Long-Term Prevention of Biofilm Formation by Polycatechol-Based Supramolecular Assemblies with Low Molecular Weight Polymers on Surfaces
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Achievement of a stable surface coating with long-term resistance to biofilm formation remains a challenge. Catechol-based polymerization chemistry and surface deposition are used as tools for surface modification of diverse materials. However, the control of surface deposition of the coating, surface coverage, coating properties, and long-term protection against biofilm formation remain to be solved. We report a new approach based on supramolecular assembly to generate long-acting antibiofilm coating. Here, we utilized catechol chemistry in combination with low molecular weight amphiphilic polymers for the generation of such coatings. Screening studies with diverse low molecular weight (LMW) polymers and different catechols are utilized to identify lead compositions, which resulted in a thick coating with high surface coverage, smoothness, and antibiofilm activity. We have identified that small supramolecular assemblies (∼10 nm) formed from a combination of polydopamine and LMW poly( N -vinyl caprolactam) (PVCL) resulted in relatively thick coating (∼300 nm) with excellent surface coverage in comparison to other polymers and catechol combinations. The coating properties, such as thickness (10–300 nm) and surface hydrophilicity (with water contact angle: 20–60°), are readily controlled. The optimal coating composition showed excellent antibiofilm properties with long-term (>28 days) antibiofilm activity against both Gram-negative ( Escherichia coli ) and Gram-positive ( Staphylococcus aureus ) strains. We further utilized the combination of optimal binary coating with silver to generate a coating with sustained release of silver ions, resulting in killing both adhered and planktonic bacteria and preventing long-term surface bacterial colonization. The new coating method utilizing LMW polymers opens a new avenue for the development of a novel class of thick, long-acting antibiofilm coatings.
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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".