Here our aim was to study whether it is possible to separate different genetic cardiac diseases (CPVT, LQT, HCM) on the basis of Ca<sup>2+</sup> transients using machine learning methods.
The purpose of this study was to evaluate serum gastrin levels, as a surrogate for impaired gastric acid secretion, in patients with KCNQ1 mutations, and to see if gastrin levels correlate with severity of cardiac disease.
Mutations that map to the KvLQT1 and minK genes account for more than 50% of an inherited cardiac disorder, the Long QT syndrome (Splawski, I., Tristani-Firouzi, M., Lehmann, M. H., Sanguinetti, M. C., and Keating, M. T. (1997) Nat.Genet.17, 338-340).