Submicron Scale‐Structured Hydrophilic Titanium Surfaces Promote Early Osteogenic Gene Response for Cell Adhesion and Cell Differentiation
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Titanium (Ti) surface roughness and surface hydrophilicity are key factors to regulate osteogenic cell responses during dental implant healing. In detail, specific integrin-mediated interactions with the extracellular environment trigger relevant osteogenic cell responses like differentiation and matrix synthesis via transcriptions factors. Aim of this study was to monitor surface-dependent osteogenic cell adhesion dynamics, proliferation, and specific osteogenic cell differentiation over a period of 7 days. MATERIALS AND METHODS: Ti disks were manufactured to present smooth pretreatment (PT) surfaces and rough sandblasted/acid-etched (SLA) surfaces. Further processing to isolate the uncontaminated TiO(2) surface from contact with atmosphere provided a highly hydrophilic surface without alteration of the surface topography (modSLA). Tissue culture polystyrene (TCPS) served as control. Human osteogenic cells were cultivated on the respective substrates. After 24 hours, 48 hours, 72 hours, and 7 days, cell morphology on the Ti substrates was visualized by scanning transmission electron microscopy. As a marker of cellular proliferation, cell count was assessed. For the analysis of cell adhesion and differentiation, specific gene expression levels of the integrin subunits β1 and αv, runx-2, collagen type Iα (COL), alkaline phosphatase (AP), and osteocalcin (OC) were obtained by real-time RT-PCR for the respective time points. Data were normalized to internal controls. RESULTS: TCPS and PT surfaces preserved a rather immature, dividing osteogenic phenotype (high proliferation rates, low integrin levels, and low specific osteogenic cell differentiation). SLA and especially modSLA surfaces promoted both cell adhesion as well as the maturation of osteogenic precursors into post-mitotic osteoblasts. In detail, during the first 48 hours, modSLA resulted in lowest cell proliferation rates but exhibited highest levels of the investigated integrins, runx-2, COL, AP, and OC. CONCLUSION: Our results revealed a strong synergistic effect between submicron-scale roughness and surface hydrophilicity on early osteogenic cell adhesion and maturation.
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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) | 0.002 | 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".