Detection and Characterization of Cholesterol-Oxidized Products Using HPLC Coupled to Dopant Assisted Atmospheric Pressure Photoionization Tandem Mass Spectrometry

Oxidation of cholesterol (Ch) by a variety of reactive oxygen species gives rise mainly to hydroperoxides and aldehydes. Despite the growing interest in Ch-oxidized products, the detection and characterization of these products is still a matter of concern. In this work, the main Ch-oxidized products, namely, 3 beta-hydroxycholest-5-ene-7 alpha-hydroperoxide (7 alpha-OOH), 3 beta-5 alpha-cholest-6-ene-5-hydroperoxide (5 alpha-OOH), 3 beta-hydroxycholest-4-ene-6 alpha-hydroperoxide (6 alpha-OOH), 3 beta-hydroxycholest-4-ene-6 beta-hydroperoxide (6 beta-OOH), and 3 beta-hydroxy-5 beta-hydroxy-B-norcholestane-6 beta-carboxaldehyde (ChAld), were detected in the same analysis using high-performance liquid chromatography (HPLC) coupled to dopant assisted atmospheric pressure photoionization tandem mass spectrometry. The use of selected reaction monitoring mode (SRM) allowed a sensitive detection of each oxidized product, while the enhanced product ion mode (EPI) helped to improve the confidence of the analyses. Isotopic labeling experiments enabled one to elucidate mechanistic features during fragmentation processes. The characteristic fragmentation pattern of Ch-oxidized products is the consecutive loss of 1120 molecules, yielding cationic fragments at m/z 401, 383, and 365. Homolytic scissions of the peroxide bond are also seen. With (18)O-labeling approach, it was possible to establish a fragmentation order for each isomer. The SRM transitions ratio along with EPI and (18)O-labeled experiments give detailed information about differences for water elimination, allowing a proper discrimination between the isomers:Phis is of special interest considering the emerging role of Ch-oxidized products in the development of diseases.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

Color detection and segmentation for road and traffic signs

This paper aims to present three new methods for color detection and segmentation of road signs. The images are taken by a digital camera mounted in a car. The RGB images are converted into IHLS color space, and new methods are applied to extract the colors of the road signs under consideration. The methods are tested on hundreds of outdoor images in different light conditions, and they show high robustness. This project is part of the research taking place in Dalarna University / Sweden in the field of the ITS.

Leakage Detection And Localization Method Based On A Hybrid Inverse/Direct Modelling Approach Suitable For Handling Multiple-Leak Scenarios

When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.

Neuronal Assembly Detection and Cell Membership Specification by Principal Component Analysis

LOPES-DOS-SANTOS, V. , CONDE-OCAZIONEZ, S. ; NICOLELIS, M. A. L. , RIBEIRO, S. T. , TORT, A. B. L. . Neuronal assembly detection and cell membership specification by principal component analysis. Plos One, v. 6, p. e20996, 2011.

Infectious bronchitis virus: detection and vaccine Strain differentiation by semi-nested RT-PCR

A semi-nested reverse transcription-polymerase chain reaction (Semi-N-RT-PCR) was developed and used to detect the S glycoprotein gene of infectious bronchitis virus (IBV) strains and to discriminate H120 vaccine strain from other strains. Viral RNA was extracted from the allantoic fluid of chicken embryos and from tissues of chickens experimentally infected with different strains of IBV. Amplification and identification of the viral RNA was performed using two sets of primers complementary to a region of the S glycoprotein gene in the Semi-N-RT-PCR assay. The pair of primers used in the first PCR consisted of universal oligonucleotides flanking a more variable region of S1-S2 gene. The second primer pair was used in the Semi-N-RT-PCR and was comprised of one of the primers from the first universal pair together with either another universal internal oligolucleotide or a oligonucleotide sequence specific for the H120 strain of IBV. The universal primers detected all reference IBV strains and field isolates tested herein. The Semi-N-RT-PCR had high sensitivity and specificity, and was able to differentiate the H120 vaccine strain from other reference IBV strains; including M41 strain. All tissue samples collected from chickens experimentally infected with H120 or M41 strains were positive in the semi-nested RT-PCR using universal primers, while only the H120-infected tissue samples were amplified by the set of primers containing the H120-oligonucleotide. In conclusion, the ability of Semi-N-RT-PCR to detect distinct IBV strains and preliminarily discriminate the vaccine strain (H120) closes a diagnostic gap and offers the opportunity to use comprehensive PCR procedures for the IBV diagnosis.

