Recovery in K(+) channels, that is, the transition from the inactivated nonconductive selectivity filter conformation toward the conductive conformation, occurs on a time scale of the order of seconds, which is astonishingly long, given that the structural differences among the filter conformations are faint (<1 Å). Computational studies and electrophysiological measurements suggested that buried water molecules bound behind the selectivity filter are at the origin of the slowness of recovery in K(+) channels. Using a combination of solid-state NMR spectroscopy (ssNMR) and long molecular dynamics simulations, we sketch a high-resolution map of the spatial and temporal distribution of water behind the selectivity filter of a membrane-embedded K(+) channel in two different gating modes. Our study demonstrates that buried water molecules with long residence times are spread all along the rear of the inactivated filter, which explains the recovery kinetics. In contrast, the same region of the structure appears to be dewetted when the selectivity filter is in the conductive state. Using proton-detected ssNMR on fully protonated channels, we demonstrate the presence of a pathway that allows for the interchange of buried and bulk water, as required for a functional influence of buried water on recovery and slow inactivation. Furthermore, we provide direct experimental evidence for the presence of additional ordered water molecules that surround the filter and that are modulated by the channel's gating mode.
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http://dx.doi.org/10.1021/ja411450y | DOI Listing |
Sci Total Environ
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Yunnan Key Laboratory of Internal Combustion Engine, Kunming University of Science and Technology, Kunming 650500, China.
Ammonia is a highly promising carbon-neutral fuel. The use of ammonia as a fuel for internal combustion engines can reduce fossil energy consumption and greenhouse gas emissions. However, the high ignition energy required for ammonia and the slow flame propagation rate result in low combustion efficiency when ammonia is used directly in internal combustion engines.
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Endocrine and Metabolic Unit, Nutrition, Metabolism and Cardiovascular Research Centre, Institute for Medical Research, National Institutes of Health, Ministry of Health Malaysia, Selangor, Malaysia.
Background: Obesity presents a growing challenge to public health, and its intricate association with genetics continues to be a compelling field of study. In countries such as Malaysia, where diverse genetic backgrounds converge, exploring the molecular genetics of obesity is even more imperative.
Objective: This scoping review aimed to explore the literature on molecular genetics of obesity in Malaysia.
J Environ Manage
January 2025
College of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, 1 Zhanlanguan Road, Beijing, 100044, China. Electronic address:
Global climate change has significantly increased the frequency and intensity of extreme precipitation events, thereby heightening flood risks for mountainous settlements. However, due to geographical and socio-economic constraints in these regions, flood-related sample data are generally scarce. This study introduces a Mean Filter (MF) grounded in the point-area duality perspective, combined with a feature selection approach utilizing multi-objective optimization algorithms.
View Article and Find Full Text PDFPLoS One
January 2025
LIB, Université de Bourgogne, Franche-Comté, Dijon, France.
The backbone extraction process is pivotal in expediting analysis and enhancing visualization in network applications. This study systematically compares seven influential statistical hypothesis-testing backbone edge filtering methods (Disparity Filter (DF), Polya Urn Filter (PF), Marginal Likelihood Filter (MLF), Noise Corrected (NC), Enhanced Configuration Model Filter (ECM), Global Statistical Significance Filter (GloSS), and Locally Adaptive Network Sparsification Filter (LANS)) across diverse networks. A similarity analysis reveals that backbones extracted with the ECM and DF filters exhibit minimal overlap with backbones derived from their alternatives.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Computer Science, National Textile University, Faisalabad, Pakistan.
Accurate diagnosis of pancreatic cancer using CT scan images is critical for early detection and treatment, potentially saving numerous lives globally. Manual identification of pancreatic tumors by radiologists is challenging and time-consuming due to the complex nature of CT scan images and variations in tumor shape, size, and location of the pancreatic tumor also make it challenging to detect and classify different types of tumors. Thus, to address this challenge we proposed a four-stage framework of computer-aided diagnosis systems.
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