46 resultados para Detection and fault location
Resumo:
Polymerase chain reaction (PCR) is now recognized as a sensitive and specific method for detecting Plasmodium species in blood. In this Study. we tested 279 blood samples, from patients with Suspected malaria, by a PCR assay utilizing species-specific colorimetric detection. and compared the results to light microscopy. Overall, both assays were in agreement for 270 of the 279 specimens. P. vivax was detected in 131 (47.0%) specimens. P. falciparum in 64 (22.9%) specimens, P. ovale in 6 (2.1%) specimens, and P. malariae in 5 (1.8%) specimens. Both P. falciparum and P. vivax were detected in a further 10 (3.6%) specimens, and 54 (19.3%) specimens were negative by both assays. In the remaining nine specimens, microscopy either failed to detect the parasite or incorrectly identified the species present. In summary, the sensitivity, specificity and simplicity of the PCR assay makes it particularly suitable for use in a diagnostic laboratory. (C) 2004 Elsevier Inc. All rights reserved.
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An anaerobic landfill leachate bioreactor was operated with crystalline cellulose and sterile landfill leacbate until a steady state was reached. Cellulose hydrolysis, acidogenesis, and methanogenesis were measured. Microorganisms attached to the cellulose surfaces were hypothesized to be the cellulose hydrolyzers. 16S rRNA gene clone libraries were prepared from this attached fraction and also from the mixed fraction (biomass associated with cellulose particles and in the planktonic phase). Both clone libraries were dominated by Firmicutes phylum sequences (100% of the attached library and 90% of the mixed library), and the majority fell into one of five lineages of the clostridia. Clone group 1 (most closely related to Clostridium stercorarium), clone group 2 (most closely related to Clostridium thermocellum), and clone group 5 (most closely related to Bacteroides cellulosolvens) comprised sequences in Clostridium group III. Clone group 3 sequences were in Clostridium group XIVa (most closely related to Clostridium sp. strain XB90). Clone group 4 sequences were affiliated with a deeply branching clostridial lineage peripherally associated with Clostridium group VI. This monophyletic group comprises a new Clostridium cluster, designated cluster VIa. Specific fluorescence in situ hybridization (FISH) probes for the five groups were designed and synthesized, and it was demonstrated in FISH experiments that bacteria targeted by the probes for clone groups 1, 2, 4, and 5 were very abundant on the surfaces of the cellulose particles and likely the key cellulolytic microorganisms in the landfill bioreactor. The FISH probe for clone group 3 targeted cells in the planktonic phase, and these organisms were hypothesized to be glucose fermenters.
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Objective: To assess the value of cusum analysis in hospital bed management. Design: Comparative analysis of medical patient flows, bed occupancy, and emergency department admission rates and access block over 2 years. Setting: Internal Medicine Services and Emergency Department in a teaching hospital. Interventions: Improvements in bed use and changes in the level of available beds. Main outcome measures: Average length of stay; percentage occupancy of available beds; number of patients waiting more than 8 hours for admission (access block); number of medical patients occupying beds in non-medical wards; and number of elective surgical admissions. Results: Cusum analysis provided a simple means of revealing important trends in patient flows that were not obvious in conventional time-series data. This prompted improvements in bed use that resulted in a decrease of 9500 occupied bed-days over a year. Unfortunately and unexpectedly, after some initial improvement, the levels of access block, medical ward congestion and elective surgical admissions all then deteriorated significantly. This was probably caused by excessive bed closures in response to the initial improvement in bed use. Conclusion: Cusum analysis is a useful technique for the early detection of significant changes in patient flows and bed use, and in determining the appropriate number of beds required for a given rate of patient flow.
