525 research outputs found

    Agricultural, socioeconomic and environmental variables as risks for human verotoxigenic Escherichia coli (VTEC) infection in Finland

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    <p>Abstract</p> <p>Background</p> <p>Verotoxigenic <it>E. coli </it>(VTEC) is the cause of severe gastrointestinal infection especially among infants. Between 10 and 20 cases are reported annually to the National Infectious Disease Register (NIDR) in Finland. The aim of this study was to identify explanatory variables for VTEC infections reported to the NIDR in Finland between 1997 and 2006. We applied a hurdle model, applicable for a dataset with an excess of zeros.</p> <p>Methods</p> <p>We enrolled 131 domestically acquired primary cases of VTEC between 1997 and 2006 from routine surveillance data. The isolated strains were characterized by virulence type, serogroup, phage type and pulsed-field gel electrophoresis. By applying a two-part Bayesian hurdle model to infectious disease surveillance data, we were able to create a model in which the covariates were associated with the probability for occurrence of the cases in the logistic regression part and the magnitude of covariate changes in the Poisson regression part if cases do occur. The model also included spatial correlations between neighbouring municipalities.</p> <p>Results</p> <p>The average annual incidence rate was 4.8 cases per million inhabitants based on the cases as reported to the NIDR. Of the 131 cases, 74 VTEC O157 and 58 non-O157 strains were isolated (one person had dual infections). The number of bulls per human population and the proportion of the population with a higher education were associated with an increased occurrence and incidence of human VTEC infections in 70 (17%) of 416 of Finnish municipalities. In addition, the proportion of fresh water per area, the proportion of cultivated land per area and the proportion of low income households with children were associated with increased incidence of VTEC infections.</p> <p>Conclusions</p> <p>With hurdle models we were able to distinguish between risk factors for the occurrence of the disease and the incidence of the disease for data characterised by an excess of zeros. The density of bulls and the proportion of the population with higher education were significant both for occurrence and incidence, while the proportion of fresh water, cultivated land, and the proportion of low income households with children were significant for the incidence of the disease.</p

    Assessing Recent Smoking Status by Measuring Exhaled Carbon Monoxide Levels

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    The main expectations of applying proteomics technologies to clinical questions are the discovery of disease related biomarkers. Despite technological advancement to increase proteome coverage and depth to meet these expectations the number of generated biomarkers for clinical use is small. One of the reasons is that found potential biomarkers often are false discoveries. Small sample sizes, in combination with patient sample heterogeneity increase the risk of false discoveries. To be able to extract relevant biological information from such data, high demands are put on the experimental design and the use of sensitive and quantitatively accurate technologies. The overall aim of this thesis was to apply quantitative proteomics methods for biomarker discovery in clinical samples. A method for reducing bias by controlling for individual variation in smoking habits is described in paper I. The aim of the method was objective assessment of recent smoking in clinical studies on inflammatory responses. In paper II, the proteome of alveolar macrophages obtained from smoking subjects with and without the inflammatory lung disease chronic obstructive pulmonary disease (COPD) were quantified by two-dimensional gel-electrophoresis (2-DE). A gender focused analysis showed protein level differences within the female group, with down-regulation of lysosomal pathway and up-regulation of oxidative pathway in COPD patients. Paper III, a mass spectrometry based proteomics analysis of tumour samples, contributes to the molecular understanding of vulvar squamous cell carcinoma (VSCC) and we identified a high risk patient subgroup of HPV-negative tumours based on the expression of four proteins, further suggesting that this subgroup is characterized by an altered ubiquitin-proteasome signalling pathway. Paper III describes a data analysis workflow for the extraction of biological information from quantitative mass spectrometry based proteomics data. High patient-to-patient tumour proteome variability was addressed by using pathway profiling on individual tumour data, followed by comparison of pathway association ranks in a multivariate analysis. We show that pathway data on individual tumour level can detect subpopulations of patients and identify pathways of specific importance in pre-defined clinical groups by the use of multivariate statistics. In paper IV, the potentials and limits of quantitative mass spectrometry on clinical samples was evaluated by defining the quantitative accuracy of isobaric labels and label-free quantification. Quantification by isobaric labels in combination with pI pre-fractionation showed a lower limit of quantification (LOQ) than a label-free analysis without pI pre-fractionation, and 6-plex TMT were more sensitive than 8-plex iTRAQ. Precursor mixing measured by isolation interference (MS1 interference) is more linked to the quantitative accuracy of isobaric labels than reporter ion interference (MS2 interference). Based on that we could define recommendations for how much isolation interference that can be accepted; in our data <30% isolation interference had little effect the quantitative accuracy. In conclusion, getting biological knowledge from proteomics studies requires a careful study design, control of possible confounding factors and the use of clinical data to identify disease subtypes. Further, to be able to draw conclusions from the data, the analysis requires accurate quantitative data and robust statistical tools to detect significant protein alterations. Methods around these issues are developed and discussed in this thesis

