118 resultados para Vibration based damage detection
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Comment on: Hassan C, Di Giulio E, Pickhardt PJ, Zullo A, Laghi A, Kim DH, Iafrate F, Morini S. Cost effectiveness of colonoscopy, based on the appropriateness of an indication. Clin Gastroenterol Hepatol. 2008 Nov;6(11):1231-6.
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We have developed a thrombin-sensitive polymeric photosensitizer prodrug (T-PS) to selectively image and eradicate inflammatory lesions in rheumatoid arthritis (RA). Thrombin is a serine protease up-regulated in synovial tissues of rheumatoid arthritis (RA) patients. T-PS consists of a polymeric backbone, to which multiple photosensitizer (PS) units are tethered via short thrombin-cleavable peptide linkers. Fluorescence emission and phototoxicity of the prodrug are efficiently quenched due to the interaction of neighboring photosensitizer units. The prodrug is passively delivered to the inflammation site via the enhanced permeability and retention (EPR) effect. Subsequent site-selective proteolytic cleavage of the peptide linkers restores its photoactivity by increasing the mutual distance between PS. Whole animal imaging in murine collagen-induced arthritis, an experimental model of RA revealed a dose-dependent fluorescence increase in arthritic paws after systemic prodrug injection. In addition, administration of T-PS resulted in much higher fluorescence selectivity for arthritic joints as compared to the free PS. Irradiation of the arthritic joints induced light dose dependent phototoxic effects such as apoptosis, vascular damage and local hemorrhage. Long-term observations showed complete regression of the latter. Irradiated non-arthritic tissues or non-irradiated arthritic tissues showed no histological effects after photodynamic therapy with T-PS. This illustrates that T-PS can localize inflammatory lesions with excellent selectivity and induce apoptosis and vascular shut down after irradiation.
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OBJECTIVE: Plasma adiponectin is strongly associated with various components of metabolic syndrome, type 2 diabetes and cardiovascular outcomes. Concentrations are highly heritable and differ between men and women. We therefore aimed to investigate the genetics of plasma adiponectin in men and women. METHODS: We combined genome-wide association scans of three population-based studies including 4659 persons. For the replication stage in 13795 subjects, we selected the 20 top signals of the combined analysis, as well as the 10 top signals with p-values less than 1.0 x 10(-4) for each the men- and the women-specific analyses. We further selected 73 SNPs that were consistently associated with metabolic syndrome parameters in previous genome-wide association studies to check for their association with plasma adiponectin. RESULTS: The ADIPOQ locus showed genome-wide significant p-values in the combined (p=4.3 x 10(-24)) as well as in both women- and men-specific analyses (p=8.7 x 10(-17) and p=2.5 x 10(-11), respectively). None of the other 39 top signal SNPs showed evidence for association in the replication analysis. None of 73 SNPs from metabolic syndrome loci exhibited association with plasma adiponectin (p>0.01). CONCLUSIONS: We demonstrated the ADIPOQ gene as the only major gene for plasma adiponectin, which explains 6.7% of the phenotypic variance. We further found that neither this gene nor any of the metabolic syndrome loci explained the sex differences observed for plasma adiponectin. Larger studies are needed to identify more moderate genetic determinants of plasma adiponectin.
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Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.
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Context: Until now, the testosterone/epitestosterone (T/E) ratio is the main marker for detection of testosterone (T) misuse in athletes. As this marker can be influenced by a number of confounding factors, additional steroid profile parameters indicating T misuse can provide substantiating evidence of doping with endogenous steroids. The evaluation of a steroid profile is currently based upon population statistics. Since large inter-individual variations exist, a paradigm shift towards subject-based references is ongoing in doping analysis. Objective: Proposition of new biomarkers for the detection of testosterone in sports using extensive steroid profiling and an adaptive model based upon Bayesian inference. Subjects: 6 healthy male volunteers were administered with testosterone undecanoate. Population statistics were performed upon steroid profiles from 2014 male Caucasian athletes participating in official sport competition. Design: An extended search for new biomarkers in a comprehensive steroid profile combined with Bayesian inference techniques as used in the Athlete Biological Passport resulted in a selection of additional biomarkers that may improve detection of testosterone misuse in sports. Results: Apart from T/E, 4 other steroid ratios (6α-OH-androstenedione/16α-OH-dehydroepiandrostenedione, 4-OH-androstenedione/16α-OH-androstenedione, 7α-OH-testosterone/7β-OH-dehydroepiandrostenedione and dihydrotestosterone/5β-androstane-3α,17β-diol) were identified as sensitive urinary biomarkers for T misuse. These new biomarkers were rated according to relative response, parameter stability, detection time and discriminative power. Conclusion: Newly selected biomarkers were found suitable for individual referencing within the concept of the Athlete's Biological Passport. The parameters showed improved detection time and discriminative power compared to the T/E ratio. Such biomarkers can support the evidence of doping with small oral doses of testosterone.
