ANGPTL2 knockdown induces autophagy to relieve alveolar macrophage pyroptosis by reducing LILRB2-mediated inhibition of TREM2.

Acute lung injury (ALI) is featured with a robust inflammatory response. Angiopoietin-like protein 2 (ANGPTL2), a pro-inflammatory protein, is complicated with various disorders. However, the role of ANGPTL2 in ALI remains to be further explored. The mice and MH-S cells were administrated with lipopolysaccharide (LPS) to evoke the lung injury in vivo and in vitro. The role and mechanism of ANGPTL was investigated by haematoxylin-eosin, measurement of wet/dry ratio, cell count, terminal deoxynucleotidyl transferase deoxyuridine triphosphate (dUTP) nick end labeling, reverse transcription quantitative polymerase chain reaction, immunofluorescence, enzyme-linked immunosorbent assay, detection of autophagic flux and western blot assays. The level of ANGPTL2 was upregulated in lung injury. Knockout of ANGPTL2 alleviated LPS-induced pathological symptoms, reduced pulmonary wet/dry weight ratio, the numbers of total cells and neutrophils in BALF, apoptosis rate and the release of pro-inflammatory mediators, and modulated polarization of alveolar macrophages in mice. Knockdown of ANGPTL2 downregulated the level of pyroptosis indicators, and elevated the level of autophagy in LPS-induced MH-S cells. Besides, downregulation of ANGPTL2 reversed the LPS-induced the expression of leukocyte immunoglobulin (Ig)-like receptor B2 (LILRB2) and triggering receptor expressed on myeloid cells 2 (TREM2), which was reversed by the overexpression of LILRB2. Importantly, knockdown of TREM2 reversed the levels of autophagy- and pyroptosis-involved proteins, and the contents of pro-inflammatory factors in LPS-induced MH-S cells transfected with si ANGPTL2, which was further inverted with the treatment of rapamycin. Therefore, ANGPTL2 silencing enhanced autophagy to alleviate alveolar macrophage pyroptosis via reducing LILRB2-mediated inhibition of TREM2.

Resistin as a potential diagnostic biomarker for sepsis: insights from DIA and ELISA analyses.

PURPOSE: The primary objective of this investigation is to systematically screen and identify differentially expressed proteins (DEPs) within the plasma of individuals afflicted with sepsis. This endeavor employs both Data-Independent Acquisition (DIA) and enzyme-linked immunosorbent assay (ELISA) methodologies. The overarching goal is to furnish accessible and precise serum biomarkers conducive to the diagnostic discernment of sepsis. METHOD: The study encompasses 53 sepsis patients admitted to the Affiliated Hospital of Southwest Medical University between January 2019 and December 2020, alongside a control cohort consisting of 16 individuals devoid of sepsis pathology. Subsequently, a subset comprising 10 randomly selected subjects from the control group and 22 from the sepsis group undergoes quantitative proteomic analysis via DIA. The acquired data undergoes Gene Ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) analyses, facilitating the construction of a Protein-Protein Interaction (PPI) network to discern potential markers. Validation of core proteins is then accomplished through ELISA. Comparative analysis between the normal and sepsis groups ensues, characterized by Receiver Operating Characteristic (ROC) curve construction to evaluate diagnostic efficacy. RESULT: A total of 187 DEPs were identified through bioinformatic methodologies. Examination reveals their predominant involvement in biological processes such as wound healing, coagulation, and blood coagulation. Functional pathway analysis further elucidates their engagement in the complement pathway and malaria. Resistin emerges as a candidate plasma biomarker, subsequently validated through ELISA. Notably, the protein exhibits significantly elevated levels in the serum of sepsis patients compared to the normal control group. ROC curve analysis underscores the robust diagnostic capacity of these biomarkers for sepsis. CONCLUSION: Data-Independent Acquisition (DIA) and Enzyme-Linked Immunosorbent Assay (ELISA) show increased Resistin levels in sepsis patients, suggesting diagnostic potential, warranting further research.

Screening of four lysosome-related genes in sepsis based on RNA sequencing technology.

