57 research outputs found

    Explicit kinetic heterogeneity: mechanistic models for interpretation of labeling data of heterogeneous cell populations

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    Estimation of division and death rates of lymphocytes in different conditions is vital for quantitative understanding of the immune system. Deuterium, in the form of deuterated glucose or heavy water, can be used to measure rates of proliferation and death of lymphocytes in vivo. Inferring these rates from labeling and delabeling curves has been subject to considerable debate with different groups suggesting different mathematical models for that purpose. We show that the three models that are most commonly used are in fact mathematically identical and differ only in their interpretation of the estimated parameters. By extending these previous models, we here propose a more mechanistic approach for the analysis of data from deuterium labeling experiments. We construct a model of "kinetic heterogeneity" in which the total cell population consists of many sub-populations with different rates of cell turnover. In this model, for a given distribution of the rates of turnover, the predicted fraction of labeled DNA accumulated and lost can be calculated. Our model reproduces several previously made experimental observations, such as a negative correlation between the length of the labeling period and the rate at which labeled DNA is lost after label cessation. We demonstrate the reliability of the new explicit kinetic heterogeneity model by applying it to artificially generated datasets, and illustrate its usefulness by fitting experimental data. In contrast to previous models, the explicit kinetic heterogeneity model 1) provides a mechanistic way of interpreting labeling data; 2) allows for a non-exponential loss of labeled cells during delabeling, and 3) can be used to describe data with variable labeling length

    Collaborative planning approach to inform the implementation of a healthcare manager intervention for hispanics with serious mental illness: a study protocol

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    Background: This study describes a collaborative planning approach that blends principles of community-based participatory research (CBPR) and intervention mapping to modify a healthcare manager intervention to a new patient population and provider group and to assess the feasibility and acceptability of this modified intervention to improve the physical health of Hispanics with serious mental illness (SMI) and at risk for cardiovascular disease (CVD). Methods: The proposed study uses a multiphase approach that applies CBPR principles and intervention-mapping steps--an intervention-planning approach--to move from intervention planning to pilot testing. In phase I, a community advisory board composed of researchers and stakeholders will be assembled to learn and review the intervention and make initial modifications. Phase II uses a combination of qualitative methods--patient focus groups and stakeholder interviews--to ensure that the modifications are acceptable to all stakeholders. Phase III uses results from phase II to further modify the intervention, develop an implementation plan, and train two care managers on the modified intervention. Phase IV consists of a 12-month open pilot study (N = 30) to assess the feasibility and acceptability of the modified intervention and explore its initial effects. Lastly, phase V consists of analysis of pilot study data and preparation for future funding to develop a more rigorous evaluation of the modified intervention. Discussion: The proposed study is one of the few projects to date to focus on improving the physical health of Hispanics with SMI and at risk for CVD by using a collaborative planning approach to enhance the transportability and use of a promising healthcare manager intervention. This study illustrates how blending health-disparities research and implementation science can help reduce the disproportionate burden of medical illness in a vulnerable population

    Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

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    The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a “middle-out” strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from “-omics” signatures are identified as key elements of a successful systems biology modeling approach in nutrition research—one that integrates physiological mechanisms and data at multiple space and time scales

    The behaviour of repeat visitors to museums: Review and empirical findings

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    This study presents a theoretical and operational framework for analysing repeat visit to museums. Starting from the literature on repeat visit in tourism, the specificities of these cultural attractions are made explicit through a review of theoretical and applied works. Consistently with previous contributors, the paper suggests that the analysis of actual past behaviours has to be preferred to the one of attitudes. The application of proper econometric models is also remarked in order to put into account individual profiles. Information coming from three techniques is then used in an integrated way in order to provide a more comprehensive view of the phenomenon. Evidence from an ad hoc survey suggests the necessity to give a greater attention to perceived cultural value during the visit, promoting cultural events during the week and addressed to children, and taking care of those visitors that come from far places also through an integrated tourist supply. © 2013 Springer Science+Business Media Dordrecht

