Zhijie He

It is unclear whether the atherogenic index of plasma (AIP) is associated with major adverse cardiovascular events (MACEs) in the general population. A total of 361,644 participants (aged 56.19 ± 8.09 years; 44.79% male) free of a history of MACEs at baseline from the UK Biobank data were included in the analysis. The AIP was calculated using log (triglyceride/high-density lipoprotein-cholesterol). Over a mean follow-up of 12.19 ± 1.60 years, 16,683 participants developed MACEs. After adjustment for traditional risk factors, each 1 unit increase in AIP was associated with a 45.3% higher risk of incident MACEs (hazard ratio (HR), 1.453 [95% confidence interval (CI) 1.371-1.540], P < 0.001). Results were similar when individuals were categorized by the AIP quartiles (HR, 1.283 [95% CI 1.217-1.351]; comparing extreme quartiles). The subgroup analyses showed that the association between AIP and risk of incident MACEs was more obvious in female participants who are < 60 years old and free of hypertension or diabetes. Sensitivity analysis included participants without any lipid-lowering medication or excluded incident MACEs in the first 2 years of follow-up confirming the robustness of the findings. Elevated AIP is a risk factor of incident MACEs in the general population, independent of traditional risk factors.Dynamic monitoring of the AIP may help select the population at high risk of cardiovascular events and guide primary prevention.

Background: Autophagy is involved in the pathophysiological process of sepsis. This study was designed to identify autophagy-related key genes in sepsis, analyze their correlation with immune cell signatures, and search for new diagnostic and prognostic biomarkers.Methods: Whole blood RNA datasets GSE65682, GSE134347, and GSE134358 were downloaded and processed. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to identify autophagy-related key genes in sepsis. Then, key genes were analyzed by functional enrichment, protein-protein interaction (PPI), transcription factor (TF)-gene and competing endogenous RNA (ceRNA) network analysis. Subsequently, key genes with diagnostic efficiency and prognostic value were identified by receiver operating characteristic (ROC) curves and survival analysis respectively. The signatures of immune cells were estimated using CIBERSORT algorithm. The correlation between significantly different immune cell signatures and key genes was assessed by correlation analysis. Finally, key genes with both diagnostic and prognostic value were verified by RT-qPCR.Results: 14 autophagy-related key genes were identified and their TF-gene and ceRNA regulatory networks were constructed. Among the key genes, 11 genes (ATIC, BCL2, EEF2, EIF2AK3, HSPA8, IKBKB, NLRC4, PARP1, PRKCQ, SH3GLB1, and WIPI1) had diagnostic efficiency (AUC > 0.90) and 5 genes (CAPN2, IKBKB, PRKCQ, SH3GLB1 and WIPI1) were associated with survival prognosis (p-value < 0.05). IKBKB, PRKCQ, SH3GLB1 and WIPI1 had both diagnostic and prognostic value, and their expression were verified by RT-qPCR. Analysis of immune cell signatures showed that the abundance of neutrophil, monocyte, M0 macrophage, gamma delta T cell, activated mast cell and M1 macrophage subtypes increased in the sepsis group, while the abundance of resting NK cell, resting memory CD4⁺ T cell, CD8⁺ T cell, naive B cell and resting dendritic cell subtypes decreased. Most of the key genes correlated with the predicted frequencies of CD8⁺ T cells, resting memory CD4⁺ T cells, M1 macrophages and naive B cells.Conclusion: We identified autophagy-related key genes with diagnostic and prognostic value in sepsis and discovered associations between key genes and immune cell signatures. This work may provide new directions for the discovery of promising biomarkers for sepsis.

Background: Diaphragmatic pacing can improve diaphragm function, which is beneficial for the prognosis of patients treated with prolonged mechanical ventilation (MV). While most previous studies have focused on the role of implanted diaphragm pacing (IDP), our study is the first to examine the effects of external diaphragmatic pacing (EDP) in mechanically ventilated patients. Specifically, the effect of EDP on diaphragm function, the success rate of weaning, the duration of MV (DMV), and the intensive care unit (ICU) length of stay (ILOS) were assessed. Methods: From September 2019 to December 2020, a total of 51 mechanically ventilated patients in the ICU of the Sun Yat-sen Memorial Hospital, Sun Yat-sen University were enrolled and randomly divided into an EDP group of 27 patients and a control group of 24 patients. The control group received routine treatment, and the EDP group received EDP treatment in addition to routine treatment. The diaphragm excursion (DE), diaphragm thickening fraction (DTF), DMV, ILOS, and average survival time were recorded to evaluate efficacy. Results: Patients treated with EDP had increased DE [exp(B) =1.86, 95% CI: 1.39 to 2.50, P2) [r=−0.54; 95% confidence interval (CI): −0.77 to −0.19; P=0.004], the arterial partial pressure of oxygen (PaO₂) (r=−0.58; 95% CI: −0.79 to −0.25; P=0.001), the PaO₂/FiO₂ ratio (r=−0.52; 95% CI: −0.75 to −0.16; P=0.006), and the serum lactate concentration (Lac) (r=−0.39; 95% CI: −0.68 to 0.003; P=0.046). Conclusions: EDP treatment can effectively reduce the DMV and prolong the average survival time of mechanically ventilated patients. Trial Registration: Chinese Clinical Trial Registry ChiCTR1900024096.

