Thiol-Reactive Polymers for Titanium Interfaces: Fabrication of Antimicrobial Coatings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Infection associated with surgical implants is a major cause of their failure. Often in such cases, the implant has to be removed and replaced, which causes undesirable patient discomfort and complications. Bacterial adhesion and growth on implant surface is the primary reason for such infections. Among the approaches to prevent implant associated infections, the conjugation of antimicrobial peptide (AMP) onto the surface of the implant is a very promising approach. In this study, we describe a facile method for the surface modification of titanium (Ti), a widely used material in dental and orthopedic implants, to prevent bacterial adhesion and growth. Thin polymeric films were synthesized on the Ti surface by using a copolymer containing the maleimide group as a thiol-reactive handle to enable the conjugation of AMPs. Robust attachment of the polymeric coating on Ti surfaces was ensured through installation of catechol moieties on the polymer as surface anchoring groups and the variation of the amount of thiol-reactive maleimide group on titanium surfaces. As a proof of concept, to demonstrate a viable application of such thiol reactive surfaces, the antimicrobial peptide E6 (RRWRIVVIRVRRC) was immobilized onto these well-characterized thin polymeric layers through Michael addition. The antimicrobial activity of peptide-modified surfaces was screened against both Gram-positive and Gram-negative bacteria. The hydrophilic polymer coatings decreased the bacterial adhesion, and the immobilized peptide killed >80% of the adhered bacteria. The developed surface modification method has broad applicability in terms of the choice of substrates and peptides in the design of bioactive surfaces.
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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) | 0.001 | 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 it