Transglutaminase 2 cross-linking activity is linked to invadopodia formation and cartilage breakdown in arthritis
Bibliographic record
Abstract
INTRODUCTION: The microenvironment surrounding inflamed synovium leads to the activation of fibroblast-like synoviocytes (FLSs), which are important contributors to cartilage destruction in rheumatoid arthritic (RA) joints. Transglutaminase 2 (TG2), an enzyme involved in extracellular matrix (ECM) cross-linking and remodeling, is activated by inflammatory signals. This study was undertaken to assess the potential contribution of TG2 to FLS-induced cartilage degradation. METHODS: Transglutaminase (TGase) activity and collagen degradation were assessed with the immunohistochemistry of control, collagen-induced arthritic (CIA) or TG2 knockdown (shRNA)-treated joint tissues. TGase activity in control (C-FLS) and arthritic (A-FLS) rat FLSs was measured by in situ 5-(biotinamido)-pentylamine incorporation. Invadopodia formation and functions were measured in rat FLSs and cells from normal (control; C-FLS) and RA patients (RA-FLS) by in situ ECM degradation. Immunoblotting, enzyme-linked immunosorbent assay (ELISA), and p3TP-Lux reporter assays were used to assess transforming growth factor-β (TGF-β) production and activation. RESULTS: TG2 and TGase activity were associated with cartilage degradation in CIA joints. In contrast, TGase activity and cartilage degradation were reduced in joints by TG2 knockdown. A-FLSs displayed higher TGase activity and TG2 expression in ECM than did C-FLSs. TG2 knockdown or TGase inhibition resulted in reduced invadopodia formation in rat and human arthritic FLSs. In contrast, increased invadopodia formation was noted in response to TGase activity induced by TGF-β, dithiothreitol (DTT), or TG2 overexpression. TG2-induced increases in invadopodia formation were blocked by TGF-β neutralization or inhibition of TGF-βR1. CONCLUSIONS: TG2, through its TGase activity, is required for ECM degradation in arthritic FLS and CIA joints. Our findings provide a potential target to prevent cartilage degradation in RA.
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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 | 0.000 |
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".