{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T14:18:31Z","timestamp":1785766711300,"version":"3.56.0"},"reference-count":75,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T00:00:00Z","timestamp":1761782400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Early diagnosis of sepsis is essential to reducing mortality. Immune cells and telomeres play important roles in sepsis, but their mechanisms were still unclear. This study aimed to explore the value of immune cells and telomere-related genes in sepsis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this study, the transcriptomic data with sepsis and control samples were obtained from public database. Multiple methods including differential expression analysis, immune infiltration analysis, weighted gene co-expression network analysis (WGCNA), 101-machine learning algorithm combinations were used to identify biomarkers which related to the immune cells and telomere. Afterwards, a nomogram was constructed to assess the clinical predictive value of biomarkers. In addition, gene set enrichment analysis (GSEA), regulatory network construction and drug prediction analysis were adopted to demonstrate the role of biomarkers in sepsis. The key cells were also identified using a single-cell dataset. Finally, the expression of biomarkers was further validated in clinical samples by reverse transcription quantitative polymerase chain reaction (RT-qPCR).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      This study obtained a total of 4 biomarkers (\n                      <jats:italic>MYO10<\/jats:italic>\n                      ,\n                      <jats:italic>SULT1B1<\/jats:italic>\n                      ,\n                      <jats:italic>MKI67<\/jats:italic>\n                      , and\n                      <jats:italic>CREB5<\/jats:italic>\n                      ), and the analysis of nomogram showed that the biomarkers had good clinical predictive value to sepsis. The enrichment analysis results revealed that the four biomarkers were enriched in the ribosome pathway. Besides, a lncRNAs-miRNAs-biomarkers network was constructed for the four biomarkers. Finally, we obtained a candidate drug (MS-275) and a key cell (CD16+ and CD14+ monocytes) respectively based on drug prediction and cell identification analysis. In addition, we found that the expression levels of\n                      <jats:italic>CREB5<\/jats:italic>\n                      and\n                      <jats:italic>SULT1B1<\/jats:italic>\n                      had significant changes during the process of key cell differentiation. The RT-qPCR results showed biomarkers were upregulated in the sepsis group, consistent with the bioinformatics analysis results.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      This study identified 4 biomarkers, namely\n                      <jats:italic>MYO10<\/jats:italic>\n                      ,\n                      <jats:italic>SULT1B1<\/jats:italic>\n                      ,\n                      <jats:italic>MKI67<\/jats:italic>\n                      , and\n                      <jats:italic>CREB5<\/jats:italic>\n                      and explored the pathogenesis of sepsis, providing new insights for potential treatment strategies by integrating transcriptomic data and single-cell analysis.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2025.1638156","type":"journal-article","created":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T06:22:43Z","timestamp":1761805363000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Portfolio analysis of single-cell RNA-sequencing and transcriptomic data unravels immune cells and telomere-related biomarkers in sepsis"],"prefix":"10.3389","volume":"16","author":[{"given":"Dan","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiyi","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunhao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,10,30]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.0287","article-title":"The third international consensus definitions for sepsis and septic shock (Sepsis-3)","volume":"315","author":"Singer","year":"2016","journal-title":"Jama"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2025.1577105","article-title":"Sepsis-induced