Validation and performance comparison of two carbon isotope ratio methods to control the misuse of androgens in humans.

Carbon isotope ratio of androgens in urine specimens is routinely determined to exclude an abuse of testosterone or testosterone prohormones by athletes. Increasing application of gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS) in the last years for target and systematic investigations on samples has resulted in the demand for rapid sample throughput as well as high selectivity in the extraction process particularly in the case of conspicuous samples. For that purpose, we present herein the complimentary use of an SPE-based assay and an HPLC fractionation method as a two-stage strategy for the isolation of testosterone metabolites and endogenous reference compounds prior to GC/C/IRMS analyses. Assays validation demonstrated acceptable performance in terms of intermediate precision (range: 0.1-0.4 per thousand) and Bland-Altman analyses revealed no significant bias (0.2 per thousand). For further validation of this two-stage analyses strategy, all the specimens (n=124) collected during a major sport event were processed.

Holographic optical tweezers combined with back-focal-plane displacement detection

A major problem with holographic optical tweezers (HOTs) is their incompatibility with laser-based position detection methods, such as back-focal-plane interferometry (BFPI). The alternatives generally used with HOTs, like high-speed video tracking, do not offer the same spatial and temporal bandwidths. This has limited the use of this technique in precise quantitative experiments. In this paper, we present an optical trap design that combines digital holography and back-focal-plane displacement detection. We show that, with a particularly simple setup, it is possible to generate a set of multiple holographic traps and an additional static non-holographic trap with orthogonal polarizations and that they can be, therefore, easily separated for measuring positions and forces with the high positional and temporal resolutions of laser-based detection. We prove that measurements from both polarizations contain less than 1% crosstalk and that traps in our setup are harmonic within the typical range. We further tested the instrument in a DNA stretching experiment and we discuss an interesting property of this configuration: the small drift of the differential signal between traps.

Supervised localimage feature detection

This thesis is about detection of local image features. The research topic belongs to the wider area of object detection, which is a machine vision and pattern recognition problem where an object must be detected (located) in an image. State-of-the-art object detection methods often divide the problem into separate interest point detection and local image description steps, but in this thesis a different technique is used, leading to higher quality image features which enable more precise localization. Instead of using interest point detection the landmark positions are marked manually. Therefore, the quality of the image features is not limited by the interest point detection phase and the learning of image features is simplified. The approach combines both interest point detection and local description into one phase for detection. Computational efficiency of the descriptor is therefore important, leaving out many of the commonly used descriptors as unsuitably heavy. Multiresolution Gabor features has been the main descriptor in this thesis and improving their efficiency is a significant part. Actual image features are formed from descriptors by using a classifierwhich can then recognize similar looking patches in new images. The main classifier is based on Gaussian mixture models. Classifiers are used in one-class classifier configuration where there are only positive training samples without explicit background class. The local image feature detection method has been tested with two freely available face detection databases and a proprietary license plate database. The localization performance was very good in these experiments. Other applications applying the same under-lying techniques are also presented, including object categorization and fault detection.

Detection of drechslera avenae in oat seeds

The fungus Drechslera avenae, the causal agent of Helminthosporium leaf spot on oats (Avena sativa), survives as mycelium in crop residues and in infected seeds. In trials carried out in the laboratory, ten methods were evaluated for their efficiency to detect D. avenae in oat seeds. In each experiment, groups of two or three methods were compared to a standard protocol, in which seeds were placed in Petri dishes containing the Reis selective medium and incubated at 25±2 °C for ten days. Data were submitted to analysis of variation and the means of the methods were compared using the Dunnett test at the 5% significance level. Overall, the highest levels of seed infection by D. avenae were observed on oat seeds plated in the osmotic, the oat-agar and the Reis media, or on seeds subjected to heat treatment previous to incubation in malt-agar. Therefore, these methods should be recommended for detection of D. avenae in oat seed testing.

Inactive endosialidase-based detection of bacterial and oncofetal polysialic acid

Polysialic acid is a carbohydrate polymer which consist of N-acetylneuraminic acid units joined by alpha2,8-linkages. It is developmentally regulated and has an important role during normal neuronal development. In adults, it participates in complex neurological processes, such as memory, neural plasticity, tumor cell growth and metastasis. Polysialic acid also constitutes the capsule of some meningitis and sepsis-causing bacteria, such as Escherichia coli K1, group B meningococci, Mannheimia haemolytica A2 and Moraxella nonliquefaciens. Polysialic acid is poorly immunogenic; therefore high affinity antibodies against it are difficult to prepare, thus specific and fast detection methods are needed. Endosialidase is an enzyme derived from the E. coli K1 bacteriophage, which specifically recognizes and degrades polysialic acid. In this study, a novel detection method for polysialic acid was developed based on a fusion protein of inactive endosialidase and the green fluorescent protein. It utilizes the ability of the mutant, inactive endosialidase to bind but not cleave polysialic acid. Sequencing of the endosialidase gene revealed that amino acid substitutions near the active site of the enzyme differentiate the active and inactive forms of the enzyme. The fusion protein was applied for the detection of polysialic acid in bacteria and neuroblastoma. The results indicate that the fusion protein is a fast, sensitive and specific reagent for the detection of polysialic acid. The use of an inactive enzyme as a specific molecular tool for the detection of its substrate represents an approach which could potentially find wide applicability in the specific detection of diverse macromolecules.

