Durable Surfaces from Film-Forming Silver Assemblies for Long-Term Zero Bacterial Adhesion without Toxicity
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The long-term prevention of biofilm formation on the surface of indwelling medical devices remains a challenge. Silver has been reutilized in recent years for combating biofilm formation due to its indisputable bactericidal potency; however, the toxicity, low stability, and short-term activity of the current silver coatings have limited their use. Here, we report the development of silver-based film-forming antibacterial engineered (SAFE) assemblies for the generation of durable lubricous antibiofilm surface long-term activity without silver toxicity that was applicable to diverse materials via a highly scalable dip/spray/solution-skinning process. The SAFE coating was obtained through a large-scale screening, resulting in effective incorporation of silver nanoparticles (∼10 nm) into a stable nonsticky coating with high surface hierarchy and coverage, which guaranteed sustained silver release. The lead coating showed zero bacterial adhesion over a 1 month experiment in the presence of a high load of diverse bacteria, including difficult-to-kill and stone-forming strains. The SAFE coating showed high biocompatibility and excellent antibiofilm activity in vivo .
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".