Evidence map›Paper›PMID 40124571›Full record

ReviewAmerican journal of clinical and experimental urology2025

Urinary exosomes as promising biomarkers for early kidney disease detection.

An-Ping Liu, Tian-Jing Sun, Tong-Ying Liu, Hai-Zhen Duan, Xu-Heng Jiang, Mo Li, Yuan-Ze Luo, Michael P Feloney, Mark Cline, Yuan-Yuan Zhang and 1 more

Abstract readReview
In one paragraph

Review in American journal of clinical and experimental urology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. 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

11 authors.

An-Ping LiuDalian Medical University Dalian 116044, Liaoning, China.
Tian-Jing SunDepartment of Emergency, Affiliated Hospital of Zunyi Medical University Zunyi 563003, Guizhou, China.
Tong-Ying LiuDepartment of Emergency, Affiliated Hospital of Zunyi Medical University Zunyi 563003, Guizhou, China.
Hai-Zhen DuanDepartment of Emergency, Affiliated Hospital of Zunyi Medical University Zunyi 563003, Guizhou, China.
Xu-Heng JiangDepartment of Emergency, Affiliated Hospital of Zunyi Medical University Zunyi 563003, Guizhou, China.
Mo LiDepartment of Emergency, Affiliated Hospital of Zunyi Medical University Zunyi 563003, Guizhou, China.
Yuan-Ze LuoDejiang County Ethnic Traditional Chinese Medicine Hospital Zunyi 563003, Guizhou, China.
Michael P FeloneyDepartment of Urology, School of Medicine, Creighton University School of Medicine Omaha, NE, USA.
Mark ClineDepartment of Pathology, Wake Forest School of Medicine Winston-Salem, NC, USA.
Yuan-Yuan ZhangWake Forest Institute of Regenerative Medicine, Wake Forest School of Medicine Winston-Salem, NC, USA.
An-Yong YuDalian Medical University Dalian 116044, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kidney injury and disease pose a significant global health burden. Despite existing diagnostic methods, early detection remains challenging due to the lack of specific molecular markers to identify and stage various kidney lesions. Urinary exosomes, extracellular vesicles secreted by kidney cells, offer a promising solution. These vesicles contain a variety of biomolecules, such as proteins, RNA, and DNA. These biomolecules can reflect the unique physiological and pathological states of the kidney. This review explores the potential of urinary exosomes as biomarkers for a range of kidney diseases, including renal failure, diabetic nephropathy, and renal tumors. By analyzing specific protein alterations within these exosomes, we aim to develop more precise and tailored diagnostic tools to detect kidney diseases at an early stage and improve patient outcomes. While challenges persist in isolating, characterizing, and extracting reliable information from urinary exosomes, overcoming these hurdles is crucial for advancing their clinical application. The successful implementation of urinary exosome-based diagnostics could revolutionize early kidney disease detection, enabling more targeted treatment and improved patient outcomes.

Indexed as

biomarkersearly diagnosiskidney diseasekidney injuryUrine exosomes

Identifiers

PMID40124571
PMCPMC11928825

What OpenQuestion holds

Textmetadata
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.