In spite of its importance for education, the relationship between learning behaviors (LB), attention deficit hyperactivity disorder symptoms (ADHD) and executive functioning (EF) in children with autism spectrum disorder (ASD) has hardly been explored. The first objective of the present study was to compare children with ASD without intellectual disability and children with typical development (TD) on ADHD symptoms and learning behaviors: Motivation/competence, attitude toward learning, persistence on the task, and strategy/flexibility. The second objective was to analyze the mediator role of behavioral regulation and metacognition components of EF between ADHD symptoms and learning behaviors in children with ASD. Participants were 89 children between 7 and 11 years old, 52 with ASD and 37 with TD, matched on age and intelligence. Their teachers filled out questionnaires assessing executive functioning as well as learning behaviors. Parents and teachers reported on inattention and hyperactivity/impulsivity behaviors. Compared to children with TD, children with ASD presented significantly more ADHD symptoms and poorer learning behaviors. In addition, there were significant mediation effects of the behavioral regulation index (BRI) and metacognition index (MI) of EF, indicating that both are part of the route through which ADHD symptoms impact to learning behaviors of children with ASD.

Sleep problems were studied in both typically developing (TD) children and those with autism spectrum disorder (ASD) using the Sleep Disturbance Scale for Children. Factors associated with these problems were also studied in children with ASD. Seventy-three children with ASD and their age and sex matched TD controls in age group of 3-12 years were enrolled in the study. Higher sleep problems were found in children with ASD than TD children. Most common sleep problem reported in children with ASD was Sleep Wake Transition Disorders, followed by Disorder of Initiation and Maintenance; while in TD controls, it was Sleep Breathing Disorders. Apart from severity of Autism; hyperactivity, sensory issues and poor motor skills were significantly associated with sleep problems, which may be important targets for intervention in children with sleep problems.

Previous neuroimaging studies of autism spectrum disorder (ASD) have focused on subjects with IQ > 70 or ASD without considering IQ levels. It remains unclear whether differences in brain anatomy in this population are associated with variations in clinical phenotype. In this study, 19 children with low functioning autism (LFA) and 19 children with high functioning autism (HFA) were compared with 27 healthy controls (HC). We found increased gray matter volume (GMV) in the left inferior temporal gyrus in subjects with both HFA and LFA and increased GMV of left middle temporal gyrus BA21 was found only in the LFA group. A significant negative correlation was found between the left inferior temporal gyrus (LITG) and the score of repetitive behavior in the HFA group.

Autism spectrum disorders (ASDs) are characterized by core domains: persistent deficits in social communication and interaction; restricted, repetitive patterns of behavior, interests, or activities. ASDs comprise heterogeneous and complex neurodevelopmental pathologies with well-defined inflammatory conditions and immune system dysfunction. Due to neurobiologic changes underlying ASD development, cell-based therapies have been proposed and applied to ASDs. Indeed, stem cells show specific immunologic properties, which make them promising candidates in ASD treatment. This comprehensive up-to-date review focuses on ASD cellular/molecular abnormalities, potentially useful stem cell types, animal models, and current clinical trials on the use of stem cells in treating autism. Limitations are also discussed.

The Clavien-Dindo grading allows for broad comparison of perioperative surgical complications, and a temporal analysis of complications following ASD-corrective surgery. NSQIP database was utilized from 2010 to 2014 to isolate patients. Complications were stratified by Clavien complication (Cc) grade, and patients grouped by highest Cc grade: I, II, III, IV, V. Secondary analysis grouped by minor (I, II, III) and severe (IV, V). Comorbidity burden was assessed with a NSQIP-modified Charlson Comorbidity Index (CCI) and frailty was measured with a 5-factor modified frailty index (mFI). From 2010 to 2014, 2971 patients (57 yrs, 58% F) underwent surgery for ASD (3.4 ± 4.1 levels; surgical approach: 46% anterior, 44% posterior, 10% combined), the rate of which increased 0.01% to 0.13. 32% suffered >1 complication. Patient breakdown by Cc grade: 0% I, 25% II, 3% III, 4% IV, 1% V. Severe Cc patients were more comorbid than minor Cc (CCI 2.8 vs 1.8), had longer operative times (394 min vs 251), and higher rates of osteotomy (29% vs 13%) and iliac fixation (16% vs 5%). Overall CCI (2.1-1.7) and perioperative complication rates (55-29%) decreased, despite increasing surgical invasiveness (2.8-4.5) and increasing frailty score (0.14 ± 0.15 vs 0.16 ± 0.16). Rates of Clavien grade II (39.80-22.20%) and IV (9.40-3.50%) complications also decreased, indicative of surgical improvements and effective preoperative patient selection. The decrease in CCI and increase in the modified frailty score may show that we are becoming more cognizant of discerning of comorbidities, but likely to not to have taken into account frailty, which may have an impact on future health socioeconomics.

