E-technology social support programs for autistic children: Can they work?

Autism is a neurodevelopmental condition with associated difficulties that present differently across individuals.One such difficulty is recognizing basic and complex facial expressions.Research has previously found that there are many evidence-based support programs available for building non-verbal communication skills.These programs are frequently administered with a therapist or in a group setting,making them inflexible in nature.Programs hosted on e-technology are becoming increasingly popular,with many parents supportive of them.Applications(apps)that are hosted on technology such as iPads or mobile phones allow users to engage in building skills in real-time social settings and own what they are learning.These technologies are frequently used by autistic children,with apps typically focusing on identifying facial features.Yet at this current time,there are mixed reviews of how to design such programs and what their theoretical backing is,with many studies using a mix of observation and psychological assessments as outcome measures.Eye-tracking and electroencephalography are established methodologies that measure neural processing and gaze behaviors while viewing faces.To better support the field moving forward,objective measures such as these are a way to measure outcomes of apps that are designed for helping children on the spectrum build skills in understanding facial expressions.

Schizophrenia-associated MicroRNA–Gene Interactions in the Dorsolateral Prefrontal Cortex

Schizophrenia-associated anomalies in gene expression in postmortem brain can be attributed to a combination of genetic and environmental influences. Given the small effect size of common variants, it is likely that we may only see the combined impact of some of these at the pathway level in small postmortem studies. At the gene level, however, there may be more impact from common environmental exposures mediated by influential epigenomic modifiers, such as microRNA(miRNA). We hypothesise that dysregulation of miRNAs and their alteration of gene expression have significant implications in the pathophysiology of schizophrenia. In this study, we integrate changes in cortical gene and miRNA expression to identify regulatory interactions and networks associated with the disorder. Gene expression analysis in post-mortem prefrontal dorsolateral cortex(BA 46)(n = 74 matched pairs of schizophrenia, schizoaffective, and control samples)was integrated with miRNA expression in the same cohort to identify gene–miRNA regulatory networks. A significant gene–miRNA interaction network was identified, including miR-92 a, miR-495,and miR-134, which converged with differentially expressed genes in pathways involved in neurodevelopment and oligodendrocyte function. The capacity for miRNA to directly regulate gene expression through respective binding sites in BCL11 A, PLP1, and SYT11 was also confirmed to support the biological relevance of this integrated network model. The observations in this study support the hypothesis that mi RNA dysregulation is an important factor in the complex pathophysiology of schizophrenia.