Inferring structure of cortical neuronal networks from activity data: A statistical physics approach.

Understanding the relation between cortical neuronal network structure and neuronal activity is a fundamental unresolved question in neuroscience, with implications to our understanding of the mechanism by which neuronal networks evolve over time, spontaneously or under stimulation. It requires a method for inferring the structure and composition of a network from neuronal activities. Tracking the evolution of networks and their changing functionality will provide invaluable insight into the occurrence of plasticity and the underlying learning process.

Behavioral therapies for the treatment of autism spectrum disorder: A systematic review.

Introduction: Autism Spectrum Disorder (ASD) is a neurodevelopment spectrum characterized by persistent deficits in social communication and interpersonal interaction, along with restricted and repetitive patterns of behavior, interest, or activities. The appropriate screening and diagnosis must be realized to improve the children's prognosis. Moreover, appropriate treatments are necessary to promote better social integration and development.

Cost-effectiveness of a machine learning risk prediction model (LungFlag) in the selection of high-risk individuals for non-small cell lung cancer screening in Spain.

Objective: The LungFlag risk prediction model uses individualized clinical variables to identify individuals at high-risk of non-small cell lung cancer (NSCLC) for screening with low-dose computed tomography (LDCT). This study evaluates the cost-effectiveness of LungFlag implementation in the Spanish setting for the identification of individuals at high-risk of NSCLC.

Methods: A model combining a decision-tree with a Markov model was adapted to the Spanish setting to calculate health outcomes and costs over a lifetime horizon, comparing two hypothetical scenarios: screening with LungFlag versus non-screening, and screening with LungFlag versus screening the entire population meeting 2013 US Preventive Services Task Force (USPSTF) criteria.

Preserved Ratio Impaired Spirometry in US Primary Care Patients Diagnosed with Chronic Obstructive Pulmonary Disease.

Background: Preserved ratio impaired spirometry (PRISm) represents a population with spirometry results that do not meet standardized COPD obstruction criteria, yet present with high respiratory symptom burden and might benefit from respiratory management and treatment. We aimed to determine prevalence of PRISm in US primary care patients diagnosed with COPD, describe their demographic, clinical, and CT scan characteristics.

Methods: An observational registry study utilizing the US APEX COPD registry, composed of patients diagnosed with COPD aged 35+ years.