Evidence map›Paper›PMID 40370561›Full record

ArticleActa pharmaceutica Sinica. B2025

Targeting farnesoid X receptor as aging intervention therapy.

Lijun Zhang, Jing Yu, Xiaoyan Gao, Yingxuan Yan, Xinyi Wang, Hang Shi, Minglv Fang, Ying Liu, Young-Bum Kim, Huanhu Zhu and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Acta pharmaceutica Sinica. B, 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. Article
  2. Bile acid signaling, metabolism, and aging.Liver research (Beijing, China) · 2026
    Review
  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

13 authors.

Lijun ZhangSchool of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Jing YuSchool of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Xiaoyan GaoSchool of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Yingxuan YanSchool of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Xinyi WangSchool of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Hang ShiSchool of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Minglv FangSchool of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Ying LiuSchool of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Young-Bum KimDivision of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02115, USA.
Huanhu ZhuSchool of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
Xiaojun WuInstitute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Cheng HuangSchool of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Shengjie FanSchool of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Environmental toxicants have been linked to aging and age-related diseases. The emerging evidence has shown that the enhancement of detoxification gene expression is a common transcriptome marker of long-lived mice,

Indexed as

AgingDetoxificationFarnesoid X receptorHealthspanLifespanLongevityObeticholic acidPregnane X receptor

Identifiers

PMID40370561
PMCPMC12069902

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.