Massage Therapy Can Prevent the Risk of Autism Spectrum Disorders in Children

Background: The prevalence of people with autism spectrum disorders in some parts of the world tends to increase, in Indonesia alone, accurate and complete data and information from people with autism spectrum disorders (ASD) are still lacking, so it is feared that many children with risk symptoms of autism spectrum disorders do not get treatment early. Aim: This study aims to prevent the risk of autism spectrum disorders in children by applying massage therapy based on analysis of the Modified Check List for Autism in Toddler (M-Chat) scores. Methods: The study was conducted from May 2019 to March 2020 at three public health centers in the city of Jakarta. An analysis was carried out before and after the application of massage in a time series of four periods on 10 children aged 18-36 months with M-Chat scores, then analyzed by receiver operating characteristic (ROC) to obtain a cut off point to determine the risk status of autism spectrum disorders. Results: The results showed that there was an effect of massage therapy on the M-Chat score of children with autism spectrum disorder risk p=0.004 <0.05 and changes in the M-Chat score of children with autism spectrum disorder risk experienced significant changes after massage in the third and fourth therapy periods. with p = 0.005 and p = 0.007 < 0.05. Conclusion: The results show that massage therapy can prevent the risk of autism spectrum disorders in children based on the Modified Check List for Autism in Toddler (M-Chat). Keywords: Massage therapy, babies, autism spectrum disorders, modified checklist for autism in toddler

Psychopathological Symptoms and Well-Being in Overweight and Underweight Adolescents: A Network Analysis

Overweight and underweight adolescents have an increased risk of psychological problems and reduced quality of life. We used a network analysis approach on a variety of psychopathology and well-being variables to identify central factors in these populations. The network analysis was conducted on data of 344 overweight adolescents (>90th BMI-percentile) and 423 underweight adolescents (<10th BMI-percentile) drawn from a large community sample (10–19 years) including behavioral and emotional problems (Youth Self-Report), eating disorder risk (SCOFF) and well-being variables (KIDSCREEN). Additionally, psychopathology and well-being scores of overweight and underweight individuals were compared with 1.560 normal weight adolescents. Compared to their normal weight peers, overweight adolescents showed elevated psychopathology and eating disorder risk as well as reduced well-being. Underweight adolescents reported increased levels of internalizing problems but no increased eating disorder risk or reduced well-being. The network analysis revealed that anxious/depressed mood and attention problems were the most central and interconnected nodes for both overweight and underweight subsamples. Among underweight individuals, social problems and socially withdrawn behavior additionally functioned as a bridge between other nodes in the network. The results support psychological interventions focusing on improving mood, coping with negative emotions and tackling inner tension.

Glycemic Disorder Risk Remote Monitoring Program in the COVID-19 Very Elderly Patients: Preliminary Results

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has necessitated the use of new technologies and new processes to care for hospitalized patients, including diabetes patients. This was the basis for the “GER-e-TEC COVID study,” an experiment involving the use of the smart MyPrediTM e-platform to automatically detect the exacerbation of glycemic disorder risk in COVID-19 older diabetic patients.Methods: The MyPrediTM platform is connected to a medical analysis system that receives physiological data from medical sensors in real time and analyzes this data to generate (when necessary) alerts. An experiment was conducted between December 14th, 2020 and February 25th, 2021 to test this alert system. During this time, the platform was used on COVID-19 patients being monitored in an internal medicine COVID-19 unit at the University Hospital of Strasbourg. The alerts were compiled and analyzed in terms of sensitivity, specificity, positive and negative predictive values with respect to clinical data.Results: 10 older diabetic COVID-19 patients in total were monitored remotely, six of whom were male. The mean age of the patients was 84.1 years. The patients used the telemedicine solution for an average of 14.5 days. 142 alerts were emitted for the glycemic disorder risk indicating hyperglycemia, with an average of 20.3 alerts per patient and a standard deviation of 26.6. In our study, we did not note any hypoglycemia, so the system emitted any alerts. For the sensitivity of alerts emitted, the results were extremely satisfactory, and also in terms of positive and negative predictive values. In terms of survival analysis, the number of alerts and gender played no role in the length of the hospital stay, regardless of the reason for the hospitalization (COVID-19 management).Conclusion: This work is a pilot study with preliminary results. To date, relatively few projects and trials in diabetic patients have been run within the “telemedicine 2.0” setting, particularly using AI, ICT and the Web 2.0 in the era of COVID-19 disease.

Rapid Assessment of the Temporal Function and Phenotypic Reversibility of Neurodevelopmental Disorder Risk Genes in C. elegans

Hundreds of genes have been implicated in neurodevelopmental disorders. Previous studies have indicated that some phenotypes caused by decreased developmental function of select risk genes can be reversed by restoring gene function in adulthood. However, very few risk genes have been assessed for adult reversibility. We developed a strategy to rapidly assess the temporal requirements and phenotypic reversibility of neurodevelopmental disorder risk gene orthologs using a conditional protein degradation system and machine vision phenotypic profiling in Caenorhabditis elegans. Using this approach, we measured the effects of degrading and re-expressing orthologs of 3 neurodevelopmental risk genes EBF3, BRN3A, and DYNC1H1 across 30 morphological, locomotor, sensory, and learning phenotypes at multiple timepoints throughout development. We found some degree of phenotypic reversibility was possible for each gene studied. However, the temporal requirements of gene function and degree of phenotypic reversibility varied by gene and phenotype. The data reflects the dynamic nature of gene function and the importance of using multiple time windows of degradation and re-expression to understand the many roles a gene can play over developmental time. This work also demonstrates a strategy of using a high-throughput model system to investigate temporal requirements of gene function across a large number of phenotypes to rapidly prioritize neurodevelopmental disorder genes for re-expression studies in other organisms.