Enhanced Initial Cell Responses to Chemically Modified Anodized Titanium
Bibliographic record
Abstract
BACKGROUND: Previously, we reported that anodized porous titanium implants have photocatalytic hydrophilicity. However, this effect was not always sufficient for the significant improvement of bone apposition. PURPOSE: The purpose of this study was to improve the photocatalytic properties of porous titanium implants by the fluoride modification of the anodized titanium dioxide (TiO(2)), and to investigate the initial cell response to it. MATERIALS AND METHODS: The ideal concentration of ammonium hydrogen fluoride (NH(4)F-HF(2)) used in this study was determined by a static water contact angle assay. The ideal concentration of NH(4)F-HF(2) was 0.175%, and experimental disks were treated with this concentration. A pluripotent mesenchymal cell line, C2C12, was cultured on the disks in order to investigate cell attachment, morphology, and proliferation. RESULTS: Cell attachment after 30 minutes of culturing was significantly higher for the ultraviolet-irradiated, fluoride-modified anodized TiO(2) (p < .05), and the simultaneous scanning electron microscope observation showed a rather flattened and extended cell morphology. The proliferation rate after 24 hours was also significantly higher for the fluoride-modified anodized TiO(2). CONCLUSION: Fluoride chemical modification enhances the hydrophilic property of the anodized TiO(2) and improves the initial cell response to it.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".