Evidence map›Paper›PMID 41244208›Full record

ReviewPeerJ2025

Research progress of tsRNAs in kidney diseases.

Jialing Wang, Yanzhe Wang, Fengqin Li, Xinmiao Xie, Xinyue Chen, Tong Wu, Xiaoxia Wang

Abstract readReview
In one paragraph

Review in PeerJ, 2025. 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. Article
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

7 authors.

Jialing Wang *Department of Nephrology, Tongren Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yanzhe Wang *Department of Nephrology, Tongren Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Fengqin LiDepartment of Nephrology, Tongren Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xinmiao XieDepartment of Nephrology, Tongren Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xinyue ChenDepartment of Nephrology, Tongren Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Tong WuDepartment of Nephrology, Tongren Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xiaoxia WangDepartment of Nephrology, Tongren Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transfer RNA-derived small RNAs (tsRNAs) are a class of regulatory non-coding RNAs generated through enzymatic cleavage of precursor or mature tRNAs. In recent years, tsRNAs have garnered growing interest in nephrology due to their diverse biological functions and potential clinical significance. This review summarizes current research on the roles of tsRNAs in kidney diseases, including their involvement in gene expression regulation, signal transduction, apoptosis, and inflammation-related pathways. We further highlight their emerging mechanistic contributions in conditions such as acute kidney injury, chronic kidney disease, and glomerulonephritis. Finally, we discuss the prospects of tsRNAs as novel biomarkers for early diagnosis, prognosis assessment, and therapeutic targeting in renal disorders, aiming to offer new insights into kidney disease pathogenesis and management.

Indexed as

Kidney DiseasesRNA, Small UntranslatedRNA, TransferAcute Kidney InjuryAnimalsApoptosisBiomarkersGene Expression RegulationHumansRenal Insufficiency, ChronicSignal TransductionBiomarkersRNA, Small UntranslatedRNA, TransferBiological functionKidney diseasesTiRNAsTRFsTsRNAs

Identifiers

PMID41244208
PMCPMC12614097

What OpenQuestion 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 OpenQuestion graph.