Effects of ovariectomy and resistance training on MMP-2 activity in skeletal muscle
Bibliographic record
Abstract
Matrix metallopeptidases (MMPs) are crucial to the maintenance of healthy tissue. The aim of this study was to investigate MMP-2 activity in gastrocnemius, soleus, tibialis anterior (TA), and extensor digitorium longus (EDL) muscle after resistance training in ovariectomized rats. Wistar adult female rats were grouped into 7 groups (n = 10 per group): sedentary (Sed-Intact); ovariectomized sedentary (Sed-Ovx); pseudo-ovariectomized sedentary (Sed-Pseudo); acute exercise (AcuteEx-Intact); ovariectomized acute exercise (AcuteEx-Ovx); strength trained (ChronicEx-Intact); and ovariectomized strength trained (ChronicEx-Ovx). A 12-week resistance training period, during which the animals climbed a 1.1-m vertical ladder with weights secured to their tails, was used. The sessions were performed once every 3 days, with 4-9 climbs and 8-12 dynamic movements per climb. The MMP-2 activity was analyzed by zymography. There was higher MMP-2 activity in soleus muscle in the ChronicEx-Intact and ChronicEx-Ovx groups, and lower MMP-2 activity in the AcuteEx-Ovx group, compared with the Sed-Intact group (p < or =0.05). The Sed-Ovx and ChronicEx-Ovx groups presented lower MMP-2 activity than the Sed-Intact group in TA. There was higher MMP-2 activity in AcuteEx-Intact and the AcuteEx-Ovx compared with the Sed-Intact and Sed-Ovx in TA, respectively (p < or = 0.05). In TA and EDL, training increased MMP-2 activity in the Sed-Intact group. No statistically significant alterations were observed for gastrocnemius muscle. Strength training increases MMP-2 activity in soleus, TA, and EDL muscle, which may be important for muscle remodeling. Ovariectomy downregulates MMP-2 in TA and EDL, which may compromise muscle function.
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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".