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      Antipurinergic therapy corrects the autism-like features in the Fragile X (Fmr1 knockout) mouse model.

      Molecular Autism
      Antipurinergic therapy (APT), Autism spectrum disorders, Cell danger response (CDR), Environment, Fragile X syndrome, Genetics, Maternal immune activation (MIA), Metabolism, Metabolomics, Mitochondria, Purinergic signaling

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          Abstract

          This study was designed to test a new approach to drug treatment of autism spectrum disorders (ASDs) in the Fragile X (Fmr1) knockout mouse model.

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          Most cited references106

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          MetaboAnalyst 2.0—a comprehensive server for metabolomic data analysis

          First released in 2009, MetaboAnalyst (www.metaboanalyst.ca) was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms. In developing MetaboAnalyst 2.0 we have also substantially improved its graphical presentation tools. All images are now generated using anti-aliasing and are available over a range of resolutions, sizes and formats (PNG, TIFF, PDF, PostScript, or SVG). To improve its performance, MetaboAnalyst 2.0 is now hosted on a much more powerful server with substantially modified code to take advantage the server’s multi-core CPUs for computationally intensive tasks. MetaboAnalyst 2.0 also maintains a collection of 50 or more FAQs and more than a dozen tutorials compiled from user queries and requests. A downloadable version of MetaboAnalyst 2.0, along detailed instructions for local installation is now available as well.
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            Mouse behavioral tasks relevant to autism: phenotypes of 10 inbred strains.

            Three defining clinical symptoms of autism are aberrant reciprocal social interactions, deficits in social communication, and repetitive behaviors, including motor stereotypies and insistence on sameness. We developed a set of behavioral tasks designed to model components of these core symptoms in mice. Male mice from 10 inbred strains were characterized in assays for sociability, preference for social novelty, and reversal of the spatial location of the reinforcer in T-maze and Morris water maze tasks. Six strains, C57BL/6J, C57L/J, DBA/2J, FVB/NJ, C3H/HeJ, and AKR/J, showed significant levels of sociability, while A/J, BALB/cByJ, BTBR T(+)tf/J, and 129S1/SvImJ mice did not. C57BL/6J, C57L/J, DBA/2J, FVB/NJ, BALB/cByJ, and BTBR T(+)tf/J showed significant preference for social novelty, while C3H/HeJ, AKR/J, A/J, and 129S1/SvImJ did not. Normal scores on relevant control measures confirmed general health and physical abilities in all strains, ruling out artifactual explanations for social deficits. Elevated plus maze scores confirmed high anxiety-like behaviors in A/J, BALB/cByJ, and 129S1/SvImJ, which could underlie components of their low social approach. Strains that showed high levels of performance on acquisition of a T-maze task were also able to reach criterion for reversal learning. On the Morris water maze task, DBA/2J, AKR/J, BTBR T(+)tf/J, and 129S1/SvImJ failed to show significant quadrant preference during the reversal probe trial. These results highlight a dissociation between social task performance and reversal learning. BTBR T(+)tf/J is a particularly interesting strain, displaying both low social approach and resistance to change in routine on the water maze, consistent with an autism-like phenotype. Our multitask strategy for modeling symptoms of autism will be useful for investigating targeted and random gene mutations, QTLs, and microarray analyses.
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              Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2010.

              (2014)
              Autism spectrum disorder (ASD). 2010. The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system in the United States that provides estimates of the prevalence of ASD and other characteristics among children aged 8 years whose parents or guardians live in 11 ADDM sites in the United States. ADDM surveillance is conducted in two phases. The first phase consists of screening and abstracting comprehensive evaluations performed by professional providers in the community. Multiple data sources for these evaluations include general pediatric health clinics and specialized programs for children with developmental disabilities. In addition, most ADDM Network sites also review and abstract records of children receiving special education services in public schools. The second phase involves review of all abstracted evaluations by trained clinicians to determine ASD surveillance case status. A child meets the surveillance case definition for ASD if a comprehensive evaluation of that child completed by a qualified professional describes behaviors consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) diagnostic criteria for any of the following conditions: autistic disorder, pervasive developmental disorder-not otherwise specified (including atypical autism), or Asperger disorder. This report provides updated prevalence estimates for ASD from the 2010 surveillance year. In addition to prevalence estimates, characteristics of the population of children with ASD are described. For 2010, the overall prevalence of ASD among the ADDM sites was 14.7 per 1,000 (one in 68) children aged 8 years. Overall ASD prevalence estimates varied among sites from 5.7 to 21.9 per 1,000 children aged 8 years. ASD prevalence estimates also varied by sex and racial/ethnic group. Approximately one in 42 boys and one in 189 girls living in the ADDM Network communities were identified as having ASD. Non-Hispanic white children were approximately 30% more likely to be identified with ASD than non-Hispanic black children and were almost 50% more likely to be identified with ASD than Hispanic children. Among the seven sites with sufficient data on intellectual ability, 31% of children with ASD were classified as having IQ scores in the range of intellectual disability (IQ ≤70), 23% in the borderline range (IQ = 71-85), and 46% in the average or above average range of intellectual ability (IQ >85). The proportion of children classified in the range of intellectual disability differed by race/ethnicity. Approximately 48% of non-Hispanic black children with ASD were classified in the range of intellectual disability compared with 38% of Hispanic children and 25% of non-Hispanic white children. The median age of earliest known ASD diagnosis was 53 months and did not differ significantly by sex or race/ethnicity. These findings from CDC's ADDM Network, which are based on 2010 data reported from 11 sites, provide updated population-based estimates of the prevalence of ASD in multiple communities in the United States. Because the ADDM Network sites do not provide a representative sample of the entire United States, the combined prevalence estimates presented in this report cannot be generalized to all children aged 8 years in the United States population. Consistent with previous reports from the ADDM Network, findings from the 2010 surveillance year were marked by significant variations in ASD prevalence by geographic area, sex, race/ethnicity, and level of intellectual ability. The extent to which this variation might be attributable to diagnostic practices, underrecognition of ASD symptoms in some racial/ethnic groups, socioeconomic disparities in access to services, and regional differences in clinical or school-based practices that might influence the findings in this report is unclear. ADDM Network investigators will continue to monitor the prevalence of ASD in select communities, with a focus on exploring changes within these communities that might affect both the observed prevalence of ASD and population-based characteristics of children identified with ASD. Although ASD is sometimes diagnosed by 2 years of age, the median age of the first ASD diagnosis remains older than age 4 years in the ADDM Network communities. Recommendations from the ADDM Network include enhancing strategies to address the need for 1) standardized, widely adopted measures to document ASD severity and functional limitations associated with ASD diagnosis; 2) improved recognition and documentation of symptoms of ASD, particularly among both boys and girls, children without intellectual disability, and children in all racial/ethnic groups; and 3) decreasing the age when children receive their first evaluation for and a diagnosis of ASD and are enrolled in community-based support systems.
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