MétaCan
Menu
Back to cohort
Record W2592797386 · doi:10.1093/biolreprod/85.s1.524

Physical and Functional Markers of Fertility in Holstein Bulls.

2011· article· en· W2592797386 on OpenAlexaffabout
Habib A. Shojaei Saadi, Tom Kroetsch, Patrick Blondin, Randy Wilde, John P. Kastelic, Jacob C. Thundathil

Bibliographic record

VenueBiology of Reproduction · 2011
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsAgriculture and Agri-Food CanadaL'Alliance BoviteqUniversity of Calgary
Fundersnot available
KeywordsSpermBiologyFertilitySemenAndrologySemen analysisSperm motilityAnimal scienceInfertilityAnatomyPopulationGeneticsMedicinePregnancy

Abstract

fetched live from OpenAlex

Dairy bull semen often has wide variations in fertility, despite meeting minimum standards for quality. The objectives of this study were to compare testicular physical characteristics and sperm characteristics of Holstein bulls to identify fertility markers. Ten mature Holstein bulls (4-5 y old) were selected and classified as either low- or high-fertility (n=5 each) based on adjusted 56-d non-return rates. Scrotal measurements (scrotal circumference, scrotal neck circumference, scrotal neck length) and testicular dimensions, scrotal infrared thermograms, and testicular ultrasonographic data were recorded. Among all of these testicular physical characteristics, only testicular width was significantly lower for low- vs high-fertility bulls. Four ejaculates were collected from each bull and cryopreserved; frozen-thawed sperm from these samples were evaluated for viability, motion characteristics, ability to fertilize oocytes in vitro, and the developmental competence of resulting embryos. Flow cytometry-based analysis of sperm stained with SYBR14/PI demonstrated that low- and high-fertility bulls differed in sperm viability. The proportion of moribund sperm was higher in sperm from low- vs high-fertility bulls, and the proportion of moribund sperm were correlated with non-return rates. Based on a higher proportion of moribund sperm, expressed as a percentage of viable sperm in low- vs high-fertility bulls, we concluded that the rate of conversion of viable sperm to a moribund state was higher in low-fertility bulls, and that viability of sperm from low-fertility bulls was inherently compromised. Several sperm kinematic parameters were significantly correlated with non-return rates. Moreover, whereas post-thaw sperm from low-fertility bulls had a forward progressive motility pattern, sperm from high-fertility bulls were in transition to hyperactivated motility (based on linearity, curve line velocity and amplitude of lateral head displacement). Accordingly, a significantly lower percentage of hyperactivated sperm were present in the post-thaw semen of low- vs high-fertility bulls. Similarly, sperm selected through a sodium-hyaluronate swim-up medium (provided capacitating conditions) demonstrated that sperm from high-fertility bulls had a higher tendency to undergo hyperactivated motility. Following in vitro fertilization, the percentage of cleaved embryos were significantly lower in low- vs high-fertility bulls. In addition, 8-cell embryos, morulae, blastocysts, and hatched blastocysts (expressed as a percentage of cleaved embryos) were significantly lower in low- vs high-fertility bulls. In conclusion, testicular physical characteristics were not predictive of fertility in bulls producing semen with acceptable standards. However, proportion of moribund sperm present in frozen-thawed sperm, rate of conversion of viable sperm to a moribund state, CASA parameters, ability of sperm to undergo hyperactivation, ability of sperm to fertilize in vitro, and developmental competence of resulting embryos, were all predictive of fertility. This study received funding support from NSERC; L'Alliance Boviteq Inc., Saint-Hyacinthe, QC; Westgen, Milner, BC; Alberta Livestock and Meat Agency; and Agriculture & Food Council, AB. (poster)

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.045
GPT teacher head0.276
Teacher spread0.232 · 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
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueBiology of ReproductionSame topicReproductive Biology and FertilityFrench-language works237,207