Endosonographic and ERCP findings in COVID-19 critical illness cholangiopathy.

A 56-year-old female developed deep jaundice months after struggling with critical illness due to COVID-19, requiring hemodialysis and tracheostomy. Lab tests included alkaline phosphatase 1,574 U/l, total bilirubin 11 mg/dl, alanine transaminase (ALT) 88 U/l and aspartate aminotransferase (AST) 101 U/l. Baseline liver tests were normal before illness. Anti-nuclear antibodies (ANA), IgG4 level and viral hepatitis were negaCritical illness cholangiopathy resulted in secondary sclerosing cholangitis. In this case, it is unclear whether the patient suffered these changes as a direct cause of COVID-19 or as a result of critical illness cholangiopathy. The overall prognosis is guarded given its progressive nature and likely need for liver transplantation.tive.

AQP4, Astrogenesis, and Hydrocephalus: A New Neurological Perspective.

Aquaporin 4 (AQP4) is a cerebral glial marker that labels ependymal cells and astrocytes' endfeet and is the main water channel responsible for the parenchymal fluid balance. However, in brain development, AQP4 is a marker of glial stem cells and plays a crucial role in the pathophysiology of pediatric hydrocephalus. Gliogenesis characterization has been hampered by a lack of biomarkers for precursor and intermediate stages and a deeper understanding of hydrocephalus etiology is needed. This manuscript is a focused review of the current research landscape on AQP4 as a possible biomarker for gliogenesis and its influence in pediatric hydrocephalus, emphasizing reactive astrogliosis. The goal is to understand brain development under hydrocephalic and normal physiologic conditions.

Altered Expression of AQP1 and AQP4 in Brain Barriers and Cerebrospinal Fluid May Affect Cerebral Water Balance during Chronic Hypertension.

Hypertension is the leading cause of cardiovascular affection and premature death worldwide. The spontaneously hypertensive rat (SHR) is the most common animal model of hypertension, which is characterized by secondary ventricular dilation and hydrocephalus. Aquaporin (AQP) 1 and 4 are the main water channels responsible for the brain's water balance. The present study focuses on defining the expression of AQPs through the time course of the development of spontaneous chronic hypertension. We performed immunofluorescence and ELISA to examine brain AQPs from 10 SHR, and 10 Wistar−Kyoto (WKY) rats studied at 6 and 12 months old. There was a significant decrease in AQP1 in the choroid plexus of the SHR-12-months group compared with the age-matched control (p < 0.05). In the ependyma, AQP4 was significantly decreased only in the SHR-12-months group compared with the control or SHR-6-months groups (p < 0.05). Per contra, AQP4 increased in astrocytes end-feet of 6 months and 12 months SHR rats (p < 0.05). CSF AQP detection was higher in the SHR-12-months group than in the age-matched control group. CSF findings were confirmed by Western blot. In SHR, ependymal and choroidal AQPs decreased over time, while CSF AQPs levels increased. In turn, astrocytes AQP4 increased in SHR rats. These AQP alterations may underlie hypertensive-dependent ventriculomegaly.

[Use of virtual reality for neurodevelopmental disorders. A review of the state of the art and future agenda]. / Uso de entornos virtuales para trastornos del neurodesarrollo: una revisión del estado del arte y agenda futura.

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. The complex relationship between physiological responses and the behavioral structure of the ASD patient requires the use of advanced techniques of signal processing based on cognitive computation. Artificial intelligence (AI) techniques, such as machine learning and neurocomputing applied to the analysis of psychophysiological signals, have demonstrated their robustness for the classification of complex cognitive constructs. Virtual reality (VR) is a tool that allows recreating real-life situations with high sensory fidelity, but at the same time individually controlling each of the situations and stimuli that influence human behavior. It also allows the measurement in real time of human reactions to such stimuli. This document analyzes the latest scientific and technological advances relevant to its applications in the diagnosis of ASD. We conclude that VR is a very valuable tool for ASD research, especially for the evaluation and diagnosis of complex skills and competencies.