    Chemokine Coreceptor Signaling in HIV-1 Infection and Pathogenesis

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    Binding of the HIV-1 envelope to its chemokine coreceptors mediates two major biological events: membrane fusion and signaling transduction. The fusion process has been well studied, yet the role of chemokine coreceptor signaling in viral infection has remained elusive through the past decade. With the recent demonstration of the signaling requirement for HIV latent infection of resting CD4 T cells, the issue of coreceptor signaling needs to be thoroughly revisited. It is likely that virus-mediated signaling events may facilitate infection in various immunologic settings in vivo where cellular conditions need to be primed; in other words, HIV may exploit the chemokine signaling network shared among immune cells to gain access to downstream cellular components, which can then serve as effective tools to break cellular barriers. This virus-hijacked aberrant signaling process may in turn facilitate pathogenesis. In this review, we summarize past and present studies on HIV coreceptor signaling. We also discuss possible roles of coreceptor signaling in facilitating viral infection and pathogenesis

    Suicide risk in schizophrenia: learning from the past to change the future

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    Suicide is a major cause of death among patients with schizophrenia. Research indicates that at least 5–13% of schizophrenic patients die by suicide, and it is likely that the higher end of range is the most accurate estimate. There is almost total agreement that the schizophrenic patient who is more likely to commit suicide is young, male, white and never married, with good premorbid function, post-psychotic depression and a history of substance abuse and suicide attempts. Hopelessness, social isolation, hospitalization, deteriorating health after a high level of premorbid functioning, recent loss or rejection, limited external support, and family stress or instability are risk factors for suicide in patients with schizophrenia. Suicidal schizophrenics usually fear further mental deterioration, and they experience either excessive treatment dependence or loss of faith in treatment. Awareness of illness has been reported as a major issue among suicidal schizophrenic patients, yet some researchers argue that insight into the illness does not increase suicide risk. Protective factors play also an important role in assessing suicide risk and should also be carefully evaluated. The neurobiological perspective offers a new approach for understanding self-destructive behavior among patients with schizophrenia and may improve the accuracy of screening schizophrenics for suicide. Although, there is general consensus on the risk factors, accurate knowledge as well as early recognition of patients at risk is still lacking in everyday clinical practice. Better knowledge may help clinicians and caretakers to implement preventive measures. This review paper is the results of a joint effort between researchers in the field of suicide in schizophrenia. Each expert provided a brief essay on one specific aspect of the problem. This is the first attempt to present a consensus report as well as the development of a set of guidelines for reducing suicide risk among schizophenia patients

    A Guide to Medications Inducing Salivary Gland Dysfunction, Xerostomia, and Subjective Sialorrhea: A Systematic Review Sponsored by the World Workshop on Oral Medicine VI

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    Allele-Independent Turnover of Human Leukocyte Antigen (HLA) Class Ia Molecules.

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    Major histocompatibility complex class I (MHCI) glycoproteins present cytosolic peptides to CD8+ T cells and regulate NK cell activity. Their heavy chains (HC) are expressed from up to three MHC gene loci (human leukocyte antigen [HLA]-A, -B, and -C in humans), whose extensive polymorphism maps predominantly to the antigen-binding groove, diversifying the bound peptide repertoire. Codominant expression of MHCI alleles is thus functionally critical, but how it is regulated is not fully understood. Here, we have examined the effect of polymorphism on the turnover rates of MHCI molecules in cell lines with functional MHCI peptide loading pathways and in monocyte-derived dendritic cells (MoDCs). Proteins were labeled biosynthetically with heavy water (2H2O), folded MHCI molecules immunoprecipitated, and tryptic digests analysed by mass spectrometry. MHCI-derived peptides were assigned to specific alleles and isotypes, and turnover rates quantified by 2H incorporation, after correcting for cell growth. MHCI turnover half-lives ranged from undetectable to a few hours, depending on cell type, activation state, donor, and MHCI isotype. However, in all settings, the turnover half-lives of alleles of the same isotype were similar. Thus, MHCI protein turnover rates appear to be allele-independent in normal human cells. We propose that this is an important feature enabling the normal function and codominant expression of MHCI alleles

    Economy and Divorces: Their Impact Over Time on the Self-Employment Rates in Spain

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    The paper used time-series data and examined the effect of economic and social variables on the male and female self-employment rates in Spain. We also employed cointegration analysis (with and without) structural breaks. We thus find strong evidence that long run relationships exist among the variables. More precisely, we find that the unemployment rates and the ratio of self-employment to employees’ earnings have a positive effect on self-employment, whereas, economic development and divorce rates have a negative effect. Importantly, we find that the economic variables have equal or stronger long run impact on females than males, with both groups reacting to changes in family circumstances. Finally, we show that the short run family circumstances are better predictors of self-employment choices rather than economic factors, with self-employment being a means of adjustment to new personal circumstances and economic needs
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