This chapter presents a general approach for the application of spatial intensity distribution analysis (SpIDA) to pharmacodynamic quantification of receptor tyrosine kinase homodimerization in response to direct ligand activation or transactivation by G protein-coupled receptors. A custom graphical user interface developed for MATLAB is used to extract quantal brightness and receptor density information from intensity histograms calculated from single fluorescence microscopy images. This approach allows measurement of monomer/oligomer protein mixtures within subcellular compartments using conventional confocal laser scanning microscopy. Application of quantitative pharmacological analysis to data obtained using SpIDA provides a universal method for comparing studies between cell lines and receptor systems. In addition, because of its compatibility with conventional immunostaining approaches, SpIDA is suitable not only for use in recombinant systems but also for the characterization of mechanisms involving endogenous proteins. Therefore, SpIDA enables these biological processes to be monitored directly in their native cellular environment.
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Sci Rep
January 2025
College of Geographic Science and Tourism, Xinjiang Normal University, Urumqi, 830054, China.
Central Asia is an ecologically fragile arid zone and a typical mixed salt‒sand region. The socioeconomic and ecological problems attributed to the shrinking of the Aral Sea in Central Asia are notable concerns within the international community. In this study, the characteristics of salt dust aerosols from the Aral Sea were analysed to explore their interannual variation characteristics and analyse the spatial and temporal distributions of salt dust sources and transport and dispersion pathways.
View Article and Find Full Text PDFComput Biol Med
January 2025
University of Rwanda, Rwanda. Electronic address:
Deep learning methods have significantly improved medical image analysis, particularly in detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some drawbacks, such as limited interpretability, extensive computational resources, and the need for extensive datasets. To tackle these issues, we introduced two novel algorithms: the Dynamic Co-Occurrence Grey Level Matrix (DC-GLM) and the Contextual Adaptation Multiscale Gabor Network (CAMSGNeT).
View Article and Find Full Text PDFJ Hazard Mater
January 2025
Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, PR China; Institute of Eco-Chongming (IEC), 20 Cuiniao Road, Chenjia Town, Chongming District, Shanghai 202162, PR China. Electronic address:
As one of the significant air pollutants, nitrogen oxides (NO = NO + NO) not only pose a great threat to human health, but also contribute to the formation of secondary pollutants such as ozone and nitrate particles. Due to substantial uncertainties in bottom-up emission inventories, simulated concentrations of air pollutants using GEOS-Chem model often largely biased from those of ground-level observations. To address this issue, we developed a new deep learning model to simulate the inverse process of the GEOS-Chem model.
View Article and Find Full Text PDFOpen Res Eur
October 2024
Univ. Lille, Univ. Artois, Univ. Littoral Côte d'Opale, ULR 7369 - URePSSS - Unité de Recherche Pluridisciplinaire Sport Santé Société, F-59000 Lille, France, University of Lille, Lille, Hauts-de-France, France.
Background: France (FR) and New Caledonia (NC) are both French territories, one in Western Europe, the other as part of the Pacific Island Countries and Territories (PICTs). Despite schooling in similar educational systems, FR and NC adolescents develop distinct relationships with physical activity, which is influenced by the geographical-cultural and symbolic structures of their respective societies. This study explored the distribution of physical activity according to geographical culture and opportunity-temporal dimensions.
View Article and Find Full Text PDFMed Phys
January 2025
Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.
Background: With increasing evidence supporting three-dimensional (3D) automated breast (AB) ultrasound (US) for supplemental screening of breast cancer in increased-risk populations, including those with dense breasts and in limited-resource settings, there is an interest in developing more robust, cost-effective, and high-resolution 3DUS imaging techniques. Compared with specialized ABUS systems, our previously developed point-of-care 3D ABUS system addresses these needs and is compatible with any conventional US transducer, which offers a cost-effective solution and improved availability in clinical practice. While conventional US transducers have high in-plane resolution (axial and lateral), their out-of-plane resolution is constrained by the poor intrinsic elevational US resolution.
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