Evidence map›Paper›PMID 40596386›Full record

ArticleScientific reports2025

Effect of enhanced early life nutrition on the M. longissimus thoracis et lumborum transcriptome of crossbred beef heifer calves.

Kate Keogh, Alan K Kelly, David A Kenny

Abstract read
In one paragraph

Article in Scientific reports, 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

3 authors.

Kate KeoghTeagasc Animal & Bioscience Research Department, Teagasc Grange, Dunsany, Co Meath, Ireland.
Alan K KellySchool of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland.
David A KennyTeagasc Animal & Bioscience Research Department, Teagasc Grange, Dunsany, Co Meath, Ireland. david.kenny@teagasc.ie.

Funding

Irish Department of Agriculture, Food and the Marine 13/S/515
6 · The paper itself

Abstract

Enhanced early-life nutrition in calves holds potential for improving economically important traits, including growth rate, milk yield and reproductive development. However, the mechanisms through which these nutritional strategies affect skeletal muscle development remain to be fully elucidated. This study aimed to evaluate the impact of enhanced dietary intake during early calf-hood on the transcriptional profile of skeletal muscle tissue. Angus × Holstein-Friesian heifer dairy-calves were offered either a high (HI, n = 10) or moderate (MOD, n = 10) diet from 3 to 21 weeks of life. At 21 weeks of age, M. longissimus thoracis et lumborum tissue was harvested from all calves and subsequently subjected to mRNA sequencing. Altered early-life nutrition led to the differential expression of 482 genes in the skeletal muscle transcriptome (False discovery rate (FDR) < 0.1; fold change > 1.5) between HI and MOD calves. Differentially expressed genes were involved in processes related to metabolism, energy production and cellular growth and proliferation and included enrichment of the Sirtuin signalling pathway and skeletal muscle system development and function. The results of this study identify novel gene transcripts involved in the molecular regulation of skeletal muscle response to nutritional modulation, offering insights into muscle development and its potential impact on tissue composition.

Indexed as

Animal Nutritional Physiological PhenomenaMuscle, SkeletalTranscriptomeAnimal FeedAnimalsCattleDietFemaleGene Expression ProfilingMuscle DevelopmentCalf-hood nutritionRNAseqSkeletal muscle

Identifiers

PMID40596386
PMCPMC12216419

What OpenQuestion 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 OpenQuestion graph.