Stochastic generation and suppression of early afterdepolarizations in a three-dimensional model of cardiac action potential

The influence of random disturbances on a three-dimensional simplification of Luo–Rudy model of the cardiac action potential is studied. We show that in the parameter region, where the deterministic model is in the equilibrium regime, noise can trigger large-amplitude oscillations that correspond with pathological early afterdepolarizations (EADs). For this stochastic excitement, the phenomenon of coherence resonance was discovered. On the contrary, in another parameter zone of the model, noise can suppress EADs. We analyze these stochastic phenomena using the stochastic sensitivity functions technique, Mahalanobis distance, the methods of principal directions, and confidence domains. © 2021 The Authors. Mathematical Methods in the Applied Sciences published by John Wiley & Sons, Ltd.Russian Science Foundation, RSF: 21-11-00062This work was supported by the Russian Science Foundation (No. 21-11-00062)

Correlation between human ether-a-go-go-related gene channel inhibition and action potential prolongation

Background and Purpose: Human ether-a-go-go-related gene (hERG; Kv11.1) channel inhibition is a widely accepted predictor of cardiac arrhythmia. hERG channel inhibition alone is often insufficient to predict pro-arrhythmic drug effects. This study used a library of dofetilide derivatives to investigate the relationship between standard measures of hERG current block in an expression system and changes in action potential duration (APD) in human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). The interference from accompanying block of Cav1.2 and Nav1.5 channels was investigated along with an in silico AP model. Experimental Approach: Drug-induced changes in APD were assessed in hiPSC-CMs using voltage-sensitive dyes. The IC50 values for dofetilide and 13 derivatives on hERG current were estimated in an HEK293 expression system. The relative potency of each drug on APD was estimated by calculating the dose (D150) required to prolong the APD at 90% (APD90) repolarization by 50%. Key Results: The D150 in hiPSC-CMs was linearly correlated with IC50 of hERG current. In silico simulations supported this finding. Three derivatives inhibited hERG without prolonging APD, and these compounds also inhibited Cav1.2 and/or Nav1.5 in a channel state-dependent manner. Adding Cav1.2 and Nav1.2 block to the in silico model recapitulated the direction but not the extent of the APD change. Conclusions and Implications: Potency of hERG current inhibition correlates linearly with an index of APD in hiPSC-CMs. The compounds that do not correlate have additional effects including concomitant block of Cav1.2 and/or Nav1.5 channels. In silico simulations of hiPSC-CMs APs confirm the principle of the multiple ion channel effects

How Do Bacteria Know They Are on a Surface and Regulate Their Response to an Adhering State?

Bacteria adhere to virtually all natural and synthetic surfaces [1,2]. Although there are a number of different reasons as to why bacteria adhere to a surface, the summarizing answer is brief: ‘‘Adhesion to a surface is a survival mechanism for bacteria’’. Nutrients in aqueous environments have the tendency to accumulate at surfaces [1,3], giving adhering bacteria a benefit over free floating, so-called planktonic ones. This is why mountain creeks may contain crystal clear, drinkable water, while stepping stones underneath the water may be covered with a slippery film of adhering microbes. In the oral cavity, adhesion to dental hard and soft tissues is life-saving to the organisms, because microbes that do not manage to adhere and remain planktonic in saliva are swallowed with an almost certain death in the gastrointestinal tract. Bacterial adhesion is generally recognized as the first step in biofilm formation, and for the human host, the ability of

To transduce a zebra finch: interrogating behavioral mechanisms in a model system for speech

