Electrophysiological characterization of drug response in hSC-derived cardiomyocytes using voltage-sensitive optical platforms

Introduction: Voltage-sensitive optical (VSO) sensors offer a minimally invasive method to study the time course of repolarization of the cardiac action potential (AP). This Comprehensive in vitro Proarrhythmia Assay (CiPA) cross-platform study investigates protocol design and measurement variability of VSO sensors for preclinical cardiac electrophysiology assays. Methods: Three commercial and one academic laboratory completed a limited study of the effects of 8 blinded compounds on the electrophysiology of 2 commercial lines of human induced pluripotent stem-cell derived cardiomyocytes (hSC-CMs). Acquisition technologies included CMOS camera and photometry; fluorescent voltage sensors included di-4-ANEPPS, FluoVolt and genetically encoded QuasAr2. The experimental protocol was standardized with respect to cell lines, plating and maintenance media, blinded compounds, and action potential parameters measured. Serum-free media was used to study the action of drugs, but the exact composition and the protocols for cell preparation and drug additions varied among sites. Results: Baseline AP waveforms differed across platforms and between cell types. Despite these differences, the relative responses to four selective ion channel blockers (E-4031, nifedipine, mexiletine, and JNJ 303 blocking IKr, ICaL, INa, and IKs, respectively) were similar across all platforms and cell lines although the absolute changes differed. Similarly, four mixed ion channel blockers (flecainide, moxifloxacin, quinidine, and ranolazine) had comparable effects in all platforms. Differences in repolarisation time course and response to drugs could be attributed to cell type and experimental method differences such as composition of the assay media, stimulated versus spontaneous activity, and single versus cumulative compound addition. Discussion: In conclusion, VSOs represent a powerful and appropriate method to assess the electrophysiological effects of drugs on iPSC-CMs for the evaluation of proarrhythmic risk. Protocol considerations and recommendations are provided toward standardizing conditions to reduce variability of baseline AP waveform characteristics and drug responses

High-precision state of charge estimation of urban-road-condition lithium-ion batteries based on optimized high-order term compensation-adaptive extended Kalman filtering.

It is significant to improve the accuracy of estimating the state of charge (SOC) of lithium-ion batteries under different working conditions on urban roads. In this study, an improved second-order polarized equivalent circuit (SO-PEC) modeling method is proposed. Accuracy test using segmented parallel exponential fitting parameter identification method. Online parameter identification using recursive least squares with variable forgetting factors(VFFRLS). An optimized higher-order term compensation-adaptive extended Kalman filter (HTC-AEKF) is proposed in the process of estimating SOC. The algorithm incorporates a noise-adaptive algorithm that introduces noise covariance into the recursive process in real-time to reduce the impact of process noise and observation noise on the accuracy of SOC estimation. Multiple iterations are performed for some of the processes in the extended Kalman filter(EKF) to compensate for the accuracy impact of missing higher-order terms in the linearization process. Model validation results show over 98% accuracy. The results after comparing with the EKF algorithm show a 4.1% improvement in SOC estimation accuracy under Hybrid Pulse Power Characterization(HPPC) working conditions. 2.7% improvement in accuracy in Dynamic Stress Test(DST) working conditions. 2.1% improvement in Beijing Bus Dynamic Stress Test(BBDST) working conditions. The superiority of the algorithm is demonstrated

High precision state of health estimation of lithium-ion batteries based on strong correlation aging feature extraction and improved hybrid kernel function least squares support vector regression machine model.

The state of health (SOH) of lithium-ion batteries plays a crucial role in maintaining the stability of electric vehicle systems. To address the issue of low accuracy in existing prediction models, this article introduces an enhanced grey wolf algorithm for optimizing the hybrid kernel least squares support vector regression machine used in lithium-ion battery SOH prediction. This research extracted four key health features from the raw data of each battery in the Cycle dataset, which is publicly accessible. Data preprocessing of health features involved Pearson correlation analysis and Hampel filtering techniques. The framework of least squares support vector regression constructs a hybrid kernel function of polynomial kernel function and radial basis function. The integration of differential evolution and the law of survival of the fittest into the grey wolf algorithm enhances its optimization ability. The improved grey wolf algorithm optimizes the parameters of the hybrid kernel least squares support vector regression machine, improving the accuracy and robustness of the model. After data validation, it is known that the optimal average absolute error value predicted by the model can reach 0.32%. This indicates that the proposed method is effective and feasible

Toxic effects and mechanism of 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) on Lemna minor

