Effects of rmBMP-7 on Osteoblastic Cells Grown on a Nanostructured Titanium Surface
Bibliographic record
Abstract
This study evaluates the effects of the availability of exogenous BMP-7 on osteoblastic cells’ differentiation on a nanotextured Ti surface obtained by chemical etching (Nano-Ti). The MC3T3-E1 and UMR-106 osteoblastic cell lines were cultured for 5 and 7 days, respectively, on a Nano-Ti surface and on a control surface (Control-Ti) in an osteogenic medium supplemented with either 40 or 200 ng/mL recombinant mouse (rm) BMP-7. The results showed that MC3T3-E1 cells exhibited distinct responsiveness when exposed to each of the two rmBMP-7 concentrations, irrespective of the surface. Even with 40 ng/mL rmBMP-7, important osteogenic effects were noticed for Control-Ti in terms of cell proliferation potential; Runx2, Osx, Alp, Bsp, Opn, and Smad1 mRNA expression; and in situ ALP activity. For Nano-Ti, the effects were limited to higher Alp, Bsp, and Opn mRNA expression and in situ ALP activity. On both surfaces, the osteogenic potential of UMR-106 cultures remained unaltered with 40 ng/mL rmBMP-7, but it was significantly reduced when the cultures were exposed to the 200 ng/mL concentration. The availability of rmBMP-7 to pre-osteoblastic cells at the concentrations used alters the expression profile of osteoblast markers, indicative of the acquisition of a more advanced stage of osteoblastic differentiation. This occurs less pronouncedly on the nanotextured Ti and without reflecting in higher mineralized matrix production by differentiated osteoblasts on both surfaces.
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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".