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Record W4402254348 · doi:10.1093/jas/skae258

One-carbon metabolites supplementation and nutrient restriction alter the fetal liver metabolomic profile during early gestation in beef heifers

2024· article· en· W4402254348 on OpenAlexaff
Kazi Sarjana Safain, Matthew S Crouse, Jessica G Syring, Yssi L Entzie, Layla E King, Mara R Hirchert, Alison K Ward, Lawrence P. Reynolds, Pawel P. Borowicz, Carl R Dahlen, Kendall C Swanson, Joel S Caton

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of Saskatchewan
FundersNational Institute of Food and AgricultureU.S. Department of Agriculture
KeywordsIsoleucineValineMetabolismMethionineInternal medicineBiologyEndocrinologyLeucineTaurineMetabolomicsNicotinamideBiochemistryAmino acidMedicineEnzymeBioinformatics

Abstract

fetched live from OpenAlex

Maternal nutrition is pivotal for proper fetal development, with one-carbon metabolites (OCM) playing a key role in fetal epigenetic programming through DNA and histone methylation. The study aimed to investigate the effects of nutrient restriction and OCM supplementation on fetal liver metabolomics in pregnant beef-heifers, focusing on metabolites and pathways associated with amino acid, vitamin and cofactor, carbohydrate, and energy metabolism at day 63 of gestation. Thirty-one crossbred Angus heifers were artificially inseminated and allocated to 4 nutritional treatments in a 2 × 2 factorial arrangement of treatments, with the 2 factors being dietary intake/rate of gain (control-diet [CON]; 0.60 kg/d ADG, vs. restricted-diet [RES]; -0.23 kg/d ADG) and OCM supplementation (supplemented [+OCM] vs. not supplemented [-OCM]). The resulting treatment groups-CON - OCM, CON + OCM, RES - OCM, and RES + OCM were maintained for 63 day post-breeding. Following this period, fetal liver tissues were collected and subjected to metabolomic analysis using UPLC-tandem mass-spectrometry. We identified 288 metabolites, with the majority (n = 54) being significantly influenced by the main effect of gain (P ≤ 0.05). Moreover, RES showed decreased abundances of most metabolites in pathways such as lysine metabolism; leucine, isoleucine, and valine metabolism; and tryptophan metabolism, compared to CON. Supplementation with OCM vs. no OCM supplementation, resulted in greater abundance of metabolites (P ≤ 0.05) affecting pathways associated with methionine, cysteine, S-adenosylmethionine and taurine metabolism; guanidino and acetamido metabolism; and nicotinate and nicotinamide metabolism. Notably, OCM supplementation with a moderate rate of gain increased the concentrations of ophthalmate, N-acetylglucosamine, and ascorbic-acid 3-sulfate, which are important for proper fetal development (P ≤ 0.05). Nutrient restriction reduced the majority of liver metabolites, while OCM supplementation increased a smaller number of metabolites. Thus, OCM supplementation may be protective of metabolite concentrations in key developmental pathways, which could potentially enhance fetal development under nutrient-restricted conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.305
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2024
Admission routes1
Has abstractyes

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