The ability to alter neuronal gene expression, either to affect levels of endogenous molecules or to express exogenous ones, is a powerful tool for linking brain and behavior. Scientists continue to finesse genetic manipulation in mice. Yet mice do not exhibit every behavior of interest. For example, Mus musculus do not readily imitate sounds, a trait known as vocal learning and a feature of speech. In contrast, thousands of bird species exhibit this ability. The circuits and underlying molecular mechanisms appear similar between disparate avian orders and are shared with humans. An advantage of studying vocal learning birds is that the neurons dedicated to this trait are nested within the surrounding brain regions, providing anatomical targets for relating brain and behavior. In songbirds, these nuclei are known as the song control system. Molecular function can be interrogated in non-traditional model organisms by exploiting the ability of viruses to insert genetic material into neurons to drive expression of experimenter-defined genes. To date, the use of viruses in the song control system is limited. Here, we review prior successes and test additional viruses for their capacity to transduce basal ganglia song control neurons. These findings provide a roadmap for troubleshooting the use of viruses in animal champions of fascinating behaviors-nowhere better featured than at the 12th International Congress

A split horseradish peroxidase for detection of intercellular protein-protein interactions and sensitive visualization of synapses

Intercellular protein-protein interactions (PPIs) enable communication between cells in diverse biological processes, including cell proliferation, immune responses, infection and synaptic transmission, but they are challenging to visualize because existing techniques1,2,3 have insufficient sensitivity and/or specificity. Here we report split horseradish peroxidase (sHRP) as a sensitive and specific tool for detection of intercellular PPIs. The two sHRP fragments, engineered through screening of 17 cut sites in HRP followed by directed evolution, reconstitute into an active form when driven together by an intercellular PPI, producing bright fluorescence or contrast for electron microscopy. Fusing the sHRP fragments to the proteins neurexin (NRX) and neuroligin (NLG), which bind each other across the synaptic cleft4, enabled sensitive visualization of synapses between specific sets of neurons, including two classes of synapses in the mouse visual system. sHRP should be widely applicable for studying mechanisms of communication between a variety of cell types

Inference for stochastic chemical kinetics using moment equations and system size expansion

Quantitative mechanistic models are valuable tools for disentangling biochemical pathways and for achieving a comprehensive understanding of biological systems. However, to be quantitative the parameters of these models have to be estimated from experimental data. In the presence of significant stochastic fluctuations this is a challenging task as stochastic simulations are usually too time-consuming and a macroscopic description using reaction rate equations (RREs) is no longer accurate. In this manuscript, we therefore consider moment-closure approximation (MA) and the system size expansion (SSE), which approximate the statistical moments of stochastic processes and tend to be more precise than macroscopic descriptions. We introduce gradient-based parameter optimization methods and uncertainty analysis methods for MA and SSE. Efficiency and reliability of the methods are assessed using simulation examples as well as by an application to data for Epo-induced JAK/STAT signaling. The application revealed that even if merely population-average data are available, MA and SSE improve parameter identifiability in comparison to RRE. Furthermore, the simulation examples revealed that the resulting estimates are more reliable for an intermediate volume regime. In this regime the estimation error is reduced and we propose methods to determine the regime boundaries. These results illustrate that inference using MA and SSE is feasible and possesses a high sensitivity

Progress in gene therapy for neurological disorders

Diseases of the nervous system have devastating effects and are widely distributed among the population, being especially prevalent in the elderly. These diseases are often caused by inherited genetic mutations that result in abnormal nervous system development, neurodegeneration, or impaired neuronal function. Other causes of neurological diseases include genetic and epigenetic changes induced by environmental insults, injury, disease-related events or inflammatory processes. Standard medical and surgical practice has not proved effective in curing or treating these diseases, and appropriate pharmaceuticals do not exist or are insufficient to slow disease progression. Gene therapy is emerging as a powerful approach with potential to treat and even cure some of the most common diseases of the nervous system. Gene therapy for neurological diseases has been made possible through progress in understanding the underlying disease mechanisms, particularly those involving sensory neurons, and also by improvement of gene vector design, therapeutic gene selection, and methods of delivery. Progress in the field has renewed our optimism for gene therapy as a treatment modality that can be used by neurologists, ophthalmologists and neurosurgeons. In this Review, we describe the promising gene therapy strategies that have the potential to treat patients with neurological diseases and discuss prospects for future development of gene therapy