PURPOSE: Screening of lysosome-related genes in sepsis patients to provide direction for lysosome-targeted therapy. METHODS: Peripheral blood samples were obtained from 22 patients diagnosed with sepsis and 10 normal controls for the purpose of RNA sequencing and subsequent analysis of differential gene expression. Concurrently, lysosome-related genes were acquired from the Gene Ontology database. The intersecting genes between the differential genes and lysosome-related genes were then subjected to PPI, GO and KEGG analyses. Core genes were identified through survival analysis, and their expression trends in different groups were determined using meta-analysis. Single-cell RNA sequencing was used to clarify the cellular localization of core genes. RESULTS: The intersection of 1328 sepsis-differential genes with 878 lysosome-related genes yielded 76 genes. PPI analysis showed that intersecting genes were mainly involved in Cellular process, Response to stimulus, Immune system process, Signal transduction, Lysosome. GO and KEGG analysis showed that intersecting genes were mainly involved in leukocyte mediated immunity, cell activation involved in immune response, lytic vacuole, lysosome. Survival analysis screened four genes positively correlated with sepsis prognosis, namely GNLY, GZMB, PRF1 and RASGRP1. The meta-analysis revealed that the expression levels of these four genes were significantly higher in the normal control group compared to the sepsis group, which aligns with the findings from RNA sequencing data. Furthermore, single-cell RNA sequencing demonstrated that T cells and NK cells exhibited high expression levels of GNLY, GZMB, PRF1, and RASGRP1. CONCLUSION: GNLY, GZMB, PRF1, and RASGRP1, which are lysosome-related genes, are closely linked to the prognosis of sepsis and could potentially serve as novel research targets for sepsis, offering valuable insights for the development of lysosome-targeted therapy. The clinical trial registration number is ChiCTR1900021261, and the registration date is February 4, 2019.

Application of Medical Adhesive in Emergency Treatment of Head and Face Injury.

PURPOSE: The aim of this study was to analyze the application effect of medical adhesive in emergency surgical scalp and facial skin treatment. To explore the better application of medical adhesive in emergency work. METHODS: A total of 180 patients with scalp and facial skin laceration admitted to the emergency department of the Affiliated Hospital of Southwest Medical University from August 2018 to August 2019 were selected. The patients were divided into the control group (n = 70) and the treatment group (n = 110) using the random number table method. The control group was treated with debridement, local anesthesia, and suture technique without medical adhesive, whereas the treatment group was treated with medical adhesive after debridement without local anesthesia. The operation time, pain degree, total cost, and satisfaction of the 2 groups were compared. RESULTS: The operation time in treatment group was shorter than that in control group (12.0 ±â€Š2.6 minutes versus 17.7 ±â€Š2.5 minutes, P < 0. 05), and the visual simulation score (VAS) of treatment group were lower than that in control group (2.45 ±â€Š1.63 versus 5.66 ±â€Š1.65, P < 0. 05), and the total cost in treatment group was higher than that in control group (¥906.6 ±â€Š69.0 versus ¥329.8 ±â€Š76.4, P < 0. 05). In control group 17 not satisfiedpatients, satisfied 37 patients, and 16 patients felt excellent; in treatment group, there are 7 not satisfiedpatients, 21 satisfied patients, and 82 felt excellent. Patients' satisfaction was compared between the 2 groups, the difference was statistically significant (P < 0.05). CONCLUSIONS: The results suggest that Medical adhesive used in scalp skin trauma and facial wounds had the advantages of shorter operation time, less pain, and higher postoperative satisfaction of patients, but higher cost than conventional suture. Medical adhesive has obvious advantages and high feasibility in the treatment of scalp and facial skin wounds.

The efficacy of tranexamic acid for brain injury: A meta-analysis of randomized controlled trials.

BACKGROUND: Tranexamic acid shows some treatment efficacy for traumatic brain injury. This systematic review and meta-analysis is conducted to investigate the efficacy of tranexamic acid for traumatic brain injury. METHODS: The databases including PubMed, EMbase, Web of science, EBSCO, and Cochrane library databases are systematically searched for collecting the randomized controlled trials (RCTs) regarding the efficacy of tranexamic acid for traumatic brain injury. RESULTS: This meta-analysis has included six RCTs. Compared with placebo group in patients with traumatic brain injury, tranexamic acid results in remarkably reduced mortality (risk ratio (RR) = 0.91; 95% confidence interval (CI) = 0.85 to 0.97; P = 0.004) and growth of hemorrhagic mass (RR = 0.78; 95% CI = 0.61 to 0.99; P = 0.04), but has no important impact on neurosurgery (RR = 0.99; 95% CI = 0.85 to 1.15; P = 0.92), extracranial surgery (RR = 1.00; 95% CI = 0.97 to 1.04; P = 0.99), unfavorable outcome (Glasgow Outcome Scale, GOS) (RR = 0.72; 95% CI = 0.47-1.11; P = 0.14), pulmonary embolism (RR = 1.86; 95% CI = 0.42-8.29; P = 0.42), and deep venous thrombosis (RR = 0.97; 95% CI = 0.64-1.47; P = 0.88). CONCLUSIONS: Tranexamic acid is associated with substantially reduced mortality and growth of hemorrhagic mass in patients with traumatic brain injury, but the need of neurosurgery and extracranial surgery, as well as the risk of unfavorable outcome (GOS) are similar between tranexamic acid and placebo.

Bioinformatics Analysis of Gene Expression Profiles for Risk Prediction in Patients with Septic Shock.

