979 resultados para Near-Duplicate Detection


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Hand, foot and mouth disease (HFMD) is a contagious viral disease that frequently affects infants and children and present with blisters and flu-like symptoms. This disease is caused by a group of enteroviruses such as enterovirus 71 (EV71) and coxsackievirus A16 (CA16). However, unlike other HFMD causing enteroviruses, EV71 have also been shown to be associated with more severe clinical manifestation such as aseptic meningitis, brainstem and cerebellar encephalitis which may lead to cardiopulmonary failure and death. Clinically, HFMD caused by EV71 is indistinguishable from other HFMD causing enteroviruses such as CA16. Molecular diagnosis methods such as the use of real-time PCR has been used commonly for the identification of EV71. In this study, two platforms namely the real-time PCR and the droplet digital PCR were compared for the detection quantitation of known EV71 viral copy number. The results reveal accurate and consistent results between the two platforms. In summary, the droplet digital PCR was demonstrated to be a promising technology for the identification and quantitation of EV71 viral copy number.

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A simple and rapid method of analysis for mercury ions (Hg2+) and cysteine (Cys) was developed with the use of graphene quantum dots (GQDs) as a fluorescent probe. In the presence of GQDs, Hg2+ cations are absorbed on their negatively charged surface by means of electrostatic interactions. Thus, the fluorescence (FL) of the GQDs would be significantly quenched as a result of the FL charge transfer, e.g. 92% quenching at 450 nm occurs for a 5 μmol L−1 Hg2+ solution. However, when Cys was added, a significant FL enhancement was observed (510% at 450 nm for a 8.0 μmol L−1 Cys solution), and Hg2+ combined with Cys rather than with the GQDs in an aqueous solution. This occurred because a strong metalsingle bondthiol bond formed, displacing the weak electrostatic interactions, and this resulted in an FL enhancement of the GQDs. The limits of detection (LOD) for Hg2+ and Cys were 0.439 nmol L−1 and 4.5 nmol L−1, respectively. Also, this method was used successfully to analyze Hg2+ and Cys in spiked water samples.

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Introduction Presently, the severity of obstructive sleep apnea (OSA) is estimated based on the apnea-hypopnea index (AHI). Unfortunately, AHI does not provide information on the severity of individual obstruction events. Previously, the severity of individual obstruction events has been suggested to be related to the outcome of the disease. In this study, we incorporate this information into AHI and test whether this novel approach would aid in discriminating patients with the highest risk. We hypothesize that the introduced adjusted AHI parameter provides a valuable supplement to AHI in the diagnosis of the severity of OSA. Methods This hypothesis was tested by means of retrospective follow-up (mean ± sd follow-up time 198.2 ± 24.7 months) of 1,068 men originally referred to night polygraphy due to suspected OSA. After exclusion of the 264 patients using CPAP, the remaining 804 patients were divided into normal (AHI < 5) and OSA (AHI ≥ 5) categories based on conventional AHI and adjusted AHI. For a more detailed analysis, the patients were divided into normal, mild, moderate, and severe OSA categories based on conventional AHI and adjusted AHI. Subsequently, the mortality and cardiovascular morbidity in these groups were determined. Results Use of the severity of individual obstruction events for adjustment of AHI led to a significant rearrangement of patients between severity categories. Due to this rearrangement, the number of deceased patients diagnosed to have OSA was increased when adjusted AHI was used as the diagnostic index. Importantly, risk ratios of all-cause mortality and cardiovascular morbidity were higher in moderate and severe OSA groups formed based on the adjusted AHI parameter than in those formed based on conventional AHI. Conclusions The adjusted AHI parameter was found to give valuable supplementary information to AHI and to potentially improve the recognition of OSA patients with the highest risk of mortality or cardiovascular morbidity.

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Changes to the redox status of biological systems have been implicated in the pathogenesis of a wide variety of disorders including cancer, Ischemia-reperfusion (I/R) injury and neurodegeneration. In times of metabolic stress e.g. ischaemia/reperfusion, reactive oxygen species (ROS) production overwhelms the intrinsic antioxidant capacity of the cell, damaging vital cellular components. The ability to quantify ROS changes in vivo, is therefore essential to understanding their biological role. Here we evaluate the suitability of a novel reversible profluorescent probe containing a redox-sensitive nitroxide moiety (methyl ester tetraethylrhodamine nitroxide, ME-TRN), as an in vivo, real-time reporter of retinal oxidative status. The reversible nature of the probe's response offers the unique advantage of being able to monitor redox changes in both oxidizing and reducing directions in real time. After intravitreal administration of the ME-TRN probe, we induced ROS production in rat retina using an established model of complete, acute retinal ischaemia followed by reperfusion. After restoration of blood flow, retinas were imaged using a Micron III rodent fundus fluorescence imaging system, to quantify the redox-response of the probe. Fluorescent intensity declined during the first 60 min of reperfusion. The ROS-induced change in probe fluorescence was ameliorated with the retinal antioxidant, lutein. Fluorescence intensity in non-Ischemia eyes did not change significantly. This new probe and imaging technology provide a reversible and real-time response to oxidative changes and may allow the in vivo testing of antioxidant therapies of potential benefit to a range of diseases linked to oxidative stress

