Interference of raw milk autochthonous microbiota on the performance of conventional methodologies for Listeria monocytogenes and Salmonella spp. detection

Pathogen detection in foods by reliable methodologies is very important to guarantee microbilogical safety. However, peculiar characteristics of certain foods, such as autochthonous microbiota, can directly influence pathogen development and detection. With the objective of verifying the performance of the official analytical methodologies for the isolation of Listeria monocytogenes and Salmonella in milk, different concentrations of these pathogens were inoculated in raw milk treatments with different levels of mesophilic aerobes, and then submitted to the traditional isolation procedures for the inoculated pathogens. Listeria monocytogenes was inoculated at the range of 0.2-5.2 log CFU/mL in treatments with 1.8-8.2 log CFU/mL. Salmonella Enteritidis was inoculated at 0.9-3.9 log CFU/mL in treatments with 3.0-8.2 log CFU/mL. The results indicated that recovery was not possible or was more difficult in the treatments with high counts of mesophilic aerobes and low levels of the pathogens, indicating interference of raw milk autochthonous microbiota. This interference was more evident for L. monocytogenes, once the pathogen recovery was not possible in treatments with mesophilic aerobes up to 4.0 log CFU/mL and inoculum under 2.0 log CFU/mL. For S. Enteritidis the interference appeared to be more non-specific. (C) 2007 Elsevier GmbH. All rights reserved.

The structure of quantum Lie algebras for the classical series, B-l, C-l and D-l

The structure constants of quantum Lie algebras depend on a quantum deformation parameter q and they reduce to the classical structure constants of a Lie algebra at q = 1. We explain the relationship between the structure constants of quantum Lie algebras and quantum Clebsch-Gordan coefficients for adjoint x adjoint --> adjoint We present a practical method for the determination of these quantum Clebsch-Gordan coefficients and are thus able to give explicit expressions for the structure constants of the quantum Lie algebras associated to the classical Lie algebras B-l, C-l and D-l. In the quantum case the structure constants of the Cartan subalgebra are non-zero and we observe that they are determined in terms of the simple quantum roots. We introduce an invariant Killing form on the quantum Lie algebras and find that it takes values which are simple q-deformations of the classical ones.

Intestinal content detection in capsule endoscopy using robust features

This work covers two aspects. First, it generally compares and summarizes the similarities and differences of state of the art feature detector and descriptor and second it presents a novel approach of detecting intestinal content (in particular bubbles) in capsule endoscopy images. Feature detectors and descriptors providing invariance to change of perspective, scale, signal-noise-ratio and lighting conditions are important and interesting topics in current research and the number of possible applications seems to be numberless. After analysing a selection of in the literature presented approaches, this work investigates in their suitability for applications information extraction in capsule endoscopy images. Eventually, a very good performing detector of intestinal content in capsule endoscopy images is presented. A accurate detection of intestinal content is crucial for all kinds of machine learning approaches and other analysis on capsule endoscopy studies because they occlude the field of view of the capsule camera and therefore those frames need to be excluded from analysis. As a so called “byproduct” of this investigation a graphical user interface supported Feature Analysis Tool is presented to execute and compare the discussed feature detectors and descriptor on arbitrary images, with configurable parameters and visualized their output. As well the presented bubble classifier is part of this tool and if a ground truth is available (or can also be generated using this tool) a detailed visualization of the validation result will be performed.

Detection of human bocavirus and human metapneumovirus by real-time PCR from patients with respiratory symptoms in Southern Brazil

The introduction of newer molecular methods has led to the discovery of new respiratory viruses, such as human metapneumovirus (hMPV) and human bocavirus (hBoV), in respiratory tract specimens. We have studied the occurrence of hMPV and hBoV in the Porto Alegre (PA) metropolitan area, one of the southernmost cities of Brazil, evaluating children with suspected lower respiratory tract infection from May 2007-June 2008. A real-time polymerase chain reaction method was used for amplification and detection of hMPV and hBoV and to evaluate coinfections with respiratory syncytial virus (RSV), influenza A and B, parainfluenza 1, 2 and 3, human rhinovirus and human adenovirus. Of the 455 nasopharyngeal aspirates tested, hMPV was detected in 14.5% of samples and hBoV in 13.2%. A unique causative viral agent was identified in 46.2% samples and the coinfection rate was 43.7%. For hBoV, 98.3% of all positive samples were from patients with mixed infections. Similarly, 84.8% of all hMPV-positive results were also observed in mixed infections. Both hBoV and hMPV usually appeared with RSV. In summary, this is the first confirmation that hMPV and hBoV circulate in PA; this provides evidence of frequent involvement of both viruses in children with clinical signs of acute viral respiratory tract infection, although they mainly appeared as coinfection agents.

