Nontoxic Black Phosphorus Quantum Dots Inhibit Insulin Amyloid Fibrillation at an Ultralow Concentration
Bibliographic record
Abstract
Amyloid are protein aggregates formed by cross β structures assemblies. Inhibiting amyloid aggregation or facilitating its disassembly are considered to be two major effective therapeutic strategies in diseases involving peptide or protein fibrillation such Alzheimer's disease or diabetes. Using thioflavin-T fluorescence, far-UV circular dichroism spectroscopy, and atomic force microscopy, we found nontoxic and biocompatible black phosphorus quantum dots (BPQDs) appear to have an exceptional capacity to inhibit insulin aggregation and to disassemble formed mature fibrils, even at an ultralow concentration (100 ng/mL). The inhibition of fibrillation persists at all stages of insulin aggregation and increases PC12 cells survival when exposed to amyloid fibrils. Molecular dynamics simulations suggest that BPQDs are able to stabilize the α-helix structure of insulin and obliterate the β-sheet structure to promote the fibril formation. These characteristics make BPQDs be promising candidate in preventing amyloidosis, disease treatment, as well as in the storage and processing of insulin.
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".