The mass, but not the frequency, of insulin secretory bursts in isolated human islets is entrained by oscillatory glucose exposure
Bibliographic record
Abstract
Insulin is secreted in discrete insulin secretory bursts. Regulation of insulin release is accomplished almost exclusively by modulation of insulin pulse mass, whereas the insulin pulse interval remains stable at approximately 4 min. It has been reported that in vivo insulin pulses can be entrained to a pulse interval of approximately 10 min by infused glucose oscillations. If oscillations in glucose concentration play an important role in the regulation of pulsatile insulin secretion, abnormal or absent glucose oscillations, which have been described in type 2 diabetes, might contribute to the defective insulin secretion. Using perifused human islets exposed to oscillatory vs. constant glucose, we questioned 1) whether the interval of insulin pulses released by human islets is entrained to infused glucose oscillations and 2) whether the exposure of islets to oscillating vs. constant glucose confers an increased signal for insulin secretion. We report that oscillatory glucose exposure does not entrain insulin pulse frequency, but it amplifies the mass of insulin secretory bursts that coincide with glucose oscillations (P < 0.001). Dose-response analyses showed that the mode of glucose drive does not influence total insulin secretion (P = not significant). The apparent entrainment of pulsatile insulin to infused glucose oscillations in nondiabetic humans in vivo might reflect the amplification of underlying insulin secretory bursts that are detected as entrained pulses at the peripheral sampling site, but without changes in the underlying pacemaker activity.
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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 | 0.001 |
| 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) | 0.001 | 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".