BACKGROUND Septic shock occurs when sepsis is associated with critically low blood pressure, and has a high mortality rate. This study aimed to undertake a bioinformatics analysis of gene expression profiles for risk prediction in septic shock. MATERIAL AND METHODS Two good quality datasets associated with septic shock were downloaded from the Gene Expression Omnibus (GEO) database, GSE64457 and GSE57065. Patients with septic shock had both sepsis and hypotension, and a normal control group was included. The differentially expressed genes (DEGs) were identified using OmicShare tools based on R. Functional enrichment of DEGs was analyzed using DAVID. The protein-protein interaction (PPI) network was established using STRING. Survival curves of key genes were constructed using GraphPad Prism version 7.0. Each putative central gene was analyzed by receiver operating characteristic (ROC) curves using MedCalc statistical software. RESULTS GSE64457 and GSE57065 included 130 RNA samples derived from whole blood from 97 patients with septic shock and 33 healthy volunteers to obtain 975 DEGs, 455 of which were significantly down-regulated and 520 were significantly upregulated (P<0.05). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis identified significantly enriched DEGs in four signaling pathways, MAPK, TNF, HIF-1, and insulin. Six genes, WDR82, ASH1L, NCOA1, TPR, SF1, and CREBBP in the center of the PPI network were associated with septic shock, according to survival curve and ROC analysis. CONCLUSIONS Bioinformatics analysis of gene expression profiles identified four signaling pathways and six genes, potentially representing molecular mechanisms for the occurrence, progression, and risk prediction in septic shock.

The protective effects of HGF against apoptosis in vascular endothelial cells caused by peripheral vascular injury.

Closed vascular injuries have danger of developing critical tissue ischemia with a high risk of amputation and limb loss. However, limited effective strategies exist at present. In this study, we investigate the role of hepatocyte growth factor (HGF) on apoptosis of vascular endothelial cells (VECs). First, apoptosis of VECs was induced by hypoxia treatment with or without HGF. Annexin V-7AAD apoptosis assay revealed that HGF overexpression significantly reduced VEC apoptosis. Then a closed peripheral vascular injury animal model was created by balloon catheter in female New Zealand rabbit. The VECs overexpressing HGF were injected into balloon injury rabbit. TUNEL and caspase 3 staining assays revealed that balloon catheter-treated artery showed severe intimal hyperplasia, with a 70% apoptosis rate (P < 0.05, vs. sham group), while HGF-overexpressing group showed a significant reduction of apoptosis. Furthermore, the expressions of Fas/FasL and their downstream apoptosis-related proteins were significantly decreased in HGF-overexpressing group when compared with those in balloon injury group as detected by western blot analysis. All these data indicated that HGF exhibited anti-apoptotic effects during VEC apoptosis, which might be mediated by the inhibition of Fas/FasL pathway. Our study provides a theoretic basis for the application of HGF in the gene therapy of closed peripheral vascular injury.

Integrative analysis of metabolomics and transcriptomics to uncover biomarkers in sepsis.

To utilize metabolomics in conjunction with RNA sequencing to identify biomarkers in the blood of sepsis patients and discover novel targets for diagnosing and treating sepsis. In January 2019 and December 2020, blood samples were collected from a cohort of 16 patients diagnosed with sepsis and 11 patients diagnosed with systemic inflammatory response syndrome (SIRS). Non-targeted metabolomics analysis was conducted using liquid chromatography coupled with mass spectrometry (LC-MS/MS technology), while gene sequencing was performed using RNA sequencing. Afterward, the metabolite data and sequencing data underwent quality control and difference analysis, with a fold change (FC) greater than or equal to 2 and a false discovery rate (FDR) less than 0.05.Co-analysis was then performed to identify differential factors with consistent expression trends based on the metabolic pathway context; KEGG enrichment analysis was performed on the crossover factors, and Meta-analysis of the targets was performed at the transcriptome level using the public dataset. In the end, a total of five samples of single nucleated cells from peripheral blood (two normal controls, one with systemic inflammatory response syndrome, and two with sepsis) were collected and examined to determine the cellular location of the essential genes using 10× single cell RNA sequencing (scRNA-seq). A total of 485 genes and 1083 metabolites were found to be differentially expressed in the sepsis group compared to the SIRS group. Among these, 40 genes were found to be differentially expressed in both the metabolome and transcriptome. Functional enrichment analysis revealed that these genes were primarily involved in biological processes related to inflammatory response, immune regulation, and amino acid metabolism. Furthermore, a meta-analysis identified four genes, namely ITGAM, CD44, C3AR1, and IL2RG, which were highly expressed in the sepsis group compared to the normal group (P < 0.05). Additionally, scRNA-seq analysis revealed that the core genes ITGAM and C3AR1 were predominantly localized within the macrophage lineage. The primary genes ITGAM and C3AR1 exhibit predominant expression in macrophages, which play a significant role in inflammatory and immune responses. Moreover, these genes show elevated expression levels in the plasma of individuals with sepsis, indicating their potential as valuable subjects for further research in sepsis.

