Self-assembly of amphiphilic helical-coiled peptide nanofibers and inhibition of fibril formation with curcumin
Bibliographic record
Abstract
Amphiphilic peptide sequences are conducive to secondary structures that self-assemble into higher-ordered peptide nanostructures. A select set of amphiphilic polycationic peptides displayed stable helical-coiled structures that self-assembled into peptide nanofibers. The progression of peptide fibril formation revealed short protofibrils that extended into thin filaments and into an entangled network of nanofibers over an extended (5 days) incubation period. Ligand binding with 8-anilinonaphthalene-1-sulfonic acid (ANS) and Congo Red (CR) confirmed the amphiphilic helical-coiled peptide structure assembly into nanofibers, whereas curcumin treatment led to inhibition of fibril formation. Considering the vast repertoire of fibrous biomaterials and peptide or protein (mis)folding contingent on fibril formation, this work relates the molecular interplay in between sequence composition, structural folding and the ligand binding events impacting peptide self-assembly into nanofibers.
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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".