Evidence map›Paper›PMID 41716288›Full record

ReviewFrontiers in cell and developmental biology2026

The dual role of autophagy in cartilage degradation: from mechanisms to targeted therapeutics.

Jiahua Mei, Shenghao Zhang, Xinrong Cui, Ruiping Yang, Jin Ke, Lili Cui, Lin Tan, Shan Zhu, Yunshu Ma

Abstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Jiahua Mei *Yunnan University of Chinese Medicine, Kunming, China.
Shenghao Zhang *Yunnan University of Chinese Medicine, Kunming, China.
Xinrong Cui *Yunnan University of Chinese Medicine, Kunming, China.
Ruiping YangYunnan University of Chinese Medicine, Kunming, China.
Jin KeYunnan University of Chinese Medicine, Kunming, China.
Lili CuiYunnan University of Chinese Medicine, Kunming, China.
Lin TanYunnan University of Chinese Medicine, Kunming, China.
Shan ZhuYunnan University of Chinese Medicine, Kunming, China.
Yunshu MaYunnan University of Chinese Medicine, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autophagy is a highly conserved cellular degradation and recycling process that plays a pivotal role in maintaining cartilage homeostasis. Normal autophagy is essential for the survival of chondrocytes and the preservation of the extracellular matrix (ECM); however, a decline in autophagic function may lead to the accumulation of damaged organelles and macromolecules, thereby reducing chondrocyte vitality and promoting apoptosis, which in turn contributes to the development of osteoarthritis (OA). This review summarizes the biological processes of autophagy, the interaction between autophagy and cartilage degeneration, as well as the interplay between autophagy and cellular senescence, apoptosis, inflammation, and oxidative stress. Furthermore, we explore key autophagic targets for the regulation of OA and discuss autophagy-targeting therapies, including mTOR inhibitors, AMPK activators, and natural products that target autophagy, along with emerging strategies aimed at modulating autophagy. Finally, the article highlights the challenges in the development of autophagy-targeting drugs for OA treatment and presents important scientific issues that warrant further investigation to guide future research.

Indexed as

autophagycartilage degenerationcellular apoptosischondrocytesosteoarthritis

Identifiers

PMID41716288
PMCPMC12913578

What OpenQuestion holds

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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.