Hasta ahora las herramientas diagnósticas de los trastornos del espectro autista (TEA) se basan mayoritariamente en criterios cualitativos de información observacional en contextos con baja validez ecológica. Una creciente actividad científica propone medidas implícitas para la evaluación y diagnóstico del TEA. Dichas medidas se basan en procesos de carácter biológico e inconsciente, subyacentes a la capacidad de cognición humana y son obtenidas a través de la adquisición y tratamiento de respuestas cerebrales, fisiológicas y comportamentales, con el objetivo de obtener la estructura comportamental del paciente TEA ante un estímulo. La compleja relación existente entre respuestas fisiológicas y la estructura comportamental del paciente TEA ante un estímulo, obliga a utilizar técnicas avanzadas de tratamiento de la señal basadas en computación cognitiva. Las técnicas de inteligencia artificial, tales como aprendizaje automático (machine learning) y neurocomputación aplicadas al análisis de señales psicofisiológicas, han demostra do su robustez para la clasificación de complejos constructos cognitivos. La realidad virtual (RV) es una herramienta que permite recrear situaciones de la vida real con una alta fidelidad sensorial, pero al mismo tiempo controlar individualmente cada una de las situaciones y estímulos que influyen en el comportamiento humano. También permite la medición en tiempo real de las reacciones humanas ante tales estímulos. Este documento analiza los últimos avances científicos y tecnológicos relevantes para sus aplicaciones en el diagnóstico del TEA. Afirmamos que la RV es una herramienta muy valiosa para la investigación del TEA, especialmente para la evaluación y diagnóstico de habilidades y competencias complejas.

[Virtual reality and digital biomarkers: a clinical tool for early autism diagnosis]. / Realidad virtual y biomarcadores digitales: una herramienta clínica para el diagnóstico del autismo.

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. In this context, virtual reality (VR) shows promise for objectively recording biosignals while users experience ecological situations. METHODS: This study outlines a novel and playful VR procedure for the early assessment of ASD, relying on multimodal biosignal recording. During a VR experience featuring 12 virtual scenes, eye gaze, motor skills, electrodermal activity and behavioural performance were measured in 39 children with ASD and 42 control peers. Machine learning models were developed to identify digital biomarkers and classify autism. RESULTS: Biosignals reported varied performance in detecting ASD, while the combined model resulting from the combination of specific-biosignal models demonstrated the ability to identify ASD with an accuracy of 83% (SD = 3%) and an AUC of 0.91 (SD = 0.04). DISCUSSION: This screening tool may support ASD diagnosis by reinforcing the outcomes of traditional assessment procedures.

Introducción: El Trastorno del Espectro Autista (TEA) es un trastorno del neurodesarrollo, y sus procedimientos tradicionales de evaluación encuentran ciertas limitaciones. El actual campo de investigación sobre TEA está explorando y respaldando métodos innovadores para evaluar el trastorno tempranamente, basándose en la detección automática de biomarcadores. Sin embargo, muchos de estos procedimientos carecen de validez ecológica en sus mediciones. En este contexto, la realidad virtual (RV) presenta un prometedor potencial para registrar objetivamente bioseñales mientras los usuarios experimentan situaciones ecológicas. Métodos: Este estudio describe un novedoso y lúdico procedimiento de RV para la evaluación temprana del TEA, basado en la grabación multimodal de bioseñales. Durante una experiencia de RV con 12 escenas virtuales, se midieron la mirada, las habilidades motoras, la actividad electrodermal y el rendimiento conductual en 39 niños con TEA y 42 compañeros de control. Se desarrollaron modelos de aprendizaje automático para identificar biomarcadores digitales y clasificar el autismo. Resultados: Las bioseñales reportaron un rendimiento variado en la detección del TEA, mientras que el modelo resultante de la combinación de los modelos de las bioseñales demostró la capacidad de identificar el TEA con una precisión del 83% (DE = 3%) y un AUC de 0.91 (DE = 0.04). Discusión: Esta herramienta de detección puede respaldar el diagnóstico del TEA al reforzar los resultados de los procedimientos tradicionales de evaluación.

