668 resultados para diagnostic approach route


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Dengue virus is the most significant human viral pathogen spread by the bite of an infected mosquito. With no vaccine or antiviral therapy currently available, disease prevention relies largely on surveillance and mosquito control. Preventing the onset of dengue outbreaks and effective vector management would be considerably enhanced through surveillance of dengue virus prevalence in natural mosquito populations. However, current approaches to the identification of virus in field-caught mosquitoes require relatively slow and labor intensive techniques such as virus isolation or RT-PCR involving specialized facilities and personnel. A rapid and portable method for detecting dengue virus-infected mosquitoes is described. Using a hand held battery operated homogenizer and a dengue diagnostic rapid strip the viral protein NS1 was detected as a marker of dengue virus infection. This method could be performed in less than 30 min in the field, requiring no downstream processing, and is able to detect a single infected mosquito in a pool of at least 50 uninfected mosquitoes. The method described in this study allows rapid, real-time monitoring of dengue virus presence in mosquito populations and could be a useful addition to effective monitoring and vector control responses.

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Members of the Calliphoridae (blowflies) are significant for medical and veterinary management, due to the ability of some species to consume living flesh as larvae, and for forensic investigations due to the ability of others to develop in corpses. Due to the difficulty of accurately identifying larval blowflies to species there is a need for DNA-based diagnostics for this family, however the widely used DNA-barcoding marker, cox1, has been shown to fail for several groups within this family. Additionally, many phylogenetic relationships within the Calliphoridae are still unresolved, particularly deeper level relationships. Sequencing whole mt genomes has been demonstrated both as an effective method for identifying the most informative diagnostic markers and for resolving phylogenetic relationships. Twenty-seven complete, or nearly so, mt genomes were sequenced representing 13 species, seven genera and four calliphorid subfamilies and a member of the related family Tachinidae. PCR and sequencing primers developed for sequencing one calliphorid species could be reused to sequence related species within the same superfamily with success rates ranging from 61% to 100%, demonstrating the speed and efficiency with which an mt genome dataset can be assembled. Comparison of molecular divergences for each of the 13 protein-coding genes and 2 ribosomal RNA genes, at a range of taxonomic scales identified novel targets for developing as diagnostic markers which were 117–200% more variable than the markers which have been used previously in calliphorids. Phylogenetic analysis of whole mt genome sequences resulted in much stronger support for family and subfamily-level relationships. The Calliphoridae are polyphyletic, with the Polleninae more closely related to the Tachinidae, and the Sarcophagidae are the sister group of the remaining calliphorids. Within the Calliphoridae, there was strong support for the monophyly of the Chrysomyinae and Luciliinae and for the sister-grouping of Luciliinae with Calliphorinae. Relationships within Chrysomya were not well resolved. Whole mt genome data, supported the previously demonstrated paraphyly of Lucilia cuprina with respect to L. sericata and allowed us to conclude that it is due to hybrid introgression prior to the last common ancestor of modern sericata populations, rather than due to recent hybridisation, nuclear pseudogenes or incomplete lineage sorting.

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This high prevalence of comorbid mental health and substance use disorders makes the accurate diagnosis of comorbid disorders an important clinical priority. However, the presence of comorbid disorders creates a number of diagnostic dilemmas, which have hindered our understanding of the comorbid disorders. This chapter discusses these diagnostic dilemmas, including issues with the reliability, validity and clinical utility of current systems of psychiatric nomenclature’s approach to diagnosing comorbid disorders. A number of alternative models for understanding comorbid disorders are briefly discussed, followed by suggestions for how research can improve our understanding of comorbid disorders.

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In early April 1998 the Centre for Disease Control (CDC) in Darwin was notified of a case with positive dengue serology. The illness appeared to have been acquired in the Northern Territory (NT). Because dengue is not endemic to the NT, locally acquired infection has significant public health implications, particularly for vector identification and control to limit the spread of infection. Dengue IgM serology was positive on two occasions but the illness was eventually presumptively identified as Kokobera infection. This case illustrates some important points about serology. The interpretation of flavivirus serology is complex and can be misleading, despite recent improvements. The best method of determining the cause of infection is still attempting to reconcile clinical illness details with incubation times and vector presence, as well as laboratory results. This approach ultimately justified the initial period of waiting for confirmatory results in this case, before the institution of public health measures necessary for a true case of dengue.

