1-2 were correlated with each other (r = 0.68, p < 0.001). Multivariate analyses showed that high day 1-2 concentrations of both nDNA and 16S rDNA were independently associated with sepsis. In addition, high day 1-2 concentration of nDNA was independently associated with negative outcomes. While 16S rDNA dissipated from the circulation within days, nDNA concentrations remained elevated throughout the follow-up period in patients with negative outcome. In conclusion, nDNA outperformed the other DAMPs regarding sepsis detection and outcome prediction. Both nDNA (a DAMP) and 16S rDNA (a PAMP) were independently linked to sepsis; nDNA was also associated with negative outcomes and persisted elevated in such cases. This highlights nDNA as an interesting marker within sepsis pathogenesis and as a promising clinical biomarker, warranting further studies., (© 2024. The Author(s).)

Background: A Two-sample Mendelian randomization (MR) Analysis was used to assess the causal relationship between non-small cell lung cancer (NSCLC) and sepsis., Method: Single nucleotide polymorphisms (SNPs) closely associated with NSCLC were utilized as instrumental variables (IVs) in this study. The Inverse Variance Weighted (IVW) method was used as the primary method for MR analysis, supplemented by the Weighted median, Weighted model, and MR-Egger regression method. Sensitivity analysis was conducted to improve result robustness, and data from various sources were validated and integrated. Bonferroni tests were applied to adjust for multiple comparisons., Results: After Bonferroni tests correcting the combined results, MR analysis revealed a significant association between genetically predicted NSCLC and an increased susceptibility to sepsis (odds ratios [OR]: 1.140, 95% confidence interval [CI]: 1.085-1.199, P = 2.61 × 10 - 7 ). The combined results demonstrated that NSCLC is associated with a heightened risk of sepsis in patients under 75 years of age (OR: 1.085, 95%CI: 1.037-1.353, P = 3.84 × 10 - 4 ). Furthermore, lung adenocarcinoma (LUAD) was found to be potentially associated with an increased susceptibility to sepsis (OR: 1.040, 95% CI: 1.009-1.073, P = 1.16 × 10 - 2 ). These results withstood multiple sensitivity analyses, demonstrating their robustness., Conclusion: This study confirms that NSCLC can significantly increase susceptibility to sepsis at the genetic level, providing valuable insights for the early identification of individuals at risk for sepsis., (© 2024. The Author(s).)

Recent empirical research posits a link between lymphocyte subgroups and both the incidence and prognosis of sepsis. Nevertheless, the potential influence of multiple confounding variables obscures any clear causative correlation. Utilizing a 2-sample Mendelian randomization approach, we conducted a meta-analysis of lymphocyte subgroups. In a genome-wide association study, flow cytometry was applied to a lymphocyte subgroup comprising 3757 Sardinians to identify genes influenced by blood immune cells. The sepsis meta-analysis data were sourced from the UK Biobank database, including 11,643 treatment groups and 47,841 control groups. Inverse variance-weighted, Mendelian randomization-Egger regression, weighted median, simple mode, and weighted mode methods were deployed to ascertain the causative relationship between lymphocyte subgroup and sepsis. Cochran Q test, the Mendelian randomization-Egger intercept test, and funnel plots were leveraged to assess the robustness of study findings. The inverse variance-weighted analysis disclosed that the absolute count of CD4 regulatory T cells (CD4 Treg AC) within the lymphocyte subgroup has a causative link to an elevated risk of sepsis, with an odds ratio of 1.08 and a 95% confidence interval of 1.02 to 1.15 (P = .011). Compared to individuals not subjected to this factor, those exposed to CD4 Treg AC have a marginally elevated sepsis risk by approximately 0.08%. No causative relationships were observed between sepsis risk and the absolute counts of other lymphocyte subgroups such as CD8+ T cells, CD4+ CD8dim T cells, natural killer T cells, B cells (B cell absolute count), and HLA DR+ natural killer cells. The 2-sample Mendelian randomization study indicated a causal relationship between the level of CD4 Treg AC and the increased risk of sepsis. The elevation in circulating lymphocyte subgroups suggests higher susceptibility to sepsis, affirming the immune susceptibility inherent to this condition. The findings from our study may propose potential targets for diagnosis and intervention of sepsis., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Sepsis, characterized by a widespread and dysregulated immune response to infection leading to organ dysfunction, presents significant challenges in diagnosis and treatment. In this study, we investigated 203 