Laminin matrix regulates beta-cell FGFR5 expression to enhance glucose-stimulated metabolism
Bibliographic record
Abstract
Abstract We previously showed that pancreatic beta-cells plated on laminin matrix express reduced levels of FGFR1, a receptor linked to beta-cell metabolism and differentiation. Due to recent evidence that adult beta-cells also express FGFR5, a co-receptor for FGFR1, we now aim to determine the effect of laminin on FGFR5 expression and consequent effects on beta-cell metabolism. Using a genetically encoded sensor for NADPH/NADP+ redox state (Apollo-NADP+), we show overexpression of FGFR5 enhances glucose-stimulated NADPH metabolism in beta-cell lines as well as mouse and human beta-cells. This enhanced response was accompanied by increased insulin secretion as well as increased expression of transcripts for glycolytic enzymes (Glucokinase/GCK, PKM2) and the functional maturity marker Urocortin 3 (UCN3). Culturing beta-cells on laminin matrix also stimulated upregulation of endogenous FGFR5 expression, and similarly enhanced beta-cell glucose-stimulated NADPH-metabolism as well as GCK and PKM2 transcript expression. The metabolism and transcript responses triggered by laminin were disrupted by R5ΔC, a truncated receptor isoform that inhibits the FGFR5/FGFR1 signaling complex. Collectively these data reveal that beta-cells respond to laminin by increasing FGFR5 expression to enhance beta-cell glucose metabolism.
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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) | 0.002 | 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".