The Composition of Dietary Fat Directly Influences Glucose-Stimulated Insulin Secretion in Rats
Bibliographic record
Abstract
Acute elevations of plasma free fatty acid (FFA) levels augment glucose-stimulated insulin secretion (GSIS). Prolonged elevations of FFA levels reportedly impair GSIS, but no one has previously compared GSIS after prolonged exposure to saturated or unsaturated fat. Rats received a low-fat diet (Low-Fat) or one enriched with either saturated (Lard) or unsaturated fat (Soy) for 4 weeks. Insulin responses during hyperglycemic clamps were augmented by saturated but not unsaturated fat (580 +/- 25, 325 +/- 30, and 380 +/- 50 pmol x l(-1) x min(-1) in Lard, Soy, and Low-Fat groups, respectively). Despite hyperinsulinemia, the amount of glucose infused was lower in the Lard compared with the Low-Fat group. Separate studies measured GSIS from the perfused pancreas. Without fatty acids in the perfusate, insulin output in the Lard group (135 +/- 22 ng/30 min) matched that of Low-Fat rats (115 +/- 13 ng/30 min), but exceeded that of Soy rats (80 +/- 7 ng/30 min). When FFAs in the perfusate mimicked the quantity and composition of plasma FFAs in intact animals, in vivo insulin secretory patterns were restored. Because the GSIS of rats consuming Lard diets consistently exceeded that of the Soy group, we also assessed responses after 48-h infusions of lard or soy oil. Again, lard oil exhibited greater insulinotropic potency. These data indicate that prolonged exposure to saturated fat enhances GSIS (but this does not entirely compensate for insulin resistance), whereas unsaturated fat, given in the diet or by infusion, impairs GSIS. Inferences regarding the impact of fatty acids on GSIS that are based on models using unsaturated fat may not reflect the effects of saturated fat.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".