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Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric sepsis by integrating bioinformatics and machine learning

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World Journal of Pediatrics 2023年第11期19卷 1094-1103页

作者： Wen‑Yuan Zhang Zhong‑Hua Chen Xiao‑Xia An Hui Li Hua‑Lin Zhang Shui‑Jing Wu Yu‑Qian Guo Kai Zhang Cong‑Li Zeng Xiang‑Ming Fang Department of Anesthesiology and Intensive Care School of MedicineThe First Affiliated HospitalZhejiang UniversityQingChun Road 79Hangzhou 310003China Department of Anesthesiology Shaoxing People’s Hospital(Shaoxing HospitalZhejiang University School of Medicine)Shaoxing 312000China Department of Anesthesiology Vagelos College of Physicians and SurgeonsColumbia UniversityNew YorkNYUSA

Background Pediatric sepsis is a complicated condition characterized by life-threatening organ failure resulting from a dysregulated host response to infection in children.It is associated with high rates of morbidity and mortality,and rapid detection and administration of antimicrobials have been emphasized.The objective of this study was to evaluate the diagnostic biomarkers of pediatric sepsis and the function of immune cell infiltration in the development of this illness.Methods Three gene expression datasets were available from the Gene Expression Omnibus collection.First,the differentially expressed genes(DEGs)were found with the use of the R program,and then gene set enrichment analysis was carried out.Subsequently,the DEGs were combined with the major module genes chosen using the weighted gene co-expression network.The hub genes were identified by the use of three machine-learning algorithms:random forest,support vector machine-recursive feature elimination,and least absolute shrinkage and selection operator.The receiver operating characteristic curve and nomogram model were used to verify the discrimination and efficacy of the hub genes.In addition,the inflammatory and immune status of pediatric sepsis was assessed using cell-type identification by estimating relative subsets of RNA transcripts(CIBERSORT).The relationship between the diagnostic markers and infiltrating immune cells was further studied.Results Overall,after overlapping key module genes and DEGs,we detected 402 overlapping genes.As pediatric sepsis diagnostic indicators,CYSTM1(AUC=0.988),MMP8(AUC=0.973),and CD177(AUC=0.986)were investigated and demonstrated statistically significant differences(Psepsis.Additionally,all diagnostic characteristics may correlate with immune cells to varying degrees.Conclusions The candidate hub genes(CD177,CYSTM1,and MMP8)were identifi

关键词： paediatric sepsis Bioinformatics Machine-Learning Biomarkers Immune cell infiltration

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