Globular adiponectin resistance develops independently of impaired insulin-stimulated glucose transport in soleus muscle from high-fat-fed rats
Bibliographic record
Abstract
High-fat (HF) diets induce insulin resistance and alter lipid metabolism, although controversy exists regarding the impact of saturated vs. polyunsaturated fats. Adiponectin (Ad) stimulates fatty acid (FA) oxidation and improves insulin sensitivity in humans and rodents, due in part to the activation of AMP-activated protein kinase (AMPK) and subsequent deactivation of acetyl coenzyme A carboxylase (ACC). In genetically obese, diabetic mice, this acute stimulatory effect on AMPK in muscle is lost. The ability of a HF diet to induce skeletal muscle Ad resistance has not been examined. The purpose of this study was to determine whether Ad's effects on FA oxidation and AMPK/ACC would be reduced following different HF diets, and if this coincided with the development of impaired maximal insulin-stimulated glucose transport. Rats were fed a control (10% kcal fat, CON), high unsaturated fat (60% kcal safflower oil, SAFF), or high saturated fat diet (60% kcal lard, LARD) for 4 wk. Following the dietary intervention, glucose transport, lipid metabolism, and AMPK/ACC phosphorylation were measured in the presence and absence of globular Ad (gAd, 2.5 microg/ml) in isolated soleus muscle. LARD rats showed reduced rates of maximal insulin-stimulated glucose transport compared with CON and SAFF (+68 vs. +172 and +184%, P < or = 0.001). gAd increased pACC (+25%, P < or = 0.01) and FA oxidation (+28%, P < or = 0.05) in CON rats, but not in either HF group. Thus 4 wk of HF feeding results in the loss of gAd stimulatory effect on ACC phosphorylation and muscle FA oxidation, and this can occur independently of impaired maximal insulin-stimulated glucose transport.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".