Antioxidant supplemention in the treatment of skeletal muscle insulin resistance: potential mechanisms and clinical relevance
Bibliographic record
Abstract
The incidence of type 2 diabetes has increased dramatically over the past several decades and this trend is projected to continue into the foreseeable future. Skeletal muscle insulin resistance is thought to be a key development in the pathogenesis of type 2 diabetes. Given this fact, interventions that prevent or reverse impairments in skeletal muscle action can have profound effects on whole-body glucose homeostasis. Traditional approaches used in this regard include exercise, weight loss, and insulin-sensitizing drugs such as thiazolidinediones (TZDs). Although these interventions have proven effective in improving glucose homeostasis, there are adherence issues seen with lifestyle interventions and undesirable side effects have been reported with TZDs. With these points in mind, the development of alternative strategies to maintain or improve skeletal muscle insulin sensitivity is warranted. In this context, the purpose of the present review is to highlight the role of antioxidant compounds in the prevention and treatment of skeletal muscle insulin resistance. Specifically, we will briefly describe the mechanisms of insulin-stimulated skeletal muscle glucose uptake and the potential mediators of oxidative stress induced insulin resistance, highlight data suggesting that antioxidant compounds can have beneficial effects on skeletal muscle insulin action, and discuss potential mechanisms mediating this effect.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".