Evidence map›Paper›PMID 36959860›Full record

ArticleFrontiers in pharmacology2023

Dapagliflozin alleviates renal fibrosis in a mouse model of adenine-induced renal injury by inhibiting TGF-β1/MAPK mediated mitochondrial damage.

Jianhua Zeng, Hao Huang, Yan Zhang, Xin Lv, Jiawei Cheng, Si Jue Zou, Yuanyuan Han, Songkai Wang, Li Gong, Zhangzhe Peng

Open access · goldFull text read
In one paragraph

Article in Frontiers in pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.4field-weighted citation impact, top 4% of its field
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

21 citing papers in PubMed, 27 citations in OpenAlex.

  1. Advances in the Targeted Drug Delivery System for Renal Fibrosis.International journal of nanomedicine · 2026
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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

10 authors at 2 institutions in 1 country.

Jianhua ZengDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Hao HuangDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Yan ZhangDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Xin LvDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Jiawei ChengDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Si Jue ZouDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Yuanyuan HanDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Songkai WangDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Li GongDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Zhangzhe PengDepartment of Nephrology, Xiangya Hospital, Central South University, Changsha, China.
Central South University · CNXiangya Hospital Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Renal fibrosis is a common pathological outcome of various chronic kidney diseases, and as yet, there is no specific treatment. Dapagliflozin has shown renal protection in some clinical trials as a glucose-lowering drug, but its role and mechanism on renal fibrosis remain unclear. In this study, we used a 0.2% adenine diet-induced renal fibrosis mouse model to investigate whether dapagliflozin could protect renal function and alleviate renal fibrosis in this animal model.

Indexed as

dapagliflozinmitochondrial damageoxidative stressrenal fibrosisTGF-β1/MAPK pathway

Identifiers

PMID36959860
PMCPMC10028454
OpenAlexW4323362052

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read135
table measurements read16
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 Socratic graph.