{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T15:37:09Z","timestamp":1780328229912,"version":"3.54.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Inflamm. Res."],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s00011-025-02068-7","type":"journal-article","created":{"date-parts":[[2025,6,29]],"date-time":"2025-06-29T23:02:22Z","timestamp":1751238142000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Identification of key genes and development of an identifying machine learning model for sepsis"],"prefix":"10.1007","volume":"74","author":[{"given":"Zhonghao","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengsong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nan","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Qin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoqiang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,6,30]]},"reference":[{"issue":"10219","key":"2068_CR1","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/S0140-6736(19)32989-7","volume":"395","author":"KE Rudd","year":"2020","unstructured":"Rudd KE, Johnson SC, Agesa KM, Shackelford KA, Tsoi D, Kievlan DR, et al. Global, regional, and national sepsis incidence and mortality, 1990\u20132017: analysis for the global burden of disease study. Lancet. 2020;395(10219):200\u201311.","journal-title":"Lancet"},{"issue":"11","key":"2068_CR2","doi-asserted-by":"publisher","first-page":"1181","DOI":"10.1007\/s00134-021-06506-y","volume":"47","author":"L Evans","year":"2021","unstructured":"Evans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021;47(11):1181\u2013247.","journal-title":"Intensive Care Med"},{"issue":"8","key":"2068_CR3","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1001\/jama.2016.0287","volume":"315","author":"M Singer","year":"2016","unstructured":"Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 2016;315(8):801\u201310.","journal-title":"JAMA"},{"key":"2068_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.intimp.2023.109909","volume":"117","author":"W Xie","year":"2023","unstructured":"Xie W, Zou S, Dong C, Yang C. SPI1-mediated autophagy of peripheral blood monocyte cells as a mechanism for sepsis based on single-cell RNA sequencing. Int Immunopharmacol. 2023;117: 109909.","journal-title":"Int Immunopharmacol"},{"issue":"4","key":"2068_CR5","doi-asserted-by":"publisher","first-page":"610","DOI":"10.1016\/j.molcel.2015.04.005","volume":"58","author":"AA Kolodziejczyk","year":"2015","unstructured":"Kolodziejczyk AA, Kim JK, Svensson V, Marioni JC, Teichmann SA. The technology and biology of single-cell RNA sequencing. Mol Cell. 2015;58(4):610\u201320.","journal-title":"Mol Cell"},{"issue":"1","key":"2068_CR6","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1186\/s13054-021-03481-0","volume":"25","author":"X Qi","year":"2021","unstructured":"Qi X, Yu Y, Sun R, Huang J, Liu L, Yang Y, et al. Identification and characterization of neutrophil heterogeneity in sepsis. Crit Care. 2021;25(1):50.","journal-title":"Crit Care"},{"issue":"2","key":"2068_CR7","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1007\/s10142-023-01016-0","volume":"23","author":"Z Li","year":"2023","unstructured":"Li Z, Qin Y, Liu X, Chen J, Tang A, Yan S, et al. Identification of predictors for neurological outcome after cardiac arrest in peripheral blood mononuclear cells through integrated bioinformatics analysis and machine learning. Funct Integr Genom. 2023;23(2):83.","journal-title":"Funct Integr Genom"},{"issue":"3","key":"2068_CR8","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1007\/s00134-019-05872-y","volume":"46","author":"LM Fleuren","year":"2020","unstructured":"Fleuren LM, Klausch TLT, Zwager CL, Schoonmade LJ, Guo T, Roggeveen LF, et al. Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy. Intensive Care Med. 2020;46(3):383\u2013400.","journal-title":"Intensive Care Med"},{"issue":"13","key":"2068_CR9","doi-asserted-by":"publisher","first-page":"3573","DOI":"10.1016\/j.cell.2021.04.048","volume":"184","author":"Y Hao","year":"2021","unstructured":"Hao Y, Hao S, Andersen-Nissen E, Mauck WM 3rd, Zheng S, Butler A, et al. Integrated analysis of multimodal single-cell data. Cell. 2021;184(13):3573-87.e29.","journal-title":"Cell"},{"issue":"D1","key":"2068_CR10","doi-asserted-by":"publisher","first-page":"D870","DOI":"10.1093\/nar\/gkac947","volume":"51","author":"C Hu","year":"2023","unstructured":"Hu C, Li T, Xu Y, Zhang X, Li F, Bai J, et al. Cell marker 2.0: an updated database of manually curated cell markers in human\/mouse and web tools based on scRNA-seq data. Nucleic Acids Res. 2023;51(D1):D870\u20136.","journal-title":"Nucleic Acids Res"},{"issue":"7835","key":"2068_CR11","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1038\/s41586-020-2922-4","volume":"587","author":"KJ Travaglini","year":"2020","unstructured":"Travaglini KJ, Nabhan AN, Penland L, Sinha R, Gillich A, Sit RV, et al. A molecular cell atlas of the human lung from single-cell RNA sequencing. Nature. 