VEGF‐A expression in osteoclasts is regulated by NF‐κB induction of HIF‐1α
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Large osteoclasts (10+ nuclei), predominant in rheumatoid arthritis and periodontal disease, have higher expression of proteases and activating receptors and also have increased resorptive activity when compared to small (2-5 nuclei) osteoclasts. We hypothesized that large and small osteoclasts activate different signaling pathways. A Signal Transduction Pathway Finder Array was used to compare gene expression of large and small osteoclasts in RAW 264.7-derived osteoclasts. Expression of vascular endothelial growth factor A (Vegfa) was higher in large osteoclasts and this result was confirmed by RT-PCR. RT-PCR further showed that RANKL treatment of RAW cells induced Vegfa expression in a time-dependent manner. Moreover, VEGF-A secretion in conditioned media was also increased in cultures with a higher proportion of large osteoclasts. To investigate the mechanism of Vegfa induction, specific inhibitors for the transcription factors NF-kappaB, AP-1, NFATc1, and HIF-1 were used. Dimethyl bisphenol A, the HIF-1alpha inhibitor, decreased Vegfa mRNA expression, whereas blocking NF-kappaB, AP-1, and NFATc1 had no effect. Furthermore, the NF-kappaB inhibitor gliotoxin inhibited Hif1alpha mRNA expression. In conclusion, VEGF-A gene and protein expression are elevated in large osteoclasts compared to small osteoclasts and this increase is regulated by HIF-1. In turn, Hif1alpha mRNA levels are induced by RANKL-mediated activation of NF-kappaB. These findings reveal further differences in signaling between large and small osteoclasts and thereby identify novel therapeutic targets for highly resorptive osteoclasts in inflammatory bone loss.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it