Metabolomics-based study of potential biomarkers of sepsis.

The purpose of our study was to explore potential characteristic biomarkers in patients with sepsis. Peripheral blood specimens from sepsis patients and normal human volunteers were processed by liquid chromatography-mass spectrometry-based analysis. Outlier data were excluded by principal component analysis and orthogonal partial least squares-discriminant analysis using the metabolomics R software package metaX and MetaboAnalyst 5.0 ( https://www.metaboanalyst.ca/home.xhtml ) online analysis software, and differential metabolite counts were identified by using volcano and heatmaps. The obtained differential metabolites were combined with KEGG (Kyoto Gene and Kyoto Encyclopedia) analysis to screen out potential core differential metabolites, and ROC curves were drawn to analyze the changes in serum metabolites in sepsis patients and to explore the potential value of the metabolites in the diagnosis of sepsis patients. By metabolomic analysis, nine differential metabolites were screened for their significance in guiding the diagnosis and differential diagnosis of sepsis namely: 3-phenyl lactic acid, N-phenylacetylglutamine, phenylethylamine, traumatin, xanthine, methyl jasmonate, indole, l-tryptophan and 1107116. In this study, nine metabolites were finally screened based on metabolomic analysis and used as potential characteristic biomarkers for the diagnosis of sepsis.

Screening of core genes prognostic for sepsis and construction of a ceRNA regulatory network.

OBJECTIVE: To screen out core genes potentially prognostic for sepsis and construct a competing endogenous RNA (ceRNA) regulatory network. METHODS: Subjects included in this project were 23 sepsis patients and 10 healthy people. RNA-seq for lncRNA, miRNA and mRNA was performed in the peripheral blood samples. Differentially expressed RNAs (DER) were screened out for further analysis. GO annotation and GSEA functional clustering were performed to view the functional enrichment of DEmRNAs. Core genes of prognostic significance were screened out with the weighted correlation network analysis (WGCNA). Meta-analysis and Survival analysis was devised in different microarray datasets. RT-qPCR was conducted to validate these core genes. A ceRNA network was accordingly constructed according to the correlation analysis and molecular interaction prediction. RESULTS: RNA-seq and differential analysis screened out 1,044 DEmRNAs, 66 DEmiRNAs and 155 DElncRNAs. The GO and GSEA analysis revealed that DEmRNAs are mainly involved in inflammatory response, immune regulation, neutrophil activation. WGCNA revealed 4 potential core genes, including CD247, IL-2Rß, TGF-ßR3 and IL-1R2. In vitro cellular experiment showed up-regulated expression of IL-1R2 while down-regulated of CD247, IL-2Rß, TGF-ßR3 in sepsis patients. Correspondingly, a ceRNA regulatory network was build based on the core genes, and multiple lncRNAs and miRNAs were identified to have a potential regulatory role in sepsis. CONCLUSION: This study identified four core genes, including CD247, IL-1R2, IL-2Rß and TGF-ßR3, with potential to be novel biomarkers for the prognosis of sepsis. In the meantime, a ceRNA network was constructed aiming to guide further study on prognostic mechanism in sepsis.

Screening of potential immune-related genes expressed during sepsis using gene sequencing technology.

To screen potential pivotal targets in sepsis through peripheral blood. Septic patients (n = 23) and healthy volunteers (n = 10) were enrolled according to SEPSIS 3.0. Peripheral blood was collected within 24 h of enrollment, RNA-seq was performed on the peripheral blood. The sequencing data was screened for DEGs (p < 0.01; logFC ≥ 2). PPI, WGCNA and survival curve analysis were used to identify potential targets. Then, 5 PBMC samples were conducted by single-cell sequencing for cell lineage location. Finally, mouse sepsis model and clinic samples were performed to verify the targets gene using RNA-seq and RT-PCR, respectively. Compared to the control group, 1007 DEGs were found in septic group. BCL9L, BCL11B, CD247, CD96, MAFG and SAMD3 were in the core of network. These six genes correlated to the survival rate of septic patients and they were mainly expressed in T cells, except that MAFG was located in monocyte cell. The expression levels of six key genes were confirmed by animal and clinical samples. BCL9L, BCL11B, CD247, CD96 and SAMD3 were decreased in sepsis and mainly expressed in the T cell; while MAFG increased in sepsis and localizes to monocytes. These genes may be therapeutic targets for sepsis.

[The role of transferrin receptor CD71 as a diagnostic and prognostic biomarker in sepsis].

