Evidence map›Paper›PMID 40620500›Full record

ReviewLiver research (Beijing, China)2025

Stem cell-based therapeutic strategies for liver aging.

Huan Niu, Yan-Nan Wang, Yu Ding, Yu-Qing Lin, Jian Qin, Jian-Cheng Wang

Abstract readReview
In one paragraph

Review in Liver research (Beijing, China), 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. 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

6 authors.

Huan NiuDepartment of Traditional Chinese Medicine, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong, China.
Yan-Nan WangSchool of Medicine, Sun Yat-sen University, Shenzhen, Guangdong, China.
Yu DingSchool of Medicine, Sun Yat-sen University, Shenzhen, Guangdong, China.
Yu-Qing LinSchool of Medicine, Sun Yat-sen University, Shenzhen, Guangdong, China.
Jian QinDepartment of Traditional Chinese Medicine, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong, China.
Jian-Cheng WangScientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aging is characterized by a gradual deterioration of the physiological integrity of cells, tissues, and organs, resulting in a decrease in the body's physiological functions and an acceleration of the onset of age-related diseases, ultimately leading to death. The aging of the liver, which is a critical metabolic organ, is closely linked to various chronic liver diseases, such as hepatitis, liver fibrosis, and cirrhosis, and it exacerbates their prognosis and is a primary risk factor for their development at all stages. Therefore, a comprehensive understanding of the causes, mechanisms, and potential therapeutic targets associated with liver aging holds significant clinical importance for delaying or potentially reversing liver aging and for treating chronic liver diseases. Stem cells, which are potential anti-aging agents, present a promising and effective alternative for managing liver aging. In this review, we systematically assess the driving factors, characteristics, and underlying mechanisms of liver aging. We then discuss the current status of the use of stem cells to mitigate liver senescence and address related liver diseases. The review reveals that a stem cell-based approach represents a promising therapeutic strategy for combating liver aging and associated diseases.

Indexed as

AgingAnti-agingAnti-liver agingChronic liver diseaseLiver agingStem cell

Identifiers

PMID40620500
PMCPMC12226799

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.