Evidence mapPaperPMID 39866478Full record

ReviewHeliyon2025

Lipidomics-based natural products for chronic kidney disease treatment.

Rui Zhang, Jingjing Wang, Chenguang Wu, Lifan Wang, Peng Liu, Ping Li

Abstract readReview
In one paragraph

Review in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Frontiers in pharmacology · 2025
    Review
  4. 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

6 authors.

Rui ZhangRenal Division, Department of Medicine, Heilongjiang Academy of Chinese Medicine Sciences, Harbin, China.
Jingjing WangRenal Division, Department of Medicine, Heilongjiang Academy of Chinese Medicine Sciences, Harbin, China.
Chenguang WuRenal Division, Department of Medicine, Heilongjiang Academy of Chinese Medicine Sciences, Harbin, China.
Lifan WangRenal Division, Department of Medicine, Heilongjiang Academy of Chinese Medicine Sciences, Harbin, China.
Peng LiuShunyi Hospital, Beijing Hospital of Traditional Chinese Medicine, Beijing, China.
Ping LiBeijing Key Lab for Immune-Mediated Inflammatory Diseases, China-Japan Friendship Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease (CKD) is by far the most prevalent disease in the world and is now a major global public health problem because of the increase in diabetes, hypertension and obesity. Traditional biomarkers of kidney function lack sensitivity and specificity for early detection and monitoring of CKD progression, necessitating more sensitive biomarkers for early diagnostic intervention. Dyslipidemia is a hallmark of CKD. Advancements in mass spectrometry (MS)-based lipidomics platforms have facilitated comprehensive analysis of lipids in biological samples and have revealed changes in the lipidome that are associated with metabolic disorders, which can be used as new biomarkers for kidney diseases. It is also critical for the discovery of new therapeutic targets and drugs. In this article, we focus on lipids in CKD, lipidomics methodologies and their applications in CKD. Additionally, we introduce novel biomarkers identified through lipidomics approaches and natural products derived from lipidomics for the treatment of CKD. We believe that our study makes a significant contribution to literature by demonstrating that natural products can improve CKD from a lipidomic perspective.

Indexed as

Chronic kidney diseaseLipidomicsLipidsNatural productsTherapeutic targets

Identifiers

PMID39866478
PMCPMC11758422

What Socratic 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 Socratic graph.