Evidence map›Paper›PMID 38375488›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2024

Network Pharmacology, Molecular Docking, and Experimental Verification to Reveal the Mitophagy-Associated Mechanism of Tangshen Formula in the Treatment of Diabetic Nephropathy.

Yinfeng Chen, Xiaying Wang, Jie Min, Jie Zheng, Xuanli Tang, Xiaoling Zhu, Dongrong Yu, De Jin

RetractedAbstract readRetracted Publication
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. 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

5 · Who and what money

Authors and funding

8 authors.

Yinfeng Chen *Department of Nephrology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, 310007, People's Republic of China.
Xiaying Wang *Department of Nephrology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, 310007, People's Republic of China.
Jie MinDepartment of Nephrology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, 310007, People's Republic of China.
Jie ZhengDepartment of Nephrology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, 310007, People's Republic of China.
Xuanli TangDepartment of Nephrology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, 310007, People's Republic of China.
Xiaoling ZhuDepartment of Nephrology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, 310007, People's Republic of China.
Dongrong YuDepartment of Nephrology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, 310007, People's Republic of China.
De JinDepartment of Nephrology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, 310007, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study investigated the mechanism of TSF in treating DN through network pharmacology, molecular docking, and experimental validation. Methods: To identify critical active ingredients, targets, and DN genes in TSF, multiple databases were utilized for screening purposes. The drug-compound-target network was constructed using Cytoscape 3.9.1 software for network topological analysis. The protein interaction relationship was analyzed using the String database platform. Metascape database conducted enrichment analysis on the key targets using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. The renoprotective effect was evaluated using a mouse model of diabetic nephropathy (db/db mice) that occurred spontaneously. Validation of the associated targets and pathways was performed using Western Blot (WB), Polymerase Chain Reaction (PCR), and Immunohistochemical methods (IHC). Results: The network analysis showed that the TSF pathway network targeted 24 important targets and 149 significant pathways. TSF might have an impact by focusing on essential objectives such as TP53, PTEN, AKT1, BCL2, BCL2L1, PINK-1, PARKIN, LC3B, and NFE2L2, along with various growth-inducing routes. Our findings demonstrated that TSF effectively repaired the structure of mitochondria in db/db mice. TSF greatly enhanced the mRNA levels of PINK-1. WB and IHC findings indicated that TSF had a notable impact on activating the PINK-1/PARKIN signaling pathway in db/db mice, significantly increasing LC3 and NRF2 expression. Conclusion: Our results indicate that TSF effectively addresses DN by activating the PINK-1/PARKIN signaling pathway and enhancing Mitochondrion structure in experimental diabetic nephropathy.

Indexed as

diabetes nephropathymitophagynetwork pharmacologyPINK1/Parkin pathwaytangshen formula

Identifiers

PMID38375488
PMCPMC10874885

What Socratic holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

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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.