Evaluation of cylindrical micelles assembled from amphiphilic β-peptides as antigen delivery nanostructures
Bibliographic record
Abstract
Supramolecular nanostructures assembled from synthetic peptides constitute promising scaffolds for the delivery of antigens for vaccine development. Amphiphilic peptides and self-assembling cross-β-peptides have been shown to promote cellular uptake of antigenic epitopes by antigen-presenting cells, to stimulate the innate immune system and to induce a robust antigen-specific humoral immune response. In this study, we evaluated the use of cylindrical micelles assembled from the amphiphilic β-peptide C16V3A3K3 as a vaccine nanoplatform, combining the properties of cross-β-sheet fibrils and micelles. The ectodomain of the matrix 2 protein (M2e) of the influenza A virus was conjugated with a tetra-Gly linker at the C-terminus of C16V3A3K3. The chimeric peptide assembled into biocompatible unbranched filaments that exposed the antigen on the surface, and these filaments were readily internalized by dendritic cells and activated the toll-like receptor 2/6. These cylindrical micelles induced a robust M2e-specific humoral immune response upon intramuscular immunization in mice without the need for co-administration with adjuvants. Although this strong humoral response did not translate into protection against a lethal infection with the H1N1 influenza virus, these cylindrical micelles assembled from amphiphilic β-peptides expand the repertoire of self-adjuvanted nanostructures to enhance antibody production against peptide epitopes.
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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) | 0.000 | 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 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".