immunosuppression: mechanisms, biomarkers and immunotherapy","volume":"16","author":"Gao","year":"2025","journal-title":"Front Immunol"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201504-0781OC","article-title":"Assessment of global incidence and mortality of hospital-treated sepsis. Current estimates and limitations","volume":"193","author":"Fleischmann","year":"2016","journal-title":"Am J Respir Crit Care Med"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1080\/14737159.2020.1680285","article-title":"Molecular and biomarker-based diagnostics in early sepsis: current challenges and future perspectives","volume":"19","author":"Schenz","year":"2019","journal-title":"Expert Rev Mol Diagn"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1016\/j.immuni.2021.10.012","article-title":"The immunology of sepsis","volume":"54","author":"van der Poll","year":"2021","journal-title":"Immunity"},{"key":"B6","doi-asserted-by":"publisher","first-page":"1901044","DOI":"10.1183\/13993003.01044-2019","article-title":"Peripheral blood leukocyte telomere length is associated with survival of sepsis patients","volume":"55","author":"Liu","year":"2020","journal-title":"Eur Respir J"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1177\/1747493018778713","article-title":"Multisociety consensus quality improvement revised consensus statement for endovascular therapy of acute ischemic stroke","volume":"13","author":"Sacks","year":"2018","journal-title":"Int J Stroke: Off J Int Stroke Soc"},{"key":"B8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cpan.2024.11.001","article-title":"Advancing pharmaceutical research: A comprehensive review of cutting-edge tools and technologies","volume":"21","author":"Chen","year":"2024","journal-title":"Curr Pharm Anal"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.18632\/aging.204248","article-title":"New hallmarks of ageing: A 2022 copenhagen ageing meeting summary","volume":"14","author":"Schmauck-Medina","year":"2022","journal-title":"Aging"},{"key":"B10","doi-asserted-by":"publisher","first-page":"e170523216998","DOI":"10.2174\/1874467217666230517104426","article-title":"A network medical framework based on inflammatory genes to identify drug candidates for abdominal aortic aneurysms","volume":"17","author":"Niu","year":"2024","journal-title":"Curr Mol Pharmacol"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.2174\/0115665232294568240201073417","article-title":"Dissecting the mechanisms of intestinal immune homeostasis by analyzing T-cell immune response in crohn\u2019s disease and colorectal cancer","volume":"24","author":"Jiang","year":"2024","journal-title":"Curr Gene Ther"},{"key":"B12","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.cell.2020.03.022","article-title":"How machine learning will transform biomedicine","volume":"181","author":"Goecks","year":"2020","journal-title":"Cell"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-021-10058-4","article-title":"Machine learning in drug discovery: A review","volume":"55","author":"Dara","year":"2022","journal-title":"Artif Intell Rev"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1097\/js9.0000000000001516","article-title":"Single-cell and bulk rna-sequence identified fibroblasts signature and cd8 + T-cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine learning: bioinformatics multi-omics study","volume":"110","author":"Li","year":"2024","journal-title":"Int J Surg (London England)"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2023.1247131","article-title":"Integrated analysis of single-cell rna-seq and chipset data unravels panoptosis-related genes in sepsis","volume":"14","author":"Dai","year":"2023","journal-title":"Front Immunol"},{"key":"B16","first-page":"5093","article-title":"Dinucleotide repeat polymorphism at the D17s518 locus","volume":"19","author":"Couch","year":"1991","journal-title":"Nucleic Acids Res"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1002\/jlb.5ma0721-825r","article-title":"Dynamic changes in human single-cell transcriptional signatures during fatal sepsis","volume":"110","author":"Qiu","year":"2021","journal-title":"J Leukocyte