Measurement of pulsatile insulin secretion in the rat: direct sampling from the hepatic portal vein
Bibliographic record
Abstract
It has previously been shown that insulin is secreted in discrete secretory bursts by sampling directly from the portal vein in the dog and humans. Deficient pulsatile insulin secretion is the basis for impaired insulin secretion in type 2 diabetes. However, while novel genetically modified disease models of diabetes are being developed in rodents, no validated method for quantifying pulsatile insulin secretion has been established for rodents. To address this we 1) developed a novel rat model with chronically implanted portal vein catheters, 2) established the parameters to permit deconvolution of portal vein insulin concentrations profiles to measure insulin secretion and resolve its pulsatile components, and 3) measured total and pulsatile insulin secretion compared with that in the dog, the species in which this sampling and deconvolution approach was validated for quantifying pulsatile insulin secretion. In rats, portal vein catheter patency and function were maintained for periods up to 2-3 wk with no postoperative complications such as catheter tract infection. Rat portal vein insulin concentration profiles in the fasting state revealed distinct insulin oscillations with a periodicity of approximately 5 min and an amplitude of up to 600 pmol/l, which was remarkably similar to that in the dogs and in humans. Deconvolution analysis of portal vein insulin concentrations revealed that the majority of insulin ( approximately 70%) in the rat is secreted in distinct insulin pulses occurring at approximately 5-min intervals. This model therefore permits direct accurate measurements of pulsatile insulin secretion in a relatively inexpensive animal. With increased introduction of genetically modified rat models will be an important tool in elucidating the underlying mechanisms of impaired pulsatile insulin secretion in 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".