Human alveolar bone cell proliferation, expression of osteoblastic phenotype, and matrix mineralization on porous titanium produced by powder metallurgy
Bibliographic record
Abstract
OBJECTIVE: This study aimed at investigating the influence of the porous titanium (Ti) structure on the osteogenic cell behaviour. MATERIALS AND METHODS: Porous Ti discs were fabricated by the powder metallurgy process with the pore size typically between 50 and 400 microm and a porosity of 60%. Osteogenic cells obtained from human alveolar bone were cultured until subconfluence and subcultured on dense Ti (control) and porous Ti for periods of up to 17 days. RESULTS: Cultures grown on porous Ti exhibited increased cell proliferation and total protein content, and lower levels of alkaline phosphatase (ALP) activity than on dense Ti. In general, gene expression of osteoblastic markers-runt-related transcription factor 2, collagen type I, alkaline phosphatase, bone morphogenetic protein-7, and osteocalcin was lower at day 7 and higher at day 17 in cultures grown on porous Ti compared with dense Ti, a finding consistent with the enhanced growth rate for such cultures. The amount of mineralized matrix was greater on porous Ti compared with the dense one. CONCLUSION: These results indicate that the porous Ti is an appropriate substrate for osteogenic cell adhesion, proliferation, and production of a mineralized matrix. Because of the three-dimensional environment it provides, porous Ti should be considered an advantageous substrate for promoting desirable implant surface-bone interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".