coagulation-related genes in sepsis patients to explore their roles in the disease. Through differential gene expression analysis, we identified 20 genes with altered expression patterns. Subsequent correlation analysis, visualized through circos plots and heatmaps, revealed significant relationships among these genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicated that these genes are involved in immune response activation, coagulation, and immune receptor activity. Disease Ontology (DO) enrichment analysis further linked these genes to autoimmune hemolytic anemia and tumor-related signaling pathways. Additionally, the CIBERSORT analysis highlighted differences in immune cell composition in sepsis patients, revealing an increase in neutrophils and monocytes and a decrease in inactive NK cells, CD8 T cells, and B cells. We employed machine learning techniques, including random forest and SVM, to construct a diagnostic model, identifying FCER1G and FYN as key biomarkers. These biomarkers were validated through their expression levels and ROC curve analysis in an independent validation cohort, demonstrating strong diagnostic potential. Single-cell analysis from the GSE167363 dataset further confirmed the distinct expression profiles of these genes across various cell types, with FCER1G predominantly expressed in monocytes, NK cells, and platelets, and FYN in CD4+ T cells and NK cells. Enrichment analysis via GSEA and ssGSEA revealed that these genes are involved in critical pathways, including intestinal immune networks, fatty acid synthesis, and antigen processing. In conclusion, our comprehensive analysis identifies FCER1G and FYN as promising biomarkers for sepsis, providing valuable insights into the molecular mechanisms of this complex condition. These findings offer new avenues for the development of targeted diagnostic and therapeutic strategies in sepsis management., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ge, Deng, Zhou, Hu, Zhang and Zheng.)

The discovery of Lactylation may pave the way for novel approaches to investigating sepsis. This study focused on the prognostic and diagnostic significance of lactylated genes in sepsis. RNA sequencing was performed on blood samples from 20 sepsis patients and 10 healthy individuals at Southwest Medical University in Luzhou, Sichuan, China. Genes associated with sepsis were identified through analysis of RNA sequencing data. Afterward, the genes that were expressed differently were compared with the lactylation genes, resulting in the identification of 55 lactylation genes linked to sepsis. The overlapping genes underwent analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Protein-Protein Network Interactions were used to screen for the core genes. The datasets GSE65682, GSE69528, GSE54514, GSE63042, and GSE95233 were obtained from the GEO database to validate core genes. Survival analysis evaluated the predictive significance of central genes in sepsis, while Receiver Operating Characteristic (ROC) Curve analysis was employed to establish the diagnostic value of genes. Additionally, a meta-analysis was conducted to confirm the precision of RNA-seq data. We obtained five peripheral blood samples, including two from healthy individuals, one from a patient with systemic inflammatory response syndrome (SIRS), and two from patients with sepsis. These samples were used to identify the specific location of core genes using 10×single-cell sequencing. High-throughput sequencing and bioinformatics techniques identified two lactylation-related genes (S100A11 and CCNA2) associated with sepsis. Survival analysis indicated that septic patients with reduced levels of S100A11 had a decreased 28-day survival rate compared to those with elevated levels. Conversely, individuals exhibiting decreased CCNA2 levels demonstrated a greater likelihood of surviving for 28 days than those in the high expression category, indicating a favorable association with survival rates among sepsis patients (P < 0.05). Both genes showed high sensitivity and specificity based on the ROC curve, with AUC values of 0.961 for S100A11 and 0.890 for CCNA2. The meta-analysis revealed that S100A11 exhibited high levels of expression in the sepsis survivors, whereas it displayed low levels of expression in the non-survivors; on the other hand, CCNA2 demonstrated low expression in the sepsis survivors and high expression in the non-survivors (P < 0.05). Single-cell RNA sequencing ultimately showed that monocyte macrophages, T cells, and B cells exhibited high expression levels of the crucial genes associated with sepsis-induced lactylation. In conclusion, the lactylation genes S100A11 and CCNA2 are strongly linked to sepsis and could be valuable markers for diagnosing, predicting outcomes, and providing guidance for sepsis., (© 2024. The Author(s).)

