A Multicenter Blinded Study to Evaluate KRAS Mutation Testing Methodologies in the Clinical Setting

Evidence that activating mutations of the KRAS oncogene abolish the response to anti-epidermal growth factor receptor therapy has revolutionized the treatment of advanced colorectal cancer. This has resulted in the urgent demand for KRAS mutation testing in the clinical setting to aid choice of therapy. The Am of this study was to evaluate six different KRAS mutation detection methodologies on two series of primary colorectal cancer samples. Two series of 80 frozen and 74 formalin-fixed paraffin-embedded tissue samples were sourced and DNA was extracted at a central site before distribution to seven different testing sites. KRAS mutations in codons 12 and 13 were assessed by using single strand conformation polymorphism analysis, pyrosequencing, high resolution melting analysis, dideoxy sequencing, or the commercially available TIB Molbiol (Berlin, Germany) or DxS Diagnostic innovations (Manchester, UK) kits. in frozen tissue samples, concordance in KRAS status (defined as consensus in at least five assays) was observed in 66/80 (83%) cases. In par-affin tissue, concordance was 46/74 (63%) if all assays were considered or 71/74 (96%) using the five best performing assays. These results demonstrate that a variety of detection methodologies are suitable and provide comparable results for KRAS mutation analysis of clinical samples. (J Mol Diagn 2009, 11:543-552; DOI: 10.2353/jmoldx.2009.090057)

Indoor radon measurements and methodologies in Latin American countries

According to the current international guidelines concerning environmental problems, it is necessary to evaluate and to know the indoor radon levels, specially since most of the natural radiation dose to man comes from radon gas and its progeny. Several countries have established National Institutions and National Programs for the study of radon and its connection with lung cancer risk and public health. The aim of this work is to present the indoor radon measurements and the detection methods used for different regions of Latin America (LA) in countries such as Argentina, Brazil, Ecuador, Mexico, Peru and Venezuela. This study shows that the passive radon devices based on alpha particle nuclear track methodology (NTM) is one of the more generalized methods in LA for long term indoor radon measurements, CR-39, LR-115 and Makrofol being the more commonly used detector materials. The participating institutions and the radon level measurements in the different countries are presented in this contribution. (C) 2001 Elsevier B.V. Ltd. All rights reserved.

Semi-selective culture medium for Xanthomonas axonopodis pv. malvacearum detection in cotton seeds (Gossypium hirsutum L.)

The cotton disease known as angular leaf spot, caused by Xanthomonas axonopodis pv. malvacearum (Xam) has been causing cotton losses in several producing regions around the world. Xam is transmitted by seeds, which may be infected both externally and internally. Infected seeds constitute the main long-distance dissemination mode of the pathogen. In view of this, the use of healthy seeds is a must. To accomplish that, detection methodologies for the bacteria must be developed be used in seed health analysis laboratories. This study aimed to develop a semi-selective medium for Xam detection in cotton seeds. The semi-selective culture medium was named MSSXAN and it was consisted of peptone (5.0 g), beef extract (3 g), sucrose (5 g), soluble starch (10 g), agar (15 g), CaCl 2 (0.25 g), Tween 80 (10 mL), distilled water (1,000 mL), crystal violet solution at 1% (150 μL), cephalexin (50 mg 1*), methyl thyophanate (10 mg*) and chlorothalonil (10 mg*) - *added after culture medium autoclaving. This MSSXAN medium shows low repressiveness to Xam and it be used for isolation of this bacteria in cotton seeds health analysis. © 2009 Academic Journals Inc.

Hazelnut Allergens: Molecular Characterisation, Detection and Clinical Relevance

In the last years, special attention has been devoted to food-induced allergies, from which hazelnut allergy is highlighted. Hazelnut is one of the most commonly consumed tree nuts, being largely used by the food industry in a wide variety of processed foods. It has been regarded as a food with potential health benefits, but also as a source of allergens capable of inducing mild to severe allergic reactions in sensitised individuals. Considering the great number of reports addressing hazelnut allergens, with an estimated increasing trend, this review intends to assemble all the relevant information available so far on the main issues: prevalence of tree nut allergy, clinical threshold levels, molecular characterisation of hazelnut allergens (Cor a 1, Cor a 2, Cor a 8, Cor a 9, Cor a 10, Cor a 11, Cor a 12, Cor a 14 and Cor a TLP) and their clinical relevance, and methodologies for hazelnut allergen detection in foods. A comprehensive overview on the current data about the molecular characterisation of hazelnut allergens is presented, relating biochemical classification and biological function with clinical importance. Recent advances on hazelnut allergen detection methodologies are summarised and compared, including all the novel protein- and DNA-based approaches.

