Evidence map›Paper›PMID 41822780›Full record

ArticleRSC advances2026

Analysis of metabolic characteristics of epristeride in zebrafish based on LC-Q-TOF MS and its potential applications in doping control.

Yirang Wang, Zhongquan Li, Jiahui Cheng, Tingyuan Zheng, Peijie Chen, Xiaojun Deng, Pei-Chao Zhang, Bing Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in RSC advances, 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. 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

8 authors.

Yirang WangResearch Institute for Doping Control, Shanghai University of Sport Shanghai 200438 China liubing2019@sus.edu.cn.
Zhongquan LiResearch Institute for Doping Control, Shanghai University of Sport Shanghai 200438 China liubing2019@sus.edu.cn.
Jiahui ChengResearch Institute for Doping Control, Shanghai University of Sport Shanghai 200438 China liubing2019@sus.edu.cn.ORCID https://orcid.org/0009-0000-3063-6470
Tingyuan ZhengResearch Institute for Doping Control, Shanghai University of Sport Shanghai 200438 China liubing2019@sus.edu.cn.
Peijie ChenResearch Institute for Doping Control, Shanghai University of Sport Shanghai 200438 China liubing2019@sus.edu.cn.
Xiaojun DengResearch Institute for Doping Control, Shanghai University of Sport Shanghai 200438 China liubing2019@sus.edu.cn.
Pei-Chao ZhangThe Center for Basic Research and Innovation of Medicine and Pharmacy (MOE), School of Pharmacy, Second Military Medical University (Naval Medical University) Shanghai P. R. China pczhang@smmu.edu.cn.
Bing LiuResearch Institute for Doping Control, Shanghai University of Sport Shanghai 200438 China liubing2019@sus.edu.cn.ORCID https://orcid.org/0000-0002-6337-3774

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

5α Reductase inhibitors (finasteride and dutasteride) have been classified as monitored substances by the World Anti-Doping Agency (WADA) due to their potential abuse as masking agents for anabolic-androgenic steroids. As a member of the same class of inhibitors, epristeride shares a similar pharmacological mechanism of action and thus poses an inherent risk of abuse. However, current research on the metabolic characteristics of epristeride remains limited, which hinders its effective monitoring in anti-doping practices. In this study, a zebrafish model combined with liquid chromatography-quadrupole-time-of-flight mass spectrometry (LC-Q-TOF MS) was employed to systematically investigate the metabolic transformation of epristeride

Identifiers

PMID41822780
PMCPMC12978312

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.