[Virtual reality and digital biomarkers: a clinical tool for early autism diagnosis].

Introduction: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition which traditional assessment procedures encounter certain limitations. The current ASD research field is exploring and endorsing innovative methods to assess the disorder early on, based on the automatic detection of biomarkers. However, many of these procedures lack ecological validity in their measurements.

The whole-body motor skills of children with autism spectrum disorder taking goal-directed actions in virtual reality.

Many symptoms of the autism spectrum disorder (ASD) are evident in early infancy, but ASD is usually diagnosed much later by procedures lacking objective measurements. It is necessary to anticipate the identification of ASD by improving the objectivity of the procedure and the use of ecological settings. In this context, atypical motor skills are reaching consensus as a promising ASD biomarker, regardless of the level of symptom severity.

[Adaptive technological interventions for autism spectrum disorder: a literature review].

Individuals with autistic spectrum disorder are often described as having communication, social, emotional, nd behavioral impairments. They are often isolated and passive, with few opportunities for positive and constructive interaction with the outside world. Moreover, they may exhibit withdrawn, stereotyped and disruptive behaviors.

Eye gaze as a biomarker in the recognition of autism spectrum disorder using virtual reality and machine learning: A proof of concept for diagnosis.

The core symptoms of autism spectrum disorder (ASD) mainly relate to social communication and interactions. ASD assessment involves expert observations in neutral settings, which introduces limitations and biases related to lack of objectivity and does not capture performance in real-world settings. To overcome these limitations, advances in technologies (e.

Machine Learning and Virtual Reality on Body Movements' Behaviors to Classify Children with Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is mostly diagnosed according to behavioral symptoms in sensory, social, and motor domains. Improper motor functioning, during diagnosis, involves the qualitative evaluation of stereotyped and repetitive behaviors, while quantitative methods that classify body movements' frequencies of children with ASD are less addressed. Recent advances in neuroscience, technology, and data analysis techniques are improving the quantitative and ecological validity methods to measure specific functioning in ASD children.

Application of Supervised Machine Learning for Behavioral Biomarkers of Autism Spectrum Disorder Based on Electrodermal Activity and Virtual Reality.

Objective: Sensory processing is the ability to capture, elaborate, and integrate information through the five senses and is impaired in over 90% of children with autism spectrum disorder (ASD). The ASD population shows hyper-hypo sensitiveness to sensory stimuli that can generate alteration in information processing, affecting cognitive and social responses to daily life situations. Structured and semi-structured interviews are generally used for ASD assessment, and the evaluation relies on the examiner's subjectivity and expertise, which can lead to misleading outcomes.

[Autism spectrum disorder biomarkers based on biosignals, virtual reality and artificial intelligence].

It has been observed that the stratification of Autism Spectrum Disorders (ASD) generated by the current scales is not effective for the personalization of early treatments. The clinical evaluation of ASD requires its consideration as a continuum of deficits, and there is a need to identify biologically significant parameters (biomarkers) that have the power to automatically characterize each individual at different stages of neurological development. The emerging field of computational psychiatry (CP) attempts to meet the needs of precision diagnosis by developing powerful computational and mathematical techniques.

[Use of virtual reality for neurodevelopmental disorders. A review of the state of the art and future agenda].

To date, the diagnostic tools for autism spectrum disorder (ASD) have been mostly based on qualitative criteria from observational information in contexts with low ecological validity. We are witnessing a growing scientific activity that proposes the use of implicit measures for the evaluation and diagnosis of ASD. These measures are based on processes of a biological and unconscious nature, underlying the capacity of human cognition, and are obtained through the acquisition and treatment of brain, physiological and behavioral responses in order to obtain the behavioral structure of the ASD patient facing a stimulus.

Abiotic amidine and guanidine hydrolysis of lamotrigine-N2-glucuronide and related compounds in wastewater: The role of pH and N2-substitution on reaction kinetics.

The stability of lamotrigine (LMG) and its principal human metabolite, lamotrigine N2-glucuronide (LMG-N2-G), was studied as a function of pH (4-9). While LMG was stable across the entire pH range, under neutral-basic conditions, LMG-N2-G was converted to three transformation products (TPs) which were identified using high resolution mass spectrometry (HRMS). The MS fragmentation studies indicated that two TPs were the result of the hydrolysis of the amidine and guanidine moieties.

[Pharmacological update in attention deficit hyperactivity disorder: models of intervention and new drugs].

INTRODUCTION. Attention deficit hyperactivity disorder (ADHD) is the most frequent neurodevelopmental problem in childhood, with significant repercussions that continue into adulthood. This means that an appropriate therapeutic intervention is vital to improve its prognosis.

Novel interfering bifunctional molecules against the CCR5 coreceptor are efficient inhibitors of HIV-1 infection.

CCR5 is the major coreceptor for the HIV-1 strains responsible for primary infection. Individuals homozygous for a 32-bp deletion in the CCR5 coding region are resistant to HIV-1 infection. Strategies to delete CCR5 functionally could thus be of substantial benefit in preventing HIV-1 infection or delaying disease.