Transcriptional Modulator Ifrd1 Regulates Osteoclast Differentiation through Enhancing the NF-κB/NFATc1 Pathway
Bibliographic record
Abstract
Bone homeostasis is maintained by the synergistic actions of bone-resorbing osteoclasts and bone-forming osteoblasts. Here, we show that the transcriptional coactivator/repressor interferon-related developmental regulator 1 (Ifrd1) is expressed in osteoclast lineages and represents a component of the machinery that regulates bone homeostasis. Ifrd1 expression was transcriptionally regulated in preosteoclasts by receptor activator of nuclear factor κB (NF-κB) ligand (RANKL) through activator protein 1. Global deletion of murine Ifrd1 increased bone formation and decreased bone resorption, leading to a higher bone mass. Deletion of Ifrd1 in osteoclast precursors prevented RANKL-induced bone loss, although no bone loss was observed under normal physiological conditions. RANKL-dependent osteoclastogenesis was impaired in vitro in Ifrd1-deleted bone marrow macrophages (BMMs). Ifrd1 deficiency increased the acetylation of p65 at residues K122 and K123 via the inhibition of histone deacetylase-dependent deacetylation in BMMs. This repressed the NF-κB-dependent transcription of nuclear factor of activated T cells, cytoplasmic 1 (NFATc1), an essential regulator of osteoclastogenesis. These findings suggest that an Ifrd1/NF-κB/NFATc1 axis plays a pivotal role in bone remodeling in vivo and represents a therapeutic target for bone diseases.
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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".