114 research outputs found

    From Cancer to Diarrhea: The Moving Target of Public Concern about Environmental Health Risks

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    Public concern about the environment can be unpredictable because it is influenced by numerous factors. Environmental health issues often emerge as important because the public is worried about their health especially when it comes to cancer. Public fear of cancer from environmental exposures is reinforced by many of the US regulations that set pollutant limits based on reducing the risk of cancers rather than other health outcomes. While fear of cancer will never dissipate, recent foodborne outbreaks are contributing to raising public awareness of the health effects from microbes. This paper adds to the dialogue about the challenges of enhancing public understanding of environmental health issues. Internal factors, such as worry, that contribute to public outrage are sometimes more important than external factors such as the media. In addition, relying on the media to inform the public about imminent public health risks may be an ineffective approach to enhancing understanding. In the end, scientists and risk communicators are forced to compete with politicians who are often very effective at manipulating public understanding of risk

    Data Integration Model for Air Quality: A Hierarchical Approach to the Global Estimation of Exposures to Ambient Air Pollution

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    This is the author accepted manuscript. Available from arXiv via the URL in this record.Air pollution is a major risk factor for global health, with both ambient and household air pollution contributing substantial components of the overall global disease burden. One of the key drivers of adverse health effects is fine particulate matter ambient pollution (PM2:5) to which an estimated 3 million deaths can be attributed annually. The primary source of information for estimating exposures has been measurements from ground monitoring networks but, although coverage is increasing, there remain regions in which monitoring is limited. Ground monitoring data therefore needs to be supplemented with information from other sources, such as satellite retrievals of aerosol optical depth and chemical transport models. A hierarchical modelling approach for integrating data from multiple sources is proposed allowing spatially-varying relationships between ground measurements and other factors that estimate air quality. Set within a Bayesian framework, the resulting Data Integration Model for Air Quality (DIMAQ) is used to estimate exposures, together with associated measures of uncertainty, on a high resolution grid covering the entire world. Bayesian analysis on this scale can be computationally challenging and here approximate Bayesian inference is performed using Integrated Nested Laplace Approximations. Model selection and assessment is performed by cross-validation with the final model offering substantial increases in predictive accuracy, particularly in regions where there is sparse ground monitoring, when compared to previous approaches: root mean square error (RMSE) reduced from 17.1 to 10.7, and population weighted RMSE from 23.1 to 12.1 gm3. Based on summaries of the posterior distributions for each grid cell, it is estimated that 92% of the world’s population reside in areas exceeding the World Health Organization’s Air Quality Guidelines.Matthew Lloyd Thomas is supported by a scholarship from the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics at Bath (SAMBa), under the project EP/L015684/1. Amelia Jobling was supported for this work by WHO contracts APW 201255146 and 201255393

    Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear and non-linear data analysis techniques

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    <p>Abstract</p> <p>Background</p> <p>Protein kinases play crucial roles in cell growth, differentiation, and apoptosis. Abnormal function of protein kinases can lead to many serious diseases, such as cancer. Kinase inhibitors have potential for treatment of these diseases. However, current inhibitors interact with a broad variety of kinases and interfere with multiple vital cellular processes, which causes toxic effects. Bioinformatics approaches that can predict inhibitor-kinase interactions from the chemical properties of the inhibitors and the kinase macromolecules might aid in design of more selective therapeutic agents, that show better efficacy and lower toxicity.</p> <p>Results</p> <p>We applied proteochemometric modelling to correlate the properties of 317 wild-type and mutated kinases and 38 inhibitors (12,046 inhibitor-kinase combinations) to the respective combination's interaction dissociation constant (K<sub>d</sub>). We compared six approaches for description of protein kinases and several linear and non-linear correlation methods. The best performing models encoded kinase sequences with amino acid physico-chemical z-scale descriptors and used support vector machines or partial least- squares projections to latent structures for the correlations. Modelling performance was estimated by double cross-validation. The best models showed high predictive ability; the squared correlation coefficient for new kinase-inhibitor pairs ranging P<sup>2 </sup>= 0.67-0.73; for new kinases it ranged P<sup>2</sup><sub>kin </sub>= 0.65-0.70. Models could also separate interacting from non-interacting inhibitor-kinase pairs with high sensitivity and specificity; the areas under the ROC curves ranging AUC = 0.92-0.93. We also investigated the relationship between the number of protein kinases in the dataset and the modelling results. Using only 10% of all data still a valid model was obtained with P<sup>2 </sup>= 0.47, P<sup>2</sup><sub>kin </sub>= 0.42 and AUC = 0.83.</p> <p>Conclusions</p> <p>Our results strongly support the applicability of proteochemometrics for kinome-wide interaction modelling. Proteochemometrics might be used to speed-up identification and optimization of protein kinase targeted and multi-targeted inhibitors.</p