Luminescence-based assay methods in drug discovery

The drug discovery process is facing new challenges in the evaluation process of the lead compounds as the number of new compounds synthesized is increasing. The potentiality of test compounds is most frequently assayed through the binding of the test compound to the target molecule or receptor, or measuring functional secondary effects caused by the test compound in the target model cells, tissues or organism. Modern homogeneous high-throughput-screening (HTS) assays for purified estrogen receptors (ER) utilize various luminescence based detection methods. Fluorescence polarization (FP) is a standard method for ER ligand binding assay. It was used to demonstrate the performance of two-photon excitation of fluorescence (TPFE) vs. the conventional one-photon excitation method. As result, the TPFE method showed improved dynamics and was found to be comparable with the conventional method. It also held potential for efficient miniaturization. Other luminescence based ER assays utilize energy transfer from a long-lifetime luminescent label e.g. lanthanide chelates (Eu, Tb) to a prompt luminescent label, the signal being read in a time-resolved mode. As an alternative to this method, a new single-label (Eu) time-resolved detection method was developed, based on the quenching of the label by a soluble quencher molecule when displaced from the receptor to the solution phase by an unlabeled competing ligand. The new method was paralleled with the standard FP method. It was shown to yield comparable results with the FP method and found to hold a significantly higher signal-tobackground ratio than FP. Cell-based functional assays for determining the extent of cell surface adhesion molecule (CAM) expression combined with microscopy analysis of the target molecules would provide improved information content, compared to an expression level assay alone. In this work, immune response was simulated by exposing endothelial cells to cytokine stimulation and the resulting increase in the level of adhesion molecule expression was analyzed on fixed cells by means of immunocytochemistry utilizing specific long-lifetime luminophore labeled antibodies against chosen adhesion molecules. Results showed that the method was capable of use in amulti-parametric assay for protein expression levels of several CAMs simultaneously, combined with analysis of the cellular localization of the chosen adhesion molecules through time-resolved luminescence microscopy inspection.

Identification and characterisation of a novel adhesin of Streptococcus suis and its use as a target of adhesion inhibition and bacterial detection

Streptococcus suis is an important pig pathogen but it is also zoonotic, i.e. capable of causing diseases in humans. Human S. suis infections are quite uncommon but potentially life-threatening and the pathogen is an emerging public health concern. This Gram-positive bacterium possesses a galabiose-specific (Galalpha1−4Gal) adhesion activity, which has been studied for over 20 years. P-fimbriated Escherichia coli−bacteria also possess a similar adhesin activity targeting the same disaccharide. The galabiose-specific adhesin of S. suis was identified by an affinity proteomics method. No function of the protein identified was formerly known and it was designated streptococcal adhesin P (SadP). The peptide sequence of SadP contains an LPXTG-motif and the protein was proven to be cell wall−anchored. SadP may be multimeric since in SDS-PAGE gel it formed a protein ladder starting from about 200 kDa. The identification was confirmed by producing knockout strains lacking functional adhesin, which had lost their ability to bind to galabiose. The adhesin gene was cloned in a bacterial expression host and properties of the recombinant adhesin were studied. The galabiose-binding properties of the recombinant protein were found to be consistent with previous results obtained studying whole bacterial cells. A live-bacteria application of surface plasmon resonance was set up, and various carbohydrate inhibitors of the galabiose-specific adhesins were studied with this assay. The potencies of the inhibitors were highly dependent on multivalency. Compared with P-fimbriated E. coli, lower concentrations of galabiose derivatives were needed to inhibit the adhesion of S. suis. Multivalent inhibitors of S. suis adhesion were found to be effective at low nanomolar concentrations. To specifically detect galabiose adhesin−expressing S. suis bacteria, a technique utilising magnetic glycoparticles and an ATP bioluminescence bacterial detection system was also developed. The identification and characterisation of the SadP adhesin give valuable information on the adhesion mechanisms of S. suis, and the results of this study may be helpful for the development of novel inhibitors and specific detection methods of this pathogen.

