RESISTANCE TRAINING AND THE GH/IGF-1 AXIS IN WOMEN
Bibliographic record
Abstract
Declining levels of anabolic hormones such as growth hormone (GH) and insulin-like growth factor-1 (IGF-1) may exacerbate age-related losses of lean body mass and physical function in women. Exercise can stimulate the GH/IGF-1 axis, however, the response may be affected by age, estrogen levels, and training status. PURPOSE To examine the effect of resistance training on the GH and IGF-1 response to exercise in women of different ages and estrogen levels. METHODS 45 subjects were recruited: 16 postmenopausal women using supplemental estrogen (HRT), 16 postmenopausal women not using estrogen (NHRT), and 13 young, premenopausal women (YW). Subjects in each group were randomly selected into a 12-week resistance training program (RT) or a control group (C). At weeks 0 and 13, subjects completed 2 sets of 10 reps of 8 exercises at 10RM intensity. Preexercise, post-exercise and 15 minute recovery blood samples were analyzed for plasma lactate and serum levels of GH, IGF-1, and estradiol (E2). YW were tested in the early follicular phase of their menstrual cycle. Group, time, and week comparisons were made using repeated measures ANOVA. RESULTS Resting E2 levels were significantly different between all groups (p < 0.01) with HRT having the highest and NHRT having the lowest. Post-exercise lactate was significantly greater at week 13 compared to week 0 (p < 0.01). GH increased significantly in response to the exercise session (p < 0.01). Post-exercise GH concentrations did not differ between groups, however, the relative change after exercise was greater in the YW-RT group compared to all other groups (p < 0.05). IGF-1 concentrations showed a small but significant post-exercise increase (p < 0.01). The relative post-exercise change in IGF-1 was significantly greater after training (p < 0.05) however there were no systematic group differences in IGF-1 responses to exercise. CONCLUSION Training status and exercise intensity appear to have a greater effect than age of E2 levels on the relative GH and IGF-1 responses to exercise. Supported by the Medical Research Fund of NB and NSERC.
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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 | 0.000 |
| 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".