    A protective personal factor against disability and dependence in the elderly: an ordinal regression analysis with nine geographically-defined samples from Spain

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    Background Sense of Coherence (SOC) is defined as a tendency to perceive life experiences as comprehensible, manageable and meaningful. The construct is split in three major domains: Comprehensibility, Manageability, and Meaningfulness. SOC has been associated with successful coping strategies in the face of illness and traumatic events and is a predictor of self-reported and objective health in a variety of contexts. In the present study we aim to evaluate the association of SOC with disability and dependence in Spanish elders. Methods A total of 377 participants aged 75 years or over from nine locations across Spain participated in the study (Mean age: 80.9 years; 65.3% women). SOC levels were considered independent variables in two ordinal logistic models on disability and dependence, respectively. Disability was established with the World health Organization-Disability Assessment Schedule 2.0 (36-item version), while dependence was measured with the Extended Katz Index on personal and instrumental activities of daily living. The models included personal (sex, age, social contacts, availability of an intimate confidant), environmental (municipality size, access to social resources) and health-related covariates (morbidity). Results High Meaningfulness was a strong protective factor against both disability (Odds Ratio [OR] = 0.50; 95% Confidence Interval [CI] = 0.29–0.87) and dependence (OR = 0.33; 95% CI = 0.19–0.58) while moderate and high Comprehensibility was protective for disability (OR = 0.40; 95% CI = 0.22–0.70 and OR = 0.39; 95%CI = 0.21–0.74), but not for dependence. Easy access to social and health resources was also highly protective against both disability and dependence. Conclusions Our results are consistent with the view that high levels of SOC are protective against disability and dependence in the elderly. Elderly individuals with limited access to social and health resources and with low SOC may be a group at risk for dependence and disability in Spain.This project was partially funded by a research contract in support of the project “Epidemiological Study of Dementia in Spain” signed by the Pfizer Foundation and Carlos III Institute of HealthS

    Nasal Delivery of an Adenovirus-Based Vaccine Bypasses Pre-Existing Immunity to the Vaccine Carrier and Improves the Immune Response in Mice

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    Pre-existing immunity to human adenovirus serotype 5 (Ad5) is common in the general population. Bypassing pre-existing immunity could maximize Ad5 vaccine efficacy. Vaccination by the intramuscular (I.M.), nasal (I.N.) or oral (P.O.) route with Ad5 expressing Ebola Zaire glycoprotein (Ad5-ZGP) fully protected naïve mice against lethal challenge with Ebola. In the presence of pre-existing immunity, only mice vaccinated I.N. survived. The frequency of IFN-γ+ CD8+ T cells was reduced by 80% and by 15% in animals vaccinated by the I.M. and P.O. routes respectively. Neutralizing antibodies could not be detected in serum from either treatment group. Pre-existing immunity did not compromise the frequency of IFN-γ+ CD8+ T cells (3.9±1% naïve vs. 3.6±1% pre-existing immunity, PEI) nor anti-Ebola neutralizing antibody (NAB, 40±10 reciprocal dilution, both groups). The number of INF-γ+ CD8+ cells detected in bronchioalveolar lavage fluid (BAL) after I.N. immunization was not compromised by pre-existing immunity to Ad5 (146±14, naïve vs. 120±16 SFC/million MNCs, PEI). However, pre-existing immunity reduced NAB levels in BAL by ∼25% in this group. To improve the immune response after oral vaccination, the Ad5-based vaccine was PEGylated. Mice given the modified vaccine did not survive challenge and had reduced levels of IFN-γ+ CD8+ T cells 10 days after administration (0.3±0.3% PEG vs. 1.7±0.5% unmodified). PEGylation did increase NAB levels 2-fold. These results provide some insight about the degree of T and B cell mediated immunity necessary for protection against Ebola virus and suggest that modification of the virus capsid can influence the type of immune response elicited by an Ad5-based vaccine
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