Modular framework for outlier detection

Outlier detection is an important form of data analysis because outliers in several cases contain the interesting and important pieces of information. In the recent years, many different outlier detection algorithms have been devised for finding different kinds of outliers in varying contexts and environments. Some effort has been put to study how to effectively combine different outlier detection methods. The combination of outlier detection algorithms as an ensemble was studied in this thesis by designing a modular framework for outlier detection, which combines arbitrary outlier detection techniques. This work resulted in an example implementation of the framework. Outlier detection capability of the ensemble method was validated using datasets and methods found in outlier detection research. The framework achieved better results than the individual outlier algorithms. Future research includes how to handle large datasets effectively and the possibilities for real-time outlier monitoring.

Detection and quantification of Roundup Ready® soybean residues in sausage samples by conventional and real-time PCR

The increasing presence of products derived from genetically modified (GM) plants in human and animal diets has led to the development of detection methods to distinguish biotechnology-derived foods from conventional ones. The conventional and real-time PCR have been used, respectively, to detect and quantify GM residues in highly processed foods. DNA extraction is a critical step during the analysis process. Some factors such as DNA degradation, matrix effects, and the presence of PCR inhibitors imply that a detection or quantification limit, established for a given method, is restricted to a matrix used during validation and cannot be projected to any other matrix outside the scope of the method. In Brazil, sausage samples were the main class of processed products in which Roundup Ready® (RR) soybean residues were detected. Thus, the validation of methodologies for the detection and quantification of those residues is absolutely necessary. Sausage samples were submitted to two different methods of DNA extraction: modified Wizard and the CTAB method. The yield and quality were compared for both methods. DNA samples were analyzed by conventional and real-time PCR for the detection and quantification of Roundup Ready® soybean in the samples. At least 200 ng of total sausage DNA was necessary for a reliable quantification. Reactions containing DNA amounts below this value led to large variations on the expected GM percentage value. In conventional PCR, the detection limit varied from 1.0 to 500 ng, depending on the GM soybean content in the sample. The precision, performance, and linearity were relatively high indicating that the method used for analysis was satisfactory.

Efficiency of methods to detect Sclerotinia sclerotiorum in commercial soybean seed lots

Most soybean pathogens are seed transmitted, deserving emphasis the fungus Sclerotinia sclerotiorum, which has been presenting worrying levels of field incidence in some soybean cropping areas in several Brazilian states. The objective of this study was to verify the efficiency of different methods for detecting S. sclerotiorum on soybean seeds artificially infected in the laboratory and from field production areas with a historical disease incidence. Seed samples of seven different cultivars collected from naturally infested fields, and one seed sample artificially inoculated in the laboratory were used. The following detection methods recommended in the literature were compared: Blotter test at 7 ºC, 14 ºC, and 21 ºC; Rolled Paper; and Neon-S. Results demonstrated that these methods showed no repeatability and had a low sensitivity for detecting the pathogen in seeds from areas with disease incidence. They were effective, however, for its detection on artificially inoculated seeds. In the Blotter test method at 7 ºC, there was a lower incidence of other fungi considered undesirable during seed analysis.

Detection of adventitious presence of genetically modified seeds in lots of non transgenic soybean

The difficulty on identifying, lack of segregation systems and absence of suitable standards for coexistence of non trangenic and transgenic soybean are contributing for contaminations that occur during productive system. The objective of this study was to evaluate the efficiency of two methods for detecting mixtures of seeds genetically modified (GM) into samples of non-GM soybean, in a way that seed lots can be assessed within the standards established by seed legislation. Two sizes of soybean samples (200 and 400 seeds), cv. BRSMG 810C (non-GM) and BRSMG 850GRR (GM), were assessed with four contamination levels (addition of GM seeds, for obtaining 0.0%, 0.5%, 1.0%, and 1.5% contamination), and two detection methods: immunoassay of lateral flux (ILF) and bioassay (pre-imbibition into 0.6% herbicide solution; 25 ºC; 16 h). The bioassay is efficient in detecting presence of GM seeds in seed samples of non-GM soybean, even for contamination lower than 1.0%, provided that seeds have high physiological quality. The ILF was positive, detecting the presence of target protein in contaminated samples, indicating test effectiveness. There was significant correlation between the two detection methods (r = 0.82; p < 0.0001). Sample size did not influence efficiency of the two methods in detecting presence of GM seeds.

