Developing capacity in health informatics in a resource poor setting: lessons from Peru

The public sectors of developing countries require strengthened capacity in health informatics. In Peru, where formal university graduate degrees in biomedical and health informatics were lacking until recently, the AMAUTA Global Informatics Research and Training Program has provided research and training for health professionals in the region since 1999. The Fogarty International Center supports the program as a collaborative partnership between Universidad Peruana Cayetano Heredia in Peru and the University of Washington in the United States of America. The program aims to train core professionals in health informatics and to strengthen the health information resource capabilities and accessibility in Peru. The program has achieved considerable success in the development and institutionalization of informatics research and training programs in Peru. Projects supported by this program are leading to the development of sustainable training opportunities for informatics and eight of ten Peruvian fellows trained at the University of Washington are now developing informatics programs and an information infrastructure in Peru. In 2007, Universidad Peruana Cayetano Heredia started offering the first graduate diploma program in biomedical informatics in Peru

Modelling the effects of environmental heterogeneity within the lung on the tuberculosis life-cycle

Funding: This work was supported by the Medical Research Council [grant number MR/P014704/1] and the PreDiCT-TB consortium (IMI Joint undertaking grant agreement number 115337, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EF-PIA companies’ in kind contribution.Progress in shortening the duration of tuberculosis (TB) treatment is hampered by the lack of a predictive model that accurately reflects the diverse environment within the lung. This is important as TB has been shown to produce distinct localisations to different areas of the lung during different disease stages, with the environmental heterogeneity within the lung of factors such as air ventilation, blood perfusion and oxygen tension believed to contribute to the apical localisation witnessed during the post-primary form of the disease. Building upon our previous model of environmental lung heterogeneity, we present a networked metapopulation model that simulates TB across the whole lung, incorporating these notions of environmental heterogeneity across the whole TB life-cycle to show how different stages of the disease are influenced by different environmental and immunological factors. The alveolar tissue in the lung is divided into distinct patches, with each patch representing a portion of the total tissue and containing environmental attributes that reflect the internal conditions at that location. We include populations of bacteria and immune cells in various states, and events are included which determine how the members of the model interact with each other and the environment. By allowing some of these events to be dependent on environmental attributes, we create a set of heterogeneous dynamics, whereby the location of the tissue within the lung determines the disease pathological events that occur there. Our results show that the environmental heterogeneity within the lung is a plausible driving force behind the apical localisation during post-primary disease. After initial infection, bacterial levels will grow in the initial infection location at the base of the lung until an adaptive immune response is initiated. During this period, bacteria are able to disseminate and create new lesions throughout the lung. During the latent stage, the lesions that are situated towards the apex are the largest in size, and once a post-primary immune-suppressing event occurs, it is the uppermost lesions that reach the highest levels of bacterial proliferation. Our sensitivity analysis also shows that it is the differential in blood perfusion, causing reduced immune activity towards the apex, which has the biggest influence of disease outputs.Publisher PDFPeer reviewe

An Agent-Based Model to study the epidemiological and evolutionary dynamics of Influenza viruses

<p>Abstract</p> <p>Background</p> <p>Influenza A viruses exhibit complex epidemiological patterns in a number of mammalian and avian hosts. Understanding transmission of these viruses necessitates taking into account their evolution, which represents a challenge for developing mathematical models. This is because the phrasing of multi-strain systems in terms of traditional compartmental ODE models either requires simplifying assumptions to be made that overlook important evolutionary processes, or leads to complex dynamical systems that are too cumbersome to analyse.</p> <p>Results</p> <p>Here, we develop an Individual-Based Model (IBM) in order to address simultaneously the ecology, epidemiology and evolution of strain-polymorphic pathogens, using Influenza A viruses as an illustrative example.</p> <p>Conclusions</p> <p>We carry out careful validation of our IBM against comparable mathematical models to demonstrate the robustness of our algorithm and the sound basis for this novel framework. We discuss how this new approach can give critical insights in the study of influenza evolution.</p

