Exercise restores insulin, but not adiponectin, response in skeletal muscle of high-fat fed rodents
Bibliographic record
Abstract
High-fat (HF) diets impair skeletal muscle response to the insulin-sensitizing adipokine adiponectin (Ad) in rodents, preceding the development of insulin resistance. Skeletal muscle insulin response in HF-fed rats can be restored with chronic exercise; whether recovery of skeletal muscle Ad response is necessary for the exercise-induced recovery of insulin-stimulated glucose transport is not known. In the current study, insulin and Ad resistance were induced in rodents with 4 wk of HF feeding (HF(4); low-fat fed animals used as control). Rats were then treadmill-exercised (HF(5)EX(1), HF(6)EX(2)) or supplemented orally with the pharmacological agent β-guadinoproprionic acid (GPA; HF(5)GPA(1), HF(6)GPA(2)) for 1 or 2 wk with continued HF feeding. Insulin and Ad responses (glucose transport and palmitate oxidation, respectively) were assessed 48 h after the last exercise bout ex vivo in isolated solei. Insulin response was impaired following 4 wk of HF feeding and improved with 1 and 2 wk of exercise and β-GPA supplementation (HF(5)EX(1), HF(6)EX(2), HF(5)GPA(1), and HF(6)GPA(2)). The recovery of insulin response generally coincided with improved Akt Thr(308) phosphorylation in HF(5)GPA(1), HF(6)EX(2), and HF(6)GPA(2), although not in HF(5)EX(1). Ad-stimulated palmitate oxidation was not restored with either treatment. Total protein contents of AdipoR1, AdipoR2, APPL1, and APPL2, as well as total and phosphorylated AMPK and ACC were unaltered by diet, exercise, and β-GPA at the assessed time points. We conclude that the exercise and pharmacologically (β-GPA)-induced recovery of skeletal muscle insulin response after HF feeding is not dependent on the restoration of Ad response, as assessed ex vivo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| 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".