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. This study aimed to assess differences in the whole-body motor skills between 20 children with ASD and 20 children with typical development during the execution of three tasks resembling regular activities presented in virtual reality. The virtual tasks asked to perform precise and goal-directed actions with different limbs vary in their degree of freedom of movement. Parametric and non-parametric statistical methods were applied to analyze differences in children's motor skills. The findings endorsed the hypothesis that when particular goal-directed movements are required, the type of action could modulate the presence of motor abnormalities in ASD. In particular, the ASD motor abnormalities emerged in the task requiring to take with the upper limbs goal-directed actions with low degree of freedom. The motor abnormalities covered (1) the body part mainly involved in the action, and (2) further body parts not directly involved in the movement. Findings were discussed against the background of atypical prospective control of movements and visuomotor discoordination in ASD. These findings contribute to advance the understanding of motor skills in ASD while deepening ecological and objective assessment procedures based on VR.

[Adaptive technological interventions for autism spectrum disorder: a literature review]. / Intervenciones tecnológicas adaptativas para el trastorno del espectro autista: una revisión bibliográfica.

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. The aforementioned conditions can seriously hamper their ability to adapt to the environment, with negative consequences on their quality of life. Phenotypic heterogeneity and manifestation, as well as symptom severity, can vary greatly from child to child. These determine the need for individualized and adaptive interventions according to specific needs, including factors such as age, intellectual ability, and specific affected areas. Early intervention would promote adaptive skills, self-determination, and autonomy towards the environment. However, wait times and costs do not allow for early assessment, and therefore intervention times are delayed, affecting the quality of life of children and parents. In addition, traditional intervention programs depend on the expertise of the therapists. One possible way to overcome this problem is by using objective adaptive technologies based on needs. This article aims to provide an overview of the empirical evidence available over the past seven years. Overall, 8 studies were selected, with 132 participants using 4 technological systems. Finally, the technological, clinical, psychological, and rehabilitative implications of the findings are discussed. Practical guidelines within this topic area are outlined as future research perspectives.

Los individuos con trastornos del espectro autista suelen describirse con deficiencias comunicativas, sociales, emocionales y de comportamiento. A menudo están aislados y son pasivos, con pocas oportunidades de interacción positiva y constructiva con el mundo exterior. Por otra parte, pueden mostrar comportamientos retraídos, estereotipados y disruptivos. Estas condiciones pueden dificultar seriamente sus habilidades adaptativas al ambiente, con consecuencias negativas en su calidad de vida. La heterogeneidad fenotípica y la manifestación, así como la gravedad de los síntomas, pueden variar considerablemente según el niño. Esos determinan la necesidad de intervenciones personalizadas y adaptivas según las necesidades específicas, incluyendo factores como la edad, las habilidades intelectuales y las áreas afectadas específicas. Una intervención temprana promovería las habilidades adaptativas, la autodeterminación y la autonomía hacia el entorno. No obstante, los tiempos de esperas y los costes no permiten una evaluación temprana y como consecuencia los tiempos de intervención se retrasan afectando la cualidad de vida de los niños y de los padres. Además, los programas tradicionales de intervención dependen de la experiencia de los terapeutas. Una posible forma de superar este problema es el uso de tecnología adaptativa objetiva según las necesidades. El objetivo de este artículo es proporcionar una visión general de las pruebas empíricas disponible en los últimos siete años. En total, se seleccionaron 8 estudios, con 132 participantes que utilizaron 4 sistemas tecnológicos. Por último, se discuten las implicaciones tecnológicas, clínicas, psicológicas y rehabilitadoras de los hallazgos. Se esbozaron directrices prácticas dentro de esta área temática como perspectivas de investigación futuras.

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.g., virtual reality) and sensors (e.g., eye-tracking tools) have been used to create realistic simulated environments and track eye movements, enriching assessments with more objective data than can be obtained via traditional measures. This study aimed to distinguish between autistic and typically developing children using visual attention behaviors through an eye-tracking paradigm in a virtual environment as a measure of attunement to and extraction of socially relevant information. The 55 children participated. Autistic children presented a higher number of frames, both overall and per scenario, and showed higher visual preferences for adults over children, as well as specific preferences for adults' rather than children's faces on which looked more at bodies. A set of multivariate supervised machine learning models were developed using recursive feature selection to recognize ASD based on extracted eye gaze features. The models achieved up to 86% accuracy (sensitivity = 91%) in recognizing autistic children. Our results should be taken as preliminary due to the relatively small sample size and the lack of an external replication dataset. However, to our knowledge, this constitutes a first proof of concept in the combined use of virtual reality, eye-tracking tools, and machine learning for ASD recognition. LAY SUMMARY: Core symptoms in children with ASD involve social communication and interaction. ASD assessment includes expert observations in neutral settings, which show limitations and biases related to lack of objectivity and do not capture performance in real settings. To overcome these limitations, this work aimed to distinguish between autistic and typically developing children in visual attention behaviors through an eye-tracking paradigm in a virtual environment as a measure of attunement to, and extraction of, socially relevant information.