Immune control of HIV-1 infection after therapy interruption: immediate versus deferred antiretroviral therapy

Abstract Background The optimal stage for initiating antiretroviral therapies in HIV-1 bearing patients is still a matter of debate. Methods We present computer simulations of HIV-1 infection aimed at identifying the pro et contra of immediate as compared to deferred Highly Active Antiretroviral Therapy (HAART). Results Our simulations highlight that a prompt specific CD8+ cytotoxic T lymphocytes response is detected when therapy is delayed. Compared to very early initiation of HAART, in deferred treated patients CD8+ T cells manage to mediate the decline of viremia in a shorter time and, at interruption of therapy, the virus experiences a stronger immune pressure. We also observe, however, that the immunological effects of the therapy fade with time in both therapeutic regimens. Thus, within one year from discontinuation, viral burden recovers to the value at which it would level off in the absence of therapy. In summary, simulations show that immediate therapy does not prolong the disease-free period and does not confer a survival benefit when compared to treatment started during the chronic infection phase. Conclusion Our conclusion is that, since there is no therapy to date that guarantees life-long protection, deferral of therapy should be preferred in order to minimize the risk of adverse effects, the occurrence of drug resistances and the costs of treatment.</p

Modeling lymphocyte homing and encounters in lymph nodes

International audienceBackgroundThe efficiency of lymph nodes depends on tissue structure and organization, which allow the coordination of lymphocyte traffic. Despite their essential role, our understanding of lymph node specific mechanisms is still incomplete and currently a topic of intense research.ResultsIn this paper, we present a hybrid discrete/continuous model of the lymph node, accounting for differences in cell velocity and chemotactic response, influenced by the spatial compartmentalization of the lymph node and the regulation of cells migration, encounter, and antigen presentation during the inflammation process.ConclusionOur model reproduces the correct timing of an immune response, including the observed time delay between duplication of T helper cells and duplication of B cells in response to antigen exposure. Furthermore, we investigate the consequences of the absence of dendritic cells at different times during infection, and the dependence of system dynamics on the regulation of lymphocyte exit from lymph nodes. In both cases, the model predicts the emergence of an impaired immune response, i.e., the response is significantly reduced in magnitude. Dendritic cell removal is also shown to delay the response time with respect to normal conditions

Bayesian Approach to Model CD137 Signaling in Human M.tuberculosis in vitro Responses

Abstract Immune responses are qualitatively and quantitatively influenced by a complex network of receptor-ligand interactions. Among them, the CD137:CD137L pathway is known to modulate innate and adaptive human responses against Mycobacterium tuberculosis. However, the underlying mechanisms of this regulation remain unclear. In this work, we developed a Bayesian Computational Model (BCM) of in vitro CD137 signaling, devised to fit previously gathered experimental data. The BCM is fed with the data and the prior distribution of the model parameters and it returns theirposterior distribution and the model evidence, which allows comparing alternative signaling mechanisms. The BCM uses a coupled system of non-linear differential equations to describe the dynamics of Antigen Presenting Cells, Natural Killer and T Cells together with the interpheron (IFN)-c and tumor necrosis factor (TNF)-a levels in the media culture. Fast and complete mixing of the media is assumed. The prior distribution of the parameters that describe the dynamics of the immunological response was obtained from the literature and theoretical considerations Our BCM applies successively the Levenberg-Marquardt algorithm to find the maximum a posteriori likelihood (MAP); the Metropolis Markov Chain Monte Carlo method to approximate the posterior distribution of the parameters and Thermodynamic Integration to calculate the evidence of alternative hypothesis. Bayes factors provided decisive evidence favoring direct CD137 signaling on T cells. Moreover, the posterior distribution of the parameters that describe the CD137 signaling showed that the regulation of IFNc levels is based more on T cells survival than on direct induction. Furthermore, the mechanisms that account for the effect of CD137 signaling on TNF-a production were based on a decrease of TNF-a production by APC and, perhaps, on the increase in APC apoptosis. BCM proved to be a useful tool to gain insight on the mechanisms of CD137 signaling during human response against Mycobacterium tuberculosis.Fil: Darío A Fernández Do Porto. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. INST QUIM FISICA D/L/MATERIALES MED AMB Y ENERG.Fil: Jerónimo Auzmendi. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. INST QUIM FISICA D/L/MATERIALES MED AMB Y ENERG.Fil: Delfina Peña. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. CONSEJO NAC.DE INVEST.CIENTIF.Y TECNICAS. OFICINA DE COORDINACION ADMINISTRATIVA CIUDAD UNIVERSITARIA. INSTITUTO DE QUIMICA BIOLOGICA DE LA FACULTAD DE CS. EXACTAS Y NATURALES. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. DTO.DE QUIMICA BIOLOGICA.Fil: Veronica E Garcia. CONSEJO NAC.DE INVEST.CIENTIF.Y TECNICAS. OFICINA DE COORDINACION ADMINISTRATIVA CIUDAD UNIVERSITARIA. INSTITUTO DE QUIMICA BIOLOGICA DE LA FACULTAD DE CS. EXACTAS Y NATURALES.Fil: Luciano Moffatt. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. INST QUIM FISICA D/L/MATERIALES MED AMB Y ENERG

