To investigate the effectiveness of a Treatment and Education of Autistic and Related Communication Handicapped Children (TEACCH) intervention in schools for improving independent task performance in children with autism spectrum disorders (ASD).
We screened relevant studies published up to December 2022 from Web of science, ERIC, PsycINFO and other databases using predefined inclusion/exclusion criteria to identify suitable intervention studies for meta-analysis. Tau-U effect sizes were calculated for each A-B comparison extracted from the included experiments. Moderated analyses were conducted to examine the type of intervention (independent variable), intervention target behaviours (dependent variable), participant characteristics, setting characteristics and intervener characteristics.
A total of 14 studies (38 participants) met the criteria and were included in the meta-analysis. The analysis results showed that TEACCH had a significant intervention effect, and the overall intervention effect size was Tau-U = 0.85[0.77, 0.91]. There were significant differences in the intervention target behaviour variables (p < 0.01), limited variation in the intervention type variables, but no differences in participant characteristics, setting characteristics and intervenor characteristics.
The use of TEACCH is effective in improving independent task completion in children with ASD and provides evidence-based recommendations for its extended use in schools.

Based on the mind-blindness hypothesis, a large number of studies have shown that individuals with autism-spectrum disorder (ASD) and autistic traits have empathy deficits. However, the recent double empathy theory contradicts the mind-blindness hypothesis and suggests that individuals with ASD and autistic traits do not necessarily lack empathy. Thus, the presence of empathy deficits in individuals with ASD and autistic traits is still controversial. We recruited 56 adolescents (28 high autistic traits, 28 low autistic traits, 14-17 years old) in this study to explore the relationship between empathy and autistic traits. The study participants were required to undertake the pain empathy task, during which the electroencephalograph (EEG) activities were recorded. Our results show that empathy was negatively associated with autistic traits at the questionnaire, behavioral, and EEG levels. Our results also suggested that empathy deficits in adolescents with autistic traits may be manifested mainly in the late stages of cognitive control processing.

This study investigated heterogeneity in language skills of children with autism and their relationship with different autistic social subtypes. Data from 90 autistic and 30 typically developing children were analyzed. Results showed that autistic social subtypes varied in language skill problems (aloof > passive > active-but-odd). There was a negative association between aloof dimension scores and language performance but positive for the active-but-odd dimension and no association in the passive one. Moreover, aloof dimension score was the main contributor to language performance. A receiver operating characteristic analysis suggested language vocabulary as an additional component in differentiating autistic social subtypes. These findings demonstrate that variations in language skills in autistic children provide additional information for discriminating their social subtype.

Autistic spectrum disorder (ASD) is one of the most complex groups of neurobehavioral and developmental conditions. The reason is the presence of three different impaired domains, such as social interaction, communication, and restricted repetitive behaviors. Some children with ASD may not be able to communicate using language or speech. Many experts propose that continued therapy in the form of software training in this area might help to bring improvement. In this work, we propose a design of software speech therapy system for ASD. We combined different devices, technologies, and features with techniques of home rehabilitation. We used TensorFlow for Image Classification, ArKit for Text-to-Speech, Cloud Database, Binary Search, Natural Language Processing, Dataset of Sentences, and Dataset of Images with two different Operating Systems designed for Smart Mobile devices in daily life. This software is a combination of different Deep Learning Technologies and makes Human-Computer Interaction Therapy very easy to conduct. In addition, we explain the way these were connected and put to work together. Additionally, we explain in detail the architecture of software and how each component works together as an integrated Therapy System. Finally, it allows the patient with ASD to perform the therapy anytime and everywhere, as well as transmitting information to a medical specialist.