Early Regressive Development of the Subcommissural Organ of Two Human Fetuses with Non-Communicating Hydrocephalus.

Hydrocephalus is a central nervous system condition characterized by CSF buildup and ventricular hypertrophy. It is divided into two types: communicative and non-communicating hydrocephalus. Congenital hydrocephalus has been linked to several changes in the subcommissural organ (SCO). However, it is unclear whether these changes occur before or as a result of the hydrocephalic illness. This report presents three cases of human fetuses with hydrocephalus: one non-communicating case, two communicating cases, and two controls. Hematoxylin-Eosin (H&E) or cresyl violet and immunohistochemistry with anti-transthyretin were used to analyze SCO morphological and secretory changes. We conclude that in the cases presented here, there could be an early regression in the SCO of the communicating cases that is not present in the non-communicating case.

AQP4 labels a subpopulation of white matter-dependent glial radial cells affected by pediatric hydrocephalus, and its expression increased in glial microvesicles released to the cerebrospinal fluid in obstructive hydrocephalus.

Hydrocephalus is a distension of the ventricular system associated with ventricular zone disruption, reactive astrogliosis, periventricular white matter ischemia, axonal impairment, and corpus callosum alterations. The condition's etiology is typically attributed to a malfunction in classical cerebrospinal fluid (CSF) bulk flow; however, this approach does not consider the unique physiology of CSF in fetal and perinatal patients. The parenchymal fluid contributes to the glymphatic system, and plays a fundamental role in pediatric hydrocephalus, with aquaporin 4 (AQP4) as the primary facilitator of these fluid movements. Despite the importance of AQP4 in the pathophysiology of hydrocephalus, it's expression in human fetal life is not well-studied. This manuscript systematically defines the brain expression of AQP4 in human brain development under control (n = 13) and hydrocephalic conditions (n = 3). Brains from 8 postconceptional weeks (PCW) onward and perinatal CSF from control (n = 2), obstructive (n = 6) and communicating (n = 6) hydrocephalic samples were analyzed through immunohistochemistry, immunofluorescence, western blot, and flow cytometry. Our results indicate that AQP4 expression is observed first in the archicortex, followed by the ganglionic eminences and then the neocortex. In the neocortex, it is initially at the perisylvian regions, and lastly at the occipital and prefrontal zones. Characteristic astrocyte end-feet labeling surrounding the vascular system was not established until 25 PCW. We also found AQP4 expression in a subpopulation of glial radial cells with processes that do not progress radially but, rather, curve following white matter tracts (corpus callosum and fornix), which were considered as glial stem cells (GSC). Under hydrocephalic conditions, GSC adjacent to characteristic ventricular zone disruption showed signs of early differentiation into astrocytes which may affect normal gliogenesis and contribute to the white matter dysgenesis. Finally, we found that AQP4 is expressed in the microvesicle fraction (p < 0.01) of CSF from patients with obstructive hydrocephalus. These findings suggest the potential use of AQP4 as a diagnostic and prognostic marker of pediatric hydrocephalus and as gliogenesis biomarker.

Progress and challenges in the comprehensive management of chronic viral hepatitis: Key ways to achieve the elimination.

