Physical Activity, Gut Microbiota, and Genetic Background for Children and Adolescents with Autism Spectrum Disorder

Plaza‐Díaz, Julio; Radar, Ana Mei; Baig, Aiman Tariq; Leyba, Marcos Federico; Costabel, Maria Macarena; Zavala-Crichton, Juan Pablo; Sanchez-Martinez, Javier; MacKenzie, Alex; Solis‐Urra, Patricio

doi:10.3390/children9121834

Cited by 3 publications

(1 citation statement)

References 208 publications

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“…Autism Spectrum Disorder (ASD) is an ND that can be diagnosed at any age but usually appears within the first two years of life [4]. The prevalence of ASD is estimated to be around one in one hundred children worldwide, though some studies report higher 2 of 15 rates [5,6].…”

Section: Introductionmentioning

confidence: 99%

Utilizing Constructed Neural Networks for Autism Screening

Toki,

Pange,

Tatsis

et al. 2024

Applied Sciences

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Autism Spectrum Disorder is known to cause difficulties in social interaction and communication, as well as repetitive patterns of behavior, interests, or hobbies. These challenges can significantly affect the individual’s daily life. Therefore, it is crucial to identify and assess children with Autism Spectrum Disorder early to significantly benefit the long-term health of children. Unfortunately, many children are not diagnosed or are misdiagnosed, which means they miss out on the necessary interventions. Clinicians and other experts face various challenges during the diagnostic process. Digital tools can facilitate early diagnosis effectively. This study aimed to explore the use of machine learning techniques on a dataset collected from a serious game designed for children with autism to investigate how these techniques can assist in classification and make the clinical process more efficient. The responses were gathered from children who participated in interactive games deployed on mobile devices, and the data were analyzed using various types of neural networks, such as multilayer perceptrons and constructed neural networks. The performance metrics of these models, including error rate, precision, and recall, were reported, and the comparative experiments revealed that the constructed neural network using the integer rule-based neural networks approach was superior. Based on the evaluation metrics, this method showed the lowest error rate of 11.77%, a high accuracy of 0.75, and a good recall of 0.66. Thus, it can be an effective way to classify both typically developed children and children with Autism Spectrum Disorder. Additionally, it can be used for automatic screening procedures in an intelligent system. The results indicate that clinicians could use these techniques to enhance conventional screening methods and contribute to providing better care for individuals with autism.

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Section: Introductionmentioning

confidence: 99%

Utilizing Constructed Neural Networks for Autism Screening

Toki,

Pange,

Tatsis

et al. 2024

Applied Sciences

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Positive effects of physical activity in autism spectrum disorder: how influences behavior, metabolic disorder and gut microbiota

Ranieri,

Mennitti,

Falcone

et al. 2023

Front. Psychiatry

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Autism spectrum disorder is a neurodevelopmental disorder characterized by social interactions and communication skills impairments that include intellectual disabilities, communication delays and self-injurious behaviors; often are present systemic comorbidities such as gastrointestinal disorders, obesity and cardiovascular disease. Moreover, in recent years has emerged a link between alterations in the intestinal microbiota and neurobehavioral symptoms in children with autism spectrum disorder. Recently, physical activity and exercise interventions are known to be beneficial for improving communication and social interaction and the composition of microbiota. In our review we intend to highlight how different types of sports can help to improve communication and social behaviors in children with autism and also show positive effects on gut microbiota composition.

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Gut Microbiome Dysbiosis as a Potential Risk Factor for Idiopathic Toe-Walking in Children: A Review

Kononova,

Kashparov,

Xue

et al. 2023

IJMS

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Idiopathic toe walking (ITW) occurs in about 5% of children. Orthopedic treatment of ITW is complicated by the lack of a known etiology. Only half of the conservative and surgical methods of treatment give a stable positive result of normalizing gait. Available data indicate that the disease is heterogeneous and multifactorial. Recently, some children with ITW have been found to have genetic variants of mutations that can lead to the development of toe walking. At the same time, some children show sensorimotor impairment, but these studies are very limited. Sensorimotor dysfunction could potentially arise from an imbalanced production of neurotransmitters that play a crucial role in motor control. Using the data obtained in the studies of several pathologies manifested by the association of sensory–motor dysfunction and intestinal dysbiosis, we attempt to substantiate the notion that malfunction of neurotransmitter production is caused by the imbalance of gut microbiota metabolites as a result of dysbiosis. This review delves into the exciting possibility of a connection between variations in the microbiome and ITW. The purpose of this review is to establish a strong theoretical foundation and highlight the benefits of further exploring the possible connection between alterations in the microbiome and TW for further studies of ITW etiology.

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Physical Activity, Gut Microbiota, and Genetic Background for Children and Adolescents with Autism Spectrum Disorder

Cited by 3 publications

References 208 publications

Utilizing Constructed Neural Networks for Autism Screening

Utilizing Constructed Neural Networks for Autism Screening

Positive effects of physical activity in autism spectrum disorder: how influences behavior, metabolic disorder and gut microbiota

Gut Microbiome Dysbiosis as a Potential Risk Factor for Idiopathic Toe-Walking in Children: A Review

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