{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T05:17:03Z","timestamp":1783055823311,"version":"3.54.6"},"reference-count":47,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T00:00:00Z","timestamp":1783036800000},"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>Introduction<\/jats:title>\n                    <jats:p>Sepsis remains a leading cause of mortality in critical care, with dysregulated inflammatory responses driving disease progression. However, the role of necroptosis in sepsis pathogenesis remains incompletely understood.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Here, through integration of multi-center cohort data (n = 1,265) and weighted gene co-expression network analysis (WGCNA), we constructed a six-gene necroptosis signature (CEBPD, CEBPB, MARCKS, SOCS3, PIM3, and JUNB) that correlated with sepsis severity and outcomes. Subsequently, we detected the expression of these genes in whole blood using qPCR. Furthermore, machine learning models incorporating this signature were evaluated across independent cohorts. Single-cell data analysis and flow cytometric analysis were further performed to characterize CD177\n                      <jats:sup>+<\/jats:sup>\n                      neutrophils in sepsis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      All six Model-score genes were upregulated in sepsis patients, with four of them showing significant differences. Machine learning models incorporating this signature achieved robust diagnostic performance across independent cohorts. At the transcriptomic level, necroptosis activation showed a strong correlation with both the IL-6\/STAT3 and TNF-\u03b1\/NF-\u03baB inflammatory pathways and distinct myeloid subsets. Single-cell data analysis further revealed that CD177\n                      <jats:sup>+<\/jats:sup>\n                      neutrophils were significantly enriched in non-surviving sepsis patients and exhibited the highest necroptosis transcriptional score. Flow cytometric analysis revealed a significant increase in neutrophils, particularly the CD177\n                      <jats:sup>+<\/jats:sup>\n                      subset, in the whole blood of septic patients. Furthermore, CD177\n                      <jats:sup>+<\/jats:sup>\n                      neutrophils displayed blunted interferon responses alongside heightened production of inflammatory mediators, with nitric oxide (NO) potentially serving as an associated factor.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Collectively, our findings suggest that CD177+ neutrophils may be involved in necroptosis-related inflammation in sepsis and provide a clinically relevant gene signature for patient stratification, offering new perspectives for potential therapeutic exploration in sepsis management.<\/jats:p>\n                  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Jiaotong University","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Hematology, Ninth Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Hematology, The First Affiliated Hospital of Xi\u2019an Jiaotong University","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin","family":"Zheng","sequence":"additional","affiliation":[{"name":"Department of Renal Transplantation, Hospital of Nephrology, The First Affiliated Hospital of Xi\u2019an Jiaotong University","place":["Xi\u2019an, Shaanxi, 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