Innervation modulates the functional connectivity between pancreatic endocrine cells
Bibliographic record
Abstract
The importance of pancreatic endocrine cell activity modulation by autonomic innervation has been debated. To investigate this question, we established an in vivo imaging model that also allows chronic and acute neuromodulation with genetic and optogenetic tools. Using the GCaMP6s biosensor together with endocrine cell fluorescent reporters, we imaged calcium dynamics simultaneously in multiple pancreatic islet cell types in live animals in control states and upon changes in innervation. We find that by 4 days post fertilization in zebrafish, a stage when islet architecture is reminiscent of that in adult rodents, prominent activity coupling between beta cells is present in basal glucose conditions. Furthermore, we show that both chronic and acute loss of nerve activity result in diminished beta-beta and alpha-beta activity coupling. Pancreatic nerves are in contact with all islet cell types, but predominantly with beta and delta cells. Surprisingly, a subset of delta cells with detectable peri-islet neural activity coupling had significantly higher homotypic coupling with other delta cells suggesting that some delta cells receive innervation that coordinates their output. Overall, these data show that innervation plays a vital role in the maintenance of homotypic and heterotypic cellular connectivity in pancreatic islets, a process critical for islet function.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".