Effects of Isoform-selective Phosphatidylinositol 3-Kinase Inhibitors on Osteoclasts
Bibliographic record
Abstract
Phosphatidylinositol 3-kinases (PI3K) participate in numerous signaling pathways, and control distinct biological functions. Studies using pan-PI3K inhibitors suggest roles for PI3K in osteoclasts, but little is known about specific PI3K isoforms in these cells. Our objective was to determine effects of isoform-selective PI3K inhibitors on osteoclasts. The following inhibitors were investigated (targets in parentheses): wortmannin and LY294002 (pan-p110), PIK75 (α), GDC0941 (α, δ), TGX221 (β), AS252424 (γ), and IC87114 (δ). In addition, we characterized a new potent and selective PI3Kδ inhibitor, GS-9820, and explored roles of PI3K isoforms in regulating osteoclast function. Osteoclasts were isolated from long bones of neonatal rats and rabbits. Wortmannin, LY294002, GDC0941, IC87114, and GS-9820 induced a dramatic retraction of osteoclasts within 15-20 min to 65-75% of the initial area. In contrast, there was no significant retraction in response to vehicle, PIK75, TGX221, or AS252424. Moreover, wortmannin and GS-9820, but not PIK75 or TGX221, disrupted actin belts. We examined effects of PI3K inhibitors on osteoclast survival. Whereas PIK75, TGX221, and GS-9820 had no significant effect on basal survival, all blocked RANKL-stimulated survival. When studied on resorbable substrates, osteoclastic resorption was suppressed by wortmannin and inhibitors of PI3Kβ and PI3Kδ, but not other isoforms. These data are consistent with a critical role for PI3Kδ in regulating osteoclast cytoskeleton and resorptive activity. In contrast, multiple PI3K isoforms contribute to the control of osteoclast survival. Thus, the PI3Kδ isoform, which is predominantly expressed in cells of hematopoietic origin, is an attractive target for anti-resorptive therapeutics.
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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 | 0.001 |
| 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".