Pancreatic beta-cell granule peptides form heteromolecular complexes which inhibit islet amyloid polypeptide fibril formation
Bibliographic record
Abstract
Islet amyloid polypeptide (IAPP), or 'amylin', is co-stored with insulin in secretory granules of pancreatic islet beta-cells. In Type 2 diabetes, IAPP converts into a beta-sheet conformation and oligomerizes to form amyloid fibrils and islet deposits. Granule components, including insulin, inhibit spontaneous IAPP fibril formation in vitro. To determine the mechanism of this inhibition, molecular interactions of insulin with human IAPP (hIAPP), rat IAPP (rIAPP) and other peptides were examined using surface plasmon resonance (BIAcore), CD and transmission electron microscopy (EM). hIAPP and rIAPP complexed with insulin, and this reaction was concentration-dependent. rIAPP and insulin, but not pro-insulin, bound to hIAPP. Insulin with a truncated B-chain, to prevent dimerization, also bound hIAPP. In the presence of insulin, hIAPP did not spontaneously develop beta-sheet secondary structure or form fibrils. Insulin interacted with pre-formed IAPP fibrils in a regular repeating pattern, as demonstrated by immunoEM, suggesting that the binding sites for insulin remain exposed in hIAPP fibrils. Since rIAPP and hIAPP form complexes with insulin (and each other), this could explain the lack of amyloid fibrils in transgenic mice expressing hIAPP. It is likely that IAPP fibrillogenesis is inhibited in secretory granules (where the hIAPP concentration is in the millimolar range) by heteromolecular complex formation with insulin. Alterations in the proportions of insulin and IAPP in granules could disrupt the stability of the peptide. The increase in the proportion of unprocessed pro-insulin produced in Type 2 diabetes could be a major factor in destabilization of hIAPP and induction of fibril formation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".