Sealing effect of hydroxyapatite coating on peri-implant migration of particles
Bibliographic record
Abstract
We have studied the beneficial effects of a hydroxyapatite (HA) coating on the prevention of the migration of wear debris along the implant-bone interface. We implanted a loaded HA-coated implant and a non-coated grit-blasted titanium alloy (Ti) implant in each distal femoral condyle of eight Labrador dogs. The test implant was surrounded by a gap communicating with the joint space and allowing access of joint fluid to the implant-bone interface. We injected polyethylene (PE) particles into the right knee three weeks after surgery and repeated this weekly for the following five weeks. The left knee received sham injections. The animals were killed eight weeks after surgery. Specimens from the implant-bone interface were examined under plain and polarised light. Only a few particles were found around HA-coated implants, but around Ti implants there was a large amount of particles. HA-coated implants had approximately 35% bone ingrowth, whereas Ti implants had virtually no bone ingrowth and were surrounded by a fibrous membrane. Our findings suggest that HA coating of implants is able to inhibit peri-implant migration of PE particles by creating a seal of tightly-bonded bone on the surface of the implant.
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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".