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The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

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The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

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The goal of this study was to utilise an objective measurement tool, via an on-board Diagnostic tool (OBDII), to explore the effectiveness of a behaviour modification intervention designed to reduce over-speed violations in a group of work-related drivers. It was predicted that over-speed violations would be decreased following participation in a behaviour modification intervention where drivers received weekly feedback on their speeding performance and goal setting exercises. The final analysis included the on-road behaviour of 16 drivers, all of whom completed each stage of the intervention program. As predicted, over-speed violations significantly decreased from pre-test to post-test, after controlling for kilometres driven. These findings offer practical guidance for industry in developing interventions designed to improve work-related driving behaviour.

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Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

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This study investigated the population genetics, demographic history and pathway of invasion of the Russian wheat aphid (RWA) from its native range in Central Asia, the Middle East and Europe to South Africa and the Americas. We screened microsatellite markers, mitochondrial DNA and endosymbiont genes in 504 RWA clones from nineteen populations worldwide. Following pathway analyses of microsatellite and endosymbiont data, we postulate that Turkey and Syria were the most likely sources of invasion to Kenya and South Africa, respectively. Furthermore, we found that one clone transferred between South Africa and the Americas was most likely responsible for the New World invasion. Finally, endosymbiont DNA was found to be a high resolution population genetic marker, extremely useful for studies of invasion over a relatively short evolutionary history time frame. This study has provided valuable insights into the factors that may have facilitated the recent global invasion by this damaging pest.

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BACKGROUND: Over the past 10 years, the use of saliva as a diagnostic fluid has gained attention and has become a translational research success story. Some of the current nanotechnologies have been demonstrated to have the analytical sensitivity required for the use of saliva as a diagnostic medium to detect and predict disease progression. However, these technologies have not yet been integrated into current clinical practice and work flow. CONTENT: As a diagnostic fluid, saliva offers advantages over serum because it can be collected noninvasively by individuals with modest training, and it offers a cost-effective approach for the screening of large populations. Gland-specific saliva can also be used for diagnosis of pathology specific to one of the major salivary glands. There is minimal risk of contracting infections during saliva collection, and saliva can be used in clinically challenging situations, such as obtaining samples from children or handicapped or anxious patients, in whom blood sampling could be a difficult act to perform. In this review we highlight the production of and secretion of saliva, the salivary proteome, transportation of biomolecules from blood capillaries to salivary glands, and the diagnostic potential of saliva for use in detection of cardiovascular disease and oral and breast cancers. We also highlight the barriers to application of saliva testing and its advancement in clinical settings. SUMMARY: Saliva has the potential to become a first-line diagnostic sample of choice owing to the advancements in detection technologies coupled with combinations of biomolecules with clinical relevance. (C) 2011 American Association for Clinical Chemistry

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Over the past 10 years, the use of saliva as a diagnostic fluid has gained attention and has become a translational research success story. Some of the current nanotechnologies have been demonstrated to have the analytical sensitivity required for the use of saliva as a diagnostic medium to detect and predict disease progression. However, these technologies have not yet been integrated into current clinical practice and work flow. As a diagnostic fluid, saliva offers advantages over serum because it can be collected noninvasively by individuals with modest training, and it offers a cost-effective approach for the screening of large populations. Gland-specific saliva can also be used for diagnosis of pathology specific to one of the major salivary glands. There is minimal risk of contracting infections during saliva collection, and saliva can be used in clinically challenging situations, such as obtaining samples from children or handicapped or anxious patients, in whom blood sampling could be a difficult act to perform. In this review we highlight the production of and secretion of saliva, the salivary proteome, transportation of biomolecules from blood capillaries to salivary glands, and the diagnostic potential of saliva for use in detection of cardiovascular disease and oral and breast cancers. We also highlight the barriers to application of saliva testing and its advancement in clinical settings. Saliva has the potential to become a first-line diagnostic sample of choice owing to the advancements in detection technologies coupled with combinations of biomolecules with clinical relevance.

