Oxidative nanopatterning of titanium generates mesoporous surfaces with antimicrobial properties
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
Mesoporous surfaces generated by oxidative nanopatterning have the capacity to selectively regulate cell behavior, but their impact on microorganisms has not yet been explored. The main objective of this study was to test the effects of such surfaces on the adherence of two common bacteria and one yeast strain that are responsible for nosocomial infections in clinical settings and biomedical applications. In addition, because surface characteristics are known to affect bacterial adhesion, we further characterized the physicochemical properties of the mesoporous surfaces. Focused ion beam (FIB) was used to generate ultrathin sections for elemental analysis by energy-dispersive X-ray spectroscopy (EDS), nanobeam electron diffraction (NBED), and high-angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) imaging. The adherence of Staphylococcus aureus, Escherichia coli and Candida albicans onto titanium disks with mesoporous and polished surfaces was compared. Disks with the two surfaces side-by-side were also used for direct visual comparison. Qualitative and quantitative results from this study indicate that bacterial adhesion is significantly hindered by the mesoporous surface. In addition, we provide evidence that it alters structural parameters of C. albicans that determine its invasiveness potential, suggesting that microorganisms can sense and respond to the mesoporous surface. Our findings demonstrate the efficiency of a simple chemical oxidative treatment in generating nanotextured surfaces with antimicrobial capacity with potential applications in the implant manufacturing industry and hospital setting.
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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) | 0.000 | 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 it