Osteopontin Upregulation and Polymerization by Transglutaminase 2 in Calcified Arteries of Matrix Gla Protein-deficient Mice
Bibliographic record
Abstract
Matrix Gla protein (MGP) is a potent inhibitor of soft tissue calcification, and Mgp gene deletion in mice results in arterial calcification. Our aim was to examine osteopontin (OPN) expression and localization, and posttranslational processing of OPN by the crosslinking enzyme transglutaminase 2 (TG2), in the calcified aorta of Mgp-deficient (Mgp(-/-)) mice. Using immunohistochemistry and light and electron microscopy, we report that following mineralization occurring in the arterial media of Mgp(-/-) aortas, OPN is upregulated and accumulates at the surface of the calcified elastic lamellae. Macrophages were observed in direct contact with this OPN-rich layer. Western blot analysis of extracted Mgp(-/-) aortas revealed that the majority of the OPN was in high molecular mass protein complexes, indicating modification by a crosslinking enzyme. Consistent with this observation, TG2 expression and gamma-glutamyl-epsilon-lysyl crosslink levels were also increased in Mgp(-/-) aortas. In addition to the mineral-inhibiting actions of OPN, and based on data linking OPN and TG2 with cell adhesion in various cell types including monocytes and macrophages, we propose that TG2 interactions with OPN lead to protein polymerization that facilitates macrophage adhesion to the calcified elastic lamellae to promote clearance of the ectopic mineral deposits.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".