SHIP1 Negatively Regulates Proliferation of Osteoclast Precursors via Akt-Dependent Alterations in D-Type Cyclins and p27
Bibliographic record
Abstract
Osteoclasts arise from macrophage progenitors in bone marrow (BMMs) as a consequence of signaling events elicited by M-CSF and receptor activator of NF-kappaB ligand, acting on their unique receptors, via c-Fms and receptor activator of NF-kappaB. Both receptors activate the PI3K and MAPK pathways, which promote cell proliferation and survival. SHIP1 is essential for normal bone homeostasis, as mice lacking the protein exhibit osteoporosis resulting from increased numbers of hyper-resorptive osteoclasts. In this study, we show that BMMs from SHIP1 null mice respond to M-CSF, but not receptor activator of NF-kappaB ligand, by increasing Akt activation. In consequence, there are up-regulation of D-type cyclins, down-regulation of the cyclin-dependent kinase inhibitor p27, and, therefore, increased phosphorylation of the retinoblastoma protein and cell proliferation. Surprisingly, cell survival of wild-type and knockout BMMs is unaltered. Finally, osteoclastogenesis and periarticular bone erosions are markedly increased in SHIP1(-/-) mice with inflammatory arthritis, a condition characterized by increased M-CSF expression. The SHIP1/Akt pathway therefore suppresses bone loss in pathological states associated with an excess of the cytokine.
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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) | 0.002 | 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".