8 resultados para matrix-based detection


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This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.

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Anisakis simplex is a nematode parasite that can infect humans who have eaten raw or undercooked seafood. Larvae invading the gastrointestinal mucosa excrete/secrete proteins that are implicated in the pathogenesis of anisakiasis and can induce IgE-mediated symptoms. Since Ani s 1 is a potent secreted allergen with important clinical relevance, its measurement could assess the quality of allergenic products used in diagnosis/immunotherapy of Anisakis allergy and track the presence of A. simplex parasites in fish foodstuffs. An antibody-based ELISA for quantification of Ani s 1 has been developed based on monoclonal antibody 4F2 as capture antibody and biotin-labelled polyclonal antibodies against Ani s 1 as detection reagent. The dose-response standard curves, obtained with natural and recombinant antigens, ranged from 4 to 2000 ng/ml and were identical and parallel to that of the A. simplex extract. The linear portion of the dose-response curve with nAni s 1 was between 15 and 250 ng/ml with inter-assay and intra-assays coefficients of variation less than 20% and 10%, respectively. The assay was specific since there was no cross-reaction with other extracts (except Ascaris extracts) and was highly sensitive (detection limit of 1·8 ng/ml), being able to detect Ani s 1 in fish extracts from codfish and monkfish.

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A new oligochromatographic assay, Speed-Oligo Novel Influenza A H1N1, was designed and optimized for the specific detection of the 2009 influenza A H1N1 virus. The assay is based on a PCR method coupled to detection of PCR products by means of a dipstick device. The target sequence is a 103-bp fragment within the hemagglutinin gene. The analytical sensitivity of the new assay was measured with serial dilutions of a plasmid that contained the target sequence, and we determined that down to one copy per reaction of the plasmid was reliably detected. Diagnostic performance was assessed with 103 RNAs from suspected cases (40 positive and 63 negative results) previously analyzed with a reference real-time PCR technique. All positive cases were confirmed, and no false-positive results were detected with the new assay. No cross-reactions were observed when other viral strains or clinical samples with other respiratory viruses were tested. According to these results, this new assay has 100% sensitivity and specificity. The turnaround time for the whole procedure was 140 min. The assay may be especially useful for the specific detection of 2009 H1N1 virus in laboratories not equipped with real-time PCR instruments

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BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

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Some sites of extrapulmonary tuberculosis and focal complications of brucellosis are very difficult to differentiate clinically, radiologically, and even histopathologically. Conventional microbiological methods for the diagnosis of extrapulmonary tuberculosis and complicated brucellosis not only lack adequate sensitivity, they are also time consuming, which could lead to an unfavourable prognosis. The aim of this work was to develop a multiplex real-time PCR assay based on SYBR Green I to simultaneously detect Brucella spp and Mycobacterium tuberculosis complex and evaluate the efficacy of the technique with different candidate genes. The IS711, bcsp31 and omp2a genes were used for the identification of Brucella spp and the IS6110, senX3-regX3 and cfp31 genes were targeted for the detection of the M. tuberculosis complex. As a result of the different combinations of primers, nine different reactions were evaluated. A test was defined as positive only when the gene combinations were capable of co-amplifying both pathogens in a single reaction tube and showed distinguishable melting temperatures for each microorganism. According to the melting analysis, only three combinations of amplicons (senX3-regX3+bcsp31, senX3-regX3+IS711 and IS6110+IS711) were visible. Detection limits of senX3-regX3+bcsp31 and senX3-regX3+IS711 were of 2 and 3 genome equivalents for M. tuberculosis complex and Brucella while for IS6110+IS711 they were of 200 and 300 genome equivalents, respectively. The three assays correctly identified all the samples, showing negative results for the control patients. The presence of multicopy elements and GC content were the components most influencing the efficiency of the test; this should be taken into account when designing a multiplex-based SYBR Green I assay. In conclusion, multiplex real time PCR assays based on the targets senX3-regX3+bcsp31 and senX3-regX3+IS711 using SYBR Green I are highly sensitive and reproducible. This may therefore be a practical approach for the rapid differential diagnosis between extrapulmonary tuberculosis and complicated brucellosis.

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Lactococcus garvieae is a Gram-positive, catalase negative coccus arranged in pairs or short chains, well-known as a fish pathogen. We report a case of Infective Endocarditis (IE) by L. garvieae in a native valve from a 68-year-old male with unknown history of contact with raw fish and an extensive history of heart disease. This case highlights the reliability of MALDI-TOF MS compared to conventional methods in the identification of rare microorganisms like this.

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This paper addresses a fully automatic landmarks detection method for breast reconstruction aesthetic assessment. The set of landmarks detected are the supraesternal notch (SSN), armpits, nipples, and inframammary fold (IMF). These landmarks are commonly used in order to perform anthropometric measurements for aesthetic assessment. The methodological approach is based on both illumination and morphological analysis. The proposed method has been tested with 21 images. A good overall performance is observed, although several improvements must be achieved in order to refine the detection of nipples and SSNs.

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We present the first evaluation of a novel molecular assay, the Speed-oligo Direct Mycobacterium tuberculosis (SO-DMT) assay, which is based on PCR combined with a dipstick for the detection of mycobacteria and the specific identification of M. tuberculosis complex (MTC) in respiratory specimens. A blind evaluation was carried out in two stages: first, under experimental conditions on convenience samples comprising 20 negative specimens, 44 smear- and culture-positive respiratory specimens, and 11 sputa inoculated with various mycobacterium-related organisms; and second, in the routine workflow of 566 fresh respiratory specimens (4.9% acid-fast bacillus [AFB] smear positives, 7.6% MTC positives, and 1.8% nontuberculous mycobacteria [NTM] culture positives) from two Mycobacterium laboratories. SO-DMT assay showed no reactivity in any of the mycobacterium-free specimens or in those with mycobacterium-related organisms. Compared to culture, the sensitivity in the selected smear-positive specimens was 0.91 (0.92 for MTC and 0.90 for NTM), and there was no molecular detection of NTM in a tuberculosis case or vice versa. With respect to culture and clinical data, the sensitivity, specificity, and positive and negative predictive values for the SO-DMT system in routine specimens were 0.76 (0.93 in smear positives [1.0 for MTC and 0.5 for NTM] and 0.56 in smear negatives [0.68 for MTC and 0.16 for NTM]), 0.99, 0.85 (1.00 in smear positives and 0.68 in smear negatives), and 0.97, respectively. Molecular misidentification of NTM cases occurred when testing 2 gastric aspirates from two children with clinically but not microbiologically confirmed lung tuberculosis. The SO-DMT assay appears to be a fast and easy alternative for detecting mycobacteria and differentiating MTC from NTM in smear-positive respiratory specimens.