Evidence map›Paper›PMID 39296670›Full record

ArticleDrug design, development and therapy2024

Huangqi-Danshen Decoction Against Renal Fibrosis in UUO Mice via TGF-β1 Induced Downstream Signaling Pathway.

Xi Huang, Yu Peng, Lingfei Lu, Liwen Gao, Shanshan Wu, Jiandong Lu, Xinhui Liu

Abstract read
In one paragraph

Article in Drug design, development and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
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.

Xi Huang *Department of Nephrology, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, People's Republic of China.
Yu Peng *Department of Nephrology, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, People's Republic of China.
Lingfei Lu *Department of Nephrology, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, People's Republic of China.
Liwen GaoDepartment of Nephrology, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, People's Republic of China.
Shanshan WuDepartment of Nephrology, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, People's Republic of China.
Jiandong LuDepartment of Nephrology, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, People's Republic of China.
Xinhui LiuDepartment of Nephrology, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Huangqi-Danshen decoction (HDD) is a Chinese medicinal herb pair with good efficacy in treating chronic kidney disease, but its mechanism needs to be clarified. Aim: To uncover the underlying mechanism of HDD antagonizing renal fibrosis through network pharmacology (NP) analysis and experimental validation. Materials and Methods: The chemical components of water extract of HDD were analyzed by combining the ultra-high performance liquid chromatography coupled with Q-Exactive mass spectrum analysis (UHPLC-QE-MS) and HERB database. NP was used to identify core common targets of HDD components and renal fibrosis. Subsequently, male C57BL/6 mice were divided into Sham, unilateral ureteral obstruction (UUO) and UUO+HDD groups. Renal function, histopathology, Western blotting, and immunohistochemistry analyses were used to evaluate the protective effect of HDD on UUO mice. The effects of HDD on signaling pathways were validated in both UUO mice and transforming growth factor-β1 (TGF-β1)-induced HK-2 cells. Results: By combining UHPLC-QE-MS analysis and HERB database, 25 components were screened in HDD extract. There were 270 intersection targets of the 25 components and renal fibrosis. Based on their scores in protein-protein interaction analysis and degree values in component-pathway-target triadic network, 6 core common targets of the 25 components and renal fibrosis were identified, namely phosphoinositide 3-kinase (PI3K), signal transducer and activator of transcription 3 (Stat3), non-receptor tyrosine kinase Src (Src), epidermal growth factor receptor (EGFR), matrix metalloproteinase 9 (MMP9), and MMP2. HDD ameliorated renal tubular damage and collagen deposition and downregulated fibrosis-related proteins expression in UUO mice. Furthermore, HDD was demonstrated to reduce PI3K, Stat3, Src, EGFR, and MMP2 expressions, and enhance MMP9 expression in the kidney of UUO mice and in TGF-β1-induced HK-2 cells. Conclusion: HDD can alleviate renal fibrosis which may be related to regulating the expression of essential proteins in the epithelial-mesenchymal transition and extracellular matrix production/degradation signaling pathways.

Indexed as

Drugs, Chinese HerbalFibrosisMice, Inbred C57BLSignal TransductionTransforming Growth Factor beta1Ureteral ObstructionAnimalsCells, CulturedChromatography, High Pressure LiquidDisease Models, AnimalHumansKidney DiseasesMaleMiceNetwork PharmacologySalvia miltiorrhizadan-shen root extractDrugs, Chinese Herbalhuangqi decoctionTransforming Growth Factor beta1chronic kidney diseaseHuangqi-Danshen decoctionnetwork pharmacologyrenal fibrosissignaling pathway

Identifiers

PMID39296670
PMCPMC11410030

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.