The Role of Wnt/β-Catenin Pathway Mediators in Aortic Valve Stenosis
Bibliographic record
Abstract
Aortic valve stenosis (AVS) is a prevailing and life-threatening cardiovascular disease in adults over 75 years of age. However, the molecular mechanisms governing the pathogenesis of AVS are yet to be fully unraveled. With accumulating evidence that Wnt signaling plays a key role in the development of AVS, the involvement of Wnt molecules has become an integral study target in AVS pathogenesis. Thus, we hypothesized that the Wnt/β-catenin pathway mediators, SFRP2, DVL2, GSK3β and β-catenin are dysregulated in patients with AVS. Using immunohistochemistry, Real-Time qPCR and Western blotting, we investigated the presence of SFRP2, GSK-3β, DVL2, and β-catenin in normal and stenotic human aortic valves. Markedly higher mRNA and protein expression of GSK-3β, DVL2, β-catenin and SFRP2 were found in stenotic aortic valves. This was further corroborated by observation of their abundant immunostaining, which displayed strong immunoreactivity in diseased aortic valves. Proteomic analyses of selective GSK3b inhibition in calcifying human aortic valve interstitial cells (HAVICs) revealed enrichment of proteins involved organophosphate metabolism, while reducing the activation of pathogenic biomolecular processes. Lastly, use of the potent calcification inhibitor, Fetuin A, in calcifying HAVICs significantly reduced the expression of Wnt signaling genes Wnt3a, Wnt5a, Wnt5b, and Wnt11. The current findings of altered expression of canonical Wnt signaling in AVS suggest a possible role for regulatory Wnts in AVS. Hence, future studies focused on targeting these molecules are warranted to underline their role in the pathogenesis of the disease.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".