2020;587(7835):619\u201325.","journal-title":"Nature"},{"issue":"7838","key":"2068_CR12","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1038\/s41586-020-2797-4","volume":"588","author":"M Litvi\u0148ukov\u00e1","year":"2020","unstructured":"Litvi\u0148ukov\u00e1 M, Talavera-L\u00f3pez C, Maatz H, Reichart D, Worth CL, Lindberg EL, et al. Cells of the adult human heart. Nature. 2020;588(7838):466\u201372.","journal-title":"Nature"},{"issue":"1","key":"2068_CR13","doi-asserted-by":"publisher","first-page":"1088","DOI":"10.1038\/s41467-021-21246-9","volume":"12","author":"S Jin","year":"2021","unstructured":"Jin S, Guerrero-Juarez CF, Zhang L, Chang I, Ramos R, Kuan CH, et al. Inference and analysis of cell-cell communication using cell chat. Nat Commun. 2021;12(1):1088.","journal-title":"Nat Commun"},{"issue":"11","key":"2068_CR14","doi-asserted-by":"publisher","first-page":"1083","DOI":"10.1038\/nmeth.4463","volume":"14","author":"S Aibar","year":"2017","unstructured":"Aibar S, Gonz\u00e1lez-Blas CB, Moerman T, Huynh-Thu VA, Imrichova H, Hulselmans G, et al. SCENIC: single-cell regulatory network inference and clustering. Nat Methods. 2017;14(11):1083\u20136.","journal-title":"Nat Methods"},{"issue":"7745","key":"2068_CR15","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1038\/s41586-019-0969-x","volume":"566","author":"J Cao","year":"2019","unstructured":"Cao J, Spielmann M, Qiu X, Huang X, Ibrahim DM, Hill AJ, et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature. 2019;566(7745):496\u2013502.","journal-title":"Nature"},{"issue":"3","key":"2068_CR16","first-page":"100141","volume":"2","author":"T Wu","year":"2021","unstructured":"Wu T, Hu E, Xu S, Chen M, Guo P, Dai Z, et al. clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. Innovation (Camb). 2021;2(3):100141.","journal-title":"Innovation (Camb)."},{"key":"2068_CR17","doi-asserted-by":"publisher","DOI":"10.3389\/fcimb.2022.934313","volume":"12","author":"E Malmstr\u00f6m","year":"2022","unstructured":"Malmstr\u00f6m E, Khan HN, Veer CV, Stunnenberg M, Meijer MT, Matsumoto H, et al. The long non-coding antisense RNA JHDM1D-AS1 regulates inflammatory responses in human monocytes. Front Cell Infect Microbiol. 2022;12: 934313.","journal-title":"Front Cell Infect Microbiol"},{"key":"2068_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2021.103776","volume":"75","author":"A Baghela","year":"2022","unstructured":"Baghela A, Pena OM, Lee AH, Baquir B, Falsafi R, An A, et al. Predicting sepsis severity at first clinical presentation: the role of endotypes and mechanistic signatures. EBioMedicine. 2022;75: 103776.","journal-title":"EBioMedicine"},{"key":"2068_CR19","unstructured":"Alliance of Genome Resources Consortium. Updates to the alliance of genome resources central infrastructure. Genetics. 2024;227(1):iyae049."},{"key":"2068_CR20","doi-asserted-by":"publisher","first-page":"8978795","DOI":"10.1155\/2021\/8978795","volume":"2021","author":"DQ Chen","year":"2021","unstructured":"Chen DQ, Shen MJ, Wang H, Li Y, Tang AL, Li S, et al. Sirt3 maintains microvascular endothelial adherens junction integrity to alleviate sepsis-induced lung inflammation by modulating the interaction of VE-Cadherin and \u03b2-Catenin. Oxid Med Cell Longev. 2021;2021:8978795.","journal-title":"Oxid Med Cell Longev"},{"issue":"3","key":"2068_CR21","doi-asserted-by":"publisher","first-page":"182","DOI":"10.5847\/wjem.j.1920-8642.2022.056","volume":"13","author":"MJ Shen","year":"2022","unstructured":"Shen MJ, Sun LC, Liu XY, Xiong MC, Li S, Tang AL, et al. Trichostatin A improves the inflammatory response and liver injury in septic mice through the FoxO3a\/autophagy signaling pathway. World J Emerg Med. 2022;13(3):182\u20138.","journal-title":"World J Emerg Med"},{"issue":"12","key":"2068_CR22","doi-asserted-by":"publisher","first-page":"5059","DOI":"10.18632\/aging.204125","volume":"14","author":"MJ Shen","year":"2022","unstructured":"Shen MJ, Yan ST, Zhang XY, Li W, Chen X, Zheng XX, et al. The circular RNA hsa_circ_0003091 regulates sepsis-induced lung injury by sponging the miR-149\/Smad2 axis. Aging (Albany NY). 