Borderline Ventricles: From Evaluation to Treatment.

A heart with a borderline ventricle refers to a situation where there is uncertainty about whether the left or right underdeveloped ventricle can effectively support the systemic or pulmonary circulation with appropriate filling pressures and sufficient physiological reserve. Pediatric cardiologists often deal with congenital heart diseases (CHDs) associated with various degrees of hypoplasia of the left or right ventricles. To date, no specific guidelines exist, and surgical management may be extremely variable in different centers and sometimes even in the same center at different times.

The mechanics of congenital heart disease: from a morphological trait to the functional echocardiographic evaluation.

Advances in pediatric cardiac surgery have resulted in a recent growing epidemic of children and young adults with congenital heart diseases (CHDs). In these patients, congenital defects themselves, surgical operations and remaining lesions may alter cardiac anatomy and impact the mechanical performance of both ventricles. Cardiac function significantly influences outcomes in CHDs, necessitating regular patient follow-up to detect clinical changes and relevant risk factors.

Calmodulin mutation in long QT syndrome 15 associated with congenital heart defects further complicated by a functional 2:1 atrioventricular block: Management from foetal life to postpartum.

We report a long QT syndrome 15 whose diagnosis was suspected during foetal life and confirmed at birth and was associated with congenital heart disease. Genetic testing revealed a rare mutation associated with the CALM2 gene. At 23 weeks of gestation, severe foetal sinus bradycardia (∼100 bpm) was detected.

Towards the extraction of the crystal cell parameters from pair distribution function profiles.

The approach based on atomic pair distribution function (PDF) has revolutionized structural investigations by X-ray/electron diffraction of nano or quasi-amorphous materials, opening up the possibility of exploring short-range order. However, the ab initio crystal structural solution by the PDF is far from being achieved due to the difficulty in determining the crystallographic properties of the unit cell. A method for estimating the crystal cell parameters directly from a PDF profile is presented, which is composed of two steps: first, the type of crystal cell is inferred using machine-learning approaches applied to the PDF profile; second, the crystal cell parameters are extracted by means of multivariate analysis combined with vector superposition techniques.