Sepsis represents a critical condition characterized by multiple-organ dysfunction resulting from inflammatory response to infection. Disulfidptosis is a newly identified type of programmed cell death that is intimately associated with the actin cytoskeleton collapse caused by glucose starvation and disulfide stress, but its role in sepsis is largely unknown. The study was to adopt a diagnostic and prognostic signature for sepsis with disulfidptosis based on the differentially expressed genes (DEGs) between sepsis and healthy people from GEO database. The disulfidptosis hub genes associated with sepsis were identified, and then developed consensus clustering and immune infiltration characteristics. Next, we evaluated disulfidptosis-related risk genes by using LASSO and Random Forest algorithms, and constructed the diagnostic sepsis model by nomogram. Finally, immune infiltration, GSVA analysis and mRNA-miRNA networks based on disulfidptosis-related DEGs were screened. There are five upregulated disulfidptosis-related genes and seven downregulated genes were filtered out. The six intersection disulfidptosis-related genes including LRPPRC, SLC7A11, GLUT, MYH9, NUBPL and GYS1 exhibited higher predictive ability for sepsis with an accuracy of 99.7%. In addition, the expression patterns of the critical genes were validated. The study provided a comprehensive view of disulfidptosis-based signatures to predict the prognosis, biological features and potential treatment directions for sepsis., (© 2024 The Author(s). Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.)

Purpose: Coronavirus Disease 2019 (COVID-19) and sepsis are closely related. This study aims to identify pivotal diagnostic candidate genes in COVID-19 patients with sepsis., Patients and Methods: We obtained a COVID-19 data set and a sepsis data set from the Gene Expression Omnibus (GEO) database. Identification of differentially expressed genes (DEGs) and module genes using the Linear Models for Microarray Data (LIMMA) and weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning algorithms (least absolute shrinkage and selection operator (LASSO) regression and Random Forest (RF)) were used to identify candidate hub genes for the diagnosis of COVID-19 patients with sepsis. Receiver operating characteristic (ROC) curves were developed to assess the diagnostic value. Finally, the data set GSE28750 was used to verify the core genes and analyze the immune infiltration., Results: The COVID-19 data set contained 3,438 DEGs， and 595 common genes were screened in sepsis. sepsis DEGs were mainly enriched in immune regulation. The intersection of DEGs for COVID-19 and core genes for sepsis was 329, which were also mainly enriched in the immune system. After developing the PPI network, 17 node genes were filtered and thirteen candidate hub genes were selected for diagnostic value evaluation using machine learning. All thirteen candidate hub genes have diagnostic value, and 8 genes with an Area Under the Curve (AUC) greater than 0.9 were selected as diagnostic genes., Conclusion: Five core genes (CD3D, IL2RB, KLRC, CD5, and HLA-DQA1) associated with immune infiltration were identified to evaluate their diagnostic utility COVID-19 patients with sepsis. This finding contributes to the identification of potential peripheral blood diagnostic candidate genes for COVID-19 patients with sepsis., (© 2024 The Author(s). Immunity, Inflammation and Disease published by John Wiley & Sons Ltd.)