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The biocontrol activity of the root-colonizing Pseudomonas fluorescens strain CHA0 is largely determined by the production of antifungal metabolites, especially 2,4-diacetylphloroglucinol. The expression of these metabolites depends on abiotic and biotic environmental factors, in particular, elements present in the rhizosphere. In this study, we have developed a new method for the in situ analysis of antifungal gene expression using flow cytometry combined with green fluorescent protein (GFP)-based reporter fusions to the phlA and prnA genes essential for the production of the antifungal compounds 2,4-diacetylphloroglucinol and pyrrolnitrin, respectively, in strain CHA0. Expression of phlA-gfp and prnA-gfp in CHA0 cells harvested from the rhizosphere of a set of plant species as well as from the roots of healthy, leaf pathogen-attacked, and physically stressed plants were analyzed using a FACSCalibur. After subtraction of background fluorescence emitted by plant-derived particles and CHA0 cells not carrying the gfp reporters, the average gene expression per bacterial cell could be calculated. Levels of phlA and prnA expression varied significantly in the rhizospheres of different plant species. Physical stress and leaf pathogen infection lowered phlA expression levels in the rhizosphere of cucumber. Our results demonstrate that the newly developed approach is suitable to monitor differences in levels of antifungal gene expression in response to various plant-derived factors. An advantage of the method is that it allows quantification of bacterial gene expression in rhizosphere populations at a single-cell level. To our best knowledge, this is the first study using flow cytometry for the in situ analysis of biocontrol gene expression in a plant-beneficial bacterium in the rhizosphere.
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Background: Detection rates for adenoma and early colorectal cancer (CRC) are unsatisfactory due to low compliance towards invasive screening procedures such as colonoscopy. There is a large unmet screening need calling for an accurate, non-invasive and cost-effective test to screen for early neoplastic and pre-neoplastic lesions. Our goal is to identify effective biomarker combinations to develop a screening test aimed at detecting precancerous lesions and early CRC stages, based on a multigene assay performed on peripheral blood mononuclear cells (PBMC).Methods: A pilot study was conducted on 92 subjects. Colonoscopy revealed 21 CRC, 30 adenomas larger than 1 cm and 41 healthy controls. A panel of 103 biomarkers was selected by two approaches: a candidate gene approach based on literature review and whole transcriptome analysis of a subset of this cohort by Illumina TAG profiling. Blood samples were taken from each patient and PBMC purified. Total RNA was extracted and the 103 biomarkers were tested by multiplex RT-qPCR on the cohort. Different univariate and multivariate statistical methods were applied on the PCR data and 60 biomarkers, with significant p-value (< 0.01) for most of the methods, were selected.Results: The 60 biomarkers are involved in several different biological functions, such as cell adhesion, cell motility, cell signaling, cell proliferation, development and cancer. Two distinct molecular signatures derived from the biomarker combinations were established based on penalized logistic regression to separate patients without lesion from those with CRC or adenoma. These signatures were validated using bootstrapping method, leading to a separation of patients without lesion from those with CRC (Se 67%, Sp 93%, AUC 0.87) and from those with adenoma larger than 1cm (Se 63%, Sp 83%, AUC 0.77). In addition, the organ and disease specificity of these signatures was confirmed by means of patients with other cancer types and inflammatory bowel diseases.Conclusions: The two defined biomarker combinations effectively detect the presence of CRC and adenomas larger than 1 cm with high sensitivity and specificity. A prospective, multicentric, pivotal study is underway in order to validate these results in a larger cohort.
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We have compared a multiplexed bead-based assay (BBA) with an enzyme immunoassay (EIA) and immunofluorescence assay (IFA) for the assessment of the Epstein-Barr virus (EBV) serostatus. Three hundred and ninety-three sera, classified according to IFA results as seronegative (n=100), acute infection (n=100), past infection (n=100) and indeterminate (n=93), were tested by BBA and EIA. Overall, the three methods gave similar results with a relatively high (75.2%) concordance with the consensus interpretation of the serostatus. The most significant discordances were: (i) 58 samples had uninterpretable results for BBA, in majority due to the detection of non-antigen specific antibody binding by control beads. (ii) almost half the samples positive for anti-Epstein-Barr nuclear antigen (EBNA) IgG by BBA or EIA were negative by IFA. Among the latter, only a minority had a history of immunocompromise or treatment, or detectable anti-early antigen antibody. This discrepancy probably reflects a poor sensitivity of IFA for anti-EBNA IgG detection. EIA and BBA had a similar performance and had substantial practical advantages over IFA with respect to testing for EBV serostatus.
