Mast Cells Enhance Sterile Inflammation in Chronic Nonbacterial Osteomyelitis
Bibliographic record
Abstract
ABSTRACT Chronic nonbacterial osteomyelitis (CNO) is an autoinflammatory bone disease. While some patients exhibit bone lesions at single sites, most patients develop chronically active or recurrent bone inflammation at multiple sites, and are then diagnosed with recurrent multifocal osteomyelitis (CRMO). Chronic multifocal osteomyelitis (CMO) mice develop IL-1β-driven sterile bone lesions reminscent of severe CRMO. Mechanistically, CMO disease arises due to loss of PSTPIP2, a negative regulator of macrophages, osteoclasts and neutrophils. The goal of this study was to evaluate the potential involvement of mast cells in CMO/CRMO disease pathophysiology. Here, we show that mast cells accumulate in the inflamed tissues from CMO mice, and mast cell protease Mcpt1 was detected in the peripheral blood. The role of mast cells in CMO disease was investigated using a transgenic model of connective tissue mast cell depletion (Mcpt5-Cre:Rosa26-Stop fl/fl -DTa) that was crossed with CMO mice. The resulting CMO/MC-mice showed a significant delay in disease onset compared to 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 tail and paw tissues. To test the relevance of mast cells to human CRMO, we tested serum samples from a cohort of healthy controls or CRMO patients at diagnosis. Interestingly, mast cell chymase was elevated in CRMO patients as well as patients with oligoclonal juvenile arthritis. Tryptase-positive mast cells were also detected in bone lesions from CRMO patients as well as patients with bacterial osteomyelitis. Taken together, our results identify mast cells as cellular contributors to bone inflammation in CMO/CRMO. Observations of this study promise potential for mast cells and derived mediators as future biomarkers and/or therapeutic targets.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".