Pharmacological modulation of transglutaminase 2 in the unilateral ureteral obstruction mouse model
Bibliographic record
Abstract
BACKGROUND: Transglutaminase 2 (TG2) is a multifunctional enzyme involved in fibrosis by promoting transforming-growth-factor-β1 and crosslinking of extracellular matrix proteins. These functions are dependent on the open conformation, while the closed state of TG2 can induce vasodilation. We explored the putative protective role of TG2 in its closed state on development of renal fibrosis and blood pressure (BP) regulation. METHODS: We studied the unilateral ureteral obstruction (UUO) mouse model treated with LDN27219, which promotes the closed conformation of TG2. Mice were subjected to 7 days UUO or sham operation and treated with vehicle (n = 10), LDN27219 (15 mg/kg/12 h, n = 9) or candesartan (5 mg/kg/day, n = 10) as a clinically comparator. Renal expression of TG2 and pro-fibrotic mediators were evaluated by Western blotting, qPCR and histology, and BP by tail-cuff measurements. RESULTS: Obstructed kidneys showed increased mRNA and protein expression of fibronectin, collagen 3α1 (Col3α1), α-smooth muscle actin and collagen staining. Despite increased renal TG2 mRNA, protein expression was reduced in all UUO groups, but with increased transamidase activity in the vehicle and candesartan groups. LDN27219 reduced mRNA expression of fibronectin and Col3α1, but their protein expression remained unchanged. In contrast to LDN27219, candesartan lowered BP without affecting expression of pro-fibrotic biomarkers. CONCLUSION: Renal TG2 mRNA and protein expression levels seem dissociated, with transamidase activity being increased. LDN27219 influences kidney pro-fibrotic markers at the mRNA level and attenuates transamidase activity but without affecting collagen content or BP. Our findings suggest that TG2 in its closed conformation has anti-fibrotic effects at the molecular level.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".