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An important aim in psychiatry is to establish valid and reliable associations linking profiles of brain functioning to clinically relevant symptoms and behaviors across patient populations. To advance progress in this area, we introduce an open dataset containing behavioral and neuroimaging data from 241 individuals aged 18 to 70, comprising 148 individuals meeting diagnostic criteria for a broad range of psychiatric illnesses and a healthy comparison group of 93 individuals. These data include high-resolution anatomical scans, multiple resting-state, and task-based functional MRI runs. Additionally, participants completed over 50 psychological and cognitive assessments. Here, we detail available behavioral data as well as raw and processed MRI derivatives. Associations between data processing and quality metrics, such as head motion, are reported. Processed data exhibit classic task activation effects and canonical functional network organization. Overall, we provide a comprehensive and analysis-ready transdiagnostic dataset to accelerate the identification of illness-relevant features of brain functioning, enabling future discoveries in basic and clinical neuroscience.
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http://dx.doi.org/10.1038/s41597-025-04895-z | DOI Listing |
JMIR Res Protoc
September 2025
Academy for Health Innovation Uganda, Infectious Diseases Institute, Makerere University, Kampala, Uganda.
Background: Sexually transmitted infections are a significant public health concern, particularly in sub-Saharan Africa, where their prevalence remains high. Promoting awareness and reducing stigma are essential strategies for addressing this challenge, but those affected often have limited access to accurate and culturally appropriate health information. Therefore, innovative solutions are essential to enhance sexual health literacy and encourage informed health-seeking behaviors.
View Article and Find Full Text PDFJAMA Netw Open
September 2025
School of Medicine and Public Health, University of Wisconsin-Madison, Madison.
Importance: It is unclear whether the duration of amyloid-β (Aβ) pathology is associated with neurodegeneration and whether this depends on the presence of tau.
Objective: To examine the association of longitudinal atrophy with Aβ positron emission tomography (PET)-positivity (Aβ+) and the estimated duration of Aβ+ (Aβ+ duration), controlling for tau-positivity.
Design, Setting, And Participants: Data for this longitudinal cohort study were drawn from the Wisconsin Registry for Alzheimer Prevention and the Wisconsin Alzheimer Disease Research Center Clinical Core Study.
Brief Bioinform
August 2025
School of Computer Science, Xi'an Polytechnic University, 710048, Xi'an, China.
Cancer, with its inherent heterogeneity, is commonly categorized into distinct subtypes based on unique traits, cellular origins, and molecular markers specific to each type. However, current studies primarily rely on complete multi-omics datasets for predicting cancer subtypes, often overlooking predictive performance in cases where some omics data may be missing and neglecting implicit relationships across multiple layers of omics data integration. This paper introduces Multi-Layer Matrix Factorization (MLMF), a novel approach for cancer subtyping that employs multi-omics data clustering.
View Article and Find Full Text PDFCureus
August 2025
Obstetrics and Gynecology, Lucina Analytics, Boca Raton, USA.
Objective Severe maternal morbidity (SMM) poses a public health dilemma. To ensure continuity of care for 12 months postpartum, the American Rescue Plan Act of 2021 permitted states to extend Medicaid postpartum coverage to 12 months. This study describes the experiences of a major national insurer in the United States.
View Article and Find Full Text PDFJMIR Ment Health
September 2025
Department of Psychology, University of California, Los Angeles, 1285 Franz Hall, Box 951563, Los Angeles, CA, 90095, United States, 1 3107941262.
Background: Youth mental health issues have been recognized as a pressing crisis in the United States in recent years. Effective, evidence-based mental health research and interventions require access to integrated datasets that consolidate diverse and fragmented data sources. However, researchers face challenges due to the lack of centralized, publicly available datasets, limiting the potential for comprehensive analysis and data-driven decision-making.
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