Background: Gastroesophageal reflux disease (GERD) is a prevalent gastrointestinal disorder. Recent studies indicate that GERD may exert systemic effects, potentially elevating the risk of severe infections, including sepsis. Nevertheless, the causal relationship between GERD and sepsis, as well as sepsis-related 28-day mortality, remains uncertain., Aim: The aim of this study is to investigate the causal relationship between GERD and the risk of sepsis, including 28-day mortality of sepsis., Methods: This study utilized a two-sample Mendelian Randomization (MR) approach to analyze data from publicly available genome-wide association studies (GWAS) databases ( https://gwas.mrcieu.ac.uk/ ). The analysis comprised 129,080 cases and 473,524 controls for GERD; 11,643 patients and 474,841 controls for sepsis; and 1,896 patients and 484,588 controls for 28-day mortality from sepsis. The objective was to evaluate the causal impact of GERD on the risk of sepsis and 28-day sepsis mortality. Genetic variation data pertinent to GERD were obtained from the most recent genome-wide association studies (GWAS). The primary analysis employed the Inverse Variance Weighted (IVW) method. Sensitivity and pleiotropy analyses were performed to validate the robustness of the findings., Results: MR analysis revealed a notable link between genetically predicted GERD and increased sepsis risk (odds ratio [OR] 1.37, 95% confidence interval [CI] 1.24-1.52; p = 2.79 × 10-9). Moreover, GERD correlated with elevated 28-day mortality of sepsis (OR 1.44, 95% CI 1.11-1.85; p = 5.34 × 10-3). These results remained consistent throughout various sensitivity analyses, indicating their resilience against potential pleiotropy and other biases., Conclusion: This study indicates that genetic predisposition to GERD may be linked to an elevated risk of sepsis and its associated 28-day mortality. However, the study does not establish a direct causal relationship for GERD itself, nor does it assess the impact of GERD treatment. Further research is needed to explore the underlying mechanisms and potential therapeutic interventions involved., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: The aim of this study was using bioinformatic tools to identify hub genes in the relationship between septic cardiomyopathy (SCM) and cuproptosis and predict potential Chinese herbal drug candidates., Methods: SCM datasets were downloaded from the gene expression omnibus. Cuproptosis related genes were collected from a research published on Science in March, 2022. The expression profiles of genes related to cuproptosis in SCM were extracted. Differentially expressed genes (DEGs) were analyzed using R package limma. A single-sample gene set enrichment analysis was conducted to measure the correlation between DEGs and immune cell infiltration. Hub genes were screened out by random forest model. Finally, HERB database and COREMINE database were used to predict Chinese herbal drugs for hub genes and carry out molecular docking., Results: A total of 9 DEGs were identified. Cuproptosis differential genes PDHB, DLAT, DLD, FDX1, GCSH, LIAS were significantly correlated with one or more cells and their functions in immune infiltration. The random forest model screened pyruvate dehydrogenase E1 beta subunit (PDHB) as the hub gene. PDHB was negatively correlated with Plasmacytoid dendritic cell infiltration. Pyruvic acid, rhodioloside and adenosine were predicted with PDHB as the target, and all three components are able to bind to PDHB., Conclusions: Cuproptosis related gene PDHB is associated with the occurrence and immune infiltration of septic cardiomyopathy. Rhodioloside and other Chinese herbal drugs may play a role in the treatment of SCM by regulating the expression of PDHB.