APPLICATION of THE HAZARD ANALYSIS and CRITICAL CONTROL POINT (HACCP) SYSTEM on THE MUSHROOM PROCESSING LINE FOR FRESH CONSUMPTION

The Hazard Analysis and Critical Control Point (HACCP) is a preventive system that intends to guarantee the safety and harmlessness of food. It improves the quality of products as it eliminates possible defects during the process, and saves costs by practically eliminating final product inspection. This work describes the typical hazards encountered on the mushroom processing line for fresh consumption. Throughout the process, only the reception stage of mushrooms has been considered a critical control point (CCP). The main hazards at this stage were: the presence of unauthorised phytosanitary products; larger doses of such products than those permitted; the presence of pathogenic bacteria or thermo-stable enterotoxins. Putting into practice such knowledge would provide any industry that processes mushrooms for fresh consumption with a self-control HACCP-based system for its own productions.

Grapevine bacterial canker in the State of São Paulo, Brazil: detection and eradication

Sintomas do cancro bacteriano da videira na variedade Red Globe foram observados em agosto de 2009 em pomar de Tupi Paulista, Estado de São Paulo, Brasil, e o agente causal Xanthomonas campestris pv. viticola foi identificado por meio de testes patológicos e moleculares. O procedimento de erradicação foi adotado e aproximadamente 4.700 plantas foram destruídas. Um levantamento realizado nas regiões produtoras do Estado de São Paulo não encontrou nenhum outro pomar contaminado, e essa espécie bacteriana é considerada ausente neste estado.

Portable smart films for ultrasensitive detection and chemical analysis using SERS and SERRS

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

Detection and thinning of edges in previously known directions

This work presents a study on the generation of digital masks aiming at edge detection with previously known directions. This solution is important when edge direction is available either from a direction histogram or from a prediction based on camera and object models. A modification in the non-maximum suppression method of thinning is also presented enabling the comparison of local maxima for any edge directions. Results with a synthetic image and with crops of a CBERS satellite images are presented showing an example with its application in road detection, provided that directions are previously known.

Multiresidue analysis of pesticides in soil by supercritical fluid extraction/gas chromatography with electron-capture detection and confirmation by gas chromatography-mass spectrometry

The applicability of supercritical fluid extraction (SFE) in pesticide multiresidue analysis (organohalogen, organonitrogen, organophosphorus, and pyrethroid) in soil samples was investigated. Fortification experiments were conducted to test the conventional extraction (solid-liquid) and to optimize the extraction procedure in SFE by varying the CO2 Modifier, temperature, extraction time, and pressure. The best efficiency was achieved at 400 bar using methanol as modifier at 60 degreesC. For the SFE method, C-18 cartridges were used for the cleanup. The analytical screening was performed by gas chromatography equipped with electron-capture detection (ECD). Recoveries for the majority of pesticides from spiked samples of soil at different residence times were 1, 20, and 40 days at the fortification level of 0.04-0.10 mg/kg ranging from 70 to 97% for both methods. The detection limits found were <0.01 mg/kg for ECD, and the confirmation of pesticide identity was performed by gas chromatography-mass spectrometry in a selected-ion monitoring mode. Multiresidue methods were applied in real soil samples, and the results of the methods developed were compared.

Detection and Identification of Abnormalities in Customer Consumptions in Power Distribution Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet network

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

Sliding mode for detection and accommodation of computation time delay fault

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

Detection and transfer of antimicrobial resistance gene integron in Salmonella Enteritidis derived from avian material

The expansion of global poultry production has increased the need to reduce or control the agents responsible for economic losses, including Salmonella spp. These bacteria are also of public health concern due to their potential to cause food poisoning, and, more recently, due to the antimicrobial resistance presented by these bacteria. Molecular biology is an important tool currently used in the diagnosis and research studies of main poultry diseases. The present studied analyzed 100 samples of Salmonella Enteritidis (SE) isolated from avian material aiming at detecting the class 1 integron gene, Integroninvolved in antimicrobial resistance, by means of polymerase chain reaction (PCR), and comparing it with plate inhibition test. Subsequently, SE samples were evaluated for their capacity to horizontally transfer this gene. There was no direct relationship between the presence of the class 1 integron gene and SE resistance to the 14 antimicrobials tested, as 80% of the studied samples were resistant to up to three antimicrobials, and did not present the aforementioned gene. However, horizontal transfer of this gene was accomplished in vitro (from Escherichia coli to Salmonella Enteritidis), demonstrating that capacity class 1 integron gene can be disseminated among enterobacteria.