COVID-19 through Adverse Outcome Pathways: Building networks to better understand the disease - 3rd CIAO AOP Design Workshop.

On April 28-29, 2021, 50 scientists from different fields of expertise met for the 3rd online CIAO workshop. The CIAO project “Modelling the Pathogenesis of COVID-19 using the Adverse Outcome Pathway (AOP) framework” aims at building a holistic assembly of the available scientific knowledge on COVID-19 using the AOP framework. An individual AOP depicts the disease progression from the initial contact with the SARS-CoV-2 virus through biological key events (KE) toward an adverse outcome such as respiratory distress, anosmia or multiorgan failure.

Alzheimer disease research in the 21st century: past and current failures, new perspectives and funding priorities.

Much of Alzheimer disease (AD) research has been traditionally based on the use of animals, which have been extensively applied in an effort to both improve our understanding of the pathophysiological mechanisms of the disease and to test novel therapeutic approaches. However, decades of such research have not effectively translated into substantial therapeutic success for human patients. Here we critically discuss these issues in order to determine how existing human-based methods can be applied to study AD pathology and develop novel therapeutics.

A mathematical model of the oral glucose tolerance test illustrating the effects of the incretins.

Despite important empirical findings, current models of the oral glucose tolerance test (OGTT) do not incorporate the essential contributions of the incretin hormones, glucagon-like peptide-1 and glucose-dependent insulinotropic peptide, to glucose-stimulated insulin secretion. In order to address this deficiency, a model was, therefore, developed in which the incretins, as well as a term reflecting net hepatic glucose balance, were included. Equations modeling the changes in incretins, hepatic glucose balance, insulin and glucose were used to simulate the responses to 50 and 100 g oral glucose loads under normal conditions.

Charting epilepsy by searching for intelligence in network space with the help of evolving autonomous agents.

The problem of demarcating neural network space is formidable. A simple fully connected recurrent network of five units (binary activations, synaptic weight resolution of 10) has 3.2 *10(26) possible initial states.