OBJECTIVE: To find new biomarkers for the diagnosis and prognosis of sepsis through analyzing the differential expression protein in sepsis by proteomics and bioinformatics analysis and enzyme linked immunosorbent assay (ELISA). METHODS: Patients with sepsis admitted to the emergency department of the Affiliated Hospital of Southwest Medical University from January to December 2019 were enrolled. And meanwhile, healthy volunteers who had normal physical examinations were included as the control group. Blood samples from two groups were collected. The samples were randomly selected for the protein concentration by data independent acquisition (DIA). Bioinformatics method was used in differentially expressed proteins by gene ontology (GO) pathway, enrichment analyses, groups meta-analysis and survival curves construction. ELISA method was used to verified marker screened. Then the data of transferrin receptor CD71 and the clinical data of procalcitonin (PCT), C-reactive protein (CRP) and blood lactic acid (Lac) were collected to construct receiver operator characteristic curve (ROC curve), and biomarker was screened for diagnostic and prognostic of sepsis. RESULTS: The result of DIA showed that 71 differentially expressed proteins were screened out from sepsis group, 6 proteins were down-regulated and 65 proteins were up-regulated. Those differentially expressed proteins were enriched in the inflammatory response, response to stress, leukocyte migration in the GO pathway and enrichment analyses. The meta-analysis showed that the expression level of CD71 was higher in sepsis group than normal control group [standardized mean difference (SMD) = -0.47, 95% confidence interval (95%CI) was -0.93 to 0.00, P < 0.01], the expression level of CD71 was higher in non-survivor group than survivor group (SMD = -0.44, 95%CI was -0.70 to -0.18, P = 0.63). Survival curve showed that the expression of CD71 was inversely correlated to survival rates, the patients with a lower expression had higher survival rates (P = 0.000 34); the ELISA showed that the level of CD71 was higher in sepsis group than normal control group (nmol/L: 156.83±84.71 vs. 87.99±47.89, P < 0.05), the level of CD71 was higher in non-survivor group than survivor group (nmol/L: 219.63±125.59 vs. 130.97±40.45, P < 0.05). The area under the ROC curve (AUC) of CD71 in diagnostic performance of sepsis was 0.790 (sensitivity was 65.1%, specificity was 90.0%), the AUC of CD71 in prognostic performance of sepsis was 0.744 (sensitivity was 57.1%, specificity was 94.1%); CD71 had a better prognostic performance than PCT (AUC = 0.547, sensitivity was 64.3%, specificity was 55.9%), CRP (AUC = 0.594, sensitivity was 64.3%, specificity was 61.8%), Lac (AUC = 0.540, sensitivity was 42.9%, specificity was 82.4%). CONCLUSIONS: CD71 had a great value of diagnostic and prognostic performance in sepsis, and it was expected to be a potential biomarker for sepsis.

[Matrix metalloproteinase 14 and plasma kallikrein 1 may be potential biomarkers in the diagnosis and treatment of sepsis: a proteomics and bioinformatics analysis].

OBJECTIVE: To analyze protein profiles in septic patients, and to find potential new targets for the diagnosis and treatment of sepsis. METHODS: A cross sectional observational study was conducted. From January to December 2019, 12 septic patients and 9 healthy volunteers were recruited in the emergency intensive care unit (EICU) of the emergency department of the Affiliated Hospital of Southwest Medical University. The peripheral blood of the two groups was collected for protein mass spectrometry analysis, and the data-independent acquisition technology was used to obtain the expression data of each protein. The obtained data was imported into the online network tool Integrated Differential Expression and Pathway analysis (IDEP2), the data underwent ID converted and were homogenized to verify their comparability, and then principal component analysis was used to eliminate outlier data. Then data with P < 0.05, log2fold change (FC) > 1 or log2FC < -1 were considered to have a statistically significant difference, and the differential proteins were screened out. On the DAVID website, the screened differential proteins would be analyzed by gene ontology (GO), and the biological process, cellular components, and molecular function of the proteins would be analyzed. Protein enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Protein-protein interaction (PPI) analysis was performed through the Search Tool for the Retrieval of Interacting Genes Database (STRING) website to find closely related proteins. RESULTS: The data in this study were shown to be comparable after normalization. A total of 125 differential proteins were screened, of which 99 were up-regulated and 26 were down-regulated. GO enrichment analysis discovered that these proteins were mainly extracellular, with cellular regulatory functions and catalytic functions involved in biological regulation, metabolic process and immune process. KEGG pathway analysis suggested that these proteins were involved in amino acid, carbohydrate metabolism and immune-related pathways. PPI analysis showed that key proteins included matrix metalloproteinase 14 (MMP14), fibulin 1 (FBLN1), plasma kallikrein 1 (KLKB1), etc., and finally screened out MMP14 and KLKB1, which were closely related to inflammation and immunity. Both might be potential new targets for early diagnosis and treatment of sepsis. CONCLUSIONS: MMP14 and KLKB1 may be potential biomarkers for the diagnosis, treatment and prognosis of sepsis.