Biol"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1016\/j.intimp.2025.114198","article-title":"Prognostic model of osteosarcoma based on telomere-related genes and analysis of immune characteristics","volume":"151","author":"Liu","year":"2025","journal-title":"Int Immunopharmacol"},{"key":"B19","doi-asserted-by":"publisher","first-page":"e3608","DOI":"10.1002\/jgm.3608","article-title":"Investigating the prognostic role of lncrnas associated with disulfidptosis-related genes in clear cell renal cell carcinoma","volume":"26","author":"Sun","year":"2024","journal-title":"J Gene Med"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-014-0550-8","article-title":"Moderated estimation of fold change and dispersion for rna-seq data with deseq2","volume":"15","author":"Love","year":"2014","journal-title":"Genome Biol"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btac409","article-title":"Ggtranscript: an R package for the visualization and interpretation of transcript isoforms using ggplot2","volume":"38","author":"Gustavsson","year":"2022","journal-title":"Bioinf (Oxford England)"},{"key":"B22","doi-asserted-by":"publisher","first-page":"e43","DOI":"10.1002\/imt2.43","article-title":"Complex heatmap visualization","volume":"1","author":"Gu","year":"2022","journal-title":"iMeta"},{"key":"B23","doi-asserted-by":"publisher","first-page":"2862","DOI":"10.3390\/ijms24032862","article-title":"Identification of anoikis-related subgroups and prognosis model in liver hepatocellular carcinoma","volume":"24","author":"Chen","year":"2023","journal-title":"Int J Mol Sci"},{"key":"B24","doi-asserted-by":"publisher","first-page":"84","DOI":"10.2174\/1389202924666230601122334","article-title":"Identification of potential genes and critical pathways in postoperative recurrence of crohn\u2019s disease by machine learning and wgcna network analysis","volume":"24","author":"Rajalingam","year":"2023","journal-title":"Curr Genomics"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.1089\/omi.2011.0118","article-title":"Clusterprofiler: an R package for comparing biological themes among gene clusters","volume":"16","author":"Yu","year":"2012","journal-title":"Omics: J Integr Biol"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.2174\/0109298665290166240426072642","article-title":"The features of shared genes among transcriptomes probed in atopic dermatitis, psoriasis, and inflammatory acne: S100a9 selection as the target gene","volume":"31","author":"Wang","year":"2024","journal-title":"Protein Pept Lett"},{"key":"B27","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1186\/s13148-019-0730-1","article-title":"Statistical predictions with glmnet","volume":"11","author":"Engebretsen","year":"2019","journal-title":"Clin Epigenet"},{"key":"B28","doi-asserted-by":"publisher","first-page":"e0274641","DOI":"10.1371\/journal.pone.0274641","article-title":"Dummy regression to predict dry fiber in agave lechuguilla torr. In two large-scale bioclimatic regions in Mexico","volume":"17","author":"L\u00f3pez-D\u00edaz","year":"2022","journal-title":"PloS One"},{"key":"B29","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1186\/s12967-020-02620-5","article-title":"Predicting 30-days mortality for mimic-iii patients with sepsis-3: A machine learning approach using xgboost","volume":"18","author":"Hou","year":"2020","journal-title":"J Trans Med"},{"key":"B30","doi-asserted-by":"publisher","first-page":"442","DOI":"10.3390\/biology12030442","article-title":"Weibull regression and machine learning survival models: methodology, comparison, and application to biomedical data related to cardiac surgery","volume":"12","author":"Cavalcante","year":"2023","journal-title":"Biology"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btab869","article-title":"Efficient gradient boosting for prognostic biomarker discovery","volume":"38","author":"Li","year":"2022","journal-title":"Bioinf (Oxford England)"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2022.990888","article-title":"Bioinformatics analysis to screen for genes related to myocardial infarction","volume":"13","author":"Yang","year":"2022","journal-title":"Front Genet"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-12-77","article-title":"Proc: an