Granzyme B Cleaves Decorin, Biglycan and Soluble Betaglycan, Releasing Active Transforming Growth Factor-β1
Bibliographic record
Abstract
OBJECTIVE: Granzyme B (GrB) is a pro-apoptotic serine protease that contributes to immune-mediated target cell apoptosis. However, during inflammation, GrB accumulates in the extracellular space, retains its activity, and is capable of cleaving extracellular matrix (ECM) proteins. Recent studies have implicated a pathogenic extracellular role for GrB in cardiovascular disease, yet the pathophysiological consequences of extracellular GrB activity remain largely unknown. The objective of this study was to identify proteoglycan (PG) substrates of GrB and examine the ability of GrB to release PG-sequestered TGF-β1 into the extracellular milieu. METHODS/RESULTS: Three extracellular GrB PG substrates were identified; decorin, biglycan and betaglycan. As all of these PGs sequester active TGF-β1, cytokine release assays were conducted to establish if GrB-mediated PG cleavage induced TGF-β1 release. Our data confirmed that GrB liberated TGF-β1 from all three substrates as well as from endogenous ECM and this process was inhibited by the GrB inhibitor 3,4-dichloroisocoumarin. The released TGF-β1 retained its activity as indicated by the induction of SMAD-3 phosphorylation in human coronary artery smooth muscle cells. CONCLUSION: In addition to contributing to ECM degradation and the loss of tissue structural integrity in vivo, increased extracellular GrB activity is also capable of inducing the release of active TGF-β1 from PGs.
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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) | 0.001 | 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 | 0.001 |
| 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".