2022;14(12):5059\u201374.","journal-title":"Aging (Albany NY)"},{"key":"2068_CR23","doi-asserted-by":"publisher","DOI":"10.3389\/fphys.2022.941257","volume":"13","author":"AL Tang","year":"2022","unstructured":"Tang AL, Peng Y, Shen MJ, Liu XY, Li S, Xiong MC, et al. Prognostic role of elevated VEGF in sepsis: a systematic review and meta-analysis. Front Physiol. 2022;13: 941257.","journal-title":"Front Physiol"},{"issue":"5","key":"2068_CR24","first-page":"343","volume":"13","author":"AL Tang","year":"2022","unstructured":"Tang AL, Shen MJ, Zhang GQ. Intestinal microcirculation dysfunction in sepsis: pathophysiology, clinical monitoring, and therapeutic interventions. World J Emerg Med. 2022;13(5):343\u20138.","journal-title":"World J Emerg Med"},{"key":"2068_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.intimp.2023.110083","volume":"118","author":"N Gao","year":"2023","unstructured":"Gao N, Tang AL, Liu XY, Chen J, Zhang GQ. p53-Dependent ferroptosis pathways in sepsis. Int Immunopharmacol. 2023;118: 110083.","journal-title":"Int Immunopharmacol"},{"key":"2068_CR26","doi-asserted-by":"publisher","first-page":"1114103","DOI":"10.3389\/fimmu.2023.1114103","volume":"14","author":"X Liu","year":"2023","unstructured":"Liu X, Tang AL, Chen J, Gao N, Zhang G, Xiao C. RIPK1 in the inflammatory response and sepsis: recent advances, drug discovery and beyond. Front Immunol. 2023;14:1114103.","journal-title":"Front Immunol"},{"key":"2068_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.intimp.2023.110049","volume":"118","author":"AL Tang","year":"2023","unstructured":"Tang AL, Liu XY, Gao N, Hu TP, Yan ST, Zhang GQ. Dl-3-n-butylphthalide improves intestinal microcirculation disorders in septic rats by regulating the PI3K\/AKT signaling pathway and autophagy. Int Immunopharmacol. 2023;118: 110049.","journal-title":"Int Immunopharmacol"},{"issue":"12","key":"2068_CR28","doi-asserted-by":"publisher","first-page":"751","DOI":"10.1038\/s41577-022-00707-2","volume":"22","author":"N Pishesha","year":"2022","unstructured":"Pishesha N, Harmand TJ, Ploegh HL. A guide to antigen processing and presentation. Nat Rev Immunol. 2022;22(12):751\u201364.","journal-title":"Nat Rev Immunol"},{"issue":"6","key":"2068_CR29","doi-asserted-by":"publisher","first-page":"R287","DOI":"10.1186\/cc13150","volume":"17","author":"MA Cazalis","year":"2013","unstructured":"Cazalis MA, Friggeri A, Cav\u00e9 L, Demaret J, Barbalat V, Cerrato E, et al. Decreased HLA-DR antigen-associated invariant chain (CD74) mRNA expression predicts mortality after septic shock. Crit Care. 2013;17(6):R287.","journal-title":"Crit Care"},{"issue":"10","key":"2068_CR30","doi-asserted-by":"publisher","DOI":"10.1002\/iid3.70033","volume":"12","author":"J Li","year":"2024","unstructured":"Li J, Pu S, Shu L, Guo M, He Z. Identification of diagnostic candidate genes in COVID-19 patients with sepsis. Immun Inflamm Dis. 2024;12(10): e70033.","journal-title":"Immun Inflamm Dis"},{"key":"2068_CR31","doi-asserted-by":"publisher","DOI":"10.3389\/fphys.2022.870657","volume":"13","author":"Z Chen","year":"2022","unstructured":"Chen Z, Chen R, Ou Y, Lu J, Jiang Q, Liu G, et al. Construction of an HLA classifier for early diagnosis, prognosis, and recognition of immunosuppression in sepsis by multiple transcriptome datasets. Front Physiol. 2022;13: 870657.","journal-title":"Front Physiol"},{"issue":"36","key":"2068_CR32","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000039494","volume":"103","author":"Y Wang","year":"2024","unstructured":"Wang Y, Xu C, Zhang Y, Zhou L, Zhang T, Yin X, et al. Causal association of immune effector proteins with sepsis: a Mendelian randomization study. Medicine (Baltimore). 2024;103(36): e39494.","journal-title":"Medicine (Baltimore)"},{"issue":"8","key":"2068_CR33","first-page":"1044","volume":"17","author":"Y Chen","year":"2013","unstructured":"Chen Y, Shi JX, Pan XF, Feng J, Zhao H. DNA microarray-based screening of differentially expressed genes related to acute lung injury and functional analysis. Eur Rev Med Pharmacol Sci. 2013;17(8):1044\u201350.","journal-title":"Eur Rev Med Pharmacol Sci"},{"key":"2068_CR34","doi-asserted-by":"publisher","first-page":"4586648","DOI":"10.1155\/2022\/4586648","volume":"2022","author":"P Tao","year":"2022","unstructured":"Tao P, He J, Ai T, Fan Y, Zeng W. Investigating the intercellular communication network of immune cell in acute respiratory distress syndrome with sepsis. Comput Math Methods Med. 2022;2022:4586648.","journal-title":"Comput Math Methods Med"},{"issue":"5","key":"2068_CR35","doi-asserted-by":"publisher","first-page":"3076","DOI":"10.4049\/jimmunol.178.5.3076","volume":"178","author":"MM Nooh","year":"2007","unstructured":"Nooh MM, El-Gengehi N, Kansal R, David CS, Kotb M. HLA transgenic mice provide evidence for a direct and dominant role of HLA class II variation in modulating the severity of streptococcal sepsis. J Immunol. 