Metabolic hormones are integral regulators of female reproductive health and function
Bibliographic record
Abstract
The female reproductive system is strongly influenced by nutrition and energy balance. It is well known that food restriction or energy depletion can induce suppression of reproductive processes, while overnutrition is associated with reproductive dysfunction. However, the intricate mechanisms through which nutritional inputs and metabolic health are integrated into the coordination of reproduction are still being defined. In this review, we describe evidence for essential contributions by hormones that are responsive to food intake or fuel stores. Key metabolic hormones-including insulin, the incretins (glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1), growth hormone, ghrelin, leptin, and adiponectin-signal throughout the hypothalamic-pituitary-gonadal axis to support or suppress reproduction. We synthesize current knowledge on how these multifaceted hormones interact with the brain, pituitary, and ovaries to regulate functioning of the female reproductive system, incorporating in vitro and in vivo data from animal models and humans. Metabolic hormones are involved in orchestrating reproductive processes in healthy states, but some also play a significant role in the pathophysiology or treatment strategies of female reproductive disorders. Further understanding of the complex interrelationships between metabolic health and female reproductive function has important implications for improving women's health overall.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".