Unimer Exchange as a Tool for Programming Enzymatic Degradation through Micellar Dynamics
Bibliographic record
Abstract
A key challenge in designing enzyme-responsive micellar nanocarriers lies in balancing their stability and enzymatic degradation. While it has been widely assumed that the micelle-unimer exchange governs enzyme accessibility to the hydrophobic blocks, this relationship had not been directly demonstrated. Here, to uncover this long-assumed mechanistic link, we synthesized a set of triblock amphiphiles that convert by an in situ transition to diblock amphiphiles via reductive cleavage of a central disulfide bond. In parallel, hydrophobicity was independently tuned by modifying the aliphatic end-groups. Enzymatic degradation studies and Förster resonance energy transfer (FRET)-based exchange assays showed two consistent trends across all systems: increasing hydrophobicity led to slower micelle-unimer exchange and reduced enzymatic degradation rates, while transition to diblock consistently enhanced both. These results provide direct evidence that exchange kinetics govern enzymatic degradation and lay the mechanistic foundation for overcoming the stability-degradability barrier for enzyme-responsive micelles by applying architectural transitions as a molecular programming tool.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".