Involvement of the orphan nuclear estrogen receptor-related receptor α in osteoclast adhesion and transmigration
Bibliographic record
Abstract
The orphan nuclear receptor, estrogen receptor-related receptor α (ERRα) is expressed in osteoblasts and osteoclasts (OCs) and has been proposed to be a modulator of estrogen signaling. To determine the role of ERRα in OC biology, we knocked down ERRα activity by transient transfection of an siRNA directed against ERRα in the RAW264.7 monocyte-macrophage cell line that differentiates into OCs in the presence of receptor activator of nuclear factor κB-ligands and macrophage colony-stimulating factor. In parallel, stable RAW cell lines expressing a dominant-negative form of ERRα and green fluorescent protein (RAW-GFP-ERRαΔAF2) were used. Expression of OC markers was assessed by real-time PCR, and adhesion and transmigration tests were performed. Actin cytoskeletal organization was visualized using confocal microscopy. We found that RAW264.7 cells expressing siRNA directed against ERRα and RAW-GFP-ERRαΔAF2 OCs displayed abnormal spreading, and decreased osteopontin and β3 integrin subunit expression compared with the corresponding control cells. Decreased adhesion and the absence of podosome belts concomitant with abnormal localization of c-src were also observed in RAW-GFP-ERRαΔAF2-derived OCs. In addition, RAW-GFP-ERRαΔAF2-derived OCs failed to transmigrate through osteoblast cell layers. Our data show that the impairment of ERRα function does not alter OC precursor proliferation and differentiation but does alter the adhesion/spreading and migration capacities of mature OCs.
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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) | 0.001 | 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".