960 resultados para Diagnostic tools


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The topic of fault detection and diagnostics (FDD) is studied from the perspective of proactive testing. Unlike most research focus in the diagnosis area in which system outputs are analyzed for diagnosis purposes, in this paper the focus is on the other side of the problem: manipulating system inputs for better diagnosis reasoning. In other words, the question of how diagnostic mechanisms can direct system inputs for better diagnosis analysis is addressed here. It is shown how the problem can be formulated as decision making problem coupled with a Bayesian Network based diagnostic mechanism. The developed mechanism is applied to the problem of supervised testing in HVAC systems.

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This project describes how Streptococcus agalactiae can be transmitted experimentally in Queensland grouper. The implications of this research furthers the relatedness between Australian S. agalactiae strains from animals and humans. Additionally, this research has developed diagnostic tools for Australian State Veterinary Laboratories and Universities, which will assist in State and National aquatic animal disease detection, surveillance, disease monitoring and reporting

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There is a critical need for screening and diagnostic tools (SDT) for autism spectrum conditions (ASC) in regional languages in South Asia. To address this, we translated four widely used SDT (Social Communication Disorder Checklist, Autism Spectrum Quotient, Social Communication Questionnaire, and Autism Diagnostic Observation Schedule) into Bengali and Hindi, two main regional languages (∼ 360 million speakers), and tested their usability in children with and without ASC. We found a significant difference in scores between children with ASC (n = 45 in Bengali, n = 40 in Hindi) and typically developing children (n = 43 in Bengali, n = 42 in Hindi) on all SDTs. These results demonstrate that these SDTs are usable in South Asia, and constitute an important resource for epidemiology research and clinical diagnosis in the region.

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We consider the issue of performing residual and local influence analyses in beta regression models with varying dispersion, which are useful for modelling random variables that assume values in the standard unit interval. In such models, both the mean and the dispersion depend upon independent variables. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. An application using real data is presented and discussed.

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Traumatic lesions of the subcutaneous fatty tissue provide important clues for forensic reconstruction. The interpretation of these patterns requires a precise description and recording of the position and extent of each lesion. During conventional autopsy, this evaluation is performed by dissecting the skin and subcutaneous tissues in successive layers. In this way, depending on the force and type of impact (right angle or tangent), several morphologically distinct stages of fatty tissue damage can be differentiated: perilobular hemorrhage (I), contusion (II), or disintegration (III) of the fat lobuli, and disintegration with development of a subcutaneous cavity (IV). In examples of virtopsy cases showing blunt trauma to the skin and fatty tissue, we analyzed whether these lesions can also be recorded and classified using multislice computed tomography (MSCT) and magnetic resonance imaging (MRI). MSCT has proven to be a valuable screening method to detect the lesions, but MRI is necessary in order to properly differentiate and classify the grade of damage. These noninvasive radiological diagnostic tools can be further developed to play an important role in forensic examinations, in particular when it comes to evaluating living trauma victims.

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We describe the case of a patient with a T-lymphoblastic lymphoma whose disseminated mucormycosis was diagnosed with delay, and we address the diagnostic and therapeutic decision-making process and review the diagnostic workup of patients with potential IFD. The diagnosis was delayed despite a suggestive radiological presentation of the patient's pulmonary lesion. The uncommon risk profile (T-lymphoblastic lymphoma, short neutropenic phases) wrongly led to a low level of suspicion. The diagnosis was also hampered by the lack of indirect markers for infections caused by Mucorales, the low sensitivity of both fungal culture and panfungal PCR, and the limited availability of species-specific PCR. A high level of suspicion of IFD is needed, and aggressive diagnostic procedures should be promptly initiated even in apparently low-risk patients with uncommon presentations. The extent of the analytical workup should be decided on a case-by-case base. Diagnostic tests such as the galactomannan and β-D-glucan test and/or PCR on biological material followed by sequencing should be chosen according to their availability and after evaluation of their specificity and sensitivity. In high-risk patients, preemptive therapy with a broad-spectrum mould-active antifungal agent should be started before definitive diagnostic findings become available.

