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Search Results: 1 - 10 of 128886 matches for " Pietro Lió "
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A new approach for epileptic seizure detection: sample entropy based feature extraction and extreme learning machine  [PDF]
Yuedong Song, Pietro Liò
Journal of Biomedical Science and Engineering (JBiSE) , 2010, DOI: 10.4236/jbise.2010.36078
Abstract: The electroencephalogram (EEG) signal plays a key role in the diagnosis of epilepsy. Substantial data is generated by the EEG recordings of ambulatory recording systems, and detection of epileptic activity requires a time-consuming analysis of the complete length of the EEG time series data by a neurology expert. A variety of automatic epilepsy detection systems have been developed during the last ten years. In this paper, we investigate the potential of a recently-proposed statistical measure parameter regarded as Sample Entropy (SampEn), as a method of feature extraction to the task of classifying three different kinds of EEG signals (normal, interictal and ictal) and detecting epileptic seizures. It is known that the value of the SampEn falls suddenly during an epileptic seizure and this fact is utilized in the proposed diagnosis system. Two different kinds of classification models, back-propagation neural network (BPNN) and the recently-developed extreme learning machine (ELM) are tested in this study. Results show that the proposed automatic epilepsy detection system which uses sample entropy (SampEn) as the only input feature, together with extreme learning machine (ELM) classification model, not only achieves high classification accuracy (95.67%) but also very fast speed.
Modelling infection spreading control in a hospital isolation room  [PDF]
Carla Balocco, Pietro Liò
Journal of Biomedical Science and Engineering (JBiSE) , 2010, DOI: 10.4236/jbise.2010.37089
Abstract: This paper investigates the airflow patterns connected to different cough conditions, the effects of these arrangements on the regions of droplet fallout and dilution time of virus diffusion of coughed gas. We focus on some of the physical processes that occur in a double bed hospital isolation room, investigating the effect of the ventilation system on the spread of particles in air. A cough model was carried out and used for the numerical simulation of virus diffusion inside an existent isolation room. Transient simulations of air pattern diffusion and air velocity field, provided by the existing typical HVAC primary air system designed for infectious patients, were performed using CFD. A multiphysics approach, combined Convection-Conduction, Incompressible Navier-Stokes models on non-isothermal air flow and Convection-Diffusion, was used. Simulations results highlighted that the flow field and velocity distribution induced by the high turbulence air inlet diffuser combined with the air return diffusers produce wide recirculation zones near the wall and partial stagnation areas near the ceiling and between the two beds, but lower particle concentration in the room and their shorter spreading distance. This type of analysis is certainly cost effective to identify all the air recirculation zones which can harbour lingering pathogens.
Community Structure in Social Networks: Applications for Epidemiological Modelling
Stephan Kitchovitch, Pietro Liò
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0022220
Abstract: During an infectious disease outbreak people will often change their behaviour to reduce their risk of infection. Furthermore, in a given population, the level of perceived risk of infection will vary greatly amongst individuals. The difference in perception could be due to a variety of factors including varying levels of information regarding the pathogen, quality of local healthcare, availability of preventative measures, etc. In this work we argue that we can split a social network, representing a population, into interacting communities with varying levels of awareness of the disease. We construct a theoretical population and study which such communities suffer most of the burden of the disease and how their awareness affects the spread of infection. We aim to gain a better understanding of the effects that community-structured networks and variations in awareness, or risk perception, have on the disease dynamics and to promote more community-resolved modelling in epidemiology.
Generazione di ibridi, generazione di donne. Costruzioni dell’umano in Aristotele e Galeno (e Palefato)
Pietro Li Causi
Storia delle Donne , 2005,
Abstract: Denying or rationalizing the mythical monstrous hybrids in Aristotle, Palaephatus and Galen is also making use of the animal as a keystone for the construction of human. In such sense, through the reflection on centaurs and monsters, the three authors build the sphere of human as tendentially separated from animal’s. This sphere also tends to include the woman seen as a “dimensional door to theriomorfic alterity”, then as a threat to identity.
Modeling TGF-β in Early Stages of Cancer Tissue Dynamics
Gianluca Ascolani, Pietro Liò
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0088533
Abstract: Recent works have highlighted a double role for the Transforming Growth Factor (-): it inhibits cancer in healthy cells and potentiates tumor progression during late stage of tumorigenicity, respectively; therefore it has been termed the “Jekyll and Hyde” of cancer or, alternatively, an “excellent servant but a bad master”. It remains unclear how this molecule could have the two opposite behaviours. In this work, we propose a - multi scale mathematical model at molecular, cellular and tissue scales. The multi scalar behaviours of the - are described by three coupled models built up together which can approximatively be related to distinct microscopic, mesoscopic, and macroscopic scales, respectively. We first model the dynamics of - at the single-cell level by taking into account the intracellular and extracellular balance and the autocrine and paracrine behaviour of -. Then we use the average estimates of the - from the first model to understand its dynamics in a model of duct breast tissue. Although the cellular model and the tissue model describe phenomena at different time scales, their cumulative dynamics explain the changes in the role of - in the progression from healthy to pre-tumoral to cancer. We estimate various parameters by using available gene expression datasets. Despite the fact that our model does not describe an explicit tissue geometry, it provides quantitative inference on the stage and progression of breast cancer tissue invasion that could be compared with epidemiological data in literature. Finally in the last model, we investigated the invasion of breast cancer cells in the bone niches and the subsequent disregulation of bone remodeling processes. The bone model provides an effective description of the bone dynamics in healthy and early stages cancer conditions and offers an evolutionary ecological perspective of the dynamics of the competition between cancer and healthy cells.
