The long QT syndrome (LQTS) is a cardiac disorder characterized by prolongation of the QT interval on electrocardiograms (ECGs), syncope and sudden death caused by a specific ventricular tachyarrhythmia known as torsade de pointes. LQTS is caused by mutations in ion channel genes including the cardiac sodium channel gene SCN5A, and potassium channel subunit genes KCNQ1, KCNH2, KCNE1, and KCNE2. Little information is available about LQTS mutations in the Chinese population. In this study, we characterized 42 Chinese LQTS families for mutations in the two most common LQTS genes, KCNQ1 and KCNH2. We report here the identification of four novel KCNQ1 mutations and three novel KCNH2 mutations. The KCNQ1 mutations include L191P in the S2-S3 cytoplasmic loop, F275S and S277L in the S5 transmembrane domain, and G306V in the channel pore. The KCNH2 mutations include L413P in transmembrane domain S1, E444D in the extracellular loop between S1 and S2, and L559H in domain S5. The location and character of these mutations expand the spectrum of KCNQ1 and KCNH2 mutations causing LQTS. Excitement, exercises, and stress appear to be the triggers for developing cardiac events (syncope, sudden death) for LQTS patients with KCNQ1 mutations F275S, S277L, and G306V, and all three KCNH2 mutations L413P, E444D and L559H. In contrast, cardiac events for an LQTS patient with KCNQ1 mutation L191P occurred during sleep or awakening from sleep. KCNH2 mutations L413P and L559H are associated with the bifid T waves on ECGs. Inderal or propanolol (a beta blocker) appears to be effective in preventing arrhythmias and syncope for an LQTS patient with the KCNQ1 L191P mutation.
Inner surface of Nepenthes slippery zone shows anisotropic superhydrophobic wettability. Here, we investigate what factors cause the anisotropy via sliding angle measurement, morphology/structure observation and model analysis. Static contact angle of ultrapure-water droplet exhibits the value of 154.80°–156.83°, and sliding angle towards pitcher bottom and up is 2.82 ± 0.45° and 5.22 ± 0.28°, respectively. The slippery zone under investigation is covered by plenty of lunate cells with both ends bending downward, and a dense layer of wax coverings without directional difference in morphology/structure. Results indicate that the slippery zone has a considerable anisotropy in superhydrophobic wettability that is most likely caused by the lunate cells. A model was proposed to quantitatively analyse how the structure characteristics of lunate cells affect the anisotropic superhydrophobicity, and found that the slope/precipice structure of lunate cells forms a ratchet effect to cause ultrapure-water droplet to roll towards pitcher bottom/up in different order of difficulty. Our investigation firstly reveals the mechanism of anisotropic superhydrophobic wettability of Nepenthes slippery zone, and inspires the bionic design of superhydrophobic surfaces with anisotropic properties.
Exploring individual brain atrophy patterns is of great value in precision medicine for Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, the current individual brain atrophy detection models are deficient. Here, we proposed a framework called generative adversarial network constrained multiple loss autoencoder (GANCMLAE) for precisely depicting individual atrophy patterns. The GANCMLAE model was trained using normal controls (NCs) from the Alzheimer's Disease Neuroimaging Initiative cohort, and the Xuanwu cohort was employed to validate the robustness of the model. The potential of the model for identifying different atrophy patterns of MCI subtypes was also assessed. Furthermore, the clinical application potential of the GANCMLAE model was investigated. The results showed that the model can achieve good image reconstruction performance on the structural similarity index measure (0.929 ± 0.003), peak signal‐to‐noise ratio (31.04 ± 0.09), and mean squared error (0.0014 ± 0.0001) with less latent loss in the Xuanwu cohort. The individual atrophy patterns extracted from this model are more precise in reflecting the clinical symptoms of MCI subtypes. The individual atrophy patterns exhibit a better discriminative power in identifying patients with AD and MCI from NCs than those of the t ‐test model, with areas under the receiver operating characteristic curve of 0.867 (95%: 0.837–0.897) and 0.752 (95%: 0.71–0.790), respectively. Similar findings are also reported in the AD and MCI subgroups. In conclusion, the GANCMLAE model can serve as an effective tool for individualised atrophy detection.
Brugada syndrome (BrS) is a life-threatening cardiac rhythm disorder characterized by persistent STsegment elevation in leads V1-V3 and right bundle branch block on electrocardiograms (ECG), and by syncope and sudden death from ventricular tachycardia (VT) and ventricular fibrillation (VF). BrS is responsible for nearly 4% of sudden cardiac deaths and considered to be the most common cause of natural death in males younger than 50 years in some Asian countries. Since the first diseasecausing gene for BrS (the cardiac sodium channel gene SCN5A) was identified in 1998, extensive investigations on both clinical and basic aspects of BrS have occurred rapidly. SCN5A mutations remain the most common cause of BrS; nearly 300 SCN5A mutations have been identified and are responsible for 20%-30% of BrS cases. Commercial genetic testing is available for SCN5A. Recently, seven other disease-causing genes for BrS have been identified and include GPD1L (BrS2), CACNA1C (Cav1.2, BrS3), CACNB2 (Cavβ2, BrS4), SCN1B (Navβ1, BrS5), KCNE3 (MiRP2, BrS6), SCN3B (Navβ3, BrS7), and HCN4 (BrS8). This article will briefly review the progress made over the past decade in our understanding of the clinical, genetic and molecular aspects of BrS.
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