Evidence map›Paper›PMID 39162795›Full record

ReviewNaunyn-Schmiedeberg's archives of pharmacology2025

Dysregulation of lipid metabolism in chronic kidney disease and the role of natural products.

Yang-Yi Jiang, Xiao-Li Jiang, Hai-Ning Yu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Naunyn-Schmiedeberg's archives of pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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. Article
  3. 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

3 authors.

Yang-Yi JiangCollege of Pharmaceutical Science, Zhejiang University of Technology, Hangzhou, China.
Xiao-Li JiangNephrology Department, Ningbo Medical Center Lihuili Hospital, Ningbo, China.
Hai-Ning YuCollege of Pharmaceutical Science, Zhejiang University of Technology, Hangzhou, China. yuhaining@zjut.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dysregulation of lipid metabolism plays a key role in the onset and progression of CKD, and a thorough understanding of its regulatory mechanisms is essential for the development of effective treatments. In recent years, an increasing number of studies have focused on the pharmacological activities of natural products and their application in the treatment of chronic diseases. Natural products, including plant extracts and bioactive compounds, have been shown to exert anti-inflammatory, antioxidant, antifibrosis, and anti-apoptotic effects through various signaling pathways in the treatment of CKD. Many natural products have been shown to target dysregulated lipid metabolism through various signaling pathways. This review summarizes the key regulatory factors and signaling pathways involved in the dysregulation of lipid metabolism in chronic kidney disease (CKD), highlighting their importance as potential therapeutic targets. Recently published research on the potential therapeutic benefits of natural products for the treatment of CKD was described. These studies have revealed the multi-target role of natural products in the regulation of lipid metabolism. Natural products show great potential in targeting lipid metabolism-related pathways, offering a novel research direction for the treatment of CKD while providing a scientific basis and experimental support for the development of new treatment strategies.

Indexed as

Biological ProductsLipid MetabolismRenal Insufficiency, ChronicAnimalsHumansSignal TransductionBiological ProductsChronic kidney diseaseDysregulated lipid metabolismLipid metabolism-related pathwaysNatural products

Identifiers

What OpenQuestion holds

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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 OpenQuestion graph.