open-source package for R and S+ to analyze and compare roc curves","volume":"12","author":"Robin","year":"2011","journal-title":"BMC Bioinf"},{"key":"B34","doi-asserted-by":"publisher","first-page":"60","DOI":"10.3390\/ani12010060","article-title":"Worldwide traceability of antibiotic residues from livestock in wastewater and soil: A systematic review","volume":"12","author":"Robles-Jimenez","year":"2021","journal-title":"Anim: An Open Access J MDPI"},{"key":"B35","doi-asserted-by":"publisher","first-page":"325","DOI":"10.21037\/atm.2018.07.38","article-title":"Overview of model validation for survival regression model with competing risks using melanoma study data","volume":"6","author":"Zhang","year":"2018","journal-title":"Ann Trans Med"},{"key":"B36","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1186\/s12890-023-02684-1","article-title":"Recognition of refractory mycoplasma pneumoniae pneumonia among myocoplasma pneumoniae pneumonia in hospitalized children: development and validation of a predictive nomogram model","volume":"23","author":"Li","year":"2023","journal-title":"BMC Pulmonary Med"},{"key":"B37","doi-asserted-by":"publisher","DOI":"10.2174\/0115665232331353240911080642","article-title":"Pan-cancer single-cell analysis revealing the heterogeneity of cancer-associated fibroblasts in skin tumors","author":"Zhang","year":"2024","journal-title":"Curr Gene Ther"},{"key":"B38","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.916934","article-title":"Differentiation of T helper 17 cells may mediate the abnormal humoral immunity in iga nephropathy and inflammatory bowel disease based on shared genetic effects","volume":"13","author":"Qing","year":"2022","journal-title":"Front Immunol"},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.1101\/gr.1239303","article-title":"Cytoscape: A software environment for integrated models of biomolecular interaction networks","volume":"13","author":"Shannon","year":"2003","journal-title":"Genome Res"},{"key":"B40","doi-asserted-by":"publisher","first-page":"3573","DOI":"10.1016\/j.cell.2021.04.048","article-title":"Integrated analysis of multimodal single-cell data","volume":"184","author":"Hao","year":"2021","journal-title":"Cell"},{"key":"B41","doi-asserted-by":"publisher","DOI":"10.3389\/fphar.2023.1133145","article-title":"Single-cell transcriptomics reveals immune infiltrate in sepsis","volume":"14","author":"Tu","year":"2023","journal-title":"Front Pharmacol"},{"key":"B42","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.4402","article-title":"Reversed graph embedding resolves complex single-cell trajectories","volume":"14","author":"Qiu","year":"2017","journal-title":"Nat Methods"},{"key":"B43","doi-asserted-by":"publisher","DOI":"10.1097\/shk.0000000000002334","article-title":"The relationship between circulating immune cell phenotypes and sepsis: A mendelian randomization study","volume":"61","author":"Liu","year":"2024","journal-title":"Shock (Augusta Ga)"},{"key":"B44","doi-asserted-by":"publisher","DOI":"10.2119\/molmed.2016.00225","article-title":"Sepsis induces telomere shortening: A potential mechanism responsible for delayed pathophysiological events in sepsis survivors","volume":"22","author":"Oliveira","year":"2017","journal-title":"Mol Med (Cambridge Mass)"},{"key":"B45","doi-asserted-by":"publisher","first-page":"546598","DOI":"10.7554\/eLife.90603","article-title":"Hundreds of myosin 10s are pushed to the tips of filopodia and could cause traffic jams on actin","volume":"12","author":"Shangguan","year":"2024","journal-title":"eLife"},{"key":"B46","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1016\/j.cell.2023.12.003","article-title":"Cytoneme signaling provides essential contributions to mammalian tissue patterning","volume":"187","author":"Hall","year":"2024","journal-title":"Cell"},{"key":"B47","doi-asserted-by":"publisher","DOI":"10.1016\/j.celrep.2023.112531","article-title":"Myo10 regulates genome stability and cancer inflammation through mediating mitosis","volume":"42","author":"Mayca Pozo","year":"2023","journal-title":"Cell Rep"},{"key":"B48","doi-asserted-by":"publisher","DOI":"10.1111\/cas.15519","article-title":"Myo10 contributes to the Malignant phenotypes of colorectal