Chronic viral hepatitis is a significant health problem throughout the world, which already represents high annual mortality. By 2040, chronic viral hepatitis due to virus B and virus C and their complications cirrhosis and hepatocellular carcinoma will be more deadly than malaria, vitellogenesis-inhibiting hormone, and tuberculosis altogether. In this review, we analyze the global impact of chronic viral hepatitis with a focus on the most vulnerable groups, the goals set by the World Health Organization for the year 2030, and the key points to achieve them, such as timely access to antiviral treatment of direct-acting antiviral, which represents the key to achieving hepatitis C virus elimination. Likewise, we review the strategies to prevent transmission and achieve control of hepatitis B virus. Finally, we address the impact that the coronavirus disease 2019 pandemic has had on implementing elimination strategies and the advantages of implementing telemedicine programs.

[Autism spectrum disorder biomarkers based on biosignals, virtual reality and artificial intelligence]. / Biomarcadores del trastorno del especto autista basados en bioseñales, realidad virtual e inteligencia artificial.

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. A growing scientific activity proposes the use of implicit measures based on biosignals for the classification of ASD. Virtual reality (VR) technologies have demonstrated potential for ASD interventions, but most of the work has used virtual reality for the learning / objective of interventions. Very few studies have used biological signals for recording and detailed analysis of behavioral responses that can be used to monitor or produce changes over time. In this paper the concept of behavioral biomarkers based on VR or VRBB is introduced. VRBB will allow the classification of ASD using a paradigm of computational psychiatry based on implicit brain processes measured through psychophysiological signals and the behavior of subjects exposed to complex replicas of social conditions using virtual reality interfaces.

Se ha observado que la estratificación de trastornos del espectro autista (TEA) generada por las escalas actuales no es efectiva para la personalización de tratamientos tempranos. La evaluación clínica de TEA requiere su consideración como un continuo de déficits, y existe la necesidad de identificar parámetros biológicamente significativos (biomarcadores) que tengan el poder de caracterizar automáticamente a cada individuo en diferentes etapas del desarrollo neurológico. El incipiente campo de la psiquiatría computacional (CP) intenta satisfacer las necesidades de diagnóstico de precisión mediante el desarrollo de potentes técnicas computacionales y matemáticas. Una creciente actividad científica propone el uso de medidas implícitas basadas en bioseñales para la clasificación de ASD. Las tecnologías de realidad virtual (VR) han demostrado potencial para las intervenciones de TEA, pero la mayoría de los trabajos han utilizado la realidad virtual para el aprendizaje / objetivo de las intervenciones. Muy pocos estudios han utilizado señales biológicas para el registro y el análisis detallado de las respuestas conductuales que se pueden utilizar para monitorear o producir cambios a lo largo del tiempo. En el presente trabajo se introduce el concepto de biomarcadores conductuales basados en VR o VRBB. Los VRBB van a permitir la clasificación de TEA utilizando un paradigma de psiquiatría computacional basado en procesos cerebrales implícitos medidos a través de señales psicofisiológicas y el comportamiento de sujetos expuestos a complejas réplicas de condiciones sociales utilizando interfaces de realidad virtual.

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. On one side, cutting-edge technologies, such as cameras, sensors, and virtual reality can accurately detect and classify behavioral biomarkers, as body movements in real-life simulations. On the other, machine-learning techniques are showing the potential for identifying and classifying patients' subgroups. Starting from these premises, three real-simulated imitation tasks have been implemented in a virtual reality system whose aim is to investigate if machine-learning methods on movement features and frequency could be useful in discriminating ASD children from children with typical neurodevelopment. In this experiment, 24 children with ASD and 25 children with typical neurodevelopment participated in a multimodal virtual reality experience, and changes in their body movements were tracked by a depth sensor camera during the presentation of visual, auditive, and olfactive stimuli. The main results showed that ASD children presented larger body movements than TD children, and that head, trunk, and feet represent the maximum classification with an accuracy of 82.98%. Regarding stimuli, visual condition showed the highest accuracy (89.36%), followed by the visual-auditive stimuli (74.47%), and visual-auditive-olfactory stimuli (70.21%). Finally, the head showed the most consistent performance along with the stimuli, from 80.85% in visual to 89.36% in visual-auditive-olfactory condition. The findings showed the feasibility of applying machine learning and virtual reality to identify body movements' biomarkers that could contribute to improving ASD diagnosis.

