Is Human Double Minute‐2 a new marker of angiogenesis in exercised human skeletal muscle?
Bibliographic record
Abstract
Protein expression of the E3 ubiquitin ligase Murine Double Minute‐2 (Mdm2) is increased in response to exercise training in mouse skeletal muscle. By regulating endothelial cell proliferation and migration in the muscle tissue, Mdm2 is indispensable for exercise‐induced angiogenesis to occur (Roudier et al., FASEB J 2012). Objective Here, we investigated in human skeletal muscle if exercise training exerts a similar effect on Human Double Minute‐2 (Hdm2), the human homologue of Mdm2 protein, and if a link is present between Hdm2 and the endothelial marker Platelet Endothelial Cell Adhesion Molecule‐1 (PECAM‐1). Method Protein levels for Hdm2 and PECAM‐1 were measured by western blot in vastus lateralis muscle biopsies from 16 young and 14 senior subjects enrolled in a 6‐week training program. Results Exercise training significantly increased Hdm2 and PECAM‐1 protein expression. In the young population, a significant correlation was observed between exercise‐induced increases in Hdm2 and PECAM‐1 proteins. Conclusion Results from our previous study in rodents translate here to human subjects and suggest that Hdm2 might represent a key regulator of exercise‐induced angiogenesis in human skeletal muscle. This work was supported by the Natural Sciences and Engineering Research Council of Canada (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".