Proteomics Combined with RNA Sequencing to Screen Biomarkers of Sepsis.

Purpose: To screen biomarkers in the serum of patients with sepsis by proteomics combined with RNA sequencing technology, and to find new diagnostic and therapeutic targets for sepsis. Patients and Methods: Blood samples of 22 sepsis patients (sepsis group) and 10 healthy volunteers (normal group) were collected from January 2019 to December 2020. Data-independent acquisition (DIA) method was employed for protein profiling, RNA sequencing was employed for gene sequencing. Subsequently, quality control and differential analysis (FC≥2; FDR<0.05) of DIA data and RNA sequencing data were performed. Then we identified expression trend-consistent divergence factors by nine-quadrant analysis; subsequent protein-protein interaction (PPI) and gene ontology (GO) functional enrichment analysis of intersection factors was performed, and meta-analysis of targets at transcriptome level was implemented using public datasets. Finally, five Peripheral blood mononuclear cell (PBMC) samples (NC=2; SIRS=1; SEPSIS =2) were collected, and cell localization analysis of core genes was performed by 10× single-cell RNA sequencing (scRNA-seq). Results: Compared with the normal group, there were 4681 differentially expressed genes and 202 differentially expressed proteins in the sepsis group. Among them, 25 factors were expressed in both proteome and transcriptome, and the analysis of PPI and GO found that they were mainly involved in biological processes such as white blood cell and neutrophil response, inflammatory and immune response. Four core genes GSTO1, C1QA, RETN, and GRN were screened by meta-analysis, all of which were highly expressed in the sepsis group compared with the normal group (P<0.05); scRNA-seq showed the core genes were mainly localized in macrophage cell lines. Conclusion: The core genes GSTO1, C1QA, RETN and GRN are mainly expressed in macrophages, widely involved in inflammation and immune responses, and are highly expressed in plasma in the sepsis, suggesting that they may become potential research targets for sepsis.

Omega-3 fatty acids plus vitamin for women with gestational diabetes or prediabetes: a meta-analysis of randomized controlled studies.

INTRODUCTION: Omega-3 fatty acids plus vitamin (e.g. vitamin D and E) may be beneficial to treat gestational diabetes mellitus (GDM), and we aimed to study the influence of omega-3 fatty acids plus vitamin versus placebo on the treatment efficacy of GDM. METHODS: We searched the databases including PubMed, Embase, and the Cochrane Central Register of Controlled Trials, and randomized controlled trials (RCTs) assessing the influence of omega-3 fatty acids and vitamins combination supplementation versus placebo on metabolic status of GDM were included. RESULTS: Five RCTs were included in the meta-analysis. Compared with control intervention for women with GDM or prediabetes, omega-3 fatty acids plus vitamin substantially reduced fasting plasma glucose (FPG, mean difference [MD] = -11.25; 95% confidence intervals [CI] = -13.73 to -8.77; p < .00001), insulin (MD=-6.16; 95% CI=-7.92 to -4.39; p < .00001), homeostasis model of assessment-insulin resistance (HOMA-IR, MD = 173.51; 95% CI = 164.72 to 182.30; p < .00001) and triglycerides (MD = 173.51; 95% CI = 164.72 to 182.30; p < .00001), as well as increased total antioxidant capacity (TAC, MD = 173.51; 95% CI = 164.72 to 182.30; p < .00001), but revealed no significant impact on total cholesterol (MD = 173.51; 95% CI = 164.72 to 182.30; p < .00001), low­density lipoprotein cholesterol (LDL-C, MD = 173.51; 95% CI = 164.72 to 182.30; p < .00001), preterm delivery (OR = 173.51; 95% CI = 164.72 to 182.30; p < .00001) or macrosomia > 4000 g (OR = 173.51; 95% CI = 164.72 to 182.30; p < .00001). CONCLUSIONS: The supplementation of omega-3 fatty acids in combination with vitamin D or E can improve glycemic control, alleviate oxidative stress, and reduce triglycerides, but had no effects on total cholesterol, preterm delivery or macrosomia > 4000 g in women with GDM or prediabetes.

Mechanisms of Panax Ginseng on Treating Sepsis by RNA-Seq Technology.

