Proton Pump Inhibitors Control Osteoclastic Resorption of Calcium Phosphate Implants and Stimulate Increased Local Reparative Bone Growth
Bibliographic record
Abstract
Calcium phosphate (CAP) rods and pastes based on dicalcium and tetracalcium phosphate chemistry were modified with a specific osteoclast proton pump inhibitor, Bafilomycin A(1), and implanted in the distal femurs of young male Wistar rats for 7, 10, and 14 days. The extent of osteoclastic resorption of these materials and the amount of regenerative bone formed were qualitatively evaluated. Resorptive activity similar to the remodeling process of natural bone was observed in the controls. In contrast, the resorption of materials containing Bafilomycin A(1) was considerably lower, even though tartrate-resistant acid phosphatase-positive osteoclasts were present at the tissue/material interface. A greater amount of newly formed bone consistently surrounded the CAP rods and pastes containing Bafilomycin A(1) in comparison to the control specimens, which indicated that this reparative bone was not resorbed as quickly as the new bone surrounding the controls. Increased local bone mass around the Bafilomycin A(1)-modified materials resulted from the diffusion of the proton pump inhibitor into the biological tissue at the defect site. Thus, through inhibition of the osteoclast proton pump, Bafilomycin A(1) slowed down not only the resorption of the implant material but also the resorption of the newly formed reparative bone, which resulted in an increased local bone mass.
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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) | 0.001 | 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".