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A novel electrochemical biosensor, DNA/hemin/nafion–graphene/GCE, was constructed for the analysis of the benzo(a)pyrene PAH, which can produce DNA damage induced by a benzo(a)pyrene (BaP) enzyme-catalytic product. This biosensor was assembled layer-by-layer, and was characterized with the use of cyclic voltammetry, electrochemical impedance spectroscopy (EIS) and atomic force microscopy. Ultimately, it was demonstrated that the hemin/nafion–graphene/GCE was a viable platform for the immobilization of DNA. This DNA biosensor was treated separately in benzo(a)pyrene, hydrogen peroxide (H2O2) and in their mixture, respectively, and differential pulse voltammetry (DPV) analysis showed that an oxidation peak was apparent after the electrode was immersed in H2O2. Such experiments indicated that in the presence of H2O2, hemin could mimic cytochrome P450 to metabolize benzo(a)pyrene, and a voltammogram of its metabolite was recorded. The DNA damage induced by this metabolite was also detected by electrochemical impedance and ultraviolet spectroscopy. Finally, a novel, indirect DPV analytical method for BaP in aqueous solution was developed based on the linear metabolite versus BaP concentration plot; this method provided a new, indirect, quantitative estimate of DNA damage.

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Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

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Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.

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A novel near-infrared spectroscopy (NIRS) method has been researched and developed for the simultaneous analyses of the chemical components and associated properties of mint (Mentha haplocalyx Briq.) tea samples. The common analytes were: total polysaccharide content, total flavonoid content, total phenolic content, and total antioxidant activity. To resolve the NIRS data matrix for such analyses, least squares support vector machines was found to be the best chemometrics method for prediction, although it was closely followed by the radial basis function/partial least squares model. Interestingly, the commonly used partial least squares was unsatisfactory in this case. Additionally, principal component analysis and hierarchical cluster analysis were able to distinguish the mint samples according to their four geographical provinces of origin, and this was further facilitated with the use of the chemometrics classification methods-K-nearest neighbors, linear discriminant analysis, and partial least squares discriminant analysis. In general, given the potential savings with sampling and analysis time as well as with the costs of special analytical reagents required for the standard individual methods, NIRS offered a very attractive alternative for the simultaneous analysis of mint samples.

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BACKGROUND: Dengue viruses (DENV) are the causative agents of dengue, the world's most prevalent arthropod-borne disease with around 40% of the world's population at risk of infection annually. Wolbachia pipientis, an obligate intracellular bacterium, is being developed as a biocontrol strategy against dengue because it limits replication of the virus in the mosquito. The Wolbachia strain wMel, which has been introduced into the mosquito vector, Aedes aegypti, has been shown to invade and spread to near fixation in field releases. Standard measures of Wolbachia's efficacy for blocking virus replication focus on the detection and quantification of virus in mosquito tissues. Examining the saliva provides a more accurate measure of transmission potential and can reveal the extrinsic incubation period (EIP), that is, the time it takes virus to arrive in the saliva following the consumption of DENV viremic blood. EIP is a key determinant of a mosquito's ability to transmit DENVs, as the earlier the virus appears in the saliva the more opportunities the mosquito will have to infect humans on subsequent bites. METHODOLOGY/PRINCIPAL FINDINGS: We used a non-destructive assay to repeatedly quantify DENV in saliva from wMel-infected and Wolbachia-free wild-type control mosquitoes following the consumption of a DENV-infected blood meal. We show that wMel lengthens the EIP, reduces the frequency at which the virus is expectorated and decreases the dengue copy number in mosquito saliva as compared to wild-type mosquitoes. These observations can at least be partially explained by an overall reduction in saliva produced by wMel mosquitoes. More generally, we found that the concentration of DENV in a blood meal is a determinant of the length of EIP, saliva virus titer and mosquito survival. CONCLUSIONS/SIGNIFICANCE: The saliva-based traits reported here offer more disease-relevant measures of Wolbachia's effects on the vector and the virus. The lengthening of EIP highlights another means, in addition to the reduction of infection frequencies and DENV titers in mosquitoes, by which Wolbachia should operate to reduce DENV transmission in the field.

