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1. TAD boundary deletion causes PITX2-related cardiac electrical and structural defects

2. Dyslipidemia, inflammation, calcification, and adiposity in aortic stenosis: a genome-wide study

5. Research Opportunities in the Treatment of Mitral Valve Prolapse: JACC Expert Panel.

6. Staphylococcus succinus Infective Endocarditis, France

9. Prognostic Implications of Residual Tricuspid Regurgitation Grading After Transcatheter Tricuspid Valve Repair

11. The role of antibody responses against glycans in bioprosthetic heart valve calcification and deterioration

12. Machine Learning–Based Phenogrouping in MVP Identifies Profiles Associated With Myocardial Fibrosis and Cardiovascular Events

14. Association between Neu5Gc carbohydrate and serum antibodies against it provides the molecular link to cancer: French NutriNet-Santé study.

20. Randomised study for the Optimal Treatment of symptomatic patients with low-gradient severe Aortic valve Stenosis and preserved left ventricular ejection fraction (ROTAS trial).

21. Genetic and In Vitro Inhibition of PCSK9 and Calcific Aortic Valve Stenosis

23. Calcification of surgical aortic bioprostheses and its impact on clinical outcome

24. A new evidence-based echocardiographic approach to predict cardiovascular events and myocardial fibrosis in mitral valve prolapse: The STAMP algorithm

25. Characterization of immunogenic Neu5Gc in bioprosthetic heart valves

27. TRI-SCORE and benefit of intervention in patients with severe tricuspid regurgitation

28. Genetic association analyses highlight biological pathways underlying mitral valve prolapse

33. Filamin A heart valve disease as a genetic cause of inherited bicuspid and tricuspid aortic valve disease

34. Prognostic Implications of Right Ventricular Dysfunction in Degenerative Mitral Regurgitation

36. Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm

37. Response by Essayagh et al to Letter Regarding Article, “The MIDA-Q Mortality Risk Score: A Quantitative Prognostic Tool for the Mitral Valve Prolapse Spectrum”

42. Differential Immune Response to Bioprosthetic Heart Valve Tissues in the α1,3Galactosyltransferase-Knockout Mouse Model

44. Role of immune cells in the development of mitral valve dystrophy

45. Machine Learning–Based Phenogrouping in Mitral Valve Prolapse Identifies Profiles Associated With Myocardial Fibrosis and Cardiovascular Events

47. Dyslipidemia, inflammation, calcification, and adiposity in aortic stenosis: a genome-wide study

49. Comparison of effective regurgitant orifice area by the PISA method and tricuspid coaptation gap measurement to identify very severe tricuspid regurgitation and stratify mortality risk

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