Evidence map›Paper›PMID 42040313›Full record

ArticleJournal of inflammation research2026

Cell Death Index Predicts Sepsis Outcomes and Highlights Necroptosis as a Therapeutic Target.

Jialing Gan, Qiuyue Long, Shuqi Fang, Shixu Song, Jing Wu, Xiaomin Li, Hongli Ye, Zhancheng Gao, Yali Zheng

Abstract read
In one paragraph

Article in Journal of inflammation research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jialing Gan *Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361101, People's Republic of China.
Qiuyue Long *Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361101, People's Republic of China.ORCID 0000-0002-5361-3260
Shuqi FangDepartment of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361101, People's Republic of China.ORCID 0009-0008-0856-6689
Shixu SongDepartment of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361101, People's Republic of China.
Jing WuDepartment of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361101, People's Republic of China.ORCID 0000-0002-7075-3687
Xiaomin LiDepartment of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361101, People's Republic of China.
Hongli YeDepartment of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361101, People's Republic of China.
Zhancheng Gao *Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361101, People's Republic of China.
Yali ZhengDepartment of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361101, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Excessive immunogenic cell death (ICD) drives early mortality in sepsis, but its dominant subtype and clinical relevance remain poorly defined. Methods: We systematically screened 3,421 genes involved in 15 forms of cell death across multiple sepsis transcriptomic datasets. Machine learning and COX regression identified two ICD-associated genes (PDZD8 and ADRB2) and were used to build a Cell Death Index (CDI). CDI performance was verified in terms of discrimination, risk stratification and clinical relevance. Gene set scoring was used to assess the association of CDI with necroptosis. Single-cell RNA sequencing was performed to investigate PDZD8 and ADRB2 expression and function. Treatment with the necroptosis inhibitor Necrostatin-1 (Nec-1) was evaluated in a cecal ligation and puncture (CLP) mouse model. Results: The CDI robustly predicted sepsis prognosis across multiple datasets (AUC: 0.628-0.70). Multivariate analysis identified CDI as an independent risk factor for 28-day mortality (OR = 1.63-2.91, p < 0.001). CDI levels were significantly elevated in sepsis patients compared to pneumonia and upper respiratory infection patients. Meanwhile, serum high-mobility group box 1 (HMGB1) was markedly elevated in sepsis cases, whereas caspase-8 (CASP8) remained unchanged, supporting an active necroptotic process. Single-cell RNA sequencing revealed that PDZD8 was highly expressed in neutrophils and associated with oxidative stress and necroptosis, while ADRB2 was enriched in NK cells and linked to suppressed inflammatory signaling. Treatment with Nec-1 in the CLP model significantly improved survival (from 0% to 90%), reduced inflammatory cytokine release, and alleviated organ damage. Conclusion: This study identifies necroptosis as the dominant ICD subtype driving immune imbalance in sepsis and establishes CDI as a clinically relevant prognostic biomarker, thereby providing mechanistic insight into sepsis pathogenesis and lay the groundwork for precision therapeutic interventions targeting necroptosis.

Indexed as

cell death indeximmunogenic cell deathnecroptosisprognosissepsis

Identifiers

PMID42040313
PMCPMC13107476

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.