Despite abundant research and clinical evidence of the effectiveness of music interventions for people in the autism spectrum, understanding of music processing in this community is limited. We explored whether research evidence of differences in music processing within the autistic community is available. We developed a scoping review to search for literature with the terms \"music\", \"processing,\" and \"autism\" (and variants). We searched PubMed, CINAHL, Scopus, Web of Science, PsycInfo, Academic Search Complete, ERIC, and Music Index databases for a total of 10,857 articles, with 5,236 duplicates. The remaining 5,621 titles and abstracts were screened for eligibility by a team of four undergraduate and graduate students and the PI. Seventy-five studies were included for data extraction. Data were analyzed with descriptive statistics regarding author, study, stimulus, and participant information, and a thematic analysis of outcome and findings. Our findings are preliminary given the emerging nature of the literature, the use of mostly non-musical auditory stimuli, passive listening experiences, and underreported demographics. However, the literature shows some evidence of differences in music processing for autistic individuals, including reduced habituation to non-musical and musical stimuli; truncated, delayed, or divergent developmental trajectories; and possible compensatory higher-order mechanisms that yield similar behavioral responses even in the presence of divergent neural correlates. Music therapists are encouraged to adopt a developmental perspective, not only of general skills, but specifically of music skill development in this community, and to extrapolate these findings with caution, given the current limitations in the evidence.

The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) controversially combined previously distinct subcategories of autism spectrum disorder (ASD) into a single diagnostic category. However, genetic convergences and divergences between different ASD subcategories are unclear. By retrieving 1725 exonic de novo mutations (DNMs) from 1628 subjects with autistic disorder (AD), 1873 from 1564 subjects with pervasive developmental disorder not otherwise specified (PDD-NOS), 276 from 247 subjects with Asperger\'s syndrome (AS), and 2077 from 2299 controls, we found that rates of putative functional DNMs (loss-of-function, predicted deleterious missense, and frameshift) in all three subcategories were significantly higher than those in control. We then investigated the convergences and divergences of the three ASD subcategories based on four genetic aspects: whether any two ASD subcategories (1) shared significantly more genes with functional DNMs, (2) exhibited similar spatio-temporal expression patterns, (3) shared significantly more candidate genes, and (4) shared some ASD-associated functional pathways. It is revealed that AD and PDD-NOS were broadly convergent in terms of all four genetic aspects, suggesting these two ASD subcategories may be genetically combined. AS was divergent to AD and PDD-NOS for aspects of functional DNMs and expression patterns, whereas AS and AD/PDD-NOS were convergent for aspects of candidate genes and functional pathways. Our results indicated that the three ASD subcategories present more genetic convergences than divergences, favouring DSM-5\'s new classification. This study suggests that specifically defined genotypes and their corresponding phenotypes should be integrated analyzed for precise diagnosis of complex disorders, such as ASD.

The purpose of this study was to investigate the effects of structured physical activity program on social interaction and communication of children with autism spectrum disorder (ASD). Fifty children with ASD from a special school were randomly divided into experimental and control groups. 25 children with ASD were placed in the experimental group, and the other 25 children as the control group participated in regular physical activity. A total of forty-one participants completed the study. A 12-week structured physical activity program was implemented with a total of 24 exercise sessions targeting social interaction and communication of children with ASD, and a quasi-experimental design was used for this study. Data were collected using quantitative and qualitative instruments. SSIS and ABLLS-R results showed that an overall improvement in social skills and social interaction for the experimental group across interim and posttests, F = 8.425, p = 0.001 (p < 0.005), and significant improvements appeared in communication, cooperation, social interaction, and self-control subdomains (p < 0.005). Conversely, no statistically significant differences were found in the control group (p > 0.005). The study concluded that the special structured physical activity program positively influenced social interaction and communication skills of children with ASD, especially in social skills, communication, prompt response, and frequency of expression.

