β1 integrin/FAK/ERK signalling pathway is essential for human fetal islet cell differentiation and survival
Bibliographic record
Abstract
beta1 integrin and collagen matrix interactions regulate the survival of cells by associating with focal adhesion kinase (FAK) and initiating MAPK/ERK signalling, but little is known about these signalling pathways during human fetal islet ontogeny. The purpose of this study was to investigate whether beta1 integrin/FAK activation of the MAPK/ERK pathway regulates human fetal islet cell expression of endocrine cell markers and survival. Isolated human (18-21 weeks fetal age) islet-epithelial cell clusters, cultured on collagen I, were examined using beta1 integrin blocking antibody, beta1 integrin siRNA and FAK expression vector. Perturbing beta1 integrin function in the human fetal islet-epithelial cell clusters resulted in a marked decrease in cell adhesion, in parallel with a reduction in the number of cells expressing PDX-1, insulin and glucagon (p < 0.05). beta1 integrin blockade disorganized focal adhesion contacts in the PDX-1(+) cells and decreased activation of FAK and ERK1/2 signalling in parallel with an increase in expression of cleaved caspases 9 and 3 (p < 0.01). Similar results were obtained following an siRNA knock-down of beta1 integrin expression. In contrast, over-expression of FAK not only increased phospho-ERK and the expression of PDX-1, insulin and glucagon (p < 0.05) but also abrogated the decreases in phospho-ERK and PDX-1 by beta1 integrin blockade. This study demonstrates that activation of the FAK/ERK signalling cascade by beta1 integrin is involved in the differentiation and survival of human fetal pancreatic islet cells.
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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 | 0.000 |
| 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".