Detecting Deceit – Guessing or Assessing? Study on the Applicability of Veracity Assessment Methods in Human Intelligence

Intelligence from a human source, that is falsely thought to be true, is potentially more harmful than a total lack of it. The veracity assessment of the gathered intelligence is one of the most important phases of the intelligence process. Lie detection and veracity assessment methods have been studied widely but a comprehensive analysis of these methods’ applicability is lacking. There are some problems related to the efficacy of lie detection and veracity assessment. According to a conventional belief an almighty lie detection method, that is almost 100% accurate and suitable for any social encounter, exists. However, scientific studies have shown that this is not the case, and popular approaches are often over simplified. The main research question of this study was: What is the applicability of veracity assessment methods, which are reliable and are based on scientific proof, in terms of the following criteria? o Accuracy, i.e. probability of detecting deception successfully o Ease of Use, i.e. easiness to apply the method correctly o Time Required to apply the method reliably o No Need for Special Equipment o Unobtrusiveness of the method In order to get an answer to the main research question, the following supporting research questions were answered first: What kinds of interviewing and interrogation techniques exist and how could they be used in the intelligence interview context, what kinds of lie detection and veracity assessment methods exist that are reliable and are based on scientific proof and what kind of uncertainty and other limitations are included in these methods? Two major databases, Google Scholar and Science Direct, were used to search and collect existing topic related studies and other papers. After the search phase, the understanding of the existing lie detection and veracity assessment methods was established through a meta-analysis. Multi Criteria Analysis utilizing Analytic Hierarchy Process was conducted to compare scientifically valid lie detection and veracity assessment methods in terms of the assessment criteria. In addition, a field study was arranged to get a firsthand experience of the applicability of different lie detection and veracity assessment methods. The Studied Features of Discourse and the Studied Features of Nonverbal Communication gained the highest ranking in overall applicability. They were assessed to be the easiest and fastest to apply, and to have required temporal and contextual sensitivity. The Plausibility and Inner Logic of the Statement, the Method for Assessing the Credibility of Evidence and the Criteria Based Content Analysis were also found to be useful, but with some limitations. The Discourse Analysis and the Polygraph were assessed to be the least applicable. Results from the field study support these findings. However, it was also discovered that the most applicable methods are not entirely troublefree either. In addition, this study highlighted that three channels of information, Content, Discourse and Nonverbal Communication, can be subjected to veracity assessment methods that are scientifically defensible. There is at least one reliable and applicable veracity assessment method for each of the three channels. All of the methods require disciplined application and a scientific working approach. There are no quick gains if high accuracy and reliability is desired. Since most of the current lie detection studies are concentrated around a scenario, where roughly half of the assessed people are totally truthful and the other half are liars who present a well prepared cover story, it is proposed that in future studies lie detection and veracity assessment methods are tested against partially truthful human sources. This kind of test setup would highlight new challenges and opportunities for the use of existing and widely studied lie detection methods, as well as for the modern ones that are still under development.

Buried Treasure: The Economics of Leak Detection and Water Loss Prevention in Ontario

On average approximately 13% of the water that is withdrawn by Canadian municipal water suppliers is lost before it reaches final users. This is an important topic for several reasons: water losses cost money, losses force water agencies to draw more water from lakes and streams thereby putting more stress on aquatic ecosystems, leaks reduce system reliability, leaks may contribute to future pipe failures, and leaks may allow contaminants to enter water systems thereby reducing water quality and threatening the health of water users. Some benefits of leak detection fall outside water agencies’ accounting purview (e.g. reduced health risks to households connected to public water supply systems) and, as a result, may not be considered adequately in water agency decision-making. Because of the regulatory environment in which Canadian water agencies operate, some of these benefits-especially those external to the agency or those that may accrue to the agency in future time periods- may not be fully counted when agencies decide on leak detection efforts. Our analysis suggests potential reforms to promote increased efforts for leak detection: adoption of a Canada-wide goal of universal water metering; development of full-cost accounting and, pricing for water supplies; and co-operation amongst the provinces to promulgate standards for leak detection efforts and provide incentives to promote improved efficiency and rational investment decision-making.

Detection of sandal spike phytoplasma using immunological and molecular techniques

Spike disease in sandal is generally diagnosed by the manifestation of external symptoms. Attempts have been made to detect the diseased plants by determining the length/breadth ratio of leaves (lyengar, 1961) and histochemical tests using Mann's stain (Parthasarathi et al., 1966), Dienes' stain (Ananthapadmanabha et a/., 1973) aniline blue and Hoechst 33258 (Ghosh et a/., 1985, Rangaswamy, 1995). But most of these techniques are insensitive, indirect detection methods leading to misinterpretation of results. Moreover, to identify disease resistant sandal trees, highly sensitive techniques are needed to detect the presence of the pathogen. In sandal forests, several host plants of sandal like Zizyphus oenop/ea (Fig. 1.3) also exhibit the yellows type disease symptoms. Immunological and molecular assays have to be developed to confirm the presence of sandal spike phytoplasma in such hosts. The major objectives of the present work includes:In situ detection of sandal spike phytoplasma by epifluorescence microscopy and scanning electron microscopy.,Purification of sandal spike phytoplasma and production of polyclonal antibodies.,Amino acid and total protein estimation of sandal spike phytoplasma.,Immunological detection of sandal spike phytoplasma., Molecular detection of sandal spike phytoplasma.,Screening for phytoplasma in host plants of spike disease affected sandal using immunological and molecular techniques.