Nested-PCR for the detection of Mycoplasma hyopneumoniae in bronchial alveolar swabs, frozen tissues and formalin-fixed paraffin-embedded swine lung samples: comparative evaluation with immunohistochemical findings and histological features

The diagnosis of Mycoplasma hyopneumoniae infection is often performed through histopathology, immunohistochemistry (IHC) and polymerase chain reaction (PCR) or a combination of these techniques. PCR can be performed on samples using several conservation methods, including swabs, frozen tissue or formalin-fixed and paraffin-embedded (FFPE) tissue. However, the formalin fixation process often inhibits DNA amplification. To evaluate whether M. hyopneumoniae DNA could be recovered from FFPE tissues, 15 lungs with cranioventral consolidation lesions were collected in a slaughterhouse from swine bred in herds with respiratory disease. Bronchial swabs and fresh lung tissue were collected, and a fragment of the corresponding lung section was placed in neutral buffered formalin for 48 hours. A PCR assay was performed to compare FFPE tissue samples with samples that were only refrigerated (bronchial swabs) or frozen (tissue pieces). M. hyopneumoniae was detected by PCR in all 15 samples of the swab and frozen tissue, while it was detected in only 11 of the 15 FFPE samples. Histological features of M. hyopneumoniae infection were presented in 11 cases and 7 of these samples stained positive in IHC. Concordance between the histological features and detection results was observed in 13 of the FFPE tissue samples. PCR was the most sensitive technique. Comparison of different sample conservation methods indicated that it is possible to detect M. hyopneumoniae from FFPE tissue. It is important to conduct further research using archived material because the efficiency of PCR could be compromised under these conditions.

Detection of Illicit Drugs and Drug Precursors with Cantilever-Enhanced Photoacoustic Spectroscopy

In this study, cantilever-enhanced photoacoustic spectroscopy (CEPAS) was applied in different drug detection schemes. The study was divided into two different applications: trace detection of vaporized drugs and drug precursors in the gas-phase, and detection of cocaine abuse in hair. The main focus, however, was the study of hair samples. In the gas-phase, methyl benzoate, a hydrolysis product of cocaine hydrochloride, and benzyl methyl ketone (BMK), a precursor of amphetamine and methamphetamine were investigated. In the solid-phase, hair samples from cocaine overdose patients were measured and compared to a drug-free reference group. As hair consists mostly of long fibrous proteins generally called keratin, proteins from fingernails and saliva were also studied for comparison. Different measurement setups were applied in this study. Gas measurements were carried out using quantum cascade lasers (QLC) as a source in the photoacoustic detection. Also, an external cavity (EC) design was used for a broader tuning range. Detection limits of 3.4 particles per billion (ppb) for methyl benzoate and 26 ppb for BMK in 0.9 s were achieved with the EC-QCL PAS setup. The achieved detection limits are sufficient for realistic drug detection applications. The measurements from drug overdose patients were carried out using Fourier transform infrared (FTIR) PAS. The drug-containing hair samples and drug-free samples were both measured with the FTIR-PAS setup, and the measured spectra were analyzed statistically with principal component analysis (PCA). The two groups were separated by their spectra with PCA and proper spectral pre-processing. To improve the method, ECQCL measurements of the hair samples, and studies using photoacoustic microsampling techniques, were performed. High quality, high-resolution spectra with a broad tuning range were recorded from a single hair fiber. This broad tuning range of an EC-QCL has not previously been used in the photoacoustic spectroscopy of solids. However, no drug detection studies were performed with the EC-QCL solid-phase setup.

Simultaneous detection of the C282Y, H63D and S65C mutations in the hemochromatosis gene using quenched-FRET real-time PCR

Hereditary hemochromatosis (HH) is a common autosomal disorder of iron metabolism mainly affecting Caucasian populations. Three recurrent disease-associated mutations have been detected in the hemochromatosis gene (HFE): C282Y, H63D, and S65C. Although HH phenotype has been associated with all three mutations, C282Y is considered the most relevant mutation responsible for hemochromatosis. Clinical complications of HH include cirrhosis of the liver, congestive cardiac failure and cardiac arrhythmias, endocrine pancreatic disease, which can be prevented by early diagnosis and treatment. Therefore, a reliable genotyping method is required for presymptomatic diagnosis. We describe the simultaneous detection of the C282Y, H63D and S65C mutations in the hemochromatosis gene by real-time PCR followed by melting curve analysis using fluorescence resonance energy transfer (FRET) probes. The acceptor fluorophore may be replaced by a quencher, increasing multiplex possibilities. Real-time PCR results were compared to the results of sequencing and conventional PCR followed by restriction digestion and detection by agarose gel electrophoresis (PCR-RFLP). Genotypes from 80 individuals obtained both by the conventional PCR-RFLP method and quenched-FRET real-time PCR were in full agreement. Sequencing also confirmed the results obtained by the new method, which proved to be an accurate, rapid and cost-effective diagnostic assay. Our findings demonstrate the usefulness of real-time PCR for the simultaneous detection of mutations in the HFE gene, which allows a reduction of a significant amount of time in sample processing compared to the PCR-RFLP method, eliminates the use of toxic reagents, reduces the risk of contamination in the laboratory, and enables full process automation.

