<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Gao C</submitter><funding>Jiangsu Provincial Key Research and Development Program</funding><funding>The National Science and Technology Major Project of China</funding><funding>The Key Program of the National Natural Science Foundation of China</funding><funding>The Natural Science Foundation of Jiangsu Province</funding><funding>Jiangsu Provincial Key Laboratory of Critical Care Medicine</funding><funding>The Special Funds of the National Natural Science Foundation of China</funding><pagination>170</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12554855</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>15(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Sepsis is characterized by a dysregulated immune response to infection, with a balance between hyperinflammation and immunosuppression, which determines the patient's immune status. Real-time monitoring of the immune status in sepsis is crucial for guiding immunotherapy. However, reliable biomarkers are lacking. This study aims to identify a panel of biomarkers for rapid bedside assessment of immune status in sepsis to guide immunotherapy decisions.&lt;h4>Results&lt;/h4>TBX21, GNLY, PRF1, and IL2RB represent the immune status in sepsis. These genes demonstrated discriminatory power in the external validation, with area under the curve values ranging from 0.891 to 0.909 across several machine learning models. 99 double-blind randomized patients with sepsis were clustered into t</pubmed_abstract><journal>Annals of intensive care</journal><pubmed_title>Development of a gene panel for immune status assessment in sepsis.</pubmed_title><pmcid>PMC12554855</pmcid><funding_grant_id>BE2019749</funding_grant_id><funding_grant_id>2023ZD0506500</funding_grant_id><funding_grant_id>81930058</funding_grant_id><funding_grant_id>BM2020004</funding_grant_id><funding_grant_id>82341032</funding_grant_id><funding_grant_id>BK20240210</funding_grant_id><pubmed_authors>Qiu H</pubmed_authors><pubmed_authors>Liu L</pubmed_authors><pubmed_authors>Lu X</pubmed_authors><pubmed_authors>Chao J</pubmed_authors><pubmed_authors>Chen H</pubmed_authors><pubmed_authors>Zhou X</pubmed_authors><pubmed_authors>Gao C</pubmed_authors><pubmed_authors>Jiang Y</pubmed_authors><pubmed_authors>Ni Y</pubmed_authors><pubmed_authors>Yang Y</pubmed_authors><pubmed_authors>Xie J</pubmed_authors><pubmed_authors>Tang Y</pubmed_authors><pubmed_authors>Wu X</pubmed_authors></additional><is_claimable>false</is_claimable><name>Development of a gene panel for immune status assessment in sepsis.</name><description>&lt;h4>Background&lt;/h4>Sepsis is characterized by a dysregulated immune response to infection, with a balance between hyperinflammation and immunosuppression, which determines the patient's immune status. Real-time monitoring of the immune status in sepsis is crucial for guiding immunotherapy. However, reliable biomarkers are lacking. This study aims to identify a panel of biomarkers for rapid bedside assessment of immune status in sepsis to guide immunotherapy decisions.&lt;h4>Results&lt;/h4>TBX21, GNLY, PRF1, and IL2RB represent the immune status in sepsis. These genes demonstrated discriminatory power in the external validation, with area under the curve values ranging from 0.891 to 0.909 across several machine learning models. 99 double-blind randomized patients with sepsis were clustered into t</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Oct</publication><modification>2026-06-05T05:29:37.371Z</modification><creation>2026-05-13T14:29:16.008Z</creation></dates><accession>S-EPMC12554855</accession><cross_references><pubmed>41139765</pubmed><doi>10.1186/s13613-025-01594-1</doi></cross_references></HashMap>