Exercising for Insulin Sensitivity – Is There a Mechanistic Relationship With Quantitative Changes in Skeletal Muscle Mass?
Bibliographic record
Abstract
Skeletal muscle (SM) tissue has been repetitively shown to play a major role in whole-body glucose homeostasis and overall metabolic health. Hence, SM hypertrophy through resistance training (RT) has been suggested to be favorable to glucose homeostasis in different populations, from young healthy to type 2 diabetic (T2D) individuals. While RT has been shown to contribute to improved metabolic health, including insulin sensitivity surrogates, in multiple studies, a universal understanding of a mechanistic explanation is currently lacking. Furthermore, exercised-improved glucose homeostasis and quantitative changes of SM mass have been hypothesized to be concurrent but not necessarily causally associated. With a straightforward focus on exercise interventions, this narrative review aims to highlight the current level of evidence of the impact of SM hypertrophy on glucose homeostasis, as well various mechanisms that are likely to explain those effects. These mechanistic insights could provide a strengthened rationale for future research assessing alternative RT strategies to the current classical modalities, such as low-load, high repetition RT or high-volume circuit-style RT, in metabolically impaired populations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".