Huntingtin-Associated Protein 1A Regulates Store-Operated Calcium Entry in Medium Spiny Neurons From Transgenic YAC128 Mice, a Model of Huntington’s Disease

Huntington’s disease (HD) is a hereditary neurodegenerative disease that is caused by polyglutamine expansion within the huntingtin (HTT) gene. One of the cellular activities that is dysregulated in HD is store-operated calcium entry (SOCE), a process by which Ca2+ release from the endoplasmic reticulum (ER) induces Ca2+ influx from the extracellular space. HTT-associated protein-1 (HAP1) is a binding partner of HTT. The aim of the present study was to examine the role of HAP1A protein in regulating SOCE in YAC128 mice, a transgenic model of HD. After Ca2+ depletion from the ER by the activation of inositol-(1,4,5)triphosphate receptor type 1 (IP3R1), we detected an increase in the activity of SOC channels when HAP1 protein isoform HAP1A was overexpressed in medium spiny neurons (MSNs) from YAC128 mice. A decrease in the activity of SOC channels in YAC128 MSNs was observed when HAP1 protein was silenced. In YAC128 MSNs that overexpressed HAP1A, an increase in activity of IP3R1 was detected while the ionomycin-sensitive ER Ca2+ pool decreased. 6-Bromo-N-(2-phenylethyl)-2,3,4,9-tetrahydro-1H-carbazol-1-amine hydrochloride (C20H22BrClN2), identified in our previous studies as a SOCE inhibitor, restored the elevation of SOCE in YAC128 MSN cultures that overexpressed HAP1A. The IP3 sponge also restored the elevation of SOCE and increased the release of Ca2+ from the ER in YAC128 MSN cultures that overexpressed HAP1A. The overexpression of HAP1A in the human neuroblastoma cell line SK-N-SH (i.e., a cellular model of HD (SK-N-SH HTT138Q)) led to the appearance of a pool of constitutively active SOC channels and an increase in the expression of STIM2 protein. Our results showed that HAP1A causes the activation of SOC channels in HD models by affecting IP3R1 activity

Identification of Quadratic Volterra Polynomials in the “Input–Output” Models of Nonlinear Systems

In this paper, we propose a new algorithm for constructing an integral model of a nonlinear dynamic system of the “input–output” type in the form of a quadratic segment of the Volterra integro-power series (polynomial). We consider nonparametric identification of models using physically realizable piecewise linear test signals in the time domain. The advantage of the presented approach is to obtain explicit formulas for calculating the transient responses (Volterra kernels), which determine the unique solution of the Volterra integral equations of the first kind with two variable integration limits. The numerical method proposed in the paper for solving the corresponding equations includes the use of smoothing splines. An important result is that the constructed identification algorithm has a low methodological error

Identification of Quadratic Volterra Polynomials in the “Input–Output” Models of Nonlinear Systems

In this paper, we propose a new algorithm for constructing an integral model of a nonlinear dynamic system of the “input–output” type in the form of a quadratic segment of the Volterra integro-power series (polynomial). We consider nonparametric identification of models using physically realizable piecewise linear test signals in the time domain. The advantage of the presented approach is to obtain explicit formulas for calculating the transient responses (Volterra kernels), which determine the unique solution of the Volterra integral equations of the first kind with two variable integration limits. The numerical method proposed in the paper for solving the corresponding equations includes the use of smoothing splines. An important result is that the constructed identification algorithm has a low methodological error