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Record W4310645563 · doi:10.3168/jds.2022-22134

Effects of additional gonadotropin-releasing hormone and prostaglandin F2α treatment to an estradiol/progesterone-based embryo transfer protocol for recipient lactating dairy cows

2022· article· en· W4310645563 on OpenAlexaff
M.H.C. Pereira, Bruno I Cappellozza, R.L.A. Cerri, C.P. Sanches, T.G. Guida, L.F.S.P. Barbosa, J.E.P. Santos, J.L.M. Vasconcelos

Bibliographic record

VenueJournal of Dairy Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of British Columbia
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsCorpus luteumEstradiol benzoateGonadotropin-releasing hormoneEstrous cycleEmbryo transferInternal medicineEndocrinologyProstaglandinPregnancyDairy cattleAndrologyHormoneMedicineBiologyAnimal scienceLuteinizing hormoneOvariectomized rat

Abstract

fetched live from OpenAlex

This study was designed to evaluate whether the utilization of a second PGF 2α treatment at the end of an estradiol/progesterone (E2/P4)-based protocol with or without GnRH at the beginning of the protocol would improve pregnancy rates of lactating Holstein cows assigned to timed embryo transfer. A total of 501 lactating Holstein cows in 5 farms were enrolled in the experiment. Within farm, cows were blocked by parity and, within block, were assigned randomly to (1) insertion of an intravaginal P4 device (controlled internal drug-releasing device; CIDR) and estradiol benzoate on d −11, PGF 2α on d −4, CIDR withdrawal and an injection of estradiol cypionate on d −2, and timed embryo transfer on d 7 (1-PGF; n=164); (2) the same treatments as 1-PGF, but with PGF 2α administered on d −4 and −2 (2-PGF; n=171); and (3) 2-PGF with the addition of a GnRH treatment on d −11 (GnRH + 2-PGF; n=166). Ovaries were scanned by transrectal ultrasonography on d −11, −4, and 7, and blood samples were collected on d −11, −4, 0, and 7 for P4 determination. Treatment comparisons were performed using contrasts. The proportion of cows with a new corpus luteum on d −4 was greater in GnRH + 2-PGF cows. Cows in 1-PGF had a greater P4 concentration on d 0 but lesser P4 on d 7 compared with cows in the other groups. Cows assigned to receive 2-PGF (2-PGF and GnRH + 2-PGF) had greater estrus expression, and a greater proportion of cows ovulated to estradiol cypionate. No further contrast effects were observed for follicle diameter, double ovulation rate, pregnancy per embryo transfer (P/ET) on d 32 and 60, or pregnancy loss. As P4 concentration on d −4 increased, P/ET on d 60 tended to increase. Cows with P4 ≥3.66 ng/mL on d −4 had greater P/ET on d 32 and 60 than those with P4 below that threshold. Regardless of treatment, cows with P4 concentration ≥3.66 ng/mL also had a greater pregnancy per synchronized protocol (P/SP) on d 60. Also, a P4 concentration on d −4 (low or high) × follicle diameter (continuous) interaction tendency was observed when evaluating P/ET. Although P/ET did not differ among cows with different follicles sizes with reduced P4 concentration on d −4 (<3.66 ng/mL), it increased in cows with larger follicles exposed to increased P4 concentration (≥3.66 ng/mL). When P4 on d 0 was evaluated, P/ET on d 32 and 60 was greater for cows with low (≤0.09 ng/mL) versus high (>0.21 ng/mL) P4; as P4 concentration on d 0 increased, P/ET linearly decreased. In summary, cows with increased P4 concentrations during growth of the ovulatory follicular wave had improved P/ET. Administering a second PGF 2α dose reduced P4 concentration on d 0 and increased ovulatory response to the protocol, but no benefits were observed on P/ET or P/SP.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · 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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.283
Teacher spread0.254 · 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 designNon-randomized trial
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
Published2022
Admission routes1
Has abstractyes

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