Sepsis is a severe disease that occurs when the body's immune system reacts excessively to infection. The body's response, which includes an intense antibacterial reaction, can damage its tissues and organs. Neutrophils are the major components of white blood cells in circulation, play a vital role in innate immunity while fighting against infections, and are considered a feature determining sepsis classification. There is a plethora of basic research detailing neutrophil functioning, among which, the study of neutrophil extracellular traps is providing novel insights into mechanisms and treatments of sepsis. This review explores their functions, dysfunctions, and influences in the context of sepsis. The interplay between neutrophils and the human microbiome and the impact of DNA methylation on neutrophil function in sepsis are crucial areas of study. The interaction between neutrophils and the human microbiome is complex, particularly in the context of sepsis, where dysbiosis may occur. We highlight the importance of deciphering neutrophils' functional alterations and their epigenetic features in sepsis because it is critical for defining sepsis endotypes and opening up the possibility for novel diagnostic methods and therapy. Specifically, epigenetic signatures are pivotal since they will provide a novel implication for a sepsis diagnostic method when used in combination with the cell-free DNA. Research is exploring how specific patterns of DNA methylation in neutrophils, detectable in cell-free DNA, could serve as biomarkers for the early detection of sepsis., Competing Interests: Conflict of interest statement. None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Leukocyte Biology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Sepsis remains a significant global health burden and contributor to mortality, yet the precise molecular mechanisms underlying the immune response are not fully elucidated. To gain insight into this issue, we performed a comprehensive analysis using a variety of techniques including bulk RNA sequencing, single-cell RNA sequencing, and enzyme-linked immunosorbent assay (ELISA). We performed enrichment analysis of differentially expressed genes in sepsis and healthy individuals by utilizing Gene Ontology (GO) analysis and indicated significant enrichment of immune-related response. Following Weighted Gene Co-Expression Network Analysis (WGCNA) and protein-protein interaction analysis (PPI) were used to identify key immune-related hub genes and validated by ELISA to show that NLRC4 is highly expressed in sepsis. Additionally, an analysis of scRNA-seq data from newly diagnosed sepsis, sepsis diagnosis at 6 hours, and healthy samples demonstrates a significant increase in both the expression levels and proportions of NLRC4 in sepsis monocytes and neutrophils. In addition, using pySCENIC we identified upstream transcription factors that regulate NLRC4. Our study provides valuable insights into the identification of NLRC4 in peripheral blood as a potential candidate gene for the diagnosis and treatment of sepsis., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Sepsis is a global health challenge that results in systemic inflammation, oxidative stress, and multi-organ dysfunction, with the heart being particularly susceptible. This study aimed to elucidate the effect of FTO, a key regulator in m 6 A methylation in septic cardiomyopathy, and its potential therapeutic implications. Cellular and animal models of septic myocardial injury were established. Moreover, it was revealed that ferroptosis, which is a form of programmed necrosis occurring with iron dependence, was activated within cardiomyocytes during septic conditions. The overexpression of FTO-suppressed ferroptosis alleviated heart inflammation and dysfunction and improved survival rates in vivo. However, the protective effects of FTO were attenuated by the overexpression of BACH1, which is a molecule negatively correlated with FTO. Mechanistically, FTO modulated the m 6 A modification of BACH1, suggesting a complex interplay in the regulation of cardiomyocyte damage and sepsis. Our findings reveal the potential of targeting the FTO/BACH1 axis and ferroptosis inhibitors as therapeutic strategies for sepsis-induced cardiac injuries., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The objective of this study was to explore the potential causalities of fat mass, nonfat mass and height (henceforth, 'anthropometric measures') with sepsis risk and mortality. We conducted the Mendelian randomization (MR) investigation using genome-wide association study (GWAS) summary statistics of anthropometric measures, sepsis, and sepsis mortality. The GWAS summary data from the UK Biobank was used. Firstly, MR analysis was performed to estimate the causal effect of anthropometric measures on the risk of sepsis. The inverse-variance weighted (IVW) method was utilized as the primary analytical approach, together with weighted median-based method. Cochrane's Q test and MR-Egger intercept test were performed to assess heterogeneity and pleiotropy, respectively. Finally, we performed a series of sensitivity analyses to enhance the precision and veracity of our findings. The IVW method showed that genetically predicted weight-related measures were suggestively linked to an increased risk of sepsis. However, height displayed no causal association with sepsis risk and mortality. Furthermore, weight-related measures also displayed significant MR association with the sepsis mortality, except body nonfat mass and right leg nonfat mass. However, MVMR analysis indicated the observed effects for weight-related measures in the univariable MR analyses are more likely a bias caused by the interrelationship between anthropometric measures. According to the MR-Egger intercept assessment, our MR examination was not influenced by horizontal pleiotropy (all p>0.05). Moreover, the reliability of the estimated causal association was confirmed by the sensitivity analyses. In conclusion, these findings provided vital new knowledge on the role of anthropometric-related measures in the sepsis etiology., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The immune response gene 1 (IRG1) and its metabolite itaconate are implicated in modulating inflammation and oxidative stress, with potential relevance to sepsis-induced myocardial dysfunction (SIMD). This study investigates their roles in SIMD using both in vivo and in vitro models. Mice were subjected to lipopolysaccharide (LPS)-induced sepsis, and cardiac function was assessed in IRG1 knockout (IRG1-/-) and wild-type mice. Exogenous 4-octyl itaconate (4-OI) supplementation was also examined for its protective effects. In vitro, bone marrow-derived macrophages and RAW264.7 cells were treated with 4-OI following Nuclear factor, erythroid 2 like 2 (NRF2)-small interfering RNA administration to elucidate the underlying mechanisms. Our results indicate that IRG1 deficiency exacerbates myocardial injury during sepsis, while 4-OI administration preserves cardiac function and reduces inflammation. Mechanistic insights reveal that 4-OI activates the NRF2/HO-1 pathway, promoting macrophage polarization and attenuating inflammation. These findings underscore the protective role of the IRG1/itaconate axis in SIMD and suggest a therapeutic potential for 4-OI in modulating macrophage responses., (© 2024. The Author(s).)

