Adaptations in pulsatile insulin secretion, hepatic insulin clearance, and β-cell mass to age-related insulin resistance in rats
Bibliographic record
Abstract
In health insulin is secreted in discrete insulin secretory bursts from pancreatic beta-cells, collectively referred to as beta-cell mass. We sought to establish the relationship between beta-cell mass, insulin secretory-burst mass, and hepatic insulin clearance over a range of age-related insulin sensitivity in adult rats. To address this, we used a novel rat model with chronically implanted portal vein catheters in which we recently established the parameters to permit deconvolution of portal vein insulin concentration profiles to measure insulin secretion and resolve its pulsatile components. In the present study, we examined total and pulsatile insulin secretion, insulin sensitivity, hepatic insulin clearance, and beta-cell mass in 35 rats aged 2-12 mo. With aging, insulin sensitivity declined, but euglycemia was sustained by an adaptive increase in fasting and glucose-stimulated insulin secretion through the mechanism of a selective augmentation of insulin pulse mass. The latter was attributable to a closely related increase in beta-cell mass (r=0.8, P<0.001). Hepatic insulin clearance increased with increasing portal vein insulin pulse amplitude, damping the delivery of insulin in the systemic circulation. In consequence, the curvilinear relationship previously reported between insulin secretion and insulin sensitivity was extended to both insulin pulse mass and beta-cell mass vs. insulin sensitivity. These data support a central role of adaptive changes in beta-cell mass to permit appropriate insulin secretion in the setting of decreasing insulin sensitivity in the aging animal. They emphasize the cooperative role of pancreatic beta-cells and the liver in regulating the secretion and delivery of insulin to the systemic circulation.
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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 | 0.000 |
| 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".