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We have carried out a discovery proteomics investigation aimed at identifying disease biomarkers present in saliva, and, more specifically, early biomarkers of inflammation. The proteomic characterization of saliva is possible due to the straightforward and non-invasive sample collection that allows repetitive analyses for pharmacokinetic studies. These advantages are particularly relevant in the case of newborn patients. The study was carried out with samples collected during the first 48 hours of life of the newborns according to an approved Ethic Committee procedure. In particular, the salivary samples were collected from healthy and infected (n=1) newborns. Proteins were extracted through cycles of sonication, precipitated in ice cold acetone, resuspended and resolved by 2D-electrophoresis. MALDI TOF/TOF mass spectrometry analysis was performed for each spot obtaining the proteins’ identifications. Then we compared healthy newborn salivary proteome and an infected newborn salivary proteome in order to investigate proteins differently expressed in inflammatory condition. In particular the protein alpha-1-antitrypsin (A1AT), correlated with inflammation, was detected differently expressed in the infected newborn saliva. Therefore, in the second part of the project we aimed to develop a robust LC-MS based method that identifies and quantifies this inflammatory protein within saliva that might represent the first relevant step to diagnose a condition of inflammation with a no-invasive assay. The same LC-MS method is also useful to investigate the presence of the F allelic variant of the A1AT in biological samples, which is correlated with the onset of pulmonary diseases. In the last part of the work we analysed newborn saliva samples in order to investigate how phospholipids and mediators of inflammation (eicosanoids) are subject to variations under inflammatory conditions and a trend was observed in lysophosphatidylcholines composition according to the inflammatory conditions.

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The superoxide radical is considered to play important roles in physiological processes as well as in the genesis of diverse cytotoxic conditions such as cancer, various cardiovascular disorders and neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), Parkinson’s disease (PD) and Alzheimer’s disease (AD). The detection and quantification of superoxide within cells is of critical importance to understand biological roles of superoxide and to develop preventive strategies against free radical-mediated diseases. Cyclic nitrone spin traps such as DMPO, EMPO, DEPMPO, BMPO and their derivatives have been widely used in conjunction with ESR spectroscopy to detect cellular superoxide with some success. However, the formation of unstable superoxide adducts from the reaction of cyclic nitrones with superoxide is a stumbling block in detecting superoxide by using electron spin resonance (ESR). A chemiluminescent probe, lucigenin, and fluorogenic probes, hydroethidium and MitoSox, are the other frequently used methods in detecting superoxide. However, luceginen undergoes redox-cycling producing superoxide by itself, and hydroethidium and MitoSox react with other oxidants apart from superoxide forming red fluorescent products contributing to artefacts in these assays. Hence, both methods were deemed to be inappropriate for superoxide detection. In this study, an effective approach, a selective mechanism-based colorimetric detection of superoxide anion has been developed by using silylated azulenyl nitrones spin traps. Since a nitrone moiety and an adjacent silyl group react readily with radicals and oxygen anions respectively, such nitrones can trap superoxide efficiently because superoxide is both a radical and an oxygen anion. Moreover, the synthesized nitrone is designed to be triggered solely by superoxide and not by other commonly observed oxygen radicals such as hydroxyl radical, alkoxyl radicals and peroxyl radical. In vitro studies have shown that these synthesized silylated azylenyl nitrones and the mitochondrial-targeted guanylhydrazone analog can trap superoxide efficiently yielding UV-vis identifiable and even potentially fluorescence-detectable orange products. Therefore, the chromotropic detection of superoxide using these nitrones can be a promising method in contrast to other available methods.

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Staphylococcus aureus, one of the major pathogenic bacteria, is associated with substantial morbidity and mortality. The disease burden of staphylococcal infections is significant, which is primarily attributed to its adaptability and resistance to environmental stresses. S. aureus has the ability to develop multiple resistances to antimicrobial agents. These high resistances make pathogenicity of S. aureus one of the most complex mechanisms to understand and manage. Proteomic and bioinformatics approaches show great potential in exploring microbial adaptation strategies, ability to cause disease by pathogenic bacteria and the development of diagnostic tools. A summary of the latest developments in the application of ‘omics’ technologies to understand resistance mechanisms in S. aureus and their future role in antistaphylococcal vaccine and/or drug discovery is given here.

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Graminicolous Downy Mildew (GDM) diseases caused by the genera Peronosclerospora (13 spp.) and Sclerophthora (6 spp. and 1 variety) are poorly studied but destructive diseases of major crops such as corn, sorghum, sugarcane and other graminoids. Eight of the 13 described Peronosclerospora spp. are able to infect corn. In particular, P. philippinensis (= P. sacchari), P. maydis, P. heteropogonis, and S. rayssiae var. zeae cause major losses in corn yields in tropical Asia. In 2012 a new species, P. australiensis, was described based on isolates previously identified as P. maydis in Australia; this species is now a pathogen of major concern. Despite the strong impact of GDM diseases, there are presently no reliable molecular methods available for their detection. GDM pathogens are among the most difficult Oomycetes to identify using molecular tools, as their taxonomy is very challenging, and little genetic sequence data are available for development of molecular tools to detect GDM pathogens to species level. For example, from over 15 genes used in identification, diagnostics or phylogeny of Phytophthora, only ITS1 and cox2 show promise for use with GDM pathogens. Multiplex/multigene conventional and qPCR assays are currently under evaluation for the detection of economically important GDM spp. Scientists from the USA, Germany, Canada, Australia, and the Philippines are collaborating on the development and testing of diagnostic tools for these pathogens of concern.