Osteoclast‐specific inactivation of the integrin‐linked kinase (ILK) inhibits bone resorption
Bibliographic record
Abstract
Bone resorption requires the adhesion of osteoclasts to extracellular matrix (ECM) components, a process mediated by the alpha(v)beta(3) integrin. Following engagement with the ECM, integrin receptors signal via multiple downstream effectors, including the integrin-linked kinase (ILK). In order to characterize the physiological role of ILK in bone resorption, we generated mice with an osteoclast-specific Ilk gene ablation by mating mice with a floxed Ilk allele with TRAP-Cre transgenic mice. The TRAP-Cre mice specifically excised floxed alleles in osteoclasts, as revealed by crossing them with the ROSA26R reporter strain. Osteoclast-specific Ilk mutant mice appeared phenotypically normal, but histomorphometric analysis of the proximal tibia revealed an increase in bone volume and trabecular thickness. Osteoclast-specific Ilk ablation was associated with an increase in osteoclastogenesis both in vitro and in vivo. However, the mutant osteoclasts displayed a decrease in resorption activity as assessed by reduced pit formation on dentin slices in vitro and decreased serum concentrations of the C-terminal telopeptide of collagen in vivo. Interestingly, compound heterozygous mice in which one allele of Ilk and one allele of the beta(3) integrin gene were inactivated (ILK(+/-); beta(3) (+/-)) also had increased trabecular thickness, confirming that beta(3) integrin and Ilk form part of the same genetic cascade. Our results show that ILK is important for the function, but not the differentiation, of osteoclasts.
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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 | 0.001 |
| 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".