Cell-to-cell contact dependence and junctional protein content are correlated with in vivo maturation of pancreatic beta cells
Bibliographic record
Abstract
In this study, we investigated the cellular distribution of junctional proteins and the dependence on cell-cell contacts of pancreatic beta cells during animal development. Fetus and newborn rat islets, which display a relatively poor insulin secretory response to glucose, present an immature morphology and cytoarchitecture when compared with young and adult islets that are responsive to glucose. At the perinatal stage, beta cells display a low junctional content of neural cell adhesion molecule (N-CAM), α- and β-catenins, ZO-1, and F-actin, while a differential distribution of N-CAM and Pan-cadherin was seen in beta cells and nonbeta cells only from young and adult islets. In the absence of intercellular contacts, the glucose-stimulated insulin secretion was completely blocked in adult beta cells, but after reaggregation they partially reestablished the secretory response to glucose. By contrast, neonatal beta cells were poorly responsive to sugar, regardless of whether they were arranged as intact islets or as isolated cells. Interestingly, after 10 days of culturing, neonatal beta cells, known to display increased junctional protein content in vitro, became responsive to glucose and concomitantly dependent on cell-cell contacts. Therefore, our data suggest that the developmental acquisition of an adult-like insulin secretory pattern is paralleled by a dependence on direct cell-cell interactions.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".