Inflammatory monocytes promote progression of Duchenne muscular dystrophy and can be therapeutically targeted via CCR2
Bibliographic record
Abstract
Myofiber necrosis and fibrosis are hallmarks of Duchenne muscular dystrophy (DMD), leading to lethal weakness of the diaphragm. Macrophages (MPs) are required for successful muscle regeneration, but the role of inflammatory monocyte (MO)-derived MPs in either promoting or mitigating DMD is unclear. We show that DMD (mdx) mouse diaphragms exhibit greatly increased expression of CCR2 and its chemokine ligands, along with inflammatory (Ly6C(high)) MO recruitment and accumulation of CD11b(high) MO-derived MPs. Loss-of-function of CCR2 preferentially reduced this CD11b(high) MP population by impeding the release of Ly6C(high) MOs from the bone marrow but not the splenic reservoir. CCR2 deficiency also helped restore the MP polarization balance by preventing excessive skewing of MPs toward a proinflammatory phenotype. These effects were linked to amelioration of histopathological features and increased muscle strength in the diaphragm. Chronic inhibition of CCR2 signaling by mutated CCL2 secreted from implanted mesenchymal stem cells resulted in similar improvements. These data uncover a previously unrecognized role of inflammatory MOs in DMD pathogenesis and indicate that CCR2 inhibition could offer a novel strategy for DMD management.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".