Abnormal Association Between Neural Activity and Genetic Expressions of Impulsivity in Attention-Deficit/Hyperactivity Disorder: An Adolescent Brain Cognitive Development Study.

Background: Impulsivity in highly heritable attention-deficit/hyperactivity disorder (ADHD) has been studied using neural activity via functional magnetic resonance imaging (fMRI) or genetic data, but rarely with multivariate methods that link both. We investigated coupled neural activity and gene expression signatures, using parallel independent component analysis (pICA) and ABCD (Adolescent Brain Cognitive Development) Study data.

Methods: Children with ADHD (n = 394; 63% male) and healthy control children (n = 1000; 47% male) of European ancestry were included.

Transfer Learning of Deep Neural Networks Pretrained Using the ABCD Dataset for General Psychopathology Prediction in Korean Adolescents.

Background: In this study, we examined whether a deep neural network (DNN), trained to predict the general psychopathology factor (p factor) using functional magnetic resonance imaging (fMRI) data from adolescents in the ABCD (Adolescent Brain Cognitive Development) Study, would generalize to Korean adolescents.

Methods: We trained a scanner-generalization neural network (SGNN) to predict p factor scores from resting-state functional connectivity (RSFC) data of 6905 ABCD Study adolescents, controlling for MRI scanner-related confounds. Then, we transferred the pretrained SGNN to a DNN to predict p factor scores for 125 adolescents, including healthy individuals and individuals with major depressive disorder, using data from Seoul National University Hospital (SNUH).

Harmonic field extension for QSM with reduced spatial coverage using physics-informed generative adversarial network.

Quantitative susceptibility mapping (QSM) is frequently employed in investigating brain iron related to brain development and diseases within deep gray matter (DGM). Nonetheless, the acquisition of whole-brain QSM data is time-intensive. An alternative approach, focusing the QSM specifically on areas of interest such as the DGM by reducing the field-of-view (FOV), can significantly decrease scan times.

Comparing variants related to chronic diseases from genome-wide association study (GWAS) and the cancer genome atlas (TCGA).

Background: Several genome-wide association studies (GWAS) have been performed to identify variants related to chronic diseases. Somatic variants in cancer tissues are associated with cancer development and prognosis. Expression quantitative trait loci (eQTL) and methylation QTL (mQTL) analyses were performed on chronic disease-related variants in TCGA dataset.

The role of empathy and psychological need satisfaction in pharmacy students' burnout and well-being.

Background: The purpose of this study was to examine the relationship between Korean pharmacy students' empathy and psychological need satisfaction and their levels of burnout and psychological well-being, using structural equation modeling.

Methods: The participants were 452 pharmacy students from five South Korean universities. The Jefferson Scale of Empathy (Health Professions Students version), the Activity-Feeling States Scale, and the Maslach Burnout Inventory-Student Survey were used to assess empathy, psychological need satisfaction, and burnout, respectively.

Assessment of Korean Pharmacy Students' Empathy Using the Jefferson Scale of Empathy.

Objective: To validate the Korean-translated Jefferson Scale of Empathy-Health Professions Student version (JSE-HPS) and to investigate the empathy levels of pharmacy students in South Korea.

Methods: The JSE-HPS and the Interpersonal Reactivity Index (IRI) were administered to 452 pharmacy students in their second and third years at 5 Korean universities. Confirmatory factor analysis (CFA), correlations, and one-way ANOVAs were conducted for data analyses.