Evidence map›Paper›PMID 41303306›Full record

ArticleInternational journal of molecular sciences2025

Multi-Omics Insights into the Effects of Long-Term Faba Bean Feeding on Muscle Quality and Metabolic Reprogramming in Nile Tilapia (

Rongni Li, Saisai Wang, Yansheng Sun, Xin Zhang

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Rongni LiFisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100068, China.ORCID 0000-0002-5631-6501
Saisai WangFisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100068, China.
Yansheng SunFisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100068, China.
Xin ZhangFisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100068, China.

Funding

National Freshwater Aquatic Germplasm Resource Bank FGRC: 18537the China Agriculture Research System CARS46-32
6 · The paper itself

Abstract

While short-term faba bean feeding is known to improve fish texture, its long-term systemic effects and the underlying molecular mechanisms in Nile tilapia remain rarely explored. This knowledge gap is critical, given the potential for extended feeding to induce distinct metabolic reprogramming and trade-offs. Here, we present the first comprehensive study investigating the 180-day impact of a 60% FB-based diet (FBD) on Nile tilapia through an integrated analysis of phenotypic traits, muscle histology, metabolome, and transcriptome. Our results revealed a fundamental trade-off: FBD feeding induced hyperplasia-driven muscle remodeling, significantly enhancing textural properties (hardness, gumminess, chewiness) and increasing intramuscular fat and collagen content, but at the cost of suppressed growth and hepatosomatic index. Metabolomics identified 243 significantly altered metabolites, outlining a systemic metabolic shift characterized by activated lipid synthesis but inhibited amino acid and energy metabolism. This multi-omics integration nominated the

Indexed as

Animal FeedCichlidsMuscle, SkeletalVicia fabaAnimalsDietEnergy MetabolismMetabolic ReprogrammingMetabolomeMetabolomicsMultiomicsTranscriptome60% faba bean-based dietchac1 geneeffects of long-term feedinghistological analysismeat quality assessmentmuscle hyperplasiatilapiatranscriptome-metabolome integration

Identifiers

PMID41303306
PMCPMC12652850

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.