    For whom is a health-promoting intervention effective? Predictive factors for performing activities of daily living independently

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    BACKGROUND: Health-promoting interventions tailored to support older persons to remain in their homes, so-called "ageing in place" is important for supporting or improving their health. The health-promoting programme "Elderly Persons in the Risk Zone," (EPRZ) was set up for this purpose and has shown positive results for maintaining independence in activities of daily living for older persons 80 years and above at 1- and 2 year follow-ups. The aim of this study was to explore factors for maintaining independence in the EPRZ health-promoting programme.METHODS: Total of 459 participants in the original trial was included in the analysis; 345 in the programme arm and 114 in the control arm. Thirteen variables, including demographic, health, and programme-specific indicators, were chosen as predictors for independence of activities of daily living. Logistic regression was performed separately for participants in the health promotion programme and in the control arm.RESULTS: In the programme arm, being younger, living alone and self-rated lack of tiredness in performing mobility activities predicted a positive effect of independence in activities of daily living at 1-year follow-up (odds ratio [OR] 1.18, 1.73, 3.02) and 2-year, (OR 1.13, 2.01, 2.02). In the control arm, being less frail was the only predictor at 1-year follow up (OR 1.6 1.09, 2.4); no variables predicted the outcome at the 2-year follow-up.CONCLUSIONS: Older persons living alone - as a risk of ill health - should be especially recognized and offered an opportunity to participate in health-promoting programmes such as "Elderly Persons in the Risk Zone". Further, screening for subjective frailty could form an advantageous guiding principle to target the right population when deciding to whom health-promoting intervention should be offered.TRIAL REGISTRATION: The original clinical trial was registered at ClinicalTrials.gov. Identifier: NCT00877058 , April 6, 2009

    Study of Bc+B_c^+ decays to the K+Kπ+K^+K^-\pi^+ final state and evidence for the decay Bc+χc0π+B_c^+\to\chi_{c0}\pi^+

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    A study of Bc+K+Kπ+B_c^+\to K^+K^-\pi^+ decays is performed for the first time using data corresponding to an integrated luminosity of 3.0 fb1\mathrm{fb}^{-1} collected by the LHCb experiment in pppp collisions at centre-of-mass energies of 77 and 88 TeV. Evidence for the decay Bc+χc0(K+K)π+B_c^+\to\chi_{c0}(\to K^+K^-)\pi^+ is reported with a significance of 4.0 standard deviations, resulting in the measurement of σ(Bc+)σ(B+)×B(Bc+χc0π+)\frac{\sigma(B_c^+)}{\sigma(B^+)}\times\mathcal{B}(B_c^+\to\chi_{c0}\pi^+) to be (9.83.0+3.4(stat)±0.8(syst))×106(9.8^{+3.4}_{-3.0}(\mathrm{stat})\pm 0.8(\mathrm{syst}))\times 10^{-6}. Here B\mathcal{B} denotes a branching fraction while σ(Bc+)\sigma(B_c^+) and σ(B+)\sigma(B^+) are the production cross-sections for Bc+B_c^+ and B+B^+ mesons. An indication of bˉc\bar b c weak annihilation is found for the region m(Kπ+)<1.834GeV ⁣/c2m(K^-\pi^+)<1.834\mathrm{\,Ge\kern -0.1em V\!/}c^2, with a significance of 2.4 standard deviations.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2016-022.html, link to supplemental material inserted in the reference

    Detection of Prion Infectivity in Fat Tissues of Scrapie-Infected Mice

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    Distribution of prion infectivity in organs and tissues is important in understanding prion disease pathogenesis and designing strategies to prevent prion infection in animals and humans. Transmission of prion disease from cattle to humans resulted in banning human consumption of ruminant nervous system and certain other tissues. In the present study, we surveyed tissue distribution of prion infectivity in mice with prion disease. We show for the first time detection of infectivity in white and brown fat. Since high amounts of ruminant fat are consumed by humans and also incorporated into animal feed, fat-containing tissues may pose a previously unappreciated hazard for spread of prion infection
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