cancer via rack1 by activating integrin\/src\/fak signaling","volume":"113","author":"Ou","year":"2022","journal-title":"Cancer Sci"},{"key":"B49","doi-asserted-by":"publisher","DOI":"10.1038\/s41589-025-02029-5","article-title":"Author correction: histone tyrosine sulfation by sult1b1 regulates H4r3me2a and gene transcription","author":"Yu","year":"2025","journal-title":"Nat Chem Biol"},{"key":"B50","doi-asserted-by":"publisher","DOI":"10.1038\/s41589-023-01267-9","article-title":"Histone tyrosine sulfation by sult1b1 regulates H4r3me2a and gene transcription","volume":"19","author":"Yu","year":"2023","journal-title":"Nat Chem Biol"},{"key":"B51","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbc.2024.105721","article-title":"Histone H3y99sulf regulates hepatocellular carcinoma responding to hypoxia","volume":"300","author":"Yin","year":"2024","journal-title":"J Biol Chem"},{"key":"B52","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1186\/s12876-021-01984-2","article-title":"Correlation of mki67 with prognosis, immune infiltration, and T cell exhaustion in hepatocellular carcinoma","volume":"21","author":"Wu","year":"2021","journal-title":"BMC Gastroenterol"},{"key":"B53","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2021.687244","article-title":"The role of ki67 in evaluating neoadjuvant endocrine therapy of hormone receptor-positive breast cancer","volume":"12","author":"Zhang","year":"2021","journal-title":"Front Endocrinol"},{"key":"B54","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1186\/s13046-020-01673-0","article-title":"Creb5 promotes invasiveness and metastasis in colorectal cancer by directly activating met","volume":"39","author":"Wang","year":"2020","journal-title":"J Exp Clin Cancer Res: CR"},{"key":"B55","doi-asserted-by":"publisher","first-page":"e757","DOI":"10.1038\/tp.2016.4","article-title":"Mir-582-5p\/mir-590-5p targeted creb1\/creb5-nf-\u03bab signaling and caused opioid-induced immunosuppression in human monocytes","volume":"6","author":"Long","year":"2016","journal-title":"Trans Psychiatry"},{"key":"B56","doi-asserted-by":"publisher","first-page":"1240","DOI":"10.3390\/cells14161240","article-title":"Creb5 promotes the proliferation of neural stem\/progenitor cells in the rat subventricular zone via the regulation of nfix expression","volume":"14","author":"Yu","year":"2025","journal-title":"Cells"},{"key":"B57","doi-asserted-by":"publisher","DOI":"10.1085\/jgp.202313357","article-title":"Disease-associated kcnma1 variants decrease circadian clock robustness in channelopathy mouse models","volume":"155","author":"Dinsdale","year":"2023","journal-title":"J Gen Physiol"},{"key":"B58","doi-asserted-by":"publisher","DOI":"10.1038\/s41420-024-01873-z","article-title":"Creb5 promotes the proliferation and self-renewal ability of glioma stem cells","volume":"10","author":"Kim","year":"2024","journal-title":"Cell Death Discov"},{"key":"B59","doi-asserted-by":"publisher","first-page":"7295","DOI":"10.1038\/s41467-022-35010-0","article-title":"Creb5 coordinates synovial joint formation with the genesis of articular cartilage","volume":"13","author":"Zhang","year":"2022","journal-title":"Nat Commun"},{"key":"B60","doi-asserted-by":"publisher","first-page":"495","DOI":"10.3109\/00498254.2014.997325","article-title":"Characterization of bovine phenol sulfotransferases: evidence of a major role for sult1b1 in the liver","volume":"45","author":"Choughule","year":"2015","journal-title":"Xenobiot Fate Foreign Compounds Biol Syst"},{"key":"B61","doi-asserted-by":"publisher","DOI":"10.1242\/dev.201187","article-title":"Ribosome biogenesis and function in development and disease","volume":"150","author":"Ni","year":"2023","journal-title":"Dev (Cambridge England)"},{"key":"B62","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.724741","article-title":"Npm1 is a prognostic biomarker involved in immune infiltration of lung adenocarcinoma and associated with M6a modification and glycolysis","volume":"12","author":"Liu","year":"2021","journal-title":"Front Immunol"},{"key":"B63","doi-asserted-by":"publisher","DOI":"10.1016\/j.jid.2021.05.038","article-title":"B- and plasma cell subsets in autoimmune diseases: translational