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Aims/hypothesis Diabetic retinopathy is a serious complication of diabetes mellitus and can lead to blindness. A genetic component, in addition to traditional risk factors, has been well described although strong genetic factors have not yet been identified. Here, we aimed to identify novel genetic risk factors for sight-threatening diabetic retinopathy using a genome-wide association study. Methods Retinopathy was assessed in white Australians with type 2 diabetes mellitus. Genome-wide association analysis was conducted for comparison of cases of sight-threatening diabetic retinopathy (n = 336) with diabetic controls with no retinopathy (n = 508). Top ranking single nucleotide polymorphisms were typed in a type 2 diabetes replication cohort, a type 1 diabetes cohort and an Indian type 2 cohort. A mouse model of proliferative retinopathy was used to assess differential expression of the nearby candidate gene GRB2 by immunohistochemistry and quantitative western blot. Results The top ranked variant was rs3805931 with p = 2.66 × 10−7, but no association was found in the replication cohort. Only rs9896052 (p = 6.55 × 10−5) was associated with sight-threatening diabetic retinopathy in both the type 2 (p = 0.035) and the type 1 (p = 0.041) replication cohorts, as well as in the Indian cohort (p = 0.016). The study-wide meta-analysis reached genome-wide significance (p = 4.15 × 10−8). The GRB2 gene is located downstream of this variant and a mouse model of retinopathy showed increased GRB2 expression in the retina. Conclusions/interpretation Genetic variation near GRB2 on chromosome 17q25.1 is associated with sight-threatening diabetic retinopathy. Several genes in this region are promising candidates and in particular GRB2 is upregulated during retinal stress and neovascularisation.

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Understanding the complex nature of diseased tissue in vivo requires development of more advanced nanomedicines, where synthesis of multifunctional polymers combines imaging multimodality with a biocompatible, tunable, and functional nanomaterial carrier. Here we describe the development of polymeric nanoparticles for multimodal imaging of disease states in vivo. The nanoparticle design utilizes the abundant functionality and tunable physicochemical properties of synthetically robust polymeric systems to facilitate targeted imaging of tumors in mice. For the first time, high-resolution 19F/1H magnetic resonance imaging is combined with sensitive and versatile fluorescence imaging in a polymeric material for in vivo detection of tumors. We highlight how control over the chemistry during synthesis allows manipulation of nanoparticle size and function and can lead to very high targeting efficiency to B16 melanoma cells, both in vitro and in vivo. Importantly, the combination of imaging modalities within a polymeric nanoparticle provides information on the tumor mass across various size scales in vivo, from millimeters down to tens of micrometers.

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This thesis presents the development of a rapid, sensitive and reproducible spectroscopic method for the detection of TNT in forensic and environmental applications. Simple nano sensors prepared by cost effective methods were utilized as sensitive platforms for the detection of TNT by surface enhanced Raman spectroscopy. The optimization of the substrate and the careful selection of a suitable recognition molecule contributed to the significant improvements of sensitive and selective targeting over current detection methods. The work presented in this thesis paves the way for effective detection and monitoring of explosives residues in law enforcement and environmental health applications.

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Metformin is the most commonly used pharmacological therapy for type 2 diabetes. We report a genome-wide association study for glycemic response to metformin in 1,024 Scottish individuals with type 2 diabetes with replication in two cohorts including 1,783 Scottish individuals and 1,113 individuals from the UK Prospective Diabetes Study. In a combined meta-analysis, we identified a SNP, rs11212617, associated with treatment success (n = 3,920, P = 2.9 P×-9, odds ratio = 1.35, 95% CI 1.22-1.49) at a locus containing ATM, the ataxia telangiectasia mutated gene. In a rat hepatoma cell line, inhibition of ATM with KU-55933 attenuated the phosphorylation and activation of AMP-activated protein kinase in response to metformin. We conclude that ATM, a gene known to be involved in DNA repair and cell cycle control, plays a role in the effect of metformin upstream of AMP-activated protein kinase, and variation in this gene alters glycemic response to metformin. © 2011 Nature America, Inc. All rights reserved.

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Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

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A double antibody sandwich enzyme linked immunosorbent assay (ELISA) was developed to detect Echis carinatus venom in various organs (brain, heart, lungs, liver, spleen and kidneys) as well as tissue at the site of injection of mice, at various time intervals (1, 6, 12, 18, 24 h and 12 h intervals up to 72 h) after death. The assay could detect E. carinatus venom levels up to 2.5 ng/ml of tissue homogenate and the venom was detected up to 72 h after death. A highly sensitive and species-specific avidin-biotin microtitre ELISA was also developed to detect venoms of four medically important Indian snakes (Bungarus caeruleus, Naja naja, E. carinatus and Daboia russelli russelli) in autopsy specimens of human victims of snake bite. The assay could detect venom levels as low as 100 pg/ml of tissue homogenate. Venoms were detected in brain, heart, lungs, liver, spleen, kidneys, tissue at the bite area and postmortem blood. In all 12 human victim cadavers tested the culprit species were identified. As observed in mice, tissue at the site of bite area showed the highest concentration of venom and the brain showed the least. Moderate amounts of venoms were found in liver, spleen, kidneys, heart and lungs. Development of a simple, rapid and species-specific diagnostic kit based on this ELISA technique useful to clinicians is discussed.