Oxidative nanopatterning of titanium surfaces promotes production and extracellular accumulation of osteopontin
Bibliographic record
Abstract
The bone-biomaterial interface has been characterized by layers of afibrillar extracellular matrix (ECM) enriched in non collagenous proteins, including osteopontin (OPN), a multifunctional protein that in bone controls cell adhesion and ECM mineralization. Physical and chemical aspects of biomaterial surfaces have been demonstrated to affect cell-ECM-substrate interactions. The present paper described the ability of oxidative nanopatterning of titanium (Ti) surfaces to control extracellular OPN deposition in vitro. Ti discs were chemically treated by a mixture of H2SO4/H2O2 for either 30 min [Nano(30') Ti] or 4 h [Nano(4h) Ti]. Non-etched Ti discs were used as control. Primary osteogenic cells derived from newborn rat calvarial bone were plated on control and etched Ti and grown under osteogenic conditions up to 7 days. High resolution scanning electron microscopy revealed that treated Ti discs exhibited a nanoporous surface and that areas of larger nanopits were noticed only for Nano(4h) Ti. Large extracellular OPN accumulation were detectable only for Nano(4h) Ti, which was associated with OPN-positive cells with typical aspects of migrating cells. At day 3, quantitative results in terms of areas of OPN labeling were as follows: Nano(4h) Ti > Nano(30') Ti > Control Ti. In conclusion, chemically nanostructured Ti surfaces may support the enhancement of endogenous extracellular OPN deposition by osteogenic cells in vitro depending on the etching time, a finding that should be taken into consideration in strategies to biofunctionalize implant surfaces with molecules with cell adhesion capacity.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".