{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T15:16:03Z","timestamp":1786115763316,"version":"build-2736575974"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T00:00:00Z","timestamp":1785974400000},"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. Med."],"abstract":"<jats:p>\n                    Sepsis exhibits marked heterogeneity in host responses. Although prior time-course transcriptomic studies have provided important information about sepsis diagnosis and mortality-associated gene-expression dynamics, many bioinformatic signatures remain optimized for cross-sectional classification or endpoint labels. Using public multi-cohort whole-blood transcriptomic and single-cell datasets, we constructed a sepsis recovery-failure axis constrained by longitudinal trajectory rules and evaluated its cross-cohort transferability, clinical relevance, and single-cell anchoring. In GSE54514, we identified 20 recovery-related genes and 20 failure-related genes and defined a recovery-failure score. Survivors showed a non-monotonic but ultimately upward movement by day 5, whereas non-survivors progressively shifted toward the failure end of the axis, with clear separation by day 5. Linear mixed-effects models using all repeated measurements from day 1 to day 5 showed a significant interaction between time and outcome that remained stable after adjustment for neutrophil proportion and baseline APACHE II. GSE57065 and GSE65682 supported transfer of the axis for host-state stratification, while also showing that cohort-wise standardization limits interpretation as a universal absolute cutoff. Additional null and cross-cohort structure analyses showed that external-cohort patient-level score variance exceeded matched random-gene expectations and that high-score patients across external cohorts shared non-axis transcriptomic effects. The score showed only weak correlations with bedside severity scores, suggesting that it may serve as a complementary host-state indicator rather than a replacement for clinical severity scores. At the single-cell level, broad PBMC annotation followed by monocyte refinement localized the strongest donor-level axis signal to classical monocytes; additional T-cell cluster screening did not identify a robust hidden T-cell cluster that superseded monocyte anchoring. In non-survivors, classical monocytes exhibited reduced interferon responses and oxidative phosphorylation together with enhanced inflammatory, IL6-JAK-STAT3, and coagulation programs. Axis displacement within interferon-activated monocytes was supported by limited cellular coverage and should be treated as exploratory. Taken together, the recovery-failure axis is a longitudinally derived host-state score that may support sepsis state stratification, disease-course monitoring, and hypothesis generation, but\n                    <jats:bold>\n                      <jats:italic>requires prospective calibration before patient-level clinical use.<\/jats:italic>\n                    <\/jats:bold>\n                  <\/jats:p>","DOI":"10.3389\/fmed.2026.1861140","type":"journal-article","created":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T05:33:34Z","timestamp":1785994414000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Construction of a sepsis recovery-failure axis and single-cell anchoring using public multi-cohort whole-blood and single-cell transcriptomic data"],"prefix":"10.3389","volume":"13","author":[{"given":"Ye","family":"Tan","sequence":"first","affiliation":[{"name":"Lianyungang Clinical College of Nanjing Medical University, Lianyungang","place":["Jiangsu, China"]},{"name":"The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang","place":["Jiangsu, China"]},{"name":"Department of Emergency Medicine, The First People\u2019s Hospital of Lianyungang, Lianyungang","place":["Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongyang","family":"Wang","sequence":"additional","affiliation":[{"name":"Lianyungang Clinical College of Nanjing Medical University, Lianyungang","place":["Jiangsu, China"]},{"name":"The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang","place":["Jiangsu, China"]},{"name":"Department of Emergency Medicine, The First People\u2019s Hospital of Lianyungang, Lianyungang","place":["Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinqiu","family":"Ding","sequence":"additional","affiliation":[{"name":"Lianyungang Clinical College of Nanjing Medical University, Lianyungang","place":["Jiangsu, China"]},{"name":"The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang","place":["Jiangsu, China"]},{"name":"Department of Emergency Medicine, The First People\u2019s Hospital of Lianyungang, Lianyungang","place":["Jiangsu, China"]},{"name":"The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang","place":["Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongpeng","family":"Xie","sequence":"additional","affiliation":[{"name":"Lianyungang Clinical College of Nanjing Medical University, Lianyungang","place":["Jiangsu, China"]},{"name":"The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang","place":["Jiangsu, China"]},{"name":"Department of Emergency Medicine, The First People\u2019s Hospital of Lianyungang, Lianyungang","place":["Jiangsu, China"]},{"name":"The Affiliated Lianyungang Hospital of Xuzhou Medical 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