Relative effects of estrogen, age, and visceral fat on pulsatile growth hormone secretion in healthy women
Bibliographic record
Abstract
Growth hormone (GH) secretion is subject to complex regulation. How pre- and postmenopausal age (PRE, POST), estradiol (E(2)) availability, and abdominal visceral fat (AVF) jointly affect peptidyl-secretagogue drive of GH secretion is not known. To this end, healthy PRE (n = 20) and POST (n = 22) women underwent a low- vs. high-E(2) clamp before receiving a continuous intravenous infusion of GH-releasing hormone (GHRH) or GH-releasing peptide (GHRP-2). According to analysis of covariance, PRE and POST women achieved age-independent hypo- and euestrogenemia under respective low- and high-E(2) clamps. All four of age (P < 0.001), E(2) status (P = 0.006), secretagogue type (P < 0.001), and an age x peptide interaction (P = 0.014) controlled pulsatile GH secretion. Independently of E(2) status, POST women had lower GH responses to both GHRH (P = 0.028) and GHRP-2 (P < 0.001) than PRE women. Independently of age, GHRP-2 was more stimulatory than GHRH during low E(2) (P = 0.011) and high E(2) (P < 0.001). Stepwise forward-selection multivariate analysis revealed that computerized tomographic estimates of AVF explained 22% of the variability in GHRH action (P = 0.002), whereas age and E(2) together explained 60% of the variability in GHRP-2 drive (P < 0.001). These data establish that age, estrogen status, and AVF are triple covariates of continuous peptide-secretagogue drive of pulsatile GH secretion in women. Each factor must be controlled for to allow valid comparisons of GH-axis activity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".