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Background. Genital ulcer disease (GUD) is commonly caused by pathogens for which suitable therapies exist, but clinical and laboratory diagnoses may be problematic. This collaborative project was undertaken to address the need for a rapid, economical, and sensitive approach to the detection and diagnosis of GUD using noninvasive techniques to sample genital ulcers. Methods. The genital ulcer disease multiplex polymerase chain reaction (GUMP) was developed as an inhouse nucleic acid amplification technique targeting serious causes of GUD, namely, herpes simplex viruses (HSVs), Haemophilus ducreyi, Treponema pallidum, and Klebsiella species. In addition, the GUMP assay included an endogenous internal control. Amplification products from GUMP were detected by enzyme linked amplicon hybridization assay (ELAHA). Results. GUMP-ELAHA was sensitive and specific in detecting a target microbe in 34.3% of specimens, including 1 detection of HSV-1, three detections of HSV-2, and 18 detections of T. pallidum. No H. ducreyi has been detected in Australia since 1998, and none was detected here. No Calymmatobacterium ( Klebsiella) granulomatis was detected in the study, but there were 3 detections during ongoing diagnostic use of GUMP-ELAHA in 2004 and 2005. The presence of C. granulomatis was confirmed by restriction enzyme digestion and nucleotide sequencing of the 16S rRNA gene for phylogenetic analysis. Conclusions. GUMP-ELAHA permitted comprehensive detection of common and rare causes of GUD and incorporated noninvasive sampling techniques. Data obtained by using GUMP-ELAHA will aid specific treatment of GUD and better define the prevalence of each microbe among at-risk populations with a view to the eradication of chancroid and donovanosis in Australia.
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Phytophthora diseases cause major losses to agricultural and horticultural production in Australia and worldwide. Most Phytophthora diseases are soilborne and difficult to control, making disease prevention an important component of many disease management strategies. Detection and identification of the causal agent, therefore, is an essential part of effective disease management. This paper describes the development and validation of a DNA-based diagnostic assay that can detect and identify 27 different Phytophthora species. We have designed PCR primers that are specific to the genus Phytophthora. The resulting amplicon after PCR is subjected to digestion by restriction enzymes to yield a specific restriction pattern or fingerprint unique to each species. The restriction patterns are compared with a key comprising restriction patterns of type specimens or representative isolates of 27 different Phytophthora species. A number of fundamental issues, such as genetic diversity within and among species which underpin the development and validation of DNA-based diagnostic assays, are addressed in this paper.
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* Chronic heart failure (CHF) is found in 1.5%–2.0% of Australians. Considered rare in people aged less than 45 years, its prevalence increases to over 10% in people aged ≥ 65 years. * CHF is one of the most common reasons for hospital admission and general practitioner consultation in the elderly (≥ 70 years). * Common causes of CHF are ischaemic heart disease (present in > 50% of new cases), hypertension (about two-thirds of cases) and idiopathic dilated cardiomyopathy (around 5%–10% of cases). * Diagnosis is based on clinical features, chest x-ray and objective measurement of ventricular function (eg, echocardiography). Plasma levels of B-type natriuretic peptide (BNP) may have a role in diagnosis, primarily as a test for exclusion. Diagnosis may be strengthened by a beneficial clinical response to treatment(s) directed towards amelioration of symptoms. * Management involves prevention, early detection, amelioration of disease progression, relief of symptoms, minimisation of exacerbations, and prolongation of survival.
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A total of 36 tonsil swab samples were collected from healthy swine prior to slaughter at the abattoirs in Can tho and Tien giang provinces of Southern Vietnam, The presence of Pasteurella multocida in these samples was detected by the combination of direct cultivation and isolation, mouse inoculation and the polymerase chain reaction (PM-PCR). P. multocida was detected in 16 samples by PCR, with 17 strains ultimately isolated. All samples were negative for serogroup B by HSB-PCR and conventional serotyping, with isolates identified as A:3, D:1 or D:3. In addition, all samples were determined to be negative for the P. multocida toxin (PMT). Characterisation of isolated P, multocida by REP-PCR and biotyping revealed nine distinct REP profiles and seven biotypes among the 17 isolates. Some correlation was seen with P. multocida isolated from a previous Australian outbreak of acute swine pasteurellosis, and those isolated from fowl cholera outbreaks in Vietnamese poultry. (C) 2000 Elsevier Science B.V. All rights reserved.
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Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).
