An integral renewal equation approach to behavioural epidemic models with information index.

We propose an integral model describing an epidemic of an infectious disease. The model is behavioural in the sense that the force of infection includes the information index that describes the opinion-driven human behavioural changes. The information index contains a memory kernel to mimic how the individuals maintain memory of the past values of the infection.

Mindfulness meditation styles differently modulate source-level MEG microstate dynamics and complexity.

Background: The investigation of mindfulness meditation practice, classically divided into focused attention meditation (FAM), and open monitoring meditation (OMM) styles, has seen a long tradition of theoretical, affective, neurophysiological and clinical studies. In particular, the high temporal resolution of magnetoencephalography (MEG) or electroencephalography (EEG) has been exploited to fill the gap between the personal experience of meditation practice and its neural correlates. Mounting evidence, in fact, shows that human brain activity is highly dynamic, transiting between different brain states (microstates).

Spatio-temporal modelling of COVID-19 incident cases using Richards' curve: An application to the Italian regions.

We introduce an extended generalised logistic growth model for discrete outcomes, in which spatial and temporal dependence are dealt with the specification of a network structure within an Auto-Regressive approach. A major challenge concerns the specification of the network structure, crucial to consistently estimate the canonical parameters of the generalised logistic curve, e.g.

Transcriptome analysis of human primary endothelial cells (HUVEC) from umbilical cords of gestational diabetic mothers reveals candidate sites for an epigenetic modulation of specific gene expression.

Within the complex pathological picture associated to diabetes, high glucose (HG) has "per se" effects on cells and tissues that involve epigenetic reprogramming of gene expression. In fetal tissues, epigenetic changes occur genome-wide and are believed to induce specific long term effects. Human umbilical vein endothelial cells (HUVEC) obtained at delivery from gestational diabetic women were used to study the transcriptomic effects of chronic hyperglycemia in fetal vascular cells using Affymetrix microarrays.

How the interval between prime and boost injection affects the immune response in a computational model of the immune system.

The immune system is able to respond more vigorously to the second contact with a given antigen than to the first contact. Vaccination protocols generally include at least two doses, in order to obtain high antibody titers. We want to analyze the relation between the time elapsed from the first dose (priming) and the second dose (boost) on the antibody titers.

A novel paradigm for cell and molecule interaction ontology: from the CMM model to IMGT-ONTOLOGY.

Background: Biology is moving fast toward the virtuous circle of other disciplines: from data to quantitative modeling and back to data. Models are usually developed by mathematicians, physicists, and computer scientists to translate qualitative or semi-quantitative biological knowledge into a quantitative approach. To eliminate semantic confusion between biology and other disciplines, it is necessary to have a list of the most important and frequently used concepts coherently defined.

Vaccine protocols optimization: in silico experiences.

Vaccines represent a special class of drugs, capable of stimulating immune system responses against pathogens and tumors. Vaccine development is a lengthy process that includes expensive laboratory experiments in order to assess safety and effectiveness. As the efficacy of a vaccine was demonstrated by biological/chemical investigations and pre-clinical studies, then a major problem is represented by the search for an optimal vaccination dosage.

Stability and phase transitions in a mathematical model of Duchenne muscular dystrophy.

We present a mathematical model to investigate the role of the immune system in the Duchenne muscular dystrophy disease. It is based on the assumption that the immune system contributes to the tissue damage and indeed its interaction with the muscle tissue after an initial endogenous damage can be described as a predator-prey system showing typical oscillations. In this article we investigate the dynamical properties of the system.

Comparative genomic analysis by microbial COGs self-attraction rate.

Whole genome analysis provides new perspectives to determine phylogenetic relationships among microorganisms. The availability of whole nucleotide sequences allows different levels of comparison among genomes by several approaches. In this work, self-attraction rates were considered for each cluster of orthologous groups of proteins (COGs) class in order to analyse gene aggregation levels in physical maps.

Implementation of a regulatory gene network to simulate the TH1/2 differentiation in an agent-based model of hypersensitivity reactions.

Motivation: An unbalanced differentiation of T helper cells from precursor type TH0 to the TH1 or TH2 phenotype in immune responses often leads to a pathological condition. In general, immune reactions biased toward TH1 responses may result in auto-immune diseases, while enhanced TH2 responses may cause allergic reactions. The aim of this work is to integrate a gene network of the TH differentiation in an agent-based model of the hyper-sensitivity reaction.

Simulating the G-protein cAMP pathway with a two-compartment reactive lattice gas.

Cellular signaling (or signal transduction) is the process by which extracellular signals are converted into cellular responses. Mathematical models of signaling pathways may help understanding their general regulatory principles, as well as the roles of the different components often involved in more than one pathway.The aim of the present work is to describe a discrete model in time and space to study the dynamics of the population of molecules involved in a specific pathway.

Optimization of HAART with genetic algorithms and agent-based models of HIV infection.

Motivation: Highly Active AntiRetroviral Therapies (HAART) can prolong life significantly to people infected by HIV since, although unable to eradicate the virus, they are quite effective in maintaining control of the infection. However, since HAART have several undesirable side effects, it is considered useful to suspend the therapy according to a suitable schedule of Structured Therapeutic Interruptions (STI). In the present article we describe an application of genetic algorithms (GA) aimed at finding the optimal schedule for a HAART simulated with an agent-based model (ABM) of the immune system that reproduces the most significant features of the response of an organism to the HIV-1 infection.