Bone Changes and Fracture Related to Menstrual Cycles and Ovulation
Bibliographic record
Abstract
Women's menstrual cycles and bone remodeling are linked in part by their co-dependency on the stress- and resource-associated variables that govern both of their cyclical natures. Therefore, it is not surprising that evolution has resulted in the same signaling molecules and pathways that regulate normal ovarian function to be involved in bone remodeling and turnover. This review will first provide an overview of the normal menstrual cycle, its modification by age and ovulatory disturbances, and how it parallels bone remodeling. Epidemiological and clinical evidence will be presented that link bone remodeling, strength, and fractures with women's history of reproductive and menstrual cycle characteristics. This combined evidence will then be presented alongside a synthesis of current concepts derived from basic science investigations focused on understanding the molecular mechanisms underlying the influence of ovarian factors on bone physiology. Osteoporosis is a significant source of morbidity for older women. The data presented in this review suggest that a woman's reproductive cycle and ovulatory characteristics foreshadow the future health of her bones. More importantly, identifying the key mechanisms underlying reproductive and bone health would not only provide essential preventative strategies, but may also uncover attractive targets for the treatment of osteoporosis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".