Mechanistic Contributions of Biological Cofactors in Islet Amyloid Polypeptide Amyloidogenesis
Bibliographic record
Abstract
Type II diabetes mellitus is associated with the deposition of fibrillar aggregates in pancreatic islets. The major protein component of islet amyloids is the glucomodulatory hormone islet amyloid polypeptide (IAPP). Islet amyloid fibrils are virtually always associated with several biomolecules, including apolipoprotein E, metals, glycosaminoglycans, and various lipids. IAPP amyloidogenesis has been originally perceived as a self-assembly homogeneous process in which the inherent aggregation propensity of the peptide and its local concentration constitute the major driving forces to fibrillization. However, over the last two decades, numerous studies have shown a prominent role of amyloid cofactors in IAPP fibrillogenesis associated with the etiology of type II diabetes. It is increasingly evident that the biochemical microenvironment in which IAPP amyloid formation occurs and the interactions of the polypeptide with various biomolecules not only modulate the rate and extent of aggregation, but could also remodel the amyloidogenesis process as well as the structure, toxicity, and stability of the resulting fibrils.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".