Mechanisms of Impaired Fasting Glucose and Glucose Intolerance Induced by a ∼50% Pancreatectomy
Bibliographic record
Abstract
Impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) often coexist and as such represent a potent risk factor for subsequent development of type 2 diabetes. beta-Cell mass is approximately 50% deficient in IFG and approximately 65% deficient in type 2 diabetes. To establish the effect of a approximately 50% deficit in beta-cell mass on carbohydrate metabolism, we performed a approximately 50% partial pancreatectomy versus sham surgery in 14 dogs. Insulin secretion was quantified from insulin concentrations measured in the portal vein at 1-min sampling intervals under basal conditions, after a 30-g oral glucose, and during a hyperglycemic clamp. Insulin sensitivity was measured by a hyperinsulinemic-euglycemic clamp combined with isotope dilution. Partial pancreatectomy resulted in IFG and IGT. After partial pancreatectomy both basal and glucose-stimulated insulin secretion were decreased through the mechanism of a selective approximately 50 and approximately 80% deficit in insulin pulse mass, respectively (P < 0.05). These defects in insulin secretion were partially offset by decreased hepatic insulin clearance (P < 0.05). Partial pancreatectomy also caused a approximately 40% decrease in insulin-stimulated glucose disposal (P < 0.05), insulin sensitivity after partial pancreatectomy being related to insulin pulse amplitude (r = 0.9, P < 0.01). We conclude that a approximately 50% deficit in beta-cell mass can recapitulate the alterations in glucose-mediated insulin secretion and insulin action in humans with IFG and IGT. These data support a mechanistic role of a deficit in beta-cell mass in the evolution of IFG/IGT and subsequently type 2 diabetes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".