Lipoproteinassociated phospholipase A2 (Lp-PLA2), encoded by the phospholipase A2 group VII (Pla2g7) gene, has been pertinent to inflammatory responses. This study investigates the correlation between Lp-PLA2 and inflammatory injury in septic mice and explores its regulatory mechanism. Lp-PLA2 was found to be upregulated in the serum of septic mice induced by cecal ligation and puncture and in the culture supernatant of RAW264.7 cells following lipopolysaccharide and adenosine triphosphate treatments. The contents of Lp-PLA2 were positively correlated with increased concentrations of proinflammatory cytokines in patients with sepsis. Both animal and cellular models showed increased concentrations of proinflammatory cytokines. Spi-1 proto-oncogene (Spi1), highly expressed in these models, was found to activate Pla2g7 transcription. Knockdown of Pla2g7 or Spi1 reduced the proinflammatory cytokine production, mitigated organ damage in mice, and suppressed macrophage migration in vitro. Retinoblastoma binding protein 6 (Rbbp6), poorly expressed in both models, was found to reduce Spi1 protein stability through ubiquitination modification. Rbbp6 overexpression similarly suppressed inflammatory activation of RAW264.7 cells, which was counteracted by Pla2g7 or Spi1 upregulation. In summary, this study demonstrates that the Pla2g7 loss and Spi1 upregulation participate in inflammatory responses in sepsis by elevating the Lp-PLA2 levels., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Sepsis, a multifaceted syndrome driven by an imbalanced host response to infection, remains a significant medical challenge. At its core lies the pivotal role of glycolysis, orchestrating immune responses especially in severe sepsis. The intertwined dynamics between glycolysis, sepsis, and immunity, however, have gaps in knowledge with several Crucial genes still shrouded in ambiguity. We harvested transcriptomic profiles from the peripheral blood of 107 septic patients juxtaposed against 29 healthy controls. Delving into this dataset, differential expression analysis shed light on genes distinctly linked to glycolysis in both cohorts. Harnessing the prowess of LASSO regression and SVM-RFE, we isolated Crucial genes, paving the way for a sepsis risk prediction model, subsequently vetted via Calibration and decision curve analysis. Using the CIBERSORT algorithm, we further mapped 22 immune cell subtypes within the septic samples, establishing potential interactions with the delineated Crucial genes. Our efforts unveiled 21 genes intricately tied to glycolysis that exhibited differential expression patterns. Gene set enrichment analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses offered insights, spotlighting pathways predominantly associated with oxidative phosphorylation, PPAR signaling pathway, Glycolysis/Gluconeogenesis and HIF-1 signaling pathway. Among the myriad genes, IER3, DSC2, and PPARG emerged as linchpins, their prominence in sepsis further validated through ROC analytics. These sentinel genes demonstrated profound affiliations with various immune cell facets, bridging the complex terrain of glycolysis, sepsis, and immune responses. In line with our endeavor to "unveil the glycolysis in sepsis," the discovery of IER3, DSC2, and PPARG reinforces their cardinal roles in sepsis pathogenesis. These revelations accentuate the intricate dance between glycolysis and immunological shifts in septic conditions, offering novel avenues for therapeutic interventions., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Septic cardiomyopathy is a secondary myocardial injury caused by sepsis. N6-methyl-adenosine (m6A) modification is involved in the pathological progression of septic cardiomyopathy; however, the pathological mechanism remains unclear. In this study, we identified the overall m6A modification pattern in septic myocardial injury and determined its potential interactions with differentially expressed genes (DEGs). A sepsis mouse model exhibiting septic symptoms and myocardial tissue damage was induced by lipopolysaccharide (LPS). LPS-induced septic myocardial