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. Recently, there has been a growing need for more objective, reliable, and valid diagnostic measures, such as biomarkers, to distinguish typical from atypical functioning and to reliably track the progression of the illness, helping to diagnose ASD. Implicit measures and ecological valid settings have been showing high accuracy on predicting outcomes and correctly classifying populations in categories. METHODS: Two experiments investigated whether sensory processing can discriminate between ASD and typical development (TD) populations using electrodermal activity (EDA) in two multimodal virtual environments (VE): forest VE and city VE. In the first experiment, 24 children with ASD diagnosis and 30 TDs participated in both virtual experiences, and changes in EDA have been recorded before and during the presentation of visual, auditive, and olfactive stimuli. In the second experiment, 40 children have been added to test the model of experiment 1. RESULTS: The first exploratory results on EDA comparison models showed that the integration of visual, auditive, and olfactive stimuli in the forest environment provided higher accuracy (90.3%) on sensory dysfunction discrimination than specific stimuli. In the second experiment, 92 subjects experienced the forest VE, and results on 72 subjects showed that stimuli integration achieved an accuracy of 83.33%. The final confirmatory test set (n = 20) achieved 85% accuracy, simulating a real application of the models. Further relevant result concerns the visual stimuli condition in the first experiment, which achieved 84.6% of accuracy in recognizing ASD sensory dysfunction. CONCLUSION: According to our studies' results, implicit measures, such as EDA, and ecological valid settings can represent valid quantitative methods, along with traditional assessment measures, to classify ASD population, enhancing knowledge on the development of relevant specific treatments.

Realidad virtual y biomarcadores digitales: una herramienta clínica para el diagnóstico del autismo / Virtual reality and digital biomarkers: a clinical tool for early autism diagnosis

Resumen Introducción : El Trastorno del Espectro Autista (TEA) es un trastorno del neurodesarrollo, y sus procedimien tos tradicionales de evaluación encuentran ciertas li mitaciones. El actual campo de investigación sobre TEA está explorando y respaldando métodos innovadores para evaluar el trastorno tempranamente, basándose en la detección automática de biomarcadores. Sin embargo, muchos de estos procedimientos carecen de validez ecológica en sus mediciones. En este contexto, la reali dad virtual (RV) presenta un prometedor potencial para registrar objetivamente bioseñales mientras los usuarios experimentan situaciones ecológicas. Métodos : Este estudio describe un novedoso y lúdi co procedimiento de RV para la evaluación temprana del TEA, basado en la grabación multimodal de bio señales. Durante una experiencia de RV con 12 esce nas virtuales, se midieron la mirada, las habilidades motoras, la actividad electrodermal y el rendimiento conductual en 39 niños con TEA y 42 compañeros de control. Se desarrollaron modelos de aprendizaje automático para identificar biomarcadores digitales y clasificar el autismo. Resultados : Las bioseñales reportaron un rendimien to variado en la detección del TEA, mientras que el modelo resultante de la combinación de los modelos de las bioseñales demostró la capacidad de identificar el TEA con una precisión del 83% (DE = 3%) y un AUC de 0.91 (DE = 0.04). Discusión : Esta herramienta de detección pue de respaldar el diagnóstico del TEA al reforzar los resultados de los procedimientos tradicionales de evaluación.

Abstract Introduction : Autism Spectrum Disorder (ASD) is a neurodevelopmental condition which traditional as sessment 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. How ever, many of these procedures lack ecological validity in their measurements. In this context, virtual reality (VR) shows promise for objectively recording biosignals while users experience ecological situations. Methods : This study outlines a novel and playful VR procedure for the early assessment of ASD, relying on multimodal biosignal recording. During a VR experience featuring 12 virtual scenes, eye gaze, motor skills, elec trodermal activity and behavioural performance were measured in 39 children with ASD and 42 control peers. Machine learning models were developed to identify digital biomarkers and classify autism. Results : Biosignals reported varied performance in detecting ASD, while the combined model resulting from the combination of specific-biosignal models demon strated the ability to identify ASD with an accuracy of 83% (SD = 3%) and an AUC of 0.91 (SD = 0.04). Discussion : This screening tool may support ASD diagnosis by reinforcing the outcomes of traditional assessment procedures.

AQP1 Overexpression in the CSF of Obstructive Hydrocephalus and Inversion of Its Polarity in the Choroid Plexus of a Chiari Malformation Type II Case.

