Noneluting Enzymatic Antibiofilm Coatings
Bibliographic record
Abstract
We developed a highly efficient, biocompatible surface coating that disperses bacterial biofilms through enzymatic cleavage of the extracellular biofilm matrix. The coating was fabricated by binding the naturally existing enzyme dispersin B (DspB) to surface-attached polymer matrices constructed via a layer-by-layer (LbL) deposition technique. LbL matrices were assembled through electrostatic interactions of poly(allylamine hydrochloride) (PAH) and poly(methacrylic acid) (PMAA), followed by chemical cross-linking with glutaraldehyde and pH-triggered removal of PMAA, producing a stable PAH hydrogel matrix used for DspB loading. The amount of DspB loaded increased linearly with the number of PAH layers in surface hydrogels. DspB was retained within these coatings in the pH range from 4 to 7.5. DspB-loaded coatings inhibited biofilm formation by two clinical strains of Staphylococcus epidermidis. Biofilm inhibition was ≥98% compared to mock-loaded coatings as determined by CFU enumeration. In addition, DspB-loaded coatings did not inhibit attachment or growth of cultured human osteoblast cells. We suggest that the use of DspB-loaded multilayer coatings presents a promising method for creating biocompatible surfaces with high antibiofilm efficiency, especially when combined with conventional antimicrobial treatment of dispersed bacteria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".