Distinct skeletal muscle fiber characteristics and gene expression in diet-sensitive versus diet-resistant obesity
Bibliographic record
Abstract
Inter-individual variability in weight gain and loss under energy surfeit and deficit conditions, respectively, are well recognized but poorly understood phenomena. We documented weight loss variability in an intensively supervised clinical weight loss program and assessed skeletal muscle gene expression and phenotypic characteristics related to variable response to a 900 kcal regimen. Matched pairs of healthy, diet-compliant, obese diet-sensitive (ODS) and diet-resistant (ODR) subjects were defined as those in the highest and lowest quintiles for weight loss rate. Physical activity energy expenditure was minimal and comparable. Following program completion and weight stabilization, skeletal muscle biopsies were obtained. Gene expression analysis of rectus femoris and vastus lateralis indicated upregulation of genes and gene sets involved in oxidative phosphorylation and glucose and fatty acid metabolism in ODS compared with ODR. In vastus lateralis, there was a higher proportion of oxidative (type I) fibers in ODS compared with ODR women and lean controls, fiber hypertrophy in ODS compared with ODR women and lean controls, and lower succinate dehydrogenase in oxidative and oxidative-glycolytic fibers in all obese compared with lean subjects. Intramuscular lipid content was generally higher in obese versus lean, and specifically higher in ODS vs. lean women. Altogether, our findings demonstrate differences in muscle gene expression and fiber composition related to clinical weight loss success.
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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 | 0.001 | 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 | 0.000 |
| 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".