On Occurrence Of Plagiarism In Published Computer Science Thesis Reports At Swedish Universities

In recent years, it has been observed that software clones and plagiarism are becoming an increased threat for one?s creativity. Clones are the results of copying and using other?s work. According to the Merriam – Webster dictionary, “A clone is one that appears to be a copy of an original form”. It is synonym to duplicate. Clones lead to redundancy of codes, but not all redundant code is a clone.On basis of this background knowledge ,in order to safeguard one?s idea and to avoid intentional code duplication for pretending other?s work as if their owns, software clone detection should be emphasized more. The objective of this paper is to review the methods for clone detection and to apply those methods for finding the extent of plagiarism occurrence among the Swedish Universities in Master level computer science department and to analyze the results.The rest part of the paper, discuss about software plagiarism detection which employs data analysis technique and then statistical analysis of the results.Plagiarism is an act of stealing and passing off the idea?s and words of another person?s as one?s own. Using data analysis technique, samples(Master level computer Science thesis report) were taken from various Swedish universities and processed in Ephorus anti plagiarism software detection. Ephorus gives the percentage of plagiarism for each thesis document, from this results statistical analysis were carried out using Minitab Software.The results gives a very low percentage of Plagiarism extent among the Swedish universities, which concludes that Plagiarism is not a threat to Sweden?s standard of education in computer science.This paper is based on data analysis, intelligence techniques, EPHORUS software plagiarism detection tool and MINITAB statistical software analysis.

Characterization of fecal contamination targeting 16S rRNA bacteroides molecular markers in the Santa Cruz River, Arizona

Understanding the origins, transport and fate of contamination is essential to effective management of water resources and public health. Individuals and organizations with management responsibilities need to understand the risks to ecosystems and to humans from contact with contamination. Managers also need to understand how key contaminants vary over time and space in order to design and prioritize mitigation strategies. Tumacacori National Historic Park (NHP) is responsible for management of its water resources for the benefit of the park and for the health of its visitors. The existence of microbial contaminants in the park poses risks that must be considered in park planning and operations. The water quality laboratory at the Maricopa Agricultural Center (in collaboration with stakeholder groups and individuals located in the ADEQ-targeted watersheds) identified biological changes in surface water quality in impaired reaches rivers to determine the sources of Escherichia coli (E. coli); bacteria utilizing innovative water quality microbial/bacterial source tracking methods. The end goal was to support targeted watershed groups and ADEQ towards E. coli reductions. In the field monitoring was conducted by the selected targeted watershed groups in conjunction with The University of Arizona Maricopa Agricultural Center Water Quality Laboratory. This consisted of collecting samples for Bacteroides testing from multiple locations on select impaired reaches, to determine contamination resulting from cattle, human recreation, and other contributions. Such testing was performed in conjunction with high flow and base flow conditions in order to accurately portray water quality conditions and variations. Microbial monitoring was conducted by The University of Arizona Water Quality Laboratory at the Maricopa Agricultural Center using genetic typing to differentiate among two categories of Bacteroides: human and all (total). Testing used microbial detection methodologies and molecular source tracking techniques.^

Technologies and Methodologies for the Detection of Harmful Algae and Their Toxins, St Petersburg, Florida, Oct 22-24 2008 : workshop proceedings

The Alliance for Coastal Technologies (ACT) Workshop "Technologies and Methodologies for the Detection of Harmful Algae and their Toxins" convened in St. Petersburg, Florida, October 22- 24, 2008 and was co-sponsored by ACT (http://act-us.info); the Cooperative Institute for Coastal and Estuarine Environmental Technology (CICEET, http://ciceet.unh.edu); and the Florida Fish and Wildlife Conservation Commission (FWC, http://www.myfwc.com). Participants from various sectors, including researchers, coastal decision makers, and technology vendors, collaborated to exchange information and build consensus. They focused on the status of currently available detection technologies and methodologies for harmful algae (HA) and their toxins, provided direction for developing operational use of existing technology, and addressed requirements for future technology developments in this area. Harmful algal blooms (HABs) in marine and freshwater systems are increasingly common worldwide and are known to cause extensive ecological, economic, and human health problems. In US waters, HABs are encountered in a growing number of locations and are also increasing in duration and severity. This expansion in HABs has led to elevated incidences of poisonous seafood, toxin-contaminated drinking water, mortality of fish and other animals dependent upon aquatic resources (including protected species), public health and economic impacts in coastal and lakeside communities, losses to aquaculture enterprises, and long-term aquatic ecosystem changes. This meeting represented the fourth ACT sponsored workshop that has addressed technology developments for improved monitoring of water-born pathogens and HA species in some form. A primary motivation was to assess the need and community support for an ACT-led Performance Demonstration of Harmful Algae Detection Technologies and Methodologies in order to facilitate their integration into regional ocean observing systems operations. The workshop focused on the identification of region-specific monitoring needs and available technologies and methodologies for detection/quantification of harmful algal species and their toxins along the US marine and freshwater coasts. To address this critical environmental issue, several technologies and methodologies have been, or are being, developed to detect and quantify various harmful algae and their associated toxins in coastal marine and freshwater environments. There are many challenges to nationwide adoption of HAB detection as part of a core monitoring infrastructure: the geographic uniqueness of primary algal species of concern around the country, the variety of HAB impacts, and the need for a clear vision of the operational requirements for monitoring the various species. Nonetheless, it was a consensus of the workshop participants that ACT should support the development of HA detection technology performance demonstrations but that these would need to be tuned regionally to algal species and toxins of concern in order to promote the adoption of state of the art technologies into HAR monitoring networks. [PDF contains 36 pages]

Improving detection probabilities for pests in stored grains

BACKGROUND: The presence of insects in stored grains is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspections of bulk grain commodities is essential to detect pests and therefore to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grains, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper we demonstrate a sampling methodology that accounts for the heterogeneous distribution of insects in bulