The influence of family history and genetics on the risk for the development of abuse or dependence is a major theme in alcoholism research. Recent research have used endophenotypes and behavioral paradigms to help detect further genetic contributions to this disease. Electronic tasks, essentially video games, which provide alcohol as a reward in controlled environments and with specified exposures have been developed to explore some of the behavioral and subjective characteristics of individuals with or at risk for alcohol substance use disorders. A generative model (containing parameters with unknown values) of a simple game involving a progressive work paradigm is described along with the associated point process signal processing that allows system identification of the model. The system is demonstrated on human subject data. The same human subject completing the task under different circumstances, e.g., with larger and smaller alcohol reward values, is assigned different parameter values. Potential meanings of the different parameter values are described.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1109/IEMBS.2011.6090741 | DOI Listing |
Front Plant Sci
January 2025
Heilongjiang Green Food Science Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, China.
Brassinosteroids (BRs) are key phytohormones influencing soybean development, yet their role in symbiosis remains unclear. Here, the RNA-Seq was used to identify important gene associated with BRs and symbiotic nitrogen fixation, and the function of candidate gene was verified by transgenic hairy roots. The result shows that the RNA-Seq analysis was conducted in which BR signaling was found to suppress nodule formation and many DEGs enriched in immunity-related pathways.
View Article and Find Full Text PDFFront Plant Sci
January 2025
Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China.
Introduction: (Hook.f. & Thomson) H.
View Article and Find Full Text PDFNanoscale Adv
January 2025
School of Chemical Engineering, Yeungnam University 280 Daehak-Ro Gyeongsan 38541 Republic of Korea
Two-dimensional (2D) hybrid materials, particularly those based on boron nitride (BN) and graphene oxide (GO), have attracted significant attention for energy applications owing to their distinct structural and electronic properties. BN/GO composites uniquely combine the mechanical strength, thermal stability and electrical insulation of BN with the high conductivity and flexibility of GO, creating advanced materials ideal for the fabrication of batteries, supercapacitors and fuel cells. These hybrids offer synergistic effects, enhanced charge transport, increased surface area, and improved chemical stability, making them promising candidates for high-performance energy systems.
View Article and Find Full Text PDFBMJ Oncol
October 2023
Clinical Genetics, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Objective: In England, through the Genomic Medicine Service Alliances (GMSAs), a national transformation project aims to embed robust pathways to deliver universal Lynch syndrome (LS) testing for patients with colorectal and endometrial cancers. Prior to commencement of the project, there was evidence of variation and low testing levels in eligible patients which is consistent with other health systems; however, we believe this is amenable to systematic improvement with responsibility for testing delivery by local cancer teams supported by regional infrastructure.
Methods And Analysis: A project team and national oversight group was formed in May 2021 with membership including 21×cancer alliances, 7×GMSAs, charities and other stakeholders who agreed key performance indicators.
JACC Asia
January 2025
Department of Frontier Cardiovascular Science, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Background: Heart failure should be diagnosed as early as possible. Although deep learning models can predict one or more echocardiographic findings from electrocardiograms (ECGs), such analyses are not comprehensive.
Objectives: This study aimed to develop a deep learning model for comprehensive prediction of echocardiographic findings from ECGs.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!