Evidence map›Paper›PMID 38892512›Full record

ArticleNutrients2024

Distinct Gut Microbiota and Arachidonic Acid Metabolism in Obesity-Prone and Obesity-Resistant Mice with a High-Fat Diet.

Huixia Zhang, Shiqi Chen, Liu Yang, Shuai Zhang, Linqian Qin, Haiyang Jiang

Abstract read
In one paragraph

Article in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Effects ofAnimals : an open access journal from MDPI · 2025
    Article
  11. Frontiers in nutrition · 2025
    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

6 authors.

Huixia ZhangNational Key Laboratory of Veterinary Public Health and Safety, Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Shiqi ChenNational Key Laboratory of Veterinary Public Health and Safety, Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Liu YangNational Key Laboratory of Veterinary Public Health and Safety, Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Shuai ZhangNational Key Laboratory of Veterinary Public Health and Safety, Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Linqian QinNational Key Laboratory of Veterinary Public Health and Safety, Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
Haiyang JiangNational Key Laboratory of Veterinary Public Health and Safety, Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.ORCID 0000-0002-0529-0719

Funding

The Ministry of Science and Technology of the People's Republic of China 2019YFC1604902
6 · The paper itself

Abstract

An imbalance of energy intake and expenditure is commonly considered as the fundamental cause of obesity. However, individual variations in susceptibility to obesity do indeed exist in both humans and animals, even among those with the same living environments and dietary intakes. To further explore the potential influencing factors of these individual variations, male C57BL/6J mice were used for the development of obesity-prone and obesity-resistant mice models and were fed high-fat diets for 16 weeks. Compared to the obesity-prone mice, the obesity-resistant group showed a lower body weight, liver weight, adipose accumulation and pro-inflammatory cytokine levels. 16S rRNA sequencing, which was conducted for fecal microbiota analysis, found that the fecal microbiome's structural composition and biodiversity had changed in the two groups. The genera

Indexed as

Arachidonic AcidDiet, High-FatGastrointestinal MicrobiomeMice, Inbred C57BLObesityAnimalsBacteriaBody WeightDisease Models, AnimalFecesMaleMiceRNA, Ribosomal, 16SArachidonic AcidRNA, Ribosomal, 16Sarachidonic acid metabolismgut microbiotaobesity proneobesity resistantwidely targeted metabolomics

Identifiers

PMID38892512
PMCPMC11174461

What Socratic holds

Textmetadata
LicenceCC BY
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.