Activation of the volume-regulated anion channels (VRAC) is considered to be involved in arrhythmia, but it has not yet been fully elucidated because of the lack of its high affinitive and selective compounds. A newly synthesized compound, YM-198313 (sodium 4-({[2-(methylthio)benzyl]amino}-5-[(1-phenylethyl)thio]isothiazol-3-olate), strongly inhibited VRAC in HeLa cells with an IC50 of 3.03+/-0.05 microM. However, YM-198313 weakly affected both the Ca2+-activated Cl- channels in HTC cells and the cAMP-activated Cl- channels in T84 cells, demonstrating that this compound is selective for VRAC among Cl- channels. At 10 microM, YM-198313 almost completely (100+/-7.8%) inhibited the VRAC current in guinea pig atrial myocytes. However, at the same concentration, YM-198313 showed little inhibitory effect on the cardiac cation currents in ventricular myocytes. We believe that YM-198313 is a potent and selective VRAC inhibitor, therefore, it should be use to clarify the role VRAC plays in arrhythmia.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1248/bpb.28.1187 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
EEG microstate analysis and machine learning classification in patients with obsessive-compulsive disorder.
J Psychiatr Res
January 2025
Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China. Electronic address:
Background: Microstate characterization of electroencephalogram (EEG) is a data-driven approach to explore the functional changes and interrelationships of multiple brain networks on a millisecond scale. This study aimed to explore the pathological changes of whole-brain functional networks in patients with obsessive-compulsive disorders (OCD) through microstate analysis and further to explore its potential value as an auxiliary diagnostic index.
Methods: Forty-eight OCD patients (33 with more than moderate anxiety symptoms, 15 with mild anxiety symptoms) and 52 healthy controls (HCs) were recruited.
Porous Silicon Particle-Assisted Mass Spectrometry Technology Unlocks Serum Metabolic Fingerprints in the Progression From Chronic Hepatitis B to Hepatocellular Carcinoma.
ACS Appl Mater Interfaces
January 2025
Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310016, China.
Hepatocellular carcinoma (HCC) is a common malignancy and generally develops from liver cirrhosis (LC), which is primarily caused by the chronic hepatitis B (CHB) virus. Reliable liquid biopsy methods for HCC screening in high-risk populations are urgently needed. Here, we establish a porous silicon-assisted laser desorption ionization mass spectrometry (PSALDI-MS) technology to profile metabolite information hidden in human serum in a high throughput manner.
View Article and Find Full Text PDFSleep stages classification based on feature extraction from music of brain.
Heliyon
January 2025
School of Music, College of Fine Arts, University of Tehran, Tehran, Iran.
Sleep stages classification one of the essential factors concerning sleep disorder diagnoses, which can contribute to many functional disease treatments or prevent the primary cognitive risks in daily activities. In this study, A novel method of mapping EEG signals to music is proposed to classify sleep stages. A total of 4.
View Article and Find Full Text PDFHierarchical graph-based integration network for propaganda detection in textual news articles on social media.
Sci Rep
January 2025
EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, 11586, Riyadh, Saudi Arabia.
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda, serving as a vital source of self-reported symptoms related to Covid-19. Existing graph-based models, such as Graph Neural Networks (GNNs), have achieved notable success in Natural Language Processing (NLP). However, utilizing GNN-based models for propaganda detection remains challenging because of the challenges related to mining distinct word interactions and storing nonconsecutive and broad contextual data.
View Article and Find Full Text PDFAnalysis of Reddit Discussions on Motivational Factors for Physical Activity: Cross-Sectional Study.
J Med Internet Res
January 2025
Department of Health Promotion, School of Public Health, Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv, Israel.
Background: Despite the ample benefits of physical activity (PA), many individuals do not meet the minimum PA recommended by health organizations. Structured questionnaires and interviews are commonly used to study why individuals perform PA and their strategies to adhere to PA. However, certain biases are inherent to these tools that limit what can be concluded from their results.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!