Functional Control of Peptide Amphiphile Assemblies via Modulation of Internal Cohesion and Surface Chemistry Switch
Bibliographic record
Abstract
Understanding the impacts of the internal cohesion and surface chemistry of supramolecular systems on the collective behaviors in the contacts between the systems and biomolecules can greatly expand the functional diversity and adaptivity of supramolecular nanostructures. Here we show how the tuned molecular interactions modulate the morphologies and internal cohesion of peptide amphiphile (PA) self-assemblies and their resultant functions. Circular dichroism spectroscopy, fluorescence probing, atomic force and electron microscopy, along with molecular dynamics simulations, revealed that the PA self-assembly formed compact long fibers when surface charge repulsion was screened, but formed loose short fibers or micelle-like assemblies when hydrogen bonding was disrupted or hydrophobic core was enhanced. More importantly, depending on the strength of the phospholipid affinity for the cationic segment of the PA, the same internal cohesion of PA nanostructures can lead to either cell death or cell survival, providing unique insights into the design of supramolecular materials.
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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".