Leucine Repeat Rich Kinase 1 Controls Osteoclast Activity by Managing Lysosomal Trafficking and Secretion
Bibliographic record
Abstract
We previously demonstrated that mice with targeted deletion of the leucine repeat rich kinase 1 (Lrrk1) gene were osteopetrotic due to the failure of osteoclasts to resorb bone. To determine how LRRK1 regulates osteoclast activity, we examined the intracellular and extracellular acidification with an acidotropic probe, acridine orange, in live osteoclasts on bone slices. We examined lysosome distribution in osteoclasts by localization of LAMP-2, cathepsin K, and v-ATPase by immunofluorescent staining with specific antibodies. We found that both vertical and horizontal cross-sectional images of the wild-type (WT) osteoclasts showed orange-staining of the intracellular acidic vacuoles/lysosomes dispersed to the ruffled border. By contrast, the LRRK1 deficient osteoclasts exhibited fluorescent orange staining in the cytoplasm away from the extracellular lacunae because of an altered distribution of the acidic vacuoles/lysosomes. In addition, WT osteoclasts displayed a peripheral distribution of LAMP-2 positive lysosomes with a typical actin ring. The clustered F-actin constitutes a peripheral sealing zone and a ruffled border which was stretched out into a resorption pit. The LAMP-2 positive lysosomes were also distributed to the sealing zone, and the cell was associated with a resorption pit. By contrast, LRRK1-deficient osteoclasts showed diffused F-actin throughout the cytoplasm. The sealing zone was weak and not associated with a resorption pit. LAMP-2 positive lysosomes were also diffuse in the cytoplasm and were not distributed to the ruffled border. Although the LRRK1-deficient osteoclast expressed normal levels of cathepsin K and v-ATPase, the lysosomal-associated cathepsin K and v-ATPase were not accumulated at the ruffled border in Lrrk1 KO osteoclasts. Our data indicate that LRRK1 controls osteoclast activity by regulating lysosomal distribution, acid secretion, and protease exocytosis.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".