Tuning interfacial molecular asymmetry to engineer protective coatings with superior surface anchoring, antifouling and antibacterial properties
Bibliographic record
Abstract
Multifunctional robust protective coatings that combine biocompatibility, antifouling and antimicrobial properties play an essential role in reducing host reactions and infection on invasive medical devices. However, developing these protective coatings generally faces a paradox: coating materials capable of achieving robust adhesion to substrates via spontaneous deposition inevitably initiate continuous biofoulant adsorption, while those employing strong hydration capability to resist biofoulant attachment have limited substrate binding ability and durability under wear. Herein, we designed a multifunctional terpolymer of poly(dopamine methyacrylamide-co-2-methacryloyloxyethyl phoasphorylcholine-co-2-(dimethylamino)-ethyl methacrylate) (P(DMA-co-MPC-co-DMAEMA)), which integrates desired yet traditionally incompatible functions (i.e., robust adhesion, antifouling, lubrication, and antimicrobial properties). Direct normal and lateral force measurements, dynamic adsorption tests, surface ion conductance mapping were applied to comprehensively investigate the nanomechanics of coating-biofloulant interactions. Catechol groups of DMA act as basal anchors for robust substrate deposition, while the highly hydrated zwitterion of MPC provides apical protection to resist biofouling and wear. Moreover, the antimicrobial property is conferred through the protonation of tertiary amine groups on DMAEMA, inhibiting infection under physiological conditions. This work provides an effective strategy for harmonizing demanded yet incompatible properties in one coating material, with significant implications for the development of multifunctional surfaces towards the advancement of invasive biomedical devices. STATEMENT OF SIGNIFICANCE: Multifunctional robust protective coatings have been widely utilized in invasive medical devices to mitigate host responses and infection. However, modified surface coatings often encounter a trade-off between robust adhesion to substrates and strong hydration capability for antifouling and antimicrobial properties. We propose a universal strategy for surface modification by dopamine-assisted co-deposition with a multifunctional terpolymer of P(DMA-co-MPC-co-DMAEMA) that simultaneously achieves robust adhesion, antifouling, and antimicrobial properties. Through elucidating the nanomechanics with fundamentally understanding the interactions between the coating and biomacromolecules, we highlight the role of DMA for substrate adhesion, MPC for biofouling resistance, and DMAEMA for antimicrobial activity. This approach presents a promising strategy for constructing multifunctional coatings on minimally invasive medical devices by tuning interfacial molecular asymmetricity to reconcile incompatible properties within one coating.
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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 | 0.001 | 0.001 |
| 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".