To investigate the toxic effect and mechanism of 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) in aquatic plants, in vivo and in vitro exposure to BDE-47 were conducted. After 14-d exposure to 5-20 mu g/L BDE-47, the growth of Lemna minor plants was significantly suppressed, and the chlorophyll and soluble protein contents in fronds markedly decreased. Accordingly, the photosynthetic efficiency (Fv/Fm, PI) decreased. When the thylakoid membranes isolated from healthy fronds was exposed to 5-20 mg/L BDE-47 directly in vitro for 1 h, the photosynthetic efficiency also decreased significantly. In both the in vitro (5-20 mu g/L) and in vivo (5-20 mg/L) experiments, BDE-47 led to an increased plasma membrane permeability. Hence, we concluded that BDE-47 had a direct toxicity to photosynthetic membranes and plasma membranes. However, direct effects on the activities of peroxidase (POD), malate dehydrogenase (MDH) and nitroreductase (NR) were not observed by adding 5-20 mg/L BDE-47 into crude enzyme extracts. The malondialdehyde (MDA) and superoxide anion radical (O-2(-)) contents in the BDE-47 treated fronds were higher than those in the control fronds, suggesting that L. minor can not effectively relieve reactive oxygen species (ROS). The data above indicates that BDE-47 is toxic to L. minor through acting directly on biomembranes, which induces the production of ROS and thus causes remarkable oxidative damage to cells. (C) 2017 Elsevier Ltd. All rights reserved

Analysis of Leakage Current of HfO2/TaOx-Based 3-D Vertical Resistive Random Access Memory Array

Three-dimensional vertical resistive random access memory (VRRAM) is proposed as a promising candidate for increasing resistive memory storage density, but the performance evaluation mechanism of 3-D VRRAM arrays is still not mature enough. The previous approach to evaluating the performance of 3-D VRRAM was based on the write and read margin. However, the leakage current (LC) of the 3-D VRRAM array is a concern as well. Excess leakage currents not only reduce the read/write tolerance and liability of the memory cell but also increase the power consumption of the entire array. In this article, a 3-D circuit HSPICE simulation is used to analyze the impact of the array size and operation voltage on the leakage current in the 3-D VRRAM architecture. The simulation results show that rapidly increasing leakage currents significantly affect the size of 3-D layers. A high read voltage is profitable for enhancing the read margin. However, the leakage current also increases. Alleviating this conflict requires a trade-off when setting the input voltage. A method to improve the array read/write efficiency is proposed by analyzing the influence of the multi-bit operations on the overall leakage current. Finally, this paper explores different methods to reduce the leakage current in the 3-D VRRAM array. The leakage current model proposed in this paper provides an efficient performance prediction solution for the initial design of 3-D VRRAM arrays

Crystal Structure of the Hyperthermophilic Inorganic Pyrophosphatase from the Archaeon Pyrococcus horikoshii

A homolog to the eubacteria inorganic pyrophosphatase (PPase, EC 3.6.1.1) was found in the genome of the hyperthermophilic archaeon Pyrococcus horikoshii. This inorganic pyrophosphatase (Pho-PPase) grows optimally at 88°C. To understand the structural basis for the thermostability of Pho-PPase, we have determined the crystal structure to 2.66 Å resolution. The crystallographic asymmetric unit contains three monomers related by approximate threefold symmetry, and a hexamer is built up by twofold crystallographic symmetry. The main-chain fold of Pho-PPase is almost identical to that of the known crystal structure of the model from Sulfolobus acidocaldarius. A detailed comparison of the crystal structure of Pho-PPase with related structures from S. acidocaldarius, Thermus thermophilus, and Escherichia coli shows significant differences that may account for the difference in their thermostabilities. A reduction in thermolabile residues, additional aromatic residues, and more intimate association between subunits all contribute to the larger thermophilicity of Pho-PPase. In particular, deletions in two loops surrounding the active site help to stabilize its conformation, while ion-pair networks unique to Pho-PPase are located in the active site and near the C-terminus. The identification of structural features that make PPases more adaptable to extreme temperature should prove helpful for future biotechnology applications

Bioinformatic Identification and Expression Analysis of Banana MicroRNAs and Their Targets

<div><p>MicroRNAs (miRNAs) represent a class of endogenous non-coding small RNAs that play important roles in multiple biological processes by degrading targeted mRNAs or repressing mRNA translation. Thousands of miRNAs have been identified in many plant species, whereas only a limited number of miRNAs have been predicted in <i>M</i>. <i>acuminata</i> (A genome) and <i>M</i>. <i>balbisiana</i> (B genome). Here, previously known plant miRNAs were BLASTed against the Expressed Sequence Tag (EST) and Genomic Survey Sequence (GSS), a database of banana genes. A total of 32 potential miRNAs belonging to 13 miRNAs families were detected using a range of filtering criteria. 244 miRNA:target pairs were subsequently predicted, most of which encode transcription factors or enzymes that participate in the regulation of development, growth, metabolism, and other physiological processes. In order to validate the predicted miRNAs and the mutual relationship between miRNAs and their target genes, qRT-PCR was applied to detect the tissue-specific expression levels of 12 putative miRNAs and 6 target genes in roots, leaves, flowers, and fruits. This study provides some important information about banana pre-miRNAs, mature miRNAs, and miRNA target genes and these findings can be applied to future research of miRNA functions.</p></div