Defective fatty acid uptake modulates insulin responsiveness and metabolic responses to diet in CD36-null mice
Bibliographic record
Abstract
Deficiency of the membrane protein FAT/CD36 causes a marked defect in fatty acid uptake by various tissues and is genetically linked to insulin resistance in rats and humans.Here, we examined insulin responsiveness of CD36 -/-mice.When fed a diet high in complex carbohydrates and low (5%) in fat, these animals cleared glucose faster than the wild-type.In vivo, uptake of 2-fluorodeoxyglucose by muscle was increased severalfold, and in vitro, insulin responsiveness of glycogenesis by the soleus was enhanced.Null mice had lower glycogen levels in muscle and liver, lower muscle triglyceride levels, and increased liver triglyceride content-all findings consistent with increased insulin-sensitivity.However, when the chow diet was switched to one high in fructose, CD36 -/-mice but not wild-type mice developed marked glucose intolerance, hyperinsulinemia, and decreased muscle glucose uptake.High-fat diets impaired glucose tolerance equally in both groups, although CD36 deficiency helped moderate insulin-responsive muscle glucose oxidation.In conclusion, CD36 deficiency enhances insulin responsiveness on a high-starch, low-fat diet.It predisposes to insulin resistance induced by high fructose and partially protects from that induced by high-fat diets.In humans, CD36 deficiency may be an important factor in the metabolic adaptation to diet and in susceptibility to some forms of diet-induced pathology.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".