Accumulating evidence suggests that brain-derived neurotrophic factor (BDNF) may be implicated in the developmental outcomes of children with autism spectrum disorder (ASD).
To use meta-analysis to determine whether children with ASD have altered peripheral blood levels of BDNF.
A systematic search of PubMed, PsycINFO, and Web of Science was performed for English-language literature through February 7, 2016. The search terms included brain-derived neurotrophic factor or BDNF in combination with autism, without year restriction. Two additional records were retrieved after a review of the reference lists of selected articles.
Studies were included if they provided data on peripheral blood levels of BDNF in children with ASD and healthy control children. Studies that included adults or with overlapping samples were excluded.
Data were extracted by 2 independent observers from 19 included studies. Data were pooled using a random-effects model with Comprehensive Meta-analysis software.
Blood levels of BDNF in children with ASD compared with healthy controls. Altered levels of BDNF were hypothesized to be related to ASD.
This meta-analysis included 19 studies with 2896 unique participants. Random-effects meta-analysis of all 19 studies showed that children with ASD had significantly increased peripheral blood levels of BDNF compared with healthy controls (Hedges g, 0.490; 95% CI, 0.185-0.794; P = .002). Subgroup analyses in 4 studies revealed that neonates diagnosed with ASD later in life had no association with blood levels of BDNF (Hedges g, 0.384; 95% CI, -0.244 to 1.011; P = .23), whereas children in the nonneonate ASD group (15 studies) demonstrated significantly increased BDNF levels compared with healthy controls (Hedges g, 0.524; 95% CI, 0.206 to 0.842; P = .001). Further analysis showed that children in the nonneonate ASD group had increased BDNF levels in serum (10 studies) (Hedges g, 0.564; 95% CI, 0.168 to 0.960; P = .005) but not in plasma (5 studies) (Hedges g, 0.436; 95% CI, -0.176 to 1.048; P = .16). Meta-regression analyses revealed that sample size had a moderating effect on the outcome of the meta-analysis in the nonneonate group. In addition, no publication bias was found in the meta-analysis.
Children with ASD have increased peripheral blood levels of BDNF, strengthening the clinical evidence of an abnormal neurotrophic factor profile in this population.

Autism spectrum disorders (ASDs) are common neurodevelopmental disorders characterized by impaired social communication, restricted and repetitive behavior or interests. Over the past 40 years, the reported prevalence for ASDs has been steadily rising world-wide. Due to the application of large-scale exome sequencing in recent years, hundreds of novel ASD associated genes have been identified. These associated genes are enriched in several common genetic signaling pathways such as synapse formation and chromatin remodeling. Intensive studies in animal models have revealed abnormal synaptic plasticity and an imbalanced ratio of excitatory to inhibitory neurotransmission in neural circuits of ASD brains. In this review, we summarize recent advances in (1) genetic heterogeneity of ASDs, (2) molecular pathways disturbed by various genetic mutations in ASDs, and (3) the development of genetic diagnostics and pharmacological treatments for ASDs. This review aims to provide a brief overview of the genetic basis of ASDs and prospects for diagnosis and treatment for ASDs.

Copy number variations (CNVs) have increasingly been reported to cause, or predispose to, human disease. However, a large fraction of these CNVs have not been accurately characterized at the single-base-pair level, thereby hampering a better understanding of the mutational mechanisms underlying CNV formation. Here, employing a composite pipeline method derived from various inference-based programs, we have characterized 26 deletion CNVs [including three novel pathogenic CNVs involving an autosomal gene (EXT2) causing hereditary osteochondromas and an X-linked gene (CLCN5) causing Dent disease, as well as 23 CNVs previously identified by inference from a cohort of Canadian autism spectrum disorder families] to the single-base-pair level of accuracy from whole-genome sequencing data. We found that breakpoint-flanking micro-mutations (within 22 bp of the breakpoint) are present in a significant fraction (5/26; 19%) of the deletion CNVs. This analysis also provided evidence that a recently described error-prone form of DNA repair (i.e., repair of DNA double-strand breaks by templated nucleotide sequence insertions derived from distant regions of the genome) not only causes human genetic disease but also impacts on human genome evolution. Our findings illustrate the importance of precise CNV breakpoint delineation for understanding the underlying mutational mechanisms and have implications for primer design in relation to the detection of deletion CNVs in clinical diagnosis.