Evidence map›Paper›PMID 40135071›Full record

ReviewJournal of diabetes research2025

Application and Progression of Single-Cell RNA Sequencing in Diabetes Mellitus and Diabetes Complications.

Jiajing Hong, Shiqi Lu, Guohui Shan, Yaoran Yang, Bailin Li, Dongyu Yang

Abstract readReview
In one paragraph

Review in Journal of diabetes research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Jiajing HongCollege of Acupuncture and Massage, Changchun University of Chinese Medicine, Changchun, China.ORCID https://orcid.org/0009-0005-7297-5039
Shiqi LuCollege of Acupuncture and Massage, Changchun University of Chinese Medicine, Changchun, China.ORCID https://orcid.org/0009-0009-0646-9436
Guohui ShanDepartment of Endocrinology, The Third Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, China.ORCID https://orcid.org/0009-0005-8306-8725
Yaoran YangCollege of Acupuncture and Massage, Changchun University of Chinese Medicine, Changchun, China.ORCID https://orcid.org/0009-0000-2091-078X
Bailin LiMedical Quality Monitoring Center, The Third Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, China.ORCID https://orcid.org/0009-0006-3420-8805
Dongyu YangCenter of Traditional Chinese Medicine, The Third Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, China.ORCID https://orcid.org/0009-0007-0126-9297

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes is a systemic metabolic disorder primarily caused by insulin deficiency and insulin resistance, leading to chronic hyperglycemia. Prolonged diabetes can result in metabolic damage to multiple organs, including the heart, brain, liver, muscles, and adipose tissue, thereby causing various chronic fatal complications such as diabetic retinopathy, diabetic cardiomyopathy, and diabetic nephropathy. Single-cell RNA sequencing (scRNA-seq) has emerged as a valuable tool for investigating the cell diversity and pathogenesis of diabetes and identifying potential therapeutic targets in diabetes or diabetes complications. This review provides a comprehensive overview of recent applications of scRNA-seq in diabetes-related researches and highlights novel biomarkers and immunotherapy targets with cell-type information for diabetes and its associated complications.

Indexed as

Diabetes ComplicationsDiabetes MellitusSequence Analysis, RNASingle-Cell AnalysisAnimalsBiomarkersHumansBiomarkersbiomarkerdiabetesdiabetes complicationsimmunotherapy targetsscRNA-seqsingle-cell RNA sequencing

Identifiers

PMID40135071
PMCPMC11936531

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.