Estrogen supplementation failed to attenuate biochemical indices of neutrophil infiltration or damage in rat skeletal muscles following ischemia
Bibliographic record
Abstract
This study examined the effects of estrogen supplementation on markers of neutrophil infiltration and damage in skeletal muscle of rats following ischemia. Male and female gonad-intact rats, with or without 14 days of estrogen supplementation were subjected to two hours of hind-limb ischemia and sacrificed at 24, 48 or 72 hours post-ischemia. Control animals were sacrificed without ischemia. Plantaris and red and white gastrocneimus muscles were removed and assayed for myeloperoxidase (MPO), a marker of neutrophil infiltration, and glucose-6-phosphate dehydrogenase (G6PD) and beta-glucuronidase (betaGLU), as markers of muscle damage. Significant elevations of MPO, G6PD and betaGLU activities were observed at various time points post-ischemia. No systematic differences between genders were noted in any of the measures. Estrogen supplementation in both male and female animals failed to significantly attenuate post-ischemia increases in MPO, G6PD and betaGLU activities in any of the muscles studied and in some cases accentuated activities of some of these measures. Unlike previous findings following exercise in skeletal muscle, this study failed to demonstrate estrogen-induced attenuation of indices of neutrophil infiltration or damage in skeletal muscles of rats up to 72 hours following ischemia. This demonstrates that estrogen may not consistently attenuate neutrophil infiltration and that a number of variables including damage modality, tissue or estrogen level may influence this.
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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".