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The present work demonstrates a systematic approach for the synthesis of pure kesterite-phase Cu2ZnSnS4 (CZTS) nanocrystals with a uniform size distribution by a one-step, thioglycolic acid (TGA)-assisted hydrothermal route. The formation mechanism and the role of TGA in the formation of CZTS compound were thoroughly studied. It has been found that TGA interacted with Cu2+ to form Cu+ at the initial reaction stage and controlled the crystal-growth of CZTS nanocrystals during the hydrothermal reaction. The consequence of the reduction of Cu2+ to Cu+ led to the formation Cu2−xS nuclei, which acted as the crystal framework for the formation of CZTS compound. CZTS was formed by the diffusion of Zn2+ and Sn4+ cations to the lattice of Cu2−xS during the hydrothermal reaction. The as-synthesized CZTS nanocrystals exhibited strong light absorption over the range of wavelength beyond 1000 nm. The band gap of the material was determined to be 1.51 eV, which is optimal for application in photoelectric energy conversion device.

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Purpose Health service quality is an important determinant for health service satisfaction and behavioral intentions. The purpose of this paper is to investigate requirements of e‐health services and to develop a measurement model to analyze the construct of “perceived e‐health service quality.” Design/methodology/approach The paper adapts the C‐OAR‐SE procedure for scale development by Rossiter. The focal aspect is the “physician‐patient relationship” which forms the core dyad in the healthcare service provision. Several in‐depth interviews were conducted in Switzerland; first with six patients (as raters), followed by two experts of the healthcare system (as judges). Based on the results and an extensive literature research, the classification of object and attributes is developed for this model. Findings The construct e‐health service quality can be described as an abstract formative object and is operationalized with 13 items: accessibility, competence, information, usability/user friendliness, security, system integration, trust, individualization, empathy, ethical conduct, degree of performance, reliability, and ability to respond. Research limitations/implications Limitations include the number of interviews with patients and experts as well as critical issues associated with C‐OAR‐SE. More empirical research is needed to confirm the quality indicators of e‐health services. Practical implications Health care providers can utilize the results for the evaluation of their service quality. Practitioners can use the hierarchical structure to measure service quality at different levels. The model provides a diagnostic tool to identify poor and/or excellent performance with regard to the e‐service delivery. Originality/value The paper contributes to knowledge with regard to the measurement of e‐health quality and improves the understanding of how customers evaluate the quality of e‐health services.

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The increasing prevalence of dementia in Australia (and worldwide) over the next few decades poses enormous social, health and economic challenges. In the absence of a cure, strategies to prevent, delay the onset of, or reduce the impact of dementia are required to contain a growing disease burden, and health and care costs. A population health approach has the potential to substantially reduce the impact of dementia. Internationally, many countries have started to adopt population health strategies that incorporate elements of dementia prevention. The authors examine some of the elements of such an approach and barriers to its implementation. International dementia frameworks and strategies were reviewed to identify options utilized for a population health approach to dementia. Internationally and nationally, dementia frameworks are being developed that include population health approaches. Most of the frameworks identified included early diagnosis and intervention, and increasing community awareness as key objectives, while several included promotion of the links between a healthy lifestyle and reduced risk for dementia. A poor evidence base (especially for illness prevention), diagnostic and technical limitations, and policy and implementation issues are significant barriers in maximizing the promise of population health approaches in this area. The review and analysis of the population health approach to dementia will inform national and jurisdictional policy development.

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Background We have previously demonstrated that circulating NT-proBNP is truncated at the N and C termini. Aims of this study are three-fold: firstly to determine whether the NT-proBNP levels correlate with NYHA functional classes when measuring with different antibody pairs; secondly to evaluate the diagnostic potential of ProBNP and; thirdly to investigate whether combining NT-proBNP assays with or without ProBNP would lead to better diagnostic accuracies. Methods Plasma samples were collected from healthy controls (n = 52) and HF patients (n = 46). Customized AlphaLISA® immunoassays were developed and validated to measure the concentrations of proBNP and NT-proBNP (with antibodies targeting 13–45, 13–76, 28–76). The diagnostic performance and predictive value of proBNP and NT-proBNP assays and their combinations were evaluated. Results Plasma proBNP assay showed acceptable diagnostic performance. NT-proBNP13–76 assay is useful in diagnosing and stratifying HF patients. The diagnostic performance of NT-proBNP13–76 demonstrated improvement over commercial NT-proBNP tests. The combination of NT-proBNP13–76 with NT-proBNP28–76 assays gave the best diagnostic assay performance. Conclusion Our results demonstrate that while there is major heterogeneity in circulating NT-proBNP, specific epitopes of the peptides are extraordinarily stable, providing ideal targets for clinically useful diagnostic assays. Future new clinical diagnostic clinical trials should include a multimarker approach rather than using a single marker to diagnose HF.