General Anesthesia During Neurodevelopment Reduces Autistic Behavior in Adult BTBR Mice, a Murine Model of Autism

Preclinical studies suggest that repeated exposure to anesthetics during a critical period of neurodevelopment induces long-term changes in synaptic transmission, plasticity, and behavior. Such changes are of great concern, as similar changes have also been identified in animal models of neurodevelopmental disorders (NDDs) such as autism. Because of overlapping synaptic changes, it is also possible that anesthetic exposures have a more significant effect in individuals diagnosed with NDDs. Thus, we evaluated the effects of early, multiple anesthetic exposures in BTBR mice, an inbred strain that displays autistic behavior. We discovered that three cycles of sevoflurane anesthesia (2.5%, 1 h) with 2-h intervals between each exposure in late postnatal BTBR mice did not aggravate, but instead improved pathophysiological mechanisms involved with autistic behavior. Sevoflurane exposures restored E/I balance (by increasing inhibitory synaptic transmission), and increased mitochondrial respiration and BDNF signaling in BTBR mice. Most importantly, such changes were associated with reduced autistic behavior in BTBR mice, as sociability was increased in the three-chamber test and repetitive behavior was reduced in the self-grooming test. Our results suggest that anesthetic exposures during neurodevelopment may affect individuals diagnosed with NDDs differently.

NON-PARAMETRIC RANDOMIZED TREE CLASSIFIER FOR DETECTION OF AUTISM DISORDER IN TODDLERS

Autism is a behavioral disorder seen in toddlers and adolescents. It is a disorder which concerns behavior of child, speech, social interaction of child as well as nonverbal communication of child is affected. The parents of affected children find it very cumbersome to manage the child. Detection of such anomalies is really important at early stages. This paper mainly focuses on early detection of autistic behavior in toddlers. There are various machine learning and deep learning algorithms. Non parametric Extreme randomized classifier is one such technique which helps in early detection of autistic behavior in toddlers. The various performance evaluation metrics used are Jaccard score, ROC Curves and Mean Squared Error. The Feature selection is done using spearman correlation to identify the features affecting the child most and represented in form of Heat map. Extra tree classifier proves a better algorithm in detection of autism at early stages of child development.

Clostridioides difficile infection increases circulating p-cresol levels and dysregulates brain dopamine metabolism: linking gut-brain axis to autism and other neurologic disorders?

Gastrointestinal illnesses are one of the most common comorbidities reported in patients with neurodevelopmental diseases, including autism spectrum disorders (ASD). Gut dysbiosis, overgrowth of C. difficile in the gut, and gut microbiota-associated alterations in central neurotransmission have been implicated in ASD, where the dopaminergic axis plays an important role in the disease pathogenesis. Human C. difficile strains produce a significant amount of the toxic metabolite p-cresol, an inhibitor of dopamine beta-hydroxylase (DBH), which catalyzes the conversion of dopamine (DA) to norepinephrine (NE). p-cresol is known to precipitate and exacerbate autistic behavior in rodents by increasing DA levels and altering DA receptor sensitivity in brain regions relevant to ASD. Therefore, we hypothesized that C. difficile infection dysregulates dopaminergic metabolism in the brain by increasing p-cresol levels in the gut and circulation and by inhibiting DBH, ultimately leading to elevated DA in the brain. For testing this hypothesis, we induced antibiotic-associated C. difficile in mice and determined the gut and serum p-cresol levels, serum DBH activity, and dopamine and its metabolite levels in different brain regions relevant to ASD. The results showed that C. difficile infection causes significant alterations in the dopaminergic axis in mice (p < 0.05). In addition, significantly increased circulating p-cresol levels and reduced DBH activity was observed in C. difficile infected animals (p < 0.05). Therefore, the results from this study suggest a potential link between C. difficile infection and alterations in the dopaminergic axis implicated in the precipitation and aggravation of ASD.

The Dopamine Hypothesis of Autism Spectrum Disorder Revisited: Current Status and Future Prospects

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental disorders characterized by social deficits and stereotyped behaviors. Despite intensive research, its etiopathogenesis remains largely unclear. Although studies consistently reported dopaminergic anomalies, a coherent dopaminergic model of ASD was lacking until recently. In 2017, we provided a theoretical framework for a “dopamine hypothesis of ASD” which proposed that autistic behavior arises from a dysfunctional midbrain dopaminergic system. Namely, we hypothesized that malfunction of 2 critical circuits originating in the midbrain, that is, the mesocorticolimbic and nigrostriatal pathways, generates the core behavioral features of ASD. Moreover, we provided key predictions of our model along with testing means. Since then, a notable number of studies referenced our work and numerous others provided support for our model. To account for these developments, we review all these recent data and discuss their implications. Furthermore, in the light of these new insights, we further refine and reconceptualize our model, debating on the possibility that various etiologies of ASD converge upon a dysfunctional midbrain dopaminergic system. In addition, we discuss future prospects, providing new means of testing our hypothesis, as well as its limitations. Along these lines, we aimed to provide a model which, if confirmed, could provide a better understanding of the etiopathogenesis of ASD along with new therapeutic strategies.

Countering Biased Judgments of Individuals Who Display Autism-Characteristic Behavior in Forensic Settings

According to expectancy violations theory, displays of behavior considered “unusual” during an interaction will trigger scrutiny of an individual. Such scrutiny may be detrimental in forensic contexts, where deception detection is emphasized. Autistic individuals, in particular, may be scrutinized unfavorably given unusual nonverbal behavior associated with the condition. Across two experiments using between-subjects’ designs, participants (overall N = 3,342) watched a scripted police-suspect interrogation, randomized to view the suspect display autism-related behaviors or none of those behaviors. Autistic behavior biased evaluations of deception and guilt as a function of violating individual behavioral expectations, regardless of whether decisive or ambiguous evidence framed the suspect as guilty or innocent. Promisingly, however, providing an autism information card attenuated such evaluations. Our research extends expectancy violations theory, advances understanding of determinants of forensic judgments, highlights important applied implications for nonverbal behavior displays in the justice system and recommends methods to protect against bias.

16p11.2 Duplication Syndrome - a Case Report

16p11.2 duplication syndrome is a rare disorder, often associated with intellectual disability, attention deficit, hyperactivity disorder, and a predisposition to epilepsy and schizophrenia. There are no specific dysmorphic features for this genetic condition, but micro-cephaly, micrognathia and hypertelorism could be present. We report a case of 16p11.2 duplication syndrome which has the typical clinical presentation &ndash; slight facial dysmorphism, impaired intellectual development, and autistic behavior. Whole-exome sequencing was performed, but no pathogenic or likely pathogenic mutations were identified. Array comparative genomic hybridization analysis established the diagnosis of 16p11.2 duplication syndrome, which illustrates the importance of this method when diagnosing children with unexplained intellectual disability.&nbsp;