Evidence map›Paper›PMID 42226934›Full record

ArticleClinical interventions in aging2026

Multi-Omics Reveals Dysregulation of the Endosome-Lysosome-Autophagy Axis and Immune-Inflammatory Imbalance in Elderly Sepsis.

Yi Gou, Ziyu Xia, Nazila Haireti, Ailikuti Aikepaer, Jianzhong Yang, Dandan Li

Abstract read
In one paragraph

Article in Clinical interventions in aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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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

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4 · The record

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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

6 authors.

Yi GouEmergency Trauma Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.ORCID 0000-0001-5653-2266
Ziyu XiaEmergency Trauma Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.
Nazila HairetiEmergency Trauma Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.
Ailikuti AikepaerEmergency Trauma Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.
Jianzhong YangEmergency Trauma Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.
Dandan LiEmergency Trauma Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Elderly sepsis (ES), characterized by dual insults of aging and sepsis, is associated with substantial morbidity and mortality and exhibits distinct pathophysiological features. Elucidating these unique mechanisms is critical for developing precise therapeutic strategies and improving patient prognoses. Methods: We performed integrative analyses of untargeted metabolomics and proteomics in four groups: young and elderly healthy controls and young and elderly patients with sepsis. Characteristic metabolites and proteins in ES were identified by using a three-step screening pipeline. Pairwise correlation analyses were conducted on the screened molecules; those with a ∣r Results: Two characteristic metabolites and seven proteins were identified: D-aspartic acid, LysoPC (18:1/0:0), SCGB3A2, ATP6V1E1, APOA1, AP1G1, INHBC, CRYZL1, and CXCL14. Enriched metabolic pathways comprised D-Amino acid metabolism, alanine, aspartate, and glutamate metabolism, and glycerophospholipid metabolism. Enriched protein-centric functional terms were linked to the endocytic vesicle lumen, proton-translocating V-type ATPase, receptor ligand activity, and signaling receptor activator activity, etc. Collectively, these findings highlight perturbations in the endosome-lysosome-autophagy axis and immune-inflammatory imbalance in ES. Conclusion: This study established a hypothesis implicating dysregulation of the endosome-lysosome-autophagy axis and immune-inflammatory imbalance in ES, thus providing a theoretical foundation for further elucidating the pathophysiological mechanisms underlying ES and developing precise therapeutic interventions.

Indexed as

AgingAutophagyEndosomesLysosomesSepsisAgedFemaleHumansInflammationMaleMetabolomicsMiddle AgedMultiomicsProteomicselderly sepsismulti-omicsproteomicsuntargeted metabolomics

Identifiers

PMID42226934
PMCPMC13222600

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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 OpenQuestion graph.