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Record W4398236660 · doi:10.3168/jds.2024-24792

Is prolonged luteal phase a problem in lactating Holstein cows?

2024· article· en· W4398236660 on OpenAlexafffund
J. Denis-Robichaud, A.P. Oliveira, Alejandro Sica, STEPHANIE SORIANO, R.L. Castro de Araujo, M.H.C. Pereira, Ky G Pohler, R.L.A. Cerri, J.L.M. Vasconcelos

Bibliographic record

VenueJournal of Dairy Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsLuteal phaseAnimal scienceHolstein CattleDairy cattleChemistryBiologyEndocrinologyFollicular phase

Abstract

fetched live from OpenAlex

In this study, the main objective was to assess if long luteal phases could have causes other than pregnancy loss. We enrolled Holstein dairy cows ≥50 DIM from a commercial herd in Brazil from October 2016 to August 2017. All cows received an estradiol-based synchronization protocol, and, on the day of insemination (d 0), were randomly assigned either an AI or a placebo insemination (PBO) in a 3:1 ratio. An ultrasound was used to assess the presence of a corpus luteum (CL) on d 17, 24, and 31, which, combined to the information from patches for the detection of estrus, was used to determine the length of the luteal phase following AI or PBO. Pregnancy was assessed by ultrasound on d 31 and cows that were pregnant were excluded from the analyses. The length of the estrous cycles was categorized as short (<17 d), normal (17-23 d), long (24-30 d), and very long (≥31 d). We compared the proportion of cows in each category between the AI and PBO groups using a cumulative ordinal mixed model. We define prolonged luteal phase as estrous cycles ≥24 d and tested its association with potential risk factors (parity, season, DIM, uterine size and position score, milk production, BCS, and the presence of a CL at enrollment to the synchronization protocol) using mixed logistic regression models. Results are presented as odds ratio (OR) and 95% Bayesian credible intervals (BCI). Data from 876 inseminations (AI: n = 616, PBO: n = 260) was collected. Overall, 12% of estrous cycles were short, 31% were normal, 19% were long, and 38% were very long. There was no difference in the odds of being in longer estrous cycle categories for the AI compared with the PBO group (OR = 0.92; 95% BCI = 0.76-1.10). Season and presence of a CL at enrollment were associated with prolonged luteal phase. In the AI group, there was a possible effect of early pregnancy losses on the lifespan of the CL, but not the PBO group, which led us to conclude that long and very long estrous cycles were not all caused by the embryonic loss. In fact, the high prevalence of cows with an extended CL lifespan in the present study suggests this could be an under- or miss-reported characteristic of high-producing lactating Holstein cows. This finding may have important repercussions in the understanding of the CL function physiology of lactating Holstein cows.

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)0.004
metaresearch head score (Gemma)0.010
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.035
GPT teacher head0.306
Teacher spread0.272 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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