Genetic manipulation of CCN2/CTGF unveils cell‐specific ECM‐remodeling effects in injured skeletal muscle
Bibliographic record
Abstract
ABSTRACT In skeletal muscle, extracellular matrix (ECM) remodeling can either support the complete regeneration of injured muscle or facilitate pathologic fibrosis and muscle degeneration. Muscular dystrophy (MD) is a group of genetic disorders that results in a progressive decline in muscle function and is characterized by the abundant deposition of fibrotic tissue. Unlike acute injury, where ECM remodeling is acute and transient, in MD, remodeling persists until fibrosis obstructs the regenerative efforts of diseased muscles. Thus, understanding how ECM is deposited and organized is critical in the context of muscle repair. Connective tissue growth factor (CTGF or CCN2) is a matricellular protein expressed by multiple cell types in response to tissue injury. Although used as a general marker of fibrosis, the cell type–dependent role of CTGF in dystrophic muscle has not been elucidated. To address this question, a conditional Ctgf myofiber and fibroblast‐knockout mouse lines were generated and crossed to a dystrophic background. Only myofiber‐selective inhibition of CTGF protected δ‐sarcoglycan–null ( Sgcd −/− ) mice from the dystrophic phenotype, and it did so by affecting collagen organization in a way that allowed for improvements in dystrophic muscle regeneration and function. To confirm that muscle‐specific CTGF functions to mediate collagen organization, we generated mice with transgenic muscle‐specific overexpression of CTGF. Again, genetic modulation of CTGF in muscle was not sufficient to drive fibrosis, but altered collagen content and organization after injury. Our results show that the myofibers are critical mediators of the deleterious effects associated with CTGF in MD and acutely injured skeletal muscle.—Petrosino, J. M., Leask, A., Accornero, F. Genetic manipulation of CCN2/CTGF unveils cell‐specific ECM‐remodeling effects in injured skeletal muscle. FASEB J. 33, 2047–2057 (2019). www.fasebj.org
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".