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Record W3189210511 · doi:10.1371/journal.pone.0248453

Plasma concentrations of progesterone in the preceding estrous cycle are associated with the intensity of estrus and fertility of Holstein cows

2021· article· en· W3189210511 on OpenAlexafffund
A.M.L. Madureira, T.A. Burnett, S. Borchardt, W. Heuwieser, Christine F. Baes, J.L.M. Vasconcelos, R.L.A. Cerri

Bibliographic record

VenuePLoS ONE · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of GuelphUniversity of British Columbia
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of CanadaGenome AlbertaGenome British ColumbiaCanadian Dairy CommissionDairy Farmers of CanadaGenome Canada
KeywordsEstrous cycleArtificial inseminationAnimal scienceEndocrinologyEstrogenInternal medicinePregnancyInseminationAndrologyBiologyMedicineSperm

Abstract

fetched live from OpenAlex

The aim of this study was to determine the association between concentrations of progesterone (P4) during previous the estrous cycle with the intensity of spontaneous or estrogen-induced estrous expression and pregnancy per artificial insemination (P/AI). A total of 1,953 AI events from lactating Holstein cows were used, consisting of 1,289 timed AI events from experiment 1 (Exp. 1) and 664 AI events from experiment 2 (Exp. 2). In Exp. 1, cows were bred after a timed AI protocol based on estradiol and P4. In Exp. 2 animals were bred upon spontaneous estrus detection. In both experiments cows were continuously monitored by an automated activity monitor (AAM), in Exp.1 a relative increase of activity was calculated (i.e., percentage of increase activity at estrus compared to cow's baseline activity) and in Exp.2, activity data from each cow were computed into an index value that ranged from 0 to 100. In Exp.2 duration (hours) of estrus were calculated and defined as the total time above the threshold (35 index). The intensity of estrous expression was determined for each event and classified as either high or low intensity using the median of each experiment. Blood samples were collected for P4 analysis in Exp. 1 at -4 d, 0 d, and 7 d relative to timed AI, and in Exp. 2 immediately following estrus (0 d), 7 d, 14 d, and 21 d post-AI. Concentration of P4 was classified as greater or lower according to the median value in each experiment. Cows with lower concentrations of P4 at AI had greater estrous expression in Exp. 1 (363.6 ± 5.2 vs. 275.9 ± 8.0% relative increase) and Exp. 2 (76.7 ± 1.9 vs. 67.4 ± 4.7 index; and 12.5 ± 0.5 vs. 9.3 ± 1.8 hours). Cows with a greater intensity of estrous expression at timed AI had greater concentrations of P4 at -4 d than cows with lower intensity estrus or no estrous expression (4.6 ± 0.2 vs. 3.6 ± 0.2 vs. 3.7 ± 0.2 ng/mL). Cows with greater concentrations of P4 at -4 d had greater P/AI (32.8 ± 4.4 vs. 22.4 ± 4.5%), whereas cows with lesser concentrations of P4 at d0 for either timed AI (35.2 ± 3.4 vs. 19.6 ± 4.6%) or spontaneous estrus (31.8 ± 2.8 vs. 23.4 ± 3.2%) had greater P/AI. Cows with greater concentrations of P4 7 d post-timed AI had greater P/AI compared with cows that had lower concentration of P4 (39.1 ± 2.9 vs. 24.7 ± 2.6%). Similarly, cows that had lower concentrations of P4 at 7 d, 14 d and 21 d post-spontaneous estrus tended to have lower P/AI when compared with cows with greater concentrations of P4. Overall, concentrations of P4 prior to and at AI were associated with greater estrous intensity and P/AI at both spontaneous and timed AI events.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.525
Threshold uncertainty score0.115

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.049
GPT teacher head0.216
Teacher spread0.167 · 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 teacher head, 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

Citations31
Published2021
Admission routes2
Has abstractyes

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