Human Mesenchymal Cell Attachment, Growth and Biomineralization on Calcium-enriched Titania-polyester Coatings
Bibliographic record
Abstract
Titanium implant osseointegration can be enhanced by surface modifications that include hydroxyapatite from Ca3(PO4)2. However, CaO may provide more surface calcium (w/w) to induce cellular responses. Therefore, the purpose of this study was to compare responses to novel CaO and Ca3(PO4)2-enriched titania-polyester (PPC) nanocomposite coatings, which were created by an electrostatic ultrafine dry powder coating technique. EDX confirmed the presence of a base polymer scaffold, biocompatible titanium, and CaO or Ca3(PO4)2. SEM showed that human embryonic palatal mesenchymal cells (ATCC CRL-1486) had attached and spread out onto all surfaces within 24 hours. Cell attachment assays showed that there was a progressive increase in cell numbers with surface CaO incorporation (0–5%), such that the PPC + 5% CaO coatings supported the most cells. Furthermore, the PPC + 5% CaO had significantly more (P = 0.006) cells attached to their surfaces than the PPC + 5% CaP coatings and titanium controls, at 24 hours. The PPC + 5% CaO also had more cells that had proliferated on their surfaces over 72 hours, although these differences were not significant (P > 0.05). Similarly, MTT assays showed that the cells had sustained metabolic activity on all surfaces. Again, metabolic activities were highest on the PPC + 5% CaO, and they were significantly higher (P < 0.05) on all CaO-enriched surfaces (1/3/5% CaO) than on the PPC + 5% CaP. Subsequently, Alizarin Red-S staining detected the initiation of biomineralization within 2 weeks, and abundant mineral deposits after 4 weeks of growth on PPC + 5% CaO and PPC + 3% CaO. These nanocomposite coatings have shown that CaO enrichments may provide a heightened cell response when compared to conventional hydroxyapatite.
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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".