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Glutamine has multiple roles in brain metabolism and its concentration can be altered in various pathological conditions. An accurate knowledge of its concentration is therefore highly desirable to monitor and study several brain disorders in vivo. However, in recent years, several MRS studies have reported conflicting glutamine concentrations in the human brain. A recent hypothesis for explaining these discrepancies is that a short T2 component of the glutamine signal may impact on its quantification at long echo times. The present study therefore aimed to investigate the impact of acquisition parameters on the quantified glutamine concentration using two different acquisition techniques, SPECIAL at ultra-short echo time and MEGA-SPECIAL at moderate echo time. For this purpose, MEGA-SPECIAL was optimized for the first time for glutamine detection. Based on the very good agreement of the glutamine concentration obtained between the two measurements, it was concluded that no impact of a short T2 component of the glutamine signal was detected.
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Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.
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OBJECTIVE: to assess the levels and determinants of interleukin (IL)-1ß, IL-6, tumour necrosis factor (TNF)-a and C-reactive protein (CRP) in a healthy Caucasian population.METHODS: population sample of 2884 men and 3201 women aged 35 to 75. IL-1ß, IL-6 and TNF-a were assessed by a multiplexed particle-based flow cytometric assay and CRP by an immunometric assay.RESULTS: Spearman rank correlations between duplicate cytokine measurements (N?=?80) ranged between 0.89 and 0.96; intra-class correlation coefficients ranged between 0.94 and 0.97, indicating good reproducibility. Among the 6085 participants, 2289 (37.6%), 451 (7.4%) and 43 (0.7%) had IL-1ß, IL-6 and TNF-a levels below detection limits, respectively. Median (interquartile range) for participants with detectable values were 1.17 (0.48-3.90) pg/ml for IL-1ß; 1.47 (0.71-3.53) pg/ml for IL-6; 2.89 (1.82-4.53) pg/ml for TNF-a and 1.3 (0.6-2.7) ng/ml for CRP. On multivariate analysis, greater age was the only factor inversely associated with IL-1ß levels. Male sex, increased BMI and smoking were associated with greater IL-6 levels, while no relationship was found for age and leisure-time PA. Male sex, greater age, increased BMI and current smoking were associated with greater TNF-a levels, while no relationship was found with leisure-time PA. CRP levels were positively related to age, BMI and smoking, and inversely to male sex and physical activity.CONCLUSION: Population-based levels of several cytokines were established. Increased age and BMI, and to a lesser degree sex and smoking, significantly and differentially impact cytokine levels, while leisure-time physical activity has little effect.
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We present the application of terrestrial laser scanning (TLS) for the monitoring and characterization of an active landslide area in Val Canaria (Ticino, Southern Swiss Alps). At catchment scale, the study area is affected by a large Deep Seated Gravitational Slope Deformation (DSGSD) area presenting, in the lower boundary, several retrogressive landslides active since the 1990s. Due to its frequent landslide events this area was periodically monitored by TLS since 2006. Periodic acquisitions provided new information on 3D displacements at the bottom of slope and the detection of centimetre to decimetre level scale changes (e.g. rockfall and pre-failure deformations). In October 2009, a major slope collapse occured at the bottom of the most unstable area. Based on the comparison between TLS data before and after the collapse, we carried out a detailed failure mechanism analysis and volume calculation.
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PURPOSE: A pleiotropic effect of statins has been reported in numerous studies. However, the association between statin use and inflammatory cytokines is controversial. We examined the associations between statin use and C-reactive protein (CRP), tumour necrosis factor α (TNF-α), interleukin-1β (IL-1β) and interleukin-6 (IL-6) in a healthy Caucasian population. METHODS: Cross-sectional study of 6184 participants aged 35-75years from Lausanne, Switzerland. Cytokines were assessed by multiplexed particle-based flow cytometric assay. Self-reported history of medication was collected for statins and other medication. 99 participants without cytokine data were excluded. RESULTS: Among the 6085 participants, 2289 (37.6%), 451 (7.4%) and 43 (0.7%) had IL-1β, IL-6 and TNF-α levels below detection limits, respectively. On multivariate analysis adjusting for age, gender, smoking status, body mass index, hypertension, diabetes, baseline cardiovascular disease, total cholesterol, anti-inflammatory use, other cytokine modifying drugs and other drugs, participants on statins had significantly lower CRP levels (adjusted mean±standard error: 1.22±1.05 vs. 1.38±1.04mg/L for use and non-use, respectively, p<0.01 on log-transformed data). Conversely, no association was found between statin use and IL-1β (p=0.91), IL-6 (p=0.25) or TNF-α (p=0.28) levels. On multivariate analysis, individuals in the statin group (β coefficient=-0.12; 95% CI=-0.21, -0.03) had lower levels of CRP as compared to those in the reference group (i.e. those not using statin). However, no significant associations were observed between IL-1β, IL-6 and TNF-α and statins. CONCLUSION: Individuals on statins have lower CRP levels; conversely, no effect was found for IL-1β, IL-6 and TNF-α levels.