Early Osseointegration Events on Neoss (R) ProActive and Bimodal Implants : A Comparison of Different Surfaces in an Animal Model
Bibliographic record
Abstract
Background: Cell interactions, adherence, and osseointegration at the bone-implant interface can be directly influenced by the surface properties of the titanium implant. Purpose: To characterize osseointegration of Neoss (R) implants with conventional (control group) and hydrophilic (test group) surface treatments. Materials and Methods: Six Labrador dogs received Neoss implants with conventional and hydrophilic surfaces. The bone-implant interfaces were evaluated 1 and 4 weeks after implantation, and osseointegration was evaluated using histological, histomorphometric, fluorescence, and resonance frequency analyses. The surfaces were also subjected to topographic and hydrophilicity analyses. Results: The topographic analyses revealed increased surface roughness in the test group compared with the control group (surface area roughness 0.42 and 0.78 mu m, respectively, for control and test group surfaces; p <= .05). The wettability values were higher in the test group (contact angles 67.2 degrees and 27.2 degrees for the control and test group surfaces, respectively; p <= .05). Implants in the test group also exhibited better stability, more bone-implant contact, and increased bone area compared with implants in the control group. Conclusion: Neoss implants in the test group improved bone formation in the early stages of osseointegration compared with implants in the control group.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".