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Record W4376598394 · doi:10.3168/jds.2022-22147

Use of intravaginal lactic acid bacteria prepartum as an approach for preventing uterine disease and its association with fertility of lactating dairy cows

2023· article· en· W4376598394 on OpenAlexafffund
A.M.L. Madureira, T.A. Burnett, Courtney T. Boyd, Matheus Baylão, R.L.A. Cerri

Bibliographic record

VenueJournal of Dairy Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of GuelphUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsMetritisMedicineIce calvingArtificial inseminationAnimal scienceIncidence (geometry)Estrous cyclePostpartum periodVaginal dischargePregnancyGynecologyObstetricsInternal medicineLactationBiologyMathematics

Abstract

fetched live from OpenAlex

The objective of this study was to evaluate the effects of the use of intravaginal probiotics prepartum on the incidence risk of metritis postpartum and conception risk after first artificial insemination (AI). A total of 606 Holstein cows were enrolled 3 wk before their expected calving date from 2 farms. Cows were randomly assigned to either receive a 2-mL dose of a combination of 3 lactic acid bacteria (probiotic treatment) washed with approximately 2 mL of a sterile saline solution, into the vaginal canal twice weekly until parturition, or no intervention (control). Metritis diagnoses were carried out on 6 and 12 d postpartum. Vaginal discharge and rectal temperature were assessed, and vaginal discharge was scored on a scale from 1 to 4, where 1 = clear and 4 = fetid, purulent discharge. Metritis was defined as cows having a vaginal discharge score of 4 with or without fever (rectal temperature ≥39.5°C) on either 6 or 12 d postpartum, or both. Cows were bred after a 60-d voluntary waiting period primarily via the detection of estrus using automated activity monitors; cows not found in estrus were enrolled onto timed AI protocols to receive first breeding before 100 DIM. Pregnancy diagnosis was carried out at d 35 ± 7 post-AI on both farms. Data were analyzed via ANOVA using linear mixed regression models and survival analysis using a Cox proportional hazard model. Total incidence risk of metritis was 23.7% and 34.4% on farm A and farm B, respectively. Overall, the incidence of metritis was not different between treatment groups (control: 41.6 ± 3.8%; probiotic: 38.6 ± 4.0%); however, an interaction by farm was detected, where the probiotic treatment reduced metritis on one farm but not on the other. Conception risk after first AI was not affected by treatment. However, we detected an interaction between parity and treatment, where multiparous cows receiving the probiotic treatment were more likely to become pregnant compared with multiparous cows within the control group (hazard ratio: 1.33; 95% confidence interval: 1.10-1.60); no effect of probiotic treatment was found on the hazard of pregnancy for primiparous cows. In addition, the probiotic treatment was associated with an increased proportion of cows being detected in estrus for the first AI postpartum. In conclusion, vaginal probiotic treatment applied during the 3 wk prepartum was associated with a decreased incidence of metritis on one farm but not the other, suggesting that farm management may be a key player influencing treatment efficacy. Overall, probiotic treatment was found to have only limited effects on fertility in the current study.

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: Observational · Consensus signal: Observational
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)0.0000.000
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 head0.045
GPT teacher head0.292
Teacher spread0.247 · 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

Citations17
Published2023
Admission routes2
Has abstractyes

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