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

Triple- and quadruple-escape peaks in HPGe detectors: Experimental observation and Monte Carlo simulation

The triple- and quadruple-escape peaks of 6.128 MeV photons from the (19)F(p,alpha gamma)(16)O nuclear reaction were observed in an HPGe detector. The experimental peak areas, measured in spectra projected with a restriction function that allows quantitative comparison of data from different multiplicities, are in reasonably good agreement with those predicted by Monte Carlo simulations done with the general-purpose radiation-transport code PENELOPE. The behaviour of the escape intensities was simulated for some gamma-ray energies and detector dimensions; the results obtained can be extended to other energies using an empirical function and statistical properties related to the phenomenon. (C) 2010 Elsevier B.V. All rights reserved.

Trigger and aperture of the surface detector array of the Pierre Auger Observatory

The surface detector array of the Pierre Auger Observatory consists of 1600 water-Cherenkov detectors, for the study of extensive air showers (EAS) generated by ultra-high-energy cosmic rays. We describe the trigger hierarchy, from the identification of candidate showers at the level of a single detector, amongst a large background (mainly random single cosmic ray muons), up to the selection of real events and the rejection of random coincidences. Such trigger makes the surface detector array fully efficient for the detection of EAS with energy above 3 x 10(18) eV, for all zenith angles between 0 degrees and 60 degrees, independently of the position of the impact point and of the mass of the primary particle. In these range of energies and angles, the exposure of the surface array can be determined purely on the basis of the geometrical acceptance. (C) 2009 Elsevier B.V. All rights reserved.

Automated two-dimensional separation flow system with electrochemical preconcentration, stripping, capillary electrophoresis and contactless conductivity detection for trace metal ion analysis

This paper describes the automation of a fully electrochemical system for preconcentration, cleanup, separation and detection, comprising the hyphenation of a thin layer electrochemical flow cell with CE coupled with contactless conductivity detection (CE-C(4)D). Traces of heavy metal ions were extracted from the pulsed-flowing sample and accumulated on a glassy carbon working electrode by electroreduction for some minutes. Anodic stripping of the accumulated metals was synchronized with hydrodynamic injection into the capillary. The effect of the angle of the slant polished tip of the CE capillary and its orientation against the working electrode in the electrochemical preconcentration (EPC) flow cell and of the accumulation time were studied, aiming at maximum CE-C(4)D signal enhancement. After 6 min of EPC, enhancement factors close to 50 times were obtained for thallium, lead, cadmium and copper ions, and about 16 for zinc ions. Limits of detection below 25 nmol/L were estimated for all target analytes but zinc. A second separation dimension was added to the CE separation capabilities by staircase scanning of the potentiostatic deposition and/or stripping potentials of metal ions, as implemented with the EPC-CE-C(4)D flow system. A matrix exchange between the deposition and stripping steps, highly valuable for sample cleanup, can be straightforwardly programmed with the multi-pumping flow management system. The automated simultaneous determination of the traces of five accumulable heavy metals together with four non-accumulated alkaline and alkaline earth metals in a single run was demonstrated, to highlight the potentiality of the system.

Border detection in digital images: An approach by fuzzy numbers

The purpose of this paper is to introduce a new approach for edge detection in gray shaded images. The proposed approach is based on the fuzzy number theory. The idea is to deal with the uncertainties concerning the gray shades making up the image, and thus calculate the appropriateness of the pixels in relation to an homogeneous region around them. The pixels not belonging to the region are then classified as border pixels. The results have shown that the technique is simple, computationally efficient and with good results when compared with both the traditional border detectors and the fuzzy edge detectors. © 2007 IEEE.

Edge detection in digital images using fuzzy numbers

The purpose of this paper is to introduce a new approach for edge detection in grey shaded images. The proposed approach is based on the fuzzy number theory. The idea is to deal with the uncertainties concerning the grey shades making up the image and, thus, calculate the appropriateness of the pixels in relation to a homogeneous region around them. The pixels not belonging to the region are then classified as border pixels. The results have shown that the technique is simple, computationally efficient and with good results when compared with both the traditional border detectors and the fuzzy edge detectors. Copyright © 2009, Inderscience Publishers.

A malware detection system inspired on the human immune system

Malicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.

Detection of oxacillin resistance in Staphylococcus aureus isolated from the neonatal and pediatric units of a brazilian teaching hospital

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)