Evidence map›Paper›PMID 42011254›Full record

ReviewJournal of pharmaceutical analysis2026

Small molecules targeting regulated cell death for chronic kidney disease therapy.

Wen-Kai Yu, Qing-Ru Zhu, Li Zhou, Xin-Lei Shen, Tian-Yang Cheng, Yi-Ni Bao, Gang Cao

Abstract readReview
In one paragraph

Review in Journal of pharmaceutical analysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Wen-Kai YuSchool of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Qing-Ru ZhuSchool of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Li ZhouSchool of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Xin-Lei ShenSchool of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Tian-Yang ChengThe Third Affiliated Hospital, Zhejiang Chinese Medical University, Hangzhou, 310009, China.
Yi-Ni BaoSchool of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Gang CaoSchool of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, 310053, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease (CKD) is a significant contributor to the global morbidity of non-communicable diseases and is predicted to become the fifth leading cause of death worldwide. However, effective treatments that directly target the underlying causes of CKD remain limited due to its complicated pathogenesis. Recent research has increasingly focused on elucidating the molecular mechanisms and identifying new therapeutic targets of CKD. In recent years, regulated cell death (RCD) has been highlighted as a central mechanism in the development and progression of CKD, suggesting that targeting specific RCD signaling pathways may offer effective strategies for CKD. Emerging research reveals that small molecules can effectively target different types of RCD in the context of CKD, including apoptosis, autophagy-dependent cell death, pyroptosis, ferroptosis, and necroptosis. In this review, we summarize current understanding of the mechanism of RCD in CKD. Importantly, we emphasize the regulatory mechanism of small molecules on disturbed RCD to alleviate CKD. Taken together, this review enhances the comprehension of small molecules as modulators of RCD against CKD, which will provide new insights and potential avenues for CKD therapy.

Identifiers

PMID42011254
PMCPMC13092030

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.