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Record W4402540773 · doi:10.1093/jas/skae234.323

227 Moderate body weight loss reduces total antioxidant capacity in pregnant beef heifers and one-carbon metabolite supplementation does not mitigate this response

2024· article· en· W4402540773 on OpenAlexaff
Rebecca M Swanson, Mara R Hirchert, Alison K Ward, Lawrence P. Reynolds, Pawel P. Borowicz, Layla E King, Kathlyn M Hauxwell, Jennifer L Hurlbert, Carl R Dahlen, Joel S Caton

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAnimal scienceGlutathione peroxidaseAntioxidantSuperoxide dismutaseWeight gainBeef cattleGestationVitamin EInseminationArtificial inseminationEstrous cycleMetaboliteBiologyChemistryEndocrinologyInternal medicinePregnancyBiochemistryMedicineBody weight

Abstract

fetched live from OpenAlex

Abstract In beef heifers, body weight (BW) gain and physiological stress are important considerations for reproductive outcomes and whole herd production efficiencies. The objective of this study was to determine if dietary one-carbon metabolite (OCM) supplementation in moderate BW loss pregnant heifers alters circulating total antioxidant capacity, superoxide dismutase, and glutathione peroxidase activity. In a replicated 2 × 2 factorial, Angus-cross heifers (n = 81) were stratified by BW to gain 0.45 kg/d (CON) or lose 0.23 kg/d (RES) and receive corn carrier with OCM supplements (+OCM) or without (−OCM). The OCM supplements consisted of vitamin B12 (20 mg) and folate (320 mg) injections weekly and dietary rumen-protected methionine (7.4 g/d) and choline (44.4 g/d) from breeding (d 0) to d 63 of gestation. The four treatment groups were: CON−OCM (n = 20), CON+OCM (n = 21), RES−OCM (n = 21), and RES+OCM (n = 19). Heifers underwent estrus synchronization and were bred via artificial insemination using female sexed semen to a single sire. Pregnancy was diagnosed and fetal sex was verified on d 35 of gestation. Blood was collected and assayed for total antioxidant capacity, superoxide dismutase, and glutathione peroxidase activity on d −2 (baseline), 35, and 63 of gestation for all three replicates. Data were analyzed using the MIXED procedure of SAS with repeated measures to determine the effect of gain, supplement, day, and their two-way and three-way interactions. The gain × supplement interaction remained in all models, but other interactions were removed if P > 0.10. Replicate and heifer BW were included in the model as covariates and covariance structure was determined by lowest AIC and BIC. Statistical significance was considered at P ≤ 0.05 and tendencies at 0.05 < P ≤ 0.10. There was no BW gain × supplement interaction, or main effect of OCM supplements in total antioxidants. There was a gain × day effect (P ≤ 0.01), in which total antioxidants were increased on d 35 and further increased on d 63 in CON compared with RES treatments. There was no gain × supplement interaction, or main effect of gain or OCM supplements in superoxide dismutase and glutathione peroxidase. However, both superoxide dismutase and glutathione peroxidase were decreased (P ≤ 0.01) on d 63 compared with d 0 and 35. These data suggest that moderate BW loss reduces total antioxidant capacity in pregnant beef heifers, which could affect redox homeostasis. However, OCM supplements did not affect total antioxidant capacity, superoxide dismutase, or glutathione peroxidase. These findings are somewhat surprising considering oxidative stress has been well characterized in nutrient-restricted pregnancies, and given the interconnection between energy metabolism and one-carbon metabolism. Future research is warranted to fully elucidate the therapeutic effects of one-carbon metabolites.

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 score0.001
Threshold uncertainty score0.004

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 head0.030
GPT teacher head0.266
Teacher spread0.236 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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