perspectives","volume":"142","author":"Dang","year":"2022","journal-title":"J Invest Dermatol"},{"key":"B64","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1186\/s13046-025-03390-y","article-title":"Targeting the hla-E-nkg2a axis in combination with ms-275 enhances nk cell-based immunotherapy against dmg","volume":"44","author":"Deng","year":"2025","journal-title":"J Exp Clin Cancer Res: CR"},{"key":"B65","doi-asserted-by":"publisher","DOI":"10.1080\/21688370.2021.1911195","article-title":"Hdac inhibitor, ms-275, increases vascular permeability by suppressing robo4 expression in endothelial cells","volume":"9","author":"Kashio","year":"2021","journal-title":"Tissue Barriers"},{"key":"B66","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1038\/nri.2017.76","article-title":"Single-cell rna sequencing to explore immune cell heterogeneity","volume":"18","author":"Papalexi","year":"2018","journal-title":"Nat Rev Immunol"},{"key":"B67","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1038\/s41420-024-02012-4","article-title":"Plac8-erk pathway modulation of monocyte function in sepsis","volume":"10","author":"Zhang","year":"2024","journal-title":"Cell Death Discov"},{"key":"B68","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1186\/s13287-017-0546-x","article-title":"Adipose-derived mesenchymal stem cells modulate cd14(++)Cd16(+) expression on monocytes from sepsis patients in vitro via prostaglandin E2","volume":"8","author":"Qiu","year":"2017","journal-title":"Stem Cell Res Ther"},{"key":"B69","doi-asserted-by":"publisher","first-page":"125","DOI":"10.21037\/atm.2020.02.35","article-title":"Single-cell transcriptomics reveals the alteration of peripheral blood mononuclear cells driven by sepsis","volume":"8","author":"Wen","year":"2020","journal-title":"Ann Trans Med"},{"key":"B70","doi-asserted-by":"publisher","DOI":"10.1182\/blood.V82.10.3170.3170","article-title":"The novel subset of cd14+\/cd16+ Blood monocytes is expanded in sepsis patients","volume":"82","author":"Fingerle","year":"1993","journal-title":"Blood"},{"key":"B71","doi-asserted-by":"publisher","first-page":"15469","DOI":"10.1038\/s41598-022-19847-5","article-title":"Distinct gene expression patterns for cd14++ and cd16++ Monocytes in preeclampsia","volume":"12","author":"Vishnyakova","year":"2022","journal-title":"Sci Rep"},{"key":"B72","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2023.1257526","article-title":"Cd14(High)Cd16(+) monocytes are the main producers of interleukin-10 following clinical heart transplantation","volume":"14","author":"Ludwig","year":"2023","journal-title":"Front Immunol"},{"key":"B73","doi-asserted-by":"publisher","DOI":"10.1189\/jlb.0806510","article-title":"The cd14+ Cd16+ Blood monocytes: their role in infection and inflammation","volume":"81","author":"Ziegler-Heitbrock","year":"2007","journal-title":"J Leukocyte Biol"},{"key":"B74","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2023.1164112","article-title":"Identification and analysis of type 2 diabetes-mellitus-associated autophagy-related genes","volume":"14","author":"Cui","year":"2023","journal-title":"Front Endocrinol"},{"key":"B75","doi-asserted-by":"publisher","first-page":"e13932","DOI":"10.7717\/peerj.13932","article-title":"Bioinformatics prediction and experimental verification of key biomarkers for diabetic kidney disease based on transcriptome sequencing in mice","volume":"10","author":"Zhao","year":"2022","journal-title":"PeerJ"}],"updated-by":[{"DOI":"10.3389\/fimmu.2025.1746347","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T00:00:00Z","timestamp":1765324800000}}],"container-title":["Frontiers in Immunology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fimmu.2025.1638156\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T13:50:05Z","timestamp":1765374605000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fimmu.2025.1638156\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,30]]},"references-count":75,"alternative-id":["10.3389\/fimmu.2025.1638156"],"URL":"https:\/\/doi.org\/10.3389\/fimmu.2025.1638156","relation":{},"ISSN":["1664-3224"],"issn-type":[{"value":"1664-3224","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,30]]},"article-number":"1638156"}}