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Objectives: Advances in surface electromyography (sEMG) techniques provide a clear indication that refinement of electrode location relative to innervation zones (IZ) is required in order to optimise the accuracy, relevance and repeatability of the sEMG signals. The aim of this study was to identify the IZ for the sternocleidomastoid and anterior scalene muscles to provide guidelines for electrode positioning for future clinical and research applications. Methods: Eleven volunteer subjects participated in this study. Myoelectric signals were detected from the sternal and clavicular heads of the stemocleidomastoid and the anterior scalene muscles bilaterally using a linear array of 8 electrodes during isometric cervical flexion contractions. The signals were reviewed and the IZ(s) were identified, marked on the subjects' skin and measurements were obtained relative to selected anatomical landmarks. Results: The position of the IZ lay consistently around the mid-point or in the superior portion of the muscles studied. Conclusions: Results suggest that electrodes should be positioned over the lower portion of the muscle and not the mid-point, which has been commonly used in previous studies. Recommendations for sensor placement on these muscles should assist investigators and clinicians to ensure improved validity in future sEMG applications. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.
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In order to understand the earthquake nucleation process, we need to understand the effective frictional behavior of faults with complex geometry and fault gouge zones. One important aspect of this is the interaction between the friction law governing the behavior of the fault on the microscopic level and the resulting macroscopic behavior of the fault zone. Numerical simulations offer a possibility to investigate the behavior of faults on many different scales and thus provide a means to gain insight into fault zone dynamics on scales which are not accessible to laboratory experiments. Numerical experiments have been performed to investigate the influence of the geometric configuration of faults with a rate- and state-dependent friction at the particle contacts on the effective frictional behavior of these faults. The numerical experiments are designed to be similar to laboratory experiments by DIETERICH and KILGORE (1994) in which a slide-hold-slide cycle was performed between two blocks of material and the resulting peak friction was plotted vs. holding time. Simulations with a flat fault without a fault gouge have been performed to verify the implementation. These have shown close agreement with comparable laboratory experiments. The simulations performed with a fault containing fault gouge have demonstrated a strong dependence of the critical slip distance D-c on the roughness of the fault surfaces and are in qualitative agreement with laboratory experiments.
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Objective. To identify differentially expressed genes in synovial fibroblasts and examine the effect on gene expression of exposure to TNF-alpha and IL-1beta. Methods. Restriction fragment differential display was used to isolate genes using degenerate primers complementary to the lysophosphatidic acid acyl transferase gene family. Differential gene expression was confirmed by reverse transcription-polymerase chain reaction and immunohistochemistry using a variety of synovial fibroblasts, including cells from patients with osteoarthritis and self-limiting parvovirus arthritis. Results. Irrespective of disease process, synovial fibroblasts constitutively produced higher levels of IL-6 and monocyte chemoattractant protein 1 (MCP-1) (CCL2) than skin fibroblasts. Seven genes were differentially expressed in synovial fibroblasts compared with skin fibroblasts. Of these genes, four [tissue factor pathway inhibitor 2 (TFPI2), growth regulatory oncogene beta (GRObeta), manganese superoxide dismutase (MnSOD) and granulocyte chemotactic protein 2 (GCP-2)] were all found to be constitutively overexpressed in synoviocytes derived from patients with osteoarthritis. These four genes were only weakly expressed in other synovial fibroblasts (rheumatoid and self-limiting parvovirus infection). However, expression in all types of fibroblasts was increased after stimulation with TNF-alpha and IL-1beta. Three other genes (aggrecan, biglycan and caldesmon) were expressed at higher levels in all types of synovial fibroblasts compared with skin fibroblasts even after stimulation with TNF-alpha and IL-1. Conclusions. Seven genes have been identified with differential expression patterns in terms of disease process (osteoarthritis vs rheumatoid arthritis), state of activation (resting vs cytokine activation) and anatomical location (synovium vs skin). Four of these genes, TFPI2, GRObeta (CXCL2), MnSOD and GCP-2 (CXCL6), were selectively overexpressed in osteoarthritis fibroblasts rather than rheumatoid fibroblasts. While these differences may represent differential behaviour of synovial fibroblasts in in vitro culture, these observations suggest that TFPI2, GRObeta (CXCL2), MnSOD and GCP-2 (CXCL6) may represent new targets for treatments specifically tailored to osteoarthritis.