Background: Children with autism spectrum disorder (ASD) and intellectual disability (ID) are an understudied population whose school inclusion is challenging.
Methods: We assessed the effects of "Developmental and Sequenced one-to-one Educational Intervention" (DS1-EI), a ten-hour-per-week adapted instruction programme for five- to nine-year-old children with ASD and ID treated in outpatient health care institutions. A single-blind multisite randomized controlled trial was conducted to compare DS1-EI given for three years with treatment as usual (TAU)(trial registration numbers: ANSM130282B-31 (April 16, 2013) and ACTRN12616000592448). The primary outcome was the change in the psycho-educational profile (PEP). Secondary variables included the Childhood Autism Rating Scale (CARS), Autism Diagnostic Interview-Revised (ADI-R), Vineland Adaptive Behaviour Scale-II (VABS-II), Children's Global Assessment Scale (CGAS) and annual assessment of educational achievement. Statistical analyses used linear mixed models.
Findings: Seventy-two participants with severe ASD and ID were recruited. Intention-to-treat and per-protocol analyses showed no significant group*time interaction for the PEP, CARS, ADI-R, VABS-II and CGAS but a significant effect for educational achievement with a better improvement in the DS1-EI group. At the 36-month time point, more DS1-EI children were included in mainstream classrooms. Additional analyses using multivariate models taking into account moderating variables at the baseline (e.g., Developmental Quotient) confirmed that DS1-EI had a significant effect on educational outcomes.
Interpretation: DS1-EI did not improve communication or social skills in children with ASD and ID compared with TAU. However, DS1-EI enhanced school skills in four domains (language, mathematics, inter modality, and school autonomy) favouring inclusion in mainstream classrooms more than TAU. Providing such adapted instruction is feasible and should be encouraged.
Funding: CNSA; Fondation Bettencourt-Schueller; Fondation EDF.
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http://dx.doi.org/10.1016/j.eclinm.2020.100537 | DOI Listing |
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Information Science and Technology College, Dalian Maritime University, No.1 Linghai Road, 116026, Dalian, Liaoning, China.
Identifying biologically significant protein complexes from protein-protein interaction (PPI) networks and understanding their roles are essential for elucidating protein functions, life processes, and disease mechanisms. Current methods typically rely on static PPI networks and model PPI data as pairwise relationships, which presents several limitations. Firstly, static PPI networks do not adequately represent the scopes and temporal dynamics of protein interactions.
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January 2025
Department of Pharmacology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany.
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Department of Orthopedic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin 150081, China.
Background: The enhancer-promoter interaction (EPI) is a critical component of gene regulatory networks, playing a significant role in understanding the complexity of gene expression. Traditional EPI prediction methods focus on one-to-one interactions, neglecting more complex one-to-many and many-to-many patterns. To address this gap, we utilize graph neural networks to comprehensively explore all interaction patterns between enhancers and promoters, capturing complex regulatory relationships for more accurate predictions.
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December 2024
Department of Bioscience and Bioinformatics, Myongji University, Yongin, 17058, Korea.
Abeliophyllum distichum and Forsythia ovata are closely related species endemic to Korea and are highly valued as ornamental shrubs in the Oleaceae family. A combination of PacBio and Illumina sequencing with Hi-C scaffolding technologies was employed to develop chromosome-level genome assemblies of these species. The assembled genome sizes are 795.
View Article and Find Full Text PDFComput Biol Med
February 2025
Department of Chemical Engineering, IIT Delhi, India; Yardi School of Artificial Intelligence, IIT Delhi, India. Electronic address:
Unified translation of medical images from one-to-many distinct modalities is desirable in healthcare settings. A ubiquitous approach for bilateral medical scan translation is one-to-one mapping with GANs. However, its efficacy in encapsulating diversity in a pool of medical scans and performing one-to-many translation is questionable.
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