Lipid-induced β-cell dysfunction in vivo in models of progressive β-cell failure
Bibliographic record
Abstract
We determined the effect of 48-h elevation of plasma free fatty acids (FFA) on insulin secretion during hyperglycemic clamps in control female Wistar rats (group a) and in the following female rat models of progressive beta-cell dysfunction: lean Zucker diabetic fatty (ZDF) rats, both wild-type (group b) and heterozygous for the fa mutation in the leptin receptor gene (group c); obese (fa/fa) Zucker rats (nonprediabetic; group d); obese prediabetic (fa/fa) ZDF rats (group e); and obese (fa/fa) diabetic ZDF rats (group f). FFA induced insulin resistance in all groups but increased C-peptide levels (index of absolute insulin secretion) only in obese prediabetic ZDF rats. Insulin secretion corrected for insulin sensitivity using a hyperbolic or power relationship (disposition index or compensation index, respectively, both indexes of beta-cell function) was decreased by FFA. The decrease was greater in normoglycemic heterozygous lean ZDF rats than in Wistar controls. In obese "prediabetic" ZDF rats with mild hyperglycemia, the FFA-induced decrease in beta-cell function was no greater than that in obese Zucker rats. However, in overtly diabetic obese ZDF rats, FFA further impaired beta-cell function. In conclusion, 1) the FFA-induced impairment in beta-cell function is accentuated in the presence of a single copy of a mutated leptin receptor gene, independent of hyperglycemia. 2) In prediabetic ZDF rats with mild hyperglycemia, lipotoxicity is not accentuated, as the beta-cell mounts a partial compensatory response for FFA-induced insulin resistance. 3) This compensation is lost in diabetic rats with more marked hyperglycemia and loss of glucose sensing.
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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 | 0.000 | 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".