The equilibria that allow bacterial persistence in human hosts

We propose that microbes that have developed persistent relationships with human hosts have evolved cross-signalling mechanisms that permit homeostasis that conforms to Nash equilibria and, more specifically, to evolutionarily stable strategies. This implies that a group of highly diverse organisms has evolved within the changing contexts of variation in effective human population size and lifespan, shaping the equilibria achieved, and creating relationships resembling climax communities. We propose that such ecosystems contain nested communities in which equilibrium at one level contributes to homeostasis at another. The model can aid prediction of equilibrium states in the context of further change: widespread immunodeficiency, changing population densities, or extinctions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62883/1/nature06198.pd

Immune Subversion and Quorum-Sensing Shape the Variation in Infectious Dose among Bacterial Pathogens

Many studies have been devoted to understand the mechanisms used by pathogenic bacteria to exploit human hosts. These mechanisms are very diverse in the detail, but share commonalities whose quantification should enlighten the evolution of virulence from both a molecular and an ecological perspective. We mined the literature for experimental data on infectious dose of bacterial pathogens in humans (ID50) and also for traits with which ID50 might be associated. These compilations were checked and complemented with genome analyses. We observed that ID50 varies in a continuous way by over 10 orders of magnitude. Low ID50 values are very strongly associated with the capacity of the bacteria to kill professional phagocytes or to survive in the intracellular milieu of these cells. Inversely, high ID50 values are associated with motile and fast-growing bacteria that use quorum-sensing based regulation of virulence factors expression. Infectious dose is not associated with genome size and shows insignificant phylogenetic inertia, in line with frequent virulence shifts associated with the horizontal gene transfer of a small number of virulence factors. Contrary to previous proposals, infectious dose shows little dependence on contact-dependent secretion systems and on the natural route of exposure. When all variables are combined, immune subversion and quorum-sensing are sufficient to explain two thirds of the variance in infectious dose. Our results show the key role of immune subversion in effective human infection by small bacterial populations. They also suggest that cooperative processes might be important for successful infection by bacteria with high ID50. Our results suggest that trade-offs between selection for population growth-related traits and selection for the ability to subvert the immune system shape bacterial infectiousness. Understanding these trade-offs provides guidelines to study the evolution of virulence and in particular the micro-evolutionary paths of emerging pathogens

CIBERER : Spanish national network for research on rare diseases: A highly productive collaborative initiative

Altres ajuts: Instituto de Salud Carlos III (ISCIII); Ministerio de Ciencia e Innovación.CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research