A novel role for interferon regulatory factor 1 (<i><scp>IRF</scp>1</i>) in regulation of bone metabolism
Bibliographic record
Abstract
Increased risk of bone fractures is observed in patients with chronic inflammatory conditions, such as inflammatory bowel disease and rheumatoid arthritis. Members of the Interferon Response Factor family of transcriptional regulators, IRF1 and IRF8, have been identified as genetic risk factors for several chronic inflammatory and autoimmune diseases. We have investigated a potential role for the Irf1 gene in bone metabolism. Here, we report that Irf1(-/-) mutant mice show altered bone morphology in association with altered trabecular bone architecture and increased cortical thickness and cellularity. Ex vivo studies on cells derived from bone marrow stimulated with Rank ligand revealed an increase in size and resorptive activity of tartrate-resistant acid-positive cells from Irf1(-/-) mutant mice compared with wild-type control mice. Irf1 deficiency was also associated with decreased proliferation of bone marrow-derived osteoblast precursors ex vivo, concomitant with increased mineralization activity compared with control cells. We show that Irf1 plays a role in bone metabolism and suggest that Irf1 regulates the maturation and activity of osteoclasts and osteoblasts. The altered bone phenotype of Irf1(-/-) mutants is strikingly similar to that of Stat1(-/-) mice, suggesting that the two interacting proteins play a critical enabling role in the common regulation of these two cell lineages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".