A Novel Strategy to Coat Dopamine-Functionalized Titanium Surfaces With Agarose-Based Hydrogels for the Controlled Release of Gentamicin
Bibliographic record
Abstract
Introduction The use of spinal implants for the treatment of back disorders is largely affected by the insurgence of infections at the implantation site. Antibacterial coatings have been proposed as a viable solution to limit such infections. However, despite being effective at short-term, conventional coatings lack the ability to prevent infections at medium and long-term. Hydrogel-based drug delivery systems may represent a solution controlling the release of the loaded antibacterial agents while improving cell integration. Agarose, in particular, is a biocompatible natural polysaccharide known to improve cell growth and already used in drug delivery system formulations. In this study, an agarose hydrogel-based coating has been developed for the controlled release of gentamicin (GS). Methods Sand blasted Ti6Al4V discs were grafted with dopamine (DOPA) solution. After, GS loaded agarose hydrogels have been produced and additioned with tannic acid (TA) and calcium chloride (CaCl 2 ) as crosslinkers. The different GS-loaded hydrogel formulations were deposited on Ti6Al4V-DOPA surfaces, and allowed to react under UV irradiation. Surface topography, wettability and composition have been analyzed with profilometry, static contact angle measurement, XPS and FTIR spectroscopy analyses. GS release was performed under pseudo-physiological conditions up to 28 days and the released GS was quantified using a specific ELISA test. The cytotoxicity of the produced coatings against human cells have been tested, along with their antibacterial activity against S. aureus bacteria. Results A homogeneous coating was obtained with all the hydrogel formulations. Moreover, the coatings presented a hydrophilic behavior and micro-scale surface roughness. The addition of TA in the hydrogel formulations showed an increase in the release time compared to the normal GS-agarose hydrogels. Moreover, the GS released from these gels was able to significantly inhibit S. aureus growth compared to the GS-agarose hydrogels. The addition of CaCl 2 to the gel formulation was able to significantly decrease cytotoxicity of the TA-modified hydrogels. Conclusions Due to their surface properties, low cytotoxicity and high antibacterial effects, the hereby proposed gentamicin-loaded agarose-hydrogels provide new insight, and represent a promising approach for the surface modification of spinal implants, greatly impacting their application in the orthopedic surgical scenario.
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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 | 0.000 | 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".