Evaluation of bone stimulation by different designs of microthreaded implants in enhancing osseointegration: An in vivo animal study supported by a numerical analysis
Bibliographic record
Abstract
BACKGROUND: An optimal shape of the thread design of the implants is required for equal distribution of stresses to the surrounding bone matrix and for stimulation and promotion of bone remodeling. PURPOSE: The study was construed with the aim of histomorphometric evaluation of bone stimulation generated by different microthread designed implants in enhancing osseointegration, and to assess the pattern of stress dissipation through a two-dimensional finite element analysis. MATERIALS AND METHODS: Computer Aided Designing of two type of microthreads, one V-shaped and the other Power-shaped microthreaded dental implants with only microthreads all along body of the implant from the neck to the apex was made and 30 implant prototypes were milled. Two-dimensional finite elemental analysis (FEA) was carried out to assess the pattern of stress distribution in the bone around these implant designs and for In vivo study 24 implant prototypes were placed in rabbits tibia and femur, out of which 12 were with V-shaped microthreads and the other 12 were with Power-shaped microthreads. Histomorphometric analysis was carried out of the sections obtained from the enbloc specimen retrieved from the sacrificed rabbits. RESULTS: FEA showed less stress around the V-shaped microthreaded implant model when compared to Power-shaped microthreaded implant model. Hitomorphometry showed statistical significance difference in new bone volume (BV) and Total BV for V-shaped microthreaded prototype implant. CONCLUSIONS: V-shaped microthreaded dental implant design can be preferred over Power-shaped microthreaded dental implant for proper stress distribution and for promoting osseointegration.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".