Faster Amylin Aggregation on Fibrillar Collagen I Hastens Diabetic Progression through β-Cell Death and Loss of Function
Bibliographic record
Abstract
Amyloid deposition of the neuroendocrine peptide amylin in islet tissues is a hallmark of type 2 diabetes (T2DM), leading to β-cell toxicity through nutrient deprivation, membrane rupture, and apoptosis. Though accumulation of toxic amylin aggregates in islet matrices is well documented, the role of the islet extracellular matrix in mediating amylin aggregation and its pathological consequences remains elusive. Here, we address this question by probing amylin interaction with collagen I (Col)─whose expression in the islet tissue increases during diabetes progression. By combining multiple biophysical techniques, we show that hydrophobic, hydrophilic, and cation-π interactions regulate amylin binding to Col, with fibrillar Col driving faster amylin aggregation. Amylin-entangled Col matrices containing high amounts of amylin induce death and loss of function in INS1E β-cells. Together, our results illustrate how amylin incorporation in islet matrices through amylin-Col interactions drives T2DM progression by impacting β-cell viability and insulin secretion.
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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".