Metabolic flexibility and obesity in children and youth
Bibliographic record
Abstract
The concept of metabolic flexibility describes the ability of skeletal muscle to switch between the oxidation of lipid as a fuel during fasting periods to the oxidation of carbohydrate during insulin stimulated period. Alterations in energy metabolism in adults with obesity, insulin resistance and/or type 2 diabetes induce a state of impaired metabolic flexibility, or metabolic inflexibility. Despite the increase in the prevalence of type 2 diabetes in obese children and youth, less is known about the factors involved in the development of metabolic inflexibility in the paediatric population. Metabolic flexibility is conditioned by nutrient partitioning in response to feeding, substrate mobilization and delivery to skeletal muscle during fasting or exercising condition, and skeletal muscle oxidative capacity. Our aim in this review was to identify among these factors those making obese children at risk of metabolic inflexibility. The development of ectopic rather than peripheral fat storage appears to be a factor strongly linked with a reduced metabolic flexibility. Tissue growth and maturation are determinants of impaired energy metabolism later in life but also as a promising way to reverse metabolic inflexibility given the plasticity of many tissues in youth. Finally, we have attempted to identify perspectives for future investigations of metabolic flexibility in obese children that will improve our understanding of the genesis of metabolic diseases associated with obesity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".