Expression and function of αβ1 integrins in pancretic beta (INS-1) cells
Bibliographic record
Abstract
Integrin-extracellular matrix interactions are important determinants of beta cell behaviours. The beta1 integrin is a well-known regulator of beta cell activities; however, little is known of its associated alpha subunits. In the present study, alphabeta1 integrin expression was examined in the rat insulinoma cell line (INS-1) to identify their role in beta cell survival and function. Seven alpha subunits associated with beta1 integrin were identified, including alpha1-6 and alphaV. Among these heterodimers, alpha3beta1 was most highly expressed. Common ligands for the alpha3beta1 integrin, including fibronectin, laminin, collagen I and collagen IV were tested to identify the most suitable matrix for INS-1 cell proliferation and function. Cells exposed to collagen I and IV demonstrated significant increases in adhesion, spreading, cell viability, proliferation, and FAK phosphorylation when compared to cells cultured on fibronectin, laminin and controls. Integrin-dependent attachment also had a beneficial effect on beta cell function, increasing Pdx-1 and insulin gene and protein expression on collagens I and IV, in parallel with increased basal insulin release and enhanced insulin secretion upon high glucose challenge. Furthermore, functional blockade of alpha3beta1 integrin decreased cell adhesion, spreading and viability on both collagens and reduced Pdx-1 and insulin expression, indicating that its interactions with collagen matrices are important for beta cell survival and function. These results demonstrate that specific alphabeta1 integrin-ECM interactions are critical regulators of INS-1 beta cell survival and function and will be important in designing optimal conditions for cell-based therapies for diabetes treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".