Computational Modeling, Formal Analysis, and Tools for Systems Biology
Ezio Bartocci?,Pietro Lió
PLOS Computational Biology , 2016, DOI: 10.1371/journal.pcbi.1004591
Abstract: As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science.
Modeling perisaccadic time perception  [PDF]
Andrea Guazzini, Pietro Liò, Andrea Passarella, Marco Conti
Journal of Biomedical Science and Engineering (JBiSE) , 2010, DOI: 10.4236/jbise.2010.312147
Abstract: There is an impressive scarcity of quantitative models of the clock patterns in the brain. We propose a mesoscopic approach, i.e. neither a description at single neuron level, nor at systemic level/too coarse granularity, of the time perception at the time of the saccade. This model uses functional pathway knowledge and is inspired by, and integrates, recent findings in both psychophysics and neurophysiology. Perceived time delays in the perisaccadic window are shown numerically consistent with recent experimental measures. Our model provides explanation for several experimental outcomes on saccades, estimates popu-lation variance of the error in time perception and represent a meaningful example for bridging psychophysics and neurophysiology. Finally we found that the insights into information processing during saccadic events lead to considerations on engineering exploitation of the underlying phenomena.
The Puzzling Role of CXCR4 in Human Immunodeficiency Virus Infection
Elisa Vicenzi, Pietro Liò, Guido Poli
Theranostics , 2013,
Abstract: The human immunodeficiency virus type-1 (HIV-1) is the etiological agent of the acquired immunodeficiency syndrome (AIDS), a disease highly lethal in the absence of combination antiretroviral therapy. HIV infects CD4+ cells of the immune system (T cells, monocyte-macrophages and dendritic cells) via interaction with a universal primary receptor, the CD4 molecule, followed by a mandatory interaction with a second receptor (co-receptor) belonging to the chemokine receptor family. Apart from some rare cases, two chemokine receptors have been evolutionarily selected to accomplish this need for HIV-1: CCR5 and CXCR4. Yet, usage of these two receptors appears to be neither casual nor simply explained by their levels of cell surface expression. While CCR5 use is the universal rule at the start of every infection regardless of the transmission route (blood-related, sexual or mother to child), CXCR4 utilization emerges later in disease coinciding with the immunological deficient phase of infection. Moreover, in most instances CXCR4 use as viral entry co-receptor is associated with maintenance of CCR5 use. Since antiviral agents preventing CCR5 utilization by the virus are already in use, while others targeting either CCR5 or CXCR4 (or both) are under investigation, understanding the biological correlates of this “asymmetrical” utilization of HIV entry co-receptors bears relevance for the clinical choice of which therapeutics should be administered to infected individuals. We will here summarize the basic knowledge and the hypotheses underlying the puzzling and yet unequivocal role of CXCR4 in HIV-1 infection.
Multiple verification in computational modeling of bone pathologies
Pietro Liò,Emanuela Merelli,Nicola Paoletti
Electronic Proceedings in Theoretical Computer Science , 2011, DOI: 10.4204/eptcs.67.8
Abstract: We introduce a model checking approach to diagnose the emerging of bone pathologies. The implementation of a new model of bone remodeling in PRISM has led to an interesting characterization of osteoporosis as a defective bone remodeling dynamics with respect to other bone pathologies. Our approach allows to derive three types of model checking-based diagnostic estimators. The first diagnostic measure focuses on the level of bone mineral density, which is currently used in medical practice. In addition, we have introduced a novel diagnostic estimator which uses the full patient clinical record, here simulated using the modeling framework. This estimator detects rapid (months) negative changes in bone mineral density. Independently of the actual bone mineral density, when the decrease occurs rapidly it is important to alarm the patient and monitor him/her more closely to detect insurgence of other bone co-morbidities. A third estimator takes into account the variance of the bone density, which could address the investigation of metabolic syndromes, diabetes and cancer. Our implementation could make use of different logical combinations of these statistical estimators and could incorporate other biomarkers for other systemic co-morbidities (for example diabetes and thalassemia). We are delighted to report that the combination of stochastic modeling with formal methods motivate new diagnostic framework for complex pathologies. In particular our approach takes into consideration important properties of biosystems such as multiscale and self-adaptiveness. The multi-diagnosis could be further expanded, inching towards the complexity of human diseases. Finally, we briefly introduce self-adaptiveness in formal methods which is a key property in the regulative mechanisms of biological systems and well known in other mathematical and engineering areas.
Disease processes as hybrid dynamical systems
Pietro Liò,Emanuela Merelli,Nicola Paoletti
Electronic Proceedings in Theoretical Computer Science , 2012, DOI: 10.4204/eptcs.92.11
Abstract: We investigate the use of hybrid techniques in complex processes of infectious diseases. Since predictive disease models in biomedicine require a multiscale approach for understanding the molecule-cell-tissue-organ-body interactions, heterogeneous methodologies are often employed for describing the different biological scales. Hybrid models provide effective means for complex disease modelling where the action and dosage of a drug or a therapy could be meaningfully investigated: the infection dynamics can be classically described in a continuous fashion, while the scheduling of multiple treatment discretely. We define an algebraic language for specifying general disease processes and multiple treatments, from which a semantics in terms of hybrid dynamical system can be derived. Then, the application of control-theoretic tools is proposed in order to compute the optimal scheduling of multiple therapies. The potentialities of our approach are shown in the case study of the SIR epidemic model and we discuss its applicability on osteomyelitis, a bacterial infection affecting the bone remodelling system in a specific and multiscale manner. We report that formal languages are helpful in giving a general homogeneous formulation for the different scales involved in a multiscale disease process; and that the combination of hybrid modelling and control theory provides solid grounds for computational medicine.
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