Purpose: To explore the potential active targets and mechanisms of Panax Ginseng in the treatment of sepsis using network pharmacology and RNA-seq technology. Patients and Methods: Patients with sepsis and healthy volunteers were collected according to SEPSIS 3.0, and their peripheral blood was used for RNA-seq analysis. The active ingredients and targets of Panax Ginseng were obtained using the TCMSP database, PPI and GO analysis were performed for disease-drug intersection targets. Then, we used Meta-analysis to screen core genes. Finally, single-cell RNA-seq was used to perform cell localization analysis on core genes. Results: RNA-seq analysis collected 4521 sepsis-related genes, TCMSP database obtained 86 Panax Ginseng active ingredients and their 294 active targets. PPI and GO analysis showed intersection targets were closely linked, and mainly involved in cellular response to chemical stress, response to drug and molecule of bacterial origin, etc. Then, core targets, IL1B, ALOX5, BCL2 and IL4R, were sorted by Meta-analysis, and all four genes have high expression in the sepsis survivor group compared to the sepsis non-survivor group; single-cell RNA-seq revealed that IL1B was mainly localized in macrophages, ALOX5 was mainly localized in macrophages and B cells, BCL2 was mainly localized in natural killer cells, T cells and B cells, IL4R was widely distributed in immune cells. Finally, according to the correspondence between the active ingredients and targets of Panax Ginseng in TCMSP database, we found that Ginsenoside rh2 regulates the expression of IL1B, Ginsenoside rf regulates the expression of IL1B and IL4R, Kaempferol regulates the expression of ALOX5 and BCL2, and ß-sitosterol regulates the expression of BCL2. Conclusion: Ginsenoside rh2, Ginsenoside rf, Kaempferol and ß-sitosterol may produce anti-sepsis effects by regulating the expression of IL1B, ALOX5, BCL2 and IL4R, thus improving the survival rate of sepsis patients.

[Hepatitis A virus cell membrane protein receptor 2 promotes endotoxin tolerance in mouse macrophages].

OBJECTIVE: To screen out the potential key genes of endotoxin tolerance (ET), and to provide theoretical and experimental evidence for treatment and prognosis of sepsis. METHODS: (1) Experiment 1 (gene chip and bioinformatics analysis): ET related data set GSE47783 was downloaded from the Gene Expression Omnibus (GEO). The data set was obtained from lipopolysaccharide (LPS) stimulated mouse macrophages to establish sepsis model (LPS group) and ET model (ET group). IDEP 0.92 software was used to screen differential expressed gene (DEG) between the two groups, analyze gene ontology (GO), and locate the main functions and signaling pathways of differential genes. The protein-protein interaction (PPI) network of DEG was constructed by the Search Tool for the Retrieval of Interacting Genes Database (STRING) to screen core genes hepatitis A virus cell membrane protein receptor 2 (HAVCR2) for following up validation study. (2) Experiment 2 (reproduction of mouse macrophage RAW264.7 model): RAW264.7 cells were cultured in vitro, the ET model (ET group, cells were cultured with 10 µg/L LPS for 24 hours and then with 100 µg/L LPS for 4 hours) and sepsis model (LPS group, cells were cultured with 100 µg/L LPS for 4 hours) were reproduced by LPS stimulation. Phosphate buffer saline (PBS) group was given equal volume of solvent PBS for 4 hours. The mRNA and protein expressions of HAVCR2 were detected by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) and Western blotting. (3) Experiment 3 (RAW264.7 cells transfected with HAVCR2 lentiviral vector): to further clarify whether HAVCR2 was involved in the formation of ET, after knockdown of HAVCR2 in RAW264.7 cells by lentiviral short hairpin RNA (shRNA) technology, the ET model (HAVCR2--ET group) was constructed again, and the control group (ET group) without knockdown of HAVCR2 was set up. RT-qPCR method was used to detect the mRNA expressions of macrophage polarization key proteins [arginase 1 (ARG1), CD206, tumor necrosis factor-α (TNF-α), interleukin-1ß (IL-1ß), nitric oxide synthase 2 (NOS2)] in cells. RESULTS: (1) Experiment 1: a total of 1 013 DEG were identified, compared with LPS group, 521 genes were up-regulated and 492 genes were down-regulated in ET group. The function of these DEG was to increase biosynthesis and reduce inflammatory reaction. Signal pathways were mainly enriched in Janus kinase/signal transducers and activators of transcription (JAK/STAT), NOD like receptor, Toll-like receptor (TLR), TNF, hypoxia inducible factor-1 (HIF-1). The first up-regulated HAVCR2 in the ET group was selected as the target of the study. (2) Experiment 2: the results of in vitro experiment showed that the mRNA expression of HAVCR2 after high-dose LPS stimulation was down-regulated as compared with PBS group, and the mRNA expression of HAVCR2 in ET group was significantly higher than that in LPS group (2-ΔΔCT: 1.10±0.10 vs. 0.60±0.10, P < 0.05). The results of Western blotting were consistent with RT-qPCR results. (3) Experiment 3: the mRNA expressions of ARG1 and CD206 in HAVCR2--ET group were significantly lower than those in ET group [ARG1 mRNA (2-ΔΔCT): 0.50±0.10 vs. 1.00±0.10, CD206 (2-ΔΔCT): 0.73±0.10 vs. 1.00±0.10], and the mRNA expressions of TNF-α and IL-1ß were significantly higher than those in ET group [TNF-α mRNA (2-ΔΔCT): 2.20±0.10 vs. 1.00±0.10, IL-1ß mRNA (2-ΔΔCT): 9.00±0.10 vs. 1.00±0.10], with significant differences (all P < 0.05). There was no significant difference in the expression of NOS2 mRNA between the two groups. CONCLUSIONS: HAVCR2 is involved in the regulation of inflammatory factors downstream of sepsis and the formation of ET, which is expected to become a new therapeutic target of sepsis.

