Mast cells enhance sterile inflammation in chronic nonbacterial osteomyelitis
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
ABSTRACT Chronic nonbacterial osteomyelitis (CNO) is an autoinflammatory bone disease, and patients with active or recurrent bone inflammation at multiple sites are diagnosed with chronic recurrent multifocal osteomyelitis (CRMO). The Chronic multifocal osteomyelitis (CMO) mouse model develops IL-1β-driven sterile bone lesions reminiscent of severe CRMO. The goal of this study was to evaluate the potential involvement of mast cells in CMO/CRMO. Here, we show that mast cells accumulate in inflamed tissues from CMO mice and that mast cell protease Mcpt1 can be detected in the peripheral blood. A transgenic model of connective tissue mast cell depletion (Mcpt5-Cre:Rosa26-Stopfl/fl-DTa) was crossed with CMO mice and the resulting mice (referred to as CMO/MC–) showed a significant delay in disease onset compared with age-matched CMO mice. At 5-6 months of age, CMO/MC– mice had fewer bone lesions and immune infiltration in the popliteal lymph nodes that drain the affected tissues. In bone marrow-derived mast cell cultures from CMO mice, cytokine production in response to the alarmin IL-33 was elevated compared with wild-type cultures. To test the relevance of mast cells to human CRMO, we tested serum samples from a cohort of healthy controls and from CRMO patients at diagnosis. Interestingly, mast cell chymase was elevated in CRMO patients as well as in patients with oligoarticular juvenile arthritis. Tryptase-positive mast cells were also detected in bone lesions from CRMO patients and patients with bacterial osteomyelitis. Together, our results identify mast cells as cellular contributors to bone inflammation in CMO/CRMO and provide rationale for further study of mast cells as therapeutic targets.
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.
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) | 0.002 | 0.001 |
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