Angio‐adaptation in unloaded skeletal muscle: new insights into an early and muscle type‐specific dynamic process
Bibliographic record
Abstract
With a remarkable plasticity, skeletal muscle adapts to an altered functional demand. Muscle angio-adaptation can either involve the growth or the regression of capillaries as respectively observed in response to endurance training or muscle unloading. Whereas the molecular mechanisms that regulate exercise-induced muscle angiogenesis have been extensively studied, understanding how muscle unloading can in contrast lead to capillary regression has received very little attention. Here we have investigated the consequences of a 9 day time course hindlimb unloading on both capillarization and expression of angio-adaptive molecules in two different rat skeletal muscles. Both soleus and plantaris muscles were atrophied similarly. In contrast, our results have shown different angio-adaptive patterns between these two muscles. Capillary regression occurred only in the soleus, a slow-twitch and oxidative postural muscle. Conversely, the level of capillarization was preserved in the plantaris, a fast-twitch and glycolytic muscle. We have also measured the time course protein expression of key pro- and anti-angiogenic signals (VEGF-A, VEGF-B, VEGF-R2, TSP-1). Our results have revealed that the angio-adaptive response to unloading was muscle-type specific, and that an integrated balance between pro- and anti-angiogenic signals plays a determinant role in regulating this process. In conclusion, we have brought new evidence that measuring the ratio between pro- and anti-angiogenic signals in order to evaluate muscle angio-adaptation was a more accurate approach than analysing the expression of molecular factors taken individually.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".