Objective: The pathogenesis of sepsis is still unclear due to its complexity, especially in children. This study aimed to analyse the immune microenvironment and regulatory networks related to sepsis in children at the molecular level and to identify key immune-related genes to provide a new basis for the early diagnosis of sepsis. Methods: The GSE145227 and GSE26440 datasets were downloaded from the Gene Expression Omnibus. The analyses included differentially expressed genes (DEGs), functional enrichment, immune cell infiltration, the competing endogenous RNA (ceRNA) interaction network, weighted gene coexpression network analysis (WGCNA), protein–protein interaction (PPI) network, key gene screening, correlation of sepsis molecular subtypes/immune infiltration with key gene expression, the diagnostic capabilities of key genes, and networks describing the interaction of key genes with transcription factors and small-molecule compounds. Finally, real-time quantitative PCR (RT–qPCR) was performed to verify the expression of key genes. Results: A total of 236 immune-related DEGs, most of which were enriched in immune-related biological functions, were found. Further analysis of immune cell infiltration showed that M0 macrophages and neutrophils infiltrated more in the sepsis group, while fewer activated memory CD4⁺ T cells, resting memory CD4⁺ T cells, and CD8⁺ T cells did. The interaction network of ceRNA was successfully constructed. Six key genes (FYN, FBL, ATM, WDR75, FOXO1 and ITK) were identified by WGCNA and PPI analysis. We found strong associations between key genes and constructed septic molecular subtypes or immune cell infiltration. Receiver operating characteristic analysis showed that the area under the curve values of the key genes for diagnosis were all greater than 0.84. Subsequently, we successfully constructed an interaction network of key genes and transcription factors/small-molecule compounds. Finally, the key genes in the samples were verified by RT–qPCR. Conclusion: Our results offer new insights into the pathogenesis of sepsis in children and provide new potential diagnostic biomarkers for the disease.

Objective. The prognostic value of the red cell distribution width (RDW) in patients with sepsis-induced acute respiratory distress syndrome (ARDS) is still elusive. This study is aimed at determining whether RDW is a prognostic indicator of sepsis-induced ARDS. Methods. This retrospective cohort study included 1161 patients with sepsis-induced ARDS. The datasets were acquired from the Medical Information Mart for Intensive Care III database. The locally weighted scatter-plot smoothing technique, Cox regression, Kaplan-Meier estimator, and subgroup analysis were carried out to evaluate the association between RDW and 90-day mortality. Results. The RDW and mortality had a roughly linear increasing relationship. The Cox regression model results were as follows: for level 2 ( ), hazard , 95% confidence , and for level 3 ( ), , 95% . The following results were obtained when RDW was treated as a continuous variable: , . The <svg...

Background: Sepsis is common in intensive care units and has a high mortality rate; yet, its pathogenesis and treatment remain unclear. Recent studies have shown that long non-coding RNA plasmacytoma variant translocation 1 (lncRNA-PVT1) plays a pro-inflammatory role in immune-related inflammatory diseases. Therefore, we investigated whether lncRNA-PVT1 plays an important pro-inflammatory effect in the inflammatory response of sepsis. Methods: Quantitative real-time PCR (RT-qPCR) was employed for the detection of lncRNA-PVT1, interleukin 1β (IL-1β), and tumor necrosis factor α (TNF-α) mRNA, and the correlations between their expressions were analyzed. After lncRNA-PVT1 knockdown by lncRNA Smart Silencer, abnormal expressions of lncRNA-PVT1, and IL-1β and TNF-α mRNA were detected. The expressions of total and phosphorylated protein of p38 were detected by western blotting. The effect of silencing lncRNA-PVT1 on p38 mitogen-activated protein kinase (MAPK) signaling pathway during lipopolysaccharide (LPS)-induced inflammation was subsequently analyzed. The MAPK selective inhibitor, SB202190, was used to block this signaling pathway, and the expressions of lncRNA-PVT1 and TNF-α were detected by RT-qPCR. Furthermore, the effect of partial blockade of the p38 MAPK signaling pathway by SB202190 on the levels of lncRNA-PVT1 was explored. Results: Following treatment of THP-1-derived macrophages with different concentrations of LPS, the levels of lncRNA-PVT1 and IL-1β, TNF-α mRNA were increased in a dose-dependent manner. Silencing of lncRNA-PVT1 reduced the expressions of IL-1β and TNF-α mRNA via inhibition of the p38 MAPK signaling pathway. Specifically, inhibiting the p38 MAPK pathway significantly decreased the LPS-induced lncRNA-PVT1 elevation. Conclusions: Our observations suggest that lncRNA-PVT1 can be silenced to ameliorate LPS-induced inflammation in macrophages via inhibition of the p38 MAPK pathway. Further, the p38 MAPK pathway can regulate the expression of lncRNA-PVT1 via a positive feedback loop.