Ovarian antral folliculogenesis during the human menstrual cycle: a review
Bibliographic record
Abstract
BACKGROUND Ovarian follicles undergo dynamic morphologic and endocrinologic changes during the human menstrual cycle. The physiologic mechanisms underlying recruitment and selection of antral follicles in women are not fully elucidated. METHODS A comprehensive review of >200 studies was conducted using PubMed. The objective was to compare and contrast different perspectives on human antral folliculogenesis. RESULTS Antral folliculogenesis has been studied using histologic, endocrinologic and/or ultrasonographic techniques. Different theories of antral follicle recruitment include: (i) continuous recruitment throughout the menstrual cycle; (ii) recruitment of a 'cohort' of antral follicles once in the late-luteal phase or early-follicular phase of each cycle and (iii) recruitment of two or three 'cohorts' or 'waves' during each cycle. Generally, a single dominant follicle is selected in the mid-follicular phase of each cycle and this follicle ovulates at mid-cycle. However, a dominant follicle may also be selected during anovulatory waves that precede the ovulatory wave in some women. CONCLUSIONS There is increasing evidence to indicate that multiple waves of antral follicles develop during the human menstrual cycle. Ovarian follicular waves in women are comparable with those documented in several animal species; however, species-specific differences exist. Enhancing our understanding of the endocrine and paracrine mechanisms underlying antral follicular wave dynamics has clinical implications for understanding age-related changes in reproductive function, optimizing hormonal contraceptive and ovarian stimulation regimens and identifying non-invasive markers of the physiologic status of follicles which are predictive of oocyte competence and assisted reproduction outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".