tissues and control myocardial tissues were subjected to methylated RNA immunoprecipitation sequencing and RNA sequencing to screen for differentially expressed m6A peaks and DEGs. We identified 859 significantly m6A-modified genes in septic myocardial tissues, including 432 upregulated and 427 downregulated genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to explore the biological importance of differentially expressed m6A methylated genes and DEGs. Differentially expressed m6A methylated genes were enriched in immune- and inflammation-related pathways. Conjoint analysis revealed co-expression of differentially expressed m6A genes and DEGs, including genes that were upregulated or downregulated and those showing opposite trends. High expression of m6A-related genes (WTAP and IGF2BP2), interleukin-17, and interleukin-17 pathway-related genes (MAPK11 and TRAF3IP2) was verified using reverse transcription-quantitative PCR. We confirmed the presence of m6A modification of the transcriptome and m6A-mediated gene expression in septic myocardial tissues., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Quantitative PCR (qPCR) is the gold standard for detection and quantitation of known DNA targets, but the scarcity of spectrally distinct fluorophores and filter sets limits the number of detectable targets. Here, we introduce color cycle multiplex amplification (CCMA) to significantly increase the number of detectable DNA targets in a single qPCR reaction using standard instrumentation. In CCMA, presence of one DNA target species results in a pre-programmed pattern of fluorescence increases. This pattern is distinguished by cycle thresholds (Cts) through rationally designed delays in amplification. For example, we design an assay wherein Staphylococcus aureus sequentially induces FAM, then Cy5.5, then ROX fluorescence increases with more than 3 cycles between each signal. CCMA offers notably higher potential for multiplexing because it uses fluorescence permutation rather than combination. With 4 distinct fluorescence colors, CCMA theoretically allows the detection of up to 136 distinct DNA target sequences using fluorescence permutation. Experimentally, we demonstrated a single-tube qPCR assay screening 21 sepsis-related bacterial DNA targets in samples of blood, sputum, pleural effusion and bronchoalveolar lavage fluid, with 89% clinical sensitivity and 100% clinical specificity, showing its potential as a powerful tool for advanced quantitative screening in molecular diagnostics., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Pyroptosis is a type of programmed cell death characterized by cell swelling and osmotic lysis, resulting in cytomembrane rupture and release of immunostimulatory components, which play a role in several pathological processes. Significant cellular responses to various stimuli involve the formation of inflammasomes, maturation of inflammatory caspases, and caspase-mediated cleavage of gasdermin. The function of pyroptosis in disease is complex but not a simple angelic or demonic role. While inflammatory diseases such as sepsis are associated with uncontrollable pyroptosis, the potent immune response induced by pyroptosis can be exploited as a therapeutic target for anti-tumor therapy. Thus, a comprehensive review of the role of pyroptosis in disease is crucial for further research and clinical translation from bench to bedside. In this review, we summarize the recent advancements in understanding the role of pyroptosis in disease, covering the related development history, molecular mechanisms including canonical, non-canonical, caspase 3/8, and granzyme-mediated pathways, and its regulatory function in health and multiple diseases. Moreover, this review also provides updates on promising therapeutic strategies by applying novel small molecule inhibitors and traditional medicines to regulate pyroptosis. The present dilemmas and future directions in the landscape of pyroptosis are also discussed from a clinical perspective, providing clues for scientists to develop novel drugs targeting pyroptosis., (© 2024. The Author(s).)