98%
921
2 minutes
20
Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disorders with heterogeneous symptomatology. Arguably, the most pervasive shortfall of ASD are the deficits in sociability and the animal models of the disorder are expected to exhibit such impairments. The most widely utilized behavioral task for assessing sociability in rodents is the Three-Chamber Social Interaction Test (SIT). However, SIT has been yielding inconsistent results in social interaction behavior across different rodent models of ASD, which could be pointing to the suboptimal methodology of the task. Here, we compared social behavior assessed in SIT and in another prominent sociability behavioral assay, Reciprocal Interaction Test (RCI), in a SH3 and multiple ankyrin repeated domains 3 (SHANK3) mouse model of ASD. Head-to-head comparison showed no association (p = 0.15, 0.25, 0.43) and a fixed bias (p = 0.01, < 0.001, < 0.001) in sociability assessment between the behavioral assays in both wild-type (WT) controls and Shank3B mice. Adult Shank3B mice of both sexes displayed normative sociability in SIT when compared to the WT controls (p = 0.74) but exhibited less than half of social interaction (p < 0.001) and almost three times more social disinterest (p < 0.001) when compared to WT mice in RCI. At least in the Shank3B mouse model of ASD, we presume RCI could be a preferable way of assessing social interaction compared to SIT. Considering the variability of animal models of ASD and the wide palette of tools available for the assessment of their behavior, a consensus approach would be needed for observational and interventional analyses.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11439274 | PMC |
http://dx.doi.org/10.1186/s12993-024-00251-0 | DOI Listing |
JMIR Hum Factors
September 2025
Seidenberg School of Computer Science and Information Systems, Pace University, New York City, NY, United States.
Background: As information and communication technologies and artificial intelligence (AI) become deeply integrated into daily life, the focus on users' digital well-being has grown across academic and industrial fields. However, fragmented perspectives and approaches to digital well-being in AI-powered systems hinder a holistic understanding, leaving researchers and practitioners struggling to design truly human-centered AI systems.
Objective: This paper aims to address the fragmentation by synthesizing diverse perspectives and approaches to digital well-being through a systematic literature review.
JAMA Dermatol
September 2025
Department of Population Health, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.
Importance: Increasingly, strategies to systematically detect melanomas invoke targeted approaches, whereby those at highest risk are prioritized for skin screening. Many tools exist to predict future melanoma risk, but most have limited accuracy and are potentially biased.
Objectives: To develop an improved melanoma risk prediction tool for invasive melanoma.
Int Urogynecol J
September 2025
Department of Public Health Sciences, University of Connecticut School of Medicine, Farmington, CT, USA.
Introduction And Hypothesis: Depressive and anxiety symptoms are known risk factors for lower urinary tract symptoms (LUTS). To inform prevention and treatment strategies, this research examined whether greater emotional support seeking weakened associations of affective symptoms with LUTS and poorer bladder health.
Methods: Data were collected from women in the USA who participated in the RISE FOR HEALTH study of bladder health.
Qual Life Res
September 2025
Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 West Wenhua Road, Jinan, 250012, Shandong, China.
Purpose: The study aimed to assess the interconnection of quality of life (QoL) variables and identify key areas for which interventions could improve QoL among men who have sex with men (MSM) living with HIV on antiretroviral therapy (ART).
Methods: A cross-sectional study was conducted in Jinan of Shandong Province, between October to December 2020. Undirected network analyses were conducted to examine and visualize the interconnections between QoL variables among MSM living with HIV.
Psychopharmacology (Berl)
September 2025
Institute of Cardiovascular Research, Sleep Medical Center, Department of Psychiatry, Fundamental and Clinical Research on Mental Disorders Key Laboratory of Luzhou, Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province, 646000, China.
Rationale: Genome-wide association studies (GWASs) are used to identify genetic variants for association with schizophrenia (SCZ) risk; however, each GWAS can only reveal a small fraction of this association.
Objectives: This study systematically analyzed multiple GWAS data sets to identify gene subnetwork and pathways associated with SCZ.
Methods: We identified gene subnetwork using dmGWAS program by combining SCZ GWASs and a human interaction network, performed gene-set analysis to test the association of gene subnetwork with clinical symptom scores and disease state, meanwhile, conducted spatiotemporal and tissue-specific expression patterns and cell-type-specific analysis of genes in the subnetwork.