Immunization and Aging: a Learning Process in the Immune Network

The immune system can be thought as a complex network of different interacting elements. A cellular automaton, defined in shape-space, was recently shown to exhibit self-regulation and complex behavior and is, therefore, a good candidate to model the immune system. Using this model to simulate a real immune system we find good agreement with recent experiments on mice. The model exhibits the experimentally observed refractory behavior of the immune system under multiple antigen presentations as well as loss of its plasticity caused by aging.Comment: 4 latex pages, 3 postscript figures attached. To be published in Physical Review Letters (Tentatively scheduled for 5th Oct. issue

Emergence of Hierarchy on a Network of Complementary Agents

Complementarity is one of the main features underlying the interactions in biological and biochemical systems. Inspired by those systems we propose a model for the dynamical evolution of a system composed by agents that interact due to their complementary attributes rather than their similarities. Each agent is represented by a bit-string and has an activity associated to it; the coupling among complementary peers depends on their activity. The connectivity of the system changes in time respecting the constraint of complementarity. We observe the formation of a network of active agents whose stability depends on the rate at which activity diffuses in the system. The model exhibits a non-equilibrium phase transition between the ordered phase, where a stable network is generated, and a disordered phase characterized by the absence of correlation among the agents. The ordered phase exhibits multi-modal distributions of connectivity and activity, indicating a hierarchy of interaction among different populations characterized by different degrees of activity. This model may be used to study the hierarchy observed in social organizations as well as in business and other networks.Comment: 13 pages, 4 figures, submitte

On the Dynamics of the Evolution of the HIV Infection

We use a cellular automata model to study the evolution of HIV infection and the onset of AIDS. The model takes into account the global features of the immune response to any pathogen, the fast mutation rate of the HIV and a fair amount of spatial localization. Our results reproduce quite well the three-phase pattern observed in T cell and virus counts of infected patients, namely, the primary response, the clinical latency period and the onset of AIDS. We have also found that the infected cells may organize themselves into special spatial structures since the primary infection, leading to a decrease on the concentration of uninfected cells. Our results suggest that these cell aggregations, which can be associated to syncytia, leads to AIDS.Comment: 4 pages, 3 postscript figure

A Dynamic Analysis of Tuberculosis Dissemination to Improve Control and Surveillance

Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes.Instituto do Milenio REDE-TBConselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Fundacao de Amparo a Ciencia e Tecnologia do Estado de Pernambuco (FACEPE)[0012-05.03/04]Fundacao de Amparo a Ciencia e Tecnologia do Estado de Pernambuco (FACEPE)[0203-1.05/08

Four whole-istic aspects of schistosome granuloma biology: fractal arrangement, internal regulation, autopoietic component and closure

This paper centers on some whole-istic organizational and functional aspects of hepatic Schistosoma mansoni granuloma, which is an extremely complex system. First, it structurally develops a collagenic topology, originated bidirectionally from an inward and outward assembly of growth units. Inward growth appears to be originated from myofibroblasts derived from small portal vessel around intravascular entrapped eggs, while outward growth arises from hepatic stellate cells. The auto-assembly of the growth units defines the three-dimensional scaffold of the schistosome granulomas. The granuloma surface irregularity and its border presented fractal dimension equal to 1.58. Second, it is internally regulated by intricate networks of immuneneuroendocrine stimuli orchestrated by leptin and leptin receptors, substance P and Vasoactive intestinal peptide. Third, it can reach the population of ± 40,000 cells and presents an autopoietic component evidenced by internal proliferation (Ki-67+ Cells), and by expression of c-Kit+ Cells, leptin and leptin receptor (Ob-R), granulocyte-colony stimulating factor (G-CSF-R), and erythropoietin (Epo-R) receptors. Fourth, the granulomas cells are intimately connected by pan-cadherins, occludin and connexin-43, building a state of closing (granuloma closure). In conclusion, the granuloma is characterized by transitory stages in such a way that its organized structure emerges as a global property which is greater than the sum of actions of its individual cells and extracellular matrix components

European Physical Journal - Special Topics

Texto completo: acesso restrito. p. 125-132Malaria is an important cause of morbidity and mortality worldwide. One striking aspect regarding malaria is the fact that individuals living in endemic areas do not develop immunity against the parasite, falling ill whenever they are exposed to the parasite. The understanding of why immunity is not developed in the usual way against Plasmodium is crucial to the improvement of treatment and prevention. In this work, we study some aspects of the dynamics of the blood cycle of malaria using both modelling and data analysis of observed case-histories described by parasitemia time series. By comparing our simulations with experimental results we have shown that the different behaviour observed among patients may be associated to differences in the efficiency of the immune system to control the infection

On the study of the dynamical aspects of parasitemia in the blood cycle of malaria

Malaria is an important cause of morbidity and mortality worldwide. One striking aspect regarding malaria is the fact that individuals living in endemic areas do not develop immunity against the parasite, falling ill whenever they are exposed tothe parasite. The understanding of why immunity is not developed in the usual way against Plasmodium is crucial to the improvement of treatment and prevention. In this work, we study some aspects of the dynamics of the blood cycle of malaria using both modelling and data analysis of observed case-histories described by parasitemia time series. By comparing our simulations with experimental results we have shown that the different behaviour observed among patients may be associated to differences in the efficiency of the immune system to control the infection. © EDP Sciences/Societa Italiana di Fisica/Springer-Verlag 2007