The Effects of Estradiol and Progesterone on Plantarflexor Muscle Fatigue in Ovariectomized Mice
Bibliographic record
Abstract
The aim of this study was to examine specific and interactional effects of estradiol and progesterone on the time-to-fatigue of eccentrically contracted plantarflexor muscles and on the percent of plantarflexor isometric torque remaining immediately after an eccentric contraction (EC) protocol. Ovariectomized 6- to 8-week-old C57BL/6 mice were implanted with 21-day 0.05 mg-placebo, 0.05 mg-17-beta estradiol (OE), 15 mg-progesterone (OP), or estradiol and progesterone pellets (OEP). On the 16th day of hormone treatment, the isometric torque of the left plantarflexor muscles was measured. The left plantarflexor muscles then underwent 1 set of 150 ECs followed by 2 immediate post-EC isometric torque measurements. A group of ovarian-intact female mice of a similar age underwent the same isometric torque measurements and EC protocol. Plantarflexor muscle fatigue during ECs took 30%-41% longer to occur in the OP group (n = 9) than it did in the intact (n = 8, P = 0.02), OC (n = 11, P = 0.003), and OEP (n = 9, P = 0.007) groups. Peak active isometric torque had decreased immediately after ECs at 2 time points (M1 and M2). The OP group exhibited the greatest percent of isometric torque remaining immediately after ECs (M1, P = 0.03; M2, P = 0.04). These findings suggest that progesterone reduces muscle fatigue in response to ECs and that this progesterone effect is blunted when estradiol also is present. Therefore, ovarian hormone status may need to be considered when evaluating a response to physical activities, especially those activities involving ECs.
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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 | 0.001 |
| 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".