The choroid plexus (ChP) is involved in the production of cerebrospinal fluid (CSF) and is intimately related to CSF physiopathology. Aquaporin-1 (AQP1) is the water channel directly implicated in CSF production and a potential therapeutic target in the management of CSF circulation disorders. Pathologies that present ventriculomegaly are associated with defective CSF turnover and AQPs are involved in both the production and reabsorption of CSF. This work examines the levels of AQP1 and its dynamics in ventriculomegaly conditions such as congenital hydrocephalus (communicating and obstructive) or type II lissencephaly versus control. We specifically address the expression of AQP1 in the CSF of 16 term-pregnancy infants where it was found to be significantly increased in obstructive cases when compared with communicating hydrocephalus or control patients. We also defined histologically the expression of AQP1 in the ChP from 6 nonsurvival preterm-pregnancy infants ranging ages between 20 and 25 gestational weeks in which AQP1 was mainly expressed at the apical pole of the ChP epithelium (ChPE) in control and lissencephalic patients. AQP1 expression from the Chiari malformation case showed an inverted polarity being expressed in the basal pole of the ChPE colocalizing with the glucose transporter 1 where this transporter is naturally located.

Malnutrition is a key prognostic factor related to high mortality-rate in patients with severe alcoholic hepatitis.

BACKGROUND AND AIM: comparatively with European or North-American populations, severe alcoholic hepatitis has a high mortality rate in Mexican population, becoming as high as 50 to 81% in those classified as ABIC B or C; this is true even when they receive specific therapy with steroids or pentoxifylline. The aim of this study was to know which clinical factors are related to early mortality (first 30 days) in Mexican patients with severe alcoholic hepatitis. SUBJECTS AND METHODS: this was a retrospective cohort study that included patients with severe alcoholic hepatitis, defined by a Maddrey's discriminant function ≥ 32, treated at a tertiary care center in a period of five years (2010 to 2015). RESULTS: seventy-six patients were included, 72 (94.7%) were males, mean age was 43 ± 9.1 year-old, and 58 (76.3%) had also cirrhosis. According to the subjective global assessment (SGA), 38 (50%) had severe malnutrition, 22 (28.9%) were at risk of malnutrition, and 16 (21.1%) were well-nourished. At 30 days, 46 patients (60.5%) died. In the multivariate analysis, only the presence of severe malnutrition was associated with 30-day mortality: OR = 6.4; 95% CI: 1.9-22.1; p = 0.003. CONCLUSIONS: the nutritional status seems to be a cardinal prognostic factor associated with early mortality (first 30 days). Malnutrition can explain the high mortality rate observed in Mexican patients with severe alcoholic hepatitis.

Systemic Hypertension Effects on the Ciliary Body and Iris. An Immunofluorescence Study with Aquaporin 1, Aquaporin 4, and Na⁺, K⁺ ATPase in Hypertensive Rats.

Aquaporin 1 (AQP1) and aquaporin 4 (AQP4) have been identified in the eye as playing an essential role in the formation of the aqueous humor along with the Na⁺/K⁺ ATPase pump. Different authors have described the relationship between blood pressure, aqueous humor production, and intraocular pressure with different conclusions, with some authors supporting a positive correlation between blood pressure and intraocular pressure while others disagree. The aim of this work was to study the effect of high blood pressure on the proteins involved in the production of aqueous humor in the ciliary body (CB) and iris. For this purpose, we used the eyes of spontaneously hypertensive rats (SHR) and their control Wistar-Kyoto rats (WKY). Immunofluorescence was performed in different eye structures to analyze the effects of hypertension in the expression of AQP1, AQP4, and the Na⁺/K⁺ ATPase α1 and α2 subunits. The results showed an increase in AQP1 and Na⁺/K⁺ ATPase α1 and a decrease in AQP4 and Na⁺/K⁺ ATPase α2 in the CB of SHR, while an increase in AQP4 and no significant differences in AQP1 were found in the iris. Therefore, systemic hypertension produced changes in the proteins implicated in the movement of water in the CB and iris that could influence the production rate of aqueous humor, which would be affected depending on the duration of systemic hypertension.