Engineering antimicrobial supramolecular polymer assemblies
Bibliographic record
Abstract
Abstract Antibacterial resistance against conventional antibiotics has emerged as a global health problem. To address this problem, antimicrobial peptides (AMPs) have been recognized as alternatives due to their fast‐killing activity and less propensity to induce resistance. Here, the AMPs are engineered via a supramolecular fashion to control and increase their biological performance. The AMPs are modified with ureido‐pyrimidinone (UPy) to obtain UPy‐AMP monomers, followed by modular self‐assembling to realize antibacterial UPy‐AMP supramolecular polymers. These positively charged assemblies are illustrated as stable, short fibrous or rod‐like UPy‐AMP nanostructures with enhanced antibacterial activity and modulable cytotoxicity. Moreover, these antibacterial UPy‐AMP assemblies can be internalized by both THP‐1 derived macrophages and human kidney cells, which would be an effective potential therapy to deliver the AMPs into mammalian cells to address intracellular infections. Overall, the results present here demonstrate that supramolecular engineering of AMPs provides a powerful tool to enhance the antibacterial activity, modulate cytotoxicity and accelerate the clinical application of AMPs.
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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".