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Patterns and trends in burden of asthma and its attributable risk factors from 1990 to 2021 among south Asian countries: a systematic analysis for the Global Burden of Disease Study 2021.
J Asthma
January 2025
Center for Global Health Research, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
Objective: Asthma poses a significant health burden in South Asia, with increasing incidence and mortality despite a global decline in age-standardized prevalence rates. This study aims to analyze asthma trends from 1990 to 2021, focusing on prevalence, incidence, mortality, and disability-adjusted life years (DALYs) across South Asia. The study also assesses the impact of risk factors like high body mass index (BMI), smoking, and occupational exposures on asthma outcomes.
View Article and Find Full Text PDFCursorial ecomorphology and temporal patterns in theropod dinosaur evolution during the mid-Cretaceous.
R Soc Open Sci
January 2025
Hokkaido University Museum, Kita 10, Nishi 8, Kita-ku, Sapporo, Hokkaido 060-0810, Japan.
Coelurosauria, including modern birds, represents a successful group of theropod dinosaurs that established a high taxonomic diversity and significant morphological modifications. In the evolutionary history of this group, a specialized foot morphology, the arctometatarsus, evolved independently in several lineages and has been considered an adaptation for cursoriality. While its functional significance has been extensively studied, the temporal pattern of this parallel evolution, as well as its origin and influencing factors, remains largely unresolved.
View Article and Find Full Text PDFResting-state fMRI activation is associated with parent-reported phenotypic features of autism in early adolescence.
Front Child Adolesc Psychiatry
November 2024
Department of Psychology, Palo Alto University, Palo Alto, CA, United States.
Introduction: Autism Spectrum Disorder (ASD) is characterized by deficits in social cognition, self-referential processing, and restricted repetitive behaviors. Despite the established clinical symptoms and neurofunctional alterations in ASD, definitive biomarkers for ASD features during neurodevelopment remain unknown. In this study, we aimed to explore if activation in brain regions of the default mode network (DMN), specifically the medial prefrontal cortex (MPC), posterior cingulate cortex (PCC), superior temporal sulcus (STS), inferior frontal gyrus (IFG), angular gyrus (AG), and the temporoparietal junction (TPJ), during resting-state functional magnetic resonance imaging (rs-fMRI) is associated with possible phenotypic features of autism (PPFA) in a large, diverse youth cohort.
View Article and Find Full Text PDFConvergent-beam attosecond x-ray crystallography.
Struct Dyn
January 2025
Center for Free-Electron Laser Science CFEL, Deutsches Elektronen-Synchrotron DESY, Notkestr. 85, 22607 Hamburg, Germany.
Sub-ångström spatial resolution of electron density coupled with sub-femtosecond to few-femtosecond temporal resolution is required to directly observe the dynamics of the electronic structure of a molecule after photoinitiation or some other ultrafast perturbation, such as by soft X-rays. Meeting this challenge, pushing the field of quantum crystallography to attosecond timescales, would bring insights into how the electronic and nuclear degrees of freedom couple, enable the study of quantum coherences involved in molecular dynamics, and ultimately enable these dynamics to be controlled. Here, we propose to reach this realm by employing convergent-beam x-ray crystallography with high-power attosecond pulses from a hard-x-ray free-electron laser.
View Article and Find Full Text PDFSTDCformer: Spatial-temporal dual-path cross-attention model for fMRI-based autism spectrum disorder identification.
Heliyon
July 2024
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China.
Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive neuroimaging technique widely utilized in the research of Autism Spectrum Disorder (ASD), providing preliminary insights into the potential biological mechanisms underlying ASD. Deep learning techniques have demonstrated significant potential in the analysis of rs-fMRI. However, accurately distinguishing between healthy control group and ASD has been a longstanding challenge.
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