Autism spectrum disorders (ASDs) are neuropsychiatric disorders associated with synaptic function and plasticity. Neural cell adhesion molecule (NCAM1) dysfunction impairs synapse formation, synaptic activity and plasticity. To explore the relationship between NCAM1 and ASD, a case-control study was conducted. This research included 40 ASD children and 39 healthy children aged 2-6 years old. We measured the levels of plasma NCAM1 in ASD and healthy control groups by ELISA kits. The severity and behavioral problems of autistic children were also examined. The level of plasma NCAM1 in ASD children was significantly lower than that in controls (p < 0.05). Additionally, NCAM1 levels were negatively correlated with social motivation, social communication and the total scores assessed by Social Responsiveness Scale (SRS). NCAM1 levels positively correlated with gross motor ability and developmental quotient in the ASD group. The area under the ROC curve of NCAM1 was 0.647. These results indicated that NCAM1 levels are associated with behavioral problems in children with ASD. These include phenotypes relating to social motivation, social communication, gross motor ability and developmental quotient. These results suggest that future studies exploring the function of NCAM1 in the context of etiology of ASD may be needed.

Clinicians and educators are increasingly using technology within the context of existing therapies and teaching methodologies. The growing use of mobile clinical tools is particularly exciting for individuals with autism spectrum disorder (ASD), as technologically based interventions have been shown to be both efficacious (to target academics, adaptive behavior, disruptive behavior, etc.) and accepted in this population (Odom et al., 2015). In addition, these tools have the potential to address two significant impediments in ASD intervention, the anxiety and/or skill deficits often associated with face-to-face interactions and skill generalization outside of the therapy office (Wieckowski & White, 2017). In other words, the use of technology may serve as an important preliminary or prerequisite step for face-to-face therapeutic progress. The purpose of this paper is to present a new, interactive clinical app that explicitly utilizes an individual's restricted interests to teach skills and improve communication. The paper will briefly review the ways in which individuals with ASD may be good candidates for technological-based interventions, explore the current role of technology in existing evidence-based therapies, and discuss the use of a new technology, Sidekicks!, that has been developed for this population. A case example will then illustrate the use of Sidekicks! and its anticipated functionality across several public service settings, including hospitals, outpatient clinics, and school systems, thereby coordinating the intervention efforts of various professionals involved in the treatment of children with ASD. Finally, limitations of the app (and of technology more generally) and the need for future research will be discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Protein homeostasis is tightly regulated by the ubiquitin proteasome pathway. Disruption of this pathway gives rise to a host of neurological disorders. Through whole exome sequencing (WES) in families with neurodevelopmental disorders, we identified mutations in PSMD12, a core component of the proteasome, underlying a neurodevelopmental disorder with intellectual disability (ID) and features of autism spectrum disorder (ASD). We performed WES on six affected siblings from a multiplex family with ID and autistic features, the affected father, and two unaffected mothers, and a trio from a simplex family with one affected child with ID and periventricular nodular heterotopia. We identified an inherited heterozygous nonsense mutation in PSMD12 (NM_002816: c.367C>T: p.R123X) in the multiplex family and a de novo nonsense mutation in the same gene (NM_002816: c.601C>T: p.R201X) in the simplex family. PSMD12 encodes a non-ATPase regulatory subunit of the 26S proteasome. We confirm the association of PSMD12 with ID, present the first cases of inherited PSMD12 mutation, and demonstrate the heterogeneity of phenotypes associated with PSMD12 mutations.

We test the hypothesis that changes in preceding physiological arousal can be used to predict imminent aggression proximally before it occurs in youth with autism spectrum disorder (ASD) who are minimally verbal (MV-ASD). We evaluate this hypothesis through statistical analyses performed on physiological biosensor data wirelessly recorded from 20 MV-ASD youth over 69 independent naturalistic observations in a hospital inpatient unit. Using ridge-regularized logistic regression, results demonstrate that, on average, our models are able to predict the onset of aggression 1 minute before it occurs using 3 minutes of prior data with a 0.71 AUC for global, and a 0.84 AUC for person-dependent models.