The intramembrane proteases SPPL2a and SPPL2b regulate the homeostasis of selected SNARE proteins.

Signal peptide peptidase (SPP) and SPP-like (SPPL) aspartyl intramembrane proteases are known to contribute to sequential processing of type II-oriented membrane proteins referred to as regulated intramembrane proteolysis. The ER-resident family members SPP and SPPL2c were shown to also cleave tail-anchored proteins, including selected SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins facilitating membrane fusion events. Here, we analysed whether the related SPPL2a and SPPL2b proteases, which localise to the endocytic or late secretory pathway, are also able to process SNARE proteins.

High-throughput phenotyping of heteromeric human ether-à-go-go-related gene potassium channel variants can discriminate pathogenic from rare benign variants.

Background: KCNH2 encodes the human ether-à-go-go-related gene potassium channel, which passes the rapid delayed rectifier potassium current. Loss-of-function variants in KCNH2 cause long QT syndrome type 2, which is associated with a markedly increased risk of cardiac arrhythmias. The majority of rare KCNH2 variants, however, are likely to be benign.

Mutation-specific peripheral and ER quality control of hERG channel cell-surface expression.

Impaired functional plasma membrane (PM) expression of the hERG K-channel is associated with Long-QT syndrome type-2 (LQT2) and increased risk of cardiac arrhythmia. Reduced PM-expression is primarily attributed to retention and degradation of misfolded channels by endoplasmic reticulum (ER) protein quality control (QC) systems. However, as the molecular pathogenesis of LQT2 was defined using severely-misfolded hERG variants with limited PM-expression, the potential contribution of post-ER (peripheral) QC pathways to the disease phenotype remains poorly established.

hERG quality control and the long QT syndrome.

Long-QT syndrome type-2 (LQT2) is characterized by reduced functional expression of the human ether-à-go-go related (hERG) gene product, resulting in impaired cardiac repolarization and predisposition to fatal arrhythmia. Previous studies have implicated abnormal trafficking of misfolded hERG as the primary mechanism of LQT2, with misfolding being caused by mutations in the hERG gene (inherited) or drug treatment (acquired). More generally, environmental and metabolic stresses present a constant challenge to the folding of proteins, including hERG, and must be countered by robust protein quality control (QC) systems.

Ubiquitination-dependent quality control of hERG K+ channel with acquired and inherited conformational defect at the plasma membrane.

Membrane trafficking in concert with the peripheral quality control machinery plays a critical role in preserving plasma membrane (PM) protein homeostasis. Unfortunately, the peripheral quality control may also dispose of partially or transiently unfolded polypeptides and thereby contribute to the loss-of-expression phenotype of conformational diseases. Defective functional PM expression of the human ether-a-go-go-related gene (hERG) K(+) channel leads to the prolongation of the ventricular action potential that causes long QT syndrome 2 (LQT2), with increased propensity for arrhythmia and sudden cardiac arrest.

Interaction of hypoxia and core temperature: potential role of TRPV1.

Hypoxia exposure in small mammals elicits an initial rise in ventilation followed by a reduction to levels that are often less than the normoxic value. The fall in ventilation is matched by a decrease in metabolism rate and a reduction in core body temperature (Tb). The transient receptor potential vanilloid 1 (TRPV1) ion channel has been implicated in thermoregulation (Caterina et al.

A distributed approach for optimizing cascaded classifier topologies in real-time stream mining systems.

In this paper, we discuss distributed optimization techniques for configuring classifiers in a real-time, informationally-distributed stream mining system. Due to the large volume of streaming data, stream mining systems must often cope with overload, which can lead to poor performance and intolerable processing delay for real-time applications. Furthermore, optimizing over an entire system of classifiers is a difficult task since changing the filtering process at one classifier can impact both the feature values of data arriving at classifiers further downstream and thus, the classification performance achieved by an ensemble of classifiers, as well as the end-to-end processing delay.