2007;178(5):3076\u201383.","journal-title":"J Immunol"},{"issue":"1","key":"2068_CR36","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1186\/s12967-021-02888-1","volume":"19","author":"R Nudel","year":"2021","unstructured":"Nudel R, Alles\u00f8e RL, Thompson WK, Werge T, Rasmussen S, Benros ME. A large-scale investigation into the role of classical HLA loci in multiple types of severe infections, with a focus on overlaps with autoimmune and mental disorders. J Transl Med. 2021;19(1):230.","journal-title":"J Transl Med"},{"issue":"1","key":"2068_CR37","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1186\/s13054-016-1505-0","volume":"20","author":"AM Drewry","year":"2016","unstructured":"Drewry AM, Ablordeppey EA, Murray ET, Beiter ER, Walton AH, Hall MW, et al. Comparison of monocyte human leukocyte antigen-DR expression and stimulated tumor necrosis factor alpha production as outcome predictors in severe sepsis: a prospective observational study. Crit Care. 2016;20(1):334.","journal-title":"Crit Care"},{"issue":"1","key":"2068_CR38","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1097\/01.CCM.0000150958.20209.A3","volume":"33","author":"A Pachot","year":"2005","unstructured":"Pachot A, Monneret G, Brion A, Venet F, Boh\u00e9 J, Bienvenu J, et al. Messenger RNA expression of major histocompatibility complex class II genes in whole blood from septic shock patients. Crit Care Med. 2005;33(1):31\u20138.","journal-title":"Crit Care Med"},{"issue":"1","key":"2068_CR39","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1186\/s13054-020-2830-x","volume":"24","author":"GP Leijte","year":"2020","unstructured":"Leijte GP, Rimmel\u00e9 T, Kox M, Bruse N, Monard C, Gossez M, et al. Monocytic HLA-DR expression kinetics in septic shock patients with different pathogens, sites of infection and adverse outcomes. Crit Care. 2020;24(1):110.","journal-title":"Crit Care"},{"issue":"1","key":"2068_CR40","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1186\/s13054-020-2754-5","volume":"24","author":"J Ho","year":"2020","unstructured":"Ho J, Chan H, Liang Y, Liu X, Zhang L, Li Q, et al. Cathelicidin preserves intestinal barrier function in polymicrobial sepsis. Crit Care. 2020;24(1):47.","journal-title":"Crit Care"},{"issue":"10","key":"2068_CR41","doi-asserted-by":"publisher","first-page":"1862","DOI":"10.1089\/dna.2020.5383","volume":"39","author":"S Zhang","year":"2020","unstructured":"Zhang S, Li N, Chen W, Fu Q, Liu Y. Time series gene expression profiles analysis identified several potential biomarkers for sepsis. DNA Cell Biol. 2020;39(10):1862\u201371.","journal-title":"DNA Cell Biol"}],"container-title":["Inflammation Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00011-025-02068-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00011-025-02068-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00011-025-02068-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T16:52:36Z","timestamp":1767199956000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00011-025-02068-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":41,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["2068"],"URL":"https:\/\/doi.org\/10.1007\/s00011-025-02068-7","relation":{},"ISSN":["1023-3830","1420-908X"],"issn-type":[{"value":"1023-3830","type":"print"},{"value":"1420-908X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,30]]},"assertion":[{"value":"10 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 May 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 June 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 June 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that there are no competing interests regarding the publication of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The GEO database is a public database. The patients included in these databases have received ethical approval. Our study is based on open-source data, so there are no ethical issues.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}],"article-number":"100"}}