Evidence map›Paper›PMID 42180997›Full record

ReviewGenes & diseases2026

Trained immunity: New insights into pathogenesis and therapeutic targets in diabetes and diabetic complications.

Qiming Gong, Yuqing Huang, Fahui Liu, Tingting Zhou, Wei Huang, Yong Xu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Genes & diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Qiming GongDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China.
Yuqing HuangDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China.
Fahui LiuXiamen Cell Therapy Research Center, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian 361005, China.
Tingting ZhouDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China.
Wei HuangDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China.
Yong XuDepartment of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus, a chronic metabolic condition, is marked by ongoing hyperglycemia and poses an increasing global health issue. Beyond its recognized contribution to the development of cardiovascular diseases and kidney problems, diabetes can profoundly impact immune system functions. Recent developments in immunology have revealed trained immunity as a mechanism through which innate immune cells experience enduring functional modifications following their first encounter with specific stimuli. This review compiles the latest evidence concerning the role of trained immunity in the development of diabetes and its complications. Moreover, it discusses emerging therapeutic opportunities that may arise from modulating trained immunity pathways. This review emphasizes the complex relationship between metabolic dysregulation and innate immune memory by synthesizing results from various studies. It proposes that focusing on trained immunity may provide innovative approaches for managing diabetes and its related complications.

Indexed as

Diabetes mellitusEpigeneticsImmunometabolismInnate immune systemTrained immunity

Identifiers

PMID42180997
PMCPMC13196325

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.