Bovine Model to Study Ovarian Function and Oocyte Competence in Women during Perimenopausal Period
Bibliographic record
Abstract
The introduction of transrectal ultrasonography in late 1980's provided a unique non‐invasive tool to image ovarian structures over time. The technique allowed assessment of dynamics of follicle growth and regression in cows leading to validation of the wave theory of follicular growth. Over the past three decades, studies in the bovine model have focused on the characteristics of the dominant follicle selection, control of wave emergence, synchronization of ovulation, and the temporal relationship of oocyte's ability to develop into a blastocyst (oocyte competence) with the status of the dominant follicle. Studies of this nature are unethical and difficult to conduct in women. Follicular waves have been described in every monovular mammalian species in which ultrasonographic approach have been applied since the first description in cattle (in 1989) including humans (in 2003). Differences in selection of the dominant follicle and control of luteal function between humans and domestic animals appear to be more in detail rather than in essence. Relatively large diameters of the dominant follicles for clinical manipulations (e.g., follicle ablation for wave emergence, monitoring gonadotropin response during superovulation, ultrasound‐guided oocyte retrieval for in vitro fertilization), long life span of cows (15 to 20 years) and presence of multiple generations of animals on the same farm make cattle as one of the most suitable model to understand ovarian and oocyte function during perimenopausal period in women. Our research group have discovered that compared to young daughters (3–5 years), old cows (≥13 years) have elevated concentrations of FSH (similar to humans) and a marked decrease in embryo recovery documenting the effects of maternal age on oocyte competence. Maternal aging in cattle altered the timing of the preovulatory LH surge. Further, transcriptome analysis of granulosa cells from aged cows detected a suboptimal response to exogenous LH treatment indicating the possible mechanism by which the maternal age influences oocyte competence. In contrast to maternal aging, follicular aging (4‐day FSH followed by 96 hours of gonadotropin starvation) in younger cows led to reduced ovulation rates, accumulation of large lipid droplets in the oocyte, fertilization failures, and decreased blastocyst rate highlighting the multifaceted nature of factors that can influence oocyte competence. Interestingly, oocyte ability to develop into embryos was maintained if FSH support was continued. As a natural extension of our research, we have started to examine the influence of FSH superstimulation on oocyte competence during pre‐pubertal age in calves as young as 4‐month of age. Our working hypothesis is that the endocrine milieu and local ovarian factors responsible for low developmental competence of oocytes during the pre‐pubertal period are unique and distinct from those that cause the loss of competence during old age in the bovine model. Support or Funding Information Research supported by grants from the Natural Sciences and Engineering Council of Canada This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".