Screening of key genes related to the prognosis of mouse sepsis.

Sepsis is a common clinical disease with high mortality, and patients with sepsis have varied prognoses. Researchers need to explore the underlying mechanisms that determine the prognosis of sepsis. Hence, a mouse model was used to evaluate new potential prognostic markers of sepsis. Mice were randomly divided into low-dose group (n=3, lipopolysaccharides [LPS], 20 mg/kg) and high-dose group (n=3; LPS, 40 mg/kg). Total RNA was extracted from the peripheral blood of mice, and samples were then subjected to RNA sequencing. When complete data were normalized, the high-dose group and low-dose group were screened for differentially expressed genes (DEGs, log2FC ≥ 1 and q value ≤ 0.05). DEGs were analyzed by gene ontology enrichment, and potential core genes were screened using protein-protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA). Moreover, the survival data in GSE65682 were used to observe the correlation between core genes and prognosis. A total of 967 DEGs were identified in the low-dose group, of which 390 were up-regulated and 577 were down-regulated. These genes were mainly enriched in white blood cell activation, lymphocyte activation, immune system response etc. LCK, ZAP70, ITK, CD247, and DOCK2 were found at the core of PPI network, while WGCNA found that interferon-inducible protein 35 (IFI35), ITGB3, and mediator complex subunit 25 (MED25) may be potential core genes. It was demonstrated that CD247, DOCK2, IFI35, ITK, and LCK core genes were positively correlated with prognosis based on GSE65682. CD247, DOCK2, IFI35, ITK, LCK, and MED25 might be important targets affecting the prognosis of sepsis.

Effect of hnRNPA2/B1 on the proliferation and apoptosis of glioma U251 cells via the regulation of AKT and STAT3 pathways.

Glioma is the most common malignant tumor in the human central nervous system. Although heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNPA2/B1) was previously presumed to be a tumor-promoting gene, the relationship between hnRNPA2/B1 and glioma is unclear. Targeting hnRNPA2/B1 interference in glioma cells can significantly inhibit proliferation and increase apoptosis of human glioma cells in vitro. In a tumor xenograft model, knockdown of hnRNPA2/B1 suppressed tumor growth in glioma cells in vivo. In terms of a mechanism, the knockdown of hnRNPA2/B1 led to inactivation of the AKT and STAT3 signaling pathways, which ultimately reduced the expression of B-cell lymphoma-2 (Bcl-2), CyclinD1 and proliferating cell nuclear antigen (PCNA). Collectively, these data suggest that the inhibition of hnRNPA2/B1 can reduce the growth of gliomas through STAT3 and AKT signaling pathways, and this inhibition is expected to be a therapeutic target for gliomas.

Emodin Retarded Renal Fibrosis Through Regulating HGF and TGFß-Smad Signaling Pathway.

BACKGROUND: Renal fibrosis is a frequently occurring type of chronic kidney disease that can cause end-stage renal disease. It has been verified that emodin or HGF can inhibit the development of renal fibrosis. However, the antifibrotic effect of emodin in combination with HGF remains unclear. METHODS: Cell viability was detected with CCK8. Gene and protein expression in HK2 cells was detected by qRT-PCR and Western blot, respectively. Moreover, a unilateral ureteral obstruction-induced mouse model of renal fibrosis was established for investigating the antifibrotic effect of emodin in combination with HGF in vivo. RESULTS: HGF notably increased the expression of collagen II in TGFß-treated HK2 cells. In addition, HGF-induced increase in collagen II expression was further enhanced by emodin. In contrast, fibronectin, αSMA and Smad2 expression in TGFß-stimulated HK2 cells was significantly inhibited by HGF and further decreased by combination treatment (emodin plus HGF). Moreover, we found that combination treatment exhibited better antifibrotic effects compared with emodin or HGF in vivo. CONCLUSION: These data demonstrated that emodin plus HGF exhibited better antifibrotic effects compared with emodin or HGF. As such, emodin in combination with HGF may serve as a new possibilty for treatment of renal fibrosis.