Maintenance of contractile properties despite impaired skeletal muscle oxidative metabolism in diet‐induced obesity.
Bibliographic record
Abstract
Diet‐induced obesity (DIO) is increasing in prevalence among youth; a time where robust muscle growth occurs. We hypothesized that consumption of a high fat diet (HFD) in early adulthood would negatively impact mouse muscle metabolism and contractile function. HFD (~60% kcal fat for 8 weeks) induced an obese and insulin resistant phenotype with reduced relative muscle mass (72 ± 1.9%) compared to control. Using isolated single muscle fibers for analysis, HFD induced a significant impairment in palmitate and glucose oxidation (72.8 ± 6.6% and 61.8 ± 9.1% of control respectively). This novel technique was validated in intact muscle. Impaired insulin responses were noted for glucose metabolism and glycogen synthesis in HFD muscle vs. control, while glucose and palmitate uptake was not altered between groups. Preliminary RT‐PCR results demonstrate no difference in CPT‐1, PGC‐1α, PPARα or UCP‐2 expression. Further gene and protein analysis into the mechanisms underlying changes in fat uptake and oxidation are currently underway. Despite metabolic impairments, HFD muscle exhibited no loss of maximal contractile force or alteration in fatigue rates. Our data suggest that HFD skeletal muscle is highly adaptive in the face of impaired substrate oxidation, as demonstrated by the preservation of contractile properties. These findings contribute to our understanding of the impact of DIO on developing skeletal muscle.
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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) | 0.000 | 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 | 0.001 |
| 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".