AMPK Activation Regulates LTBP4-Dependent TGF-β1 Secretion by Pro-inflammatory Macrophages and Controls Fibrosis in Duchenne Muscular Dystrophy
Bibliographic record
Abstract
Chronic inflammation and fibrosis characterize Duchenne muscular dystrophy (DMD). We show that pro-inflammatory macrophages are associated with fibrosis in mouse and human DMD muscle. DMD-derived Ly6C pos macrophages exhibit a profibrotic activity by sustaining fibroblast production of collagen I. This is mediated by the high production of latent-TGF-β1 due to the higher expression of LTBP4, for which polymorphisms are associated with the progression of fibrosis in DMD patients. Skewing macrophage phenotype via AMPK activation decreases ltbp4 expression by Ly6C pos macrophages, blunts the production of latent-TGF-β1, and eventually reduces fibrosis and improves DMD muscle force. Moreover, fibro-adipogenic progenitors are the main providers of TGF-β-activating enzymes in mouse and human DMD, leading to collagen production by fibroblasts. In vivo pharmacological inhibition of TGF-β-activating enzymes improves the dystrophic phenotype. Thus, an AMPK-LTBP4 axis in inflammatory macrophages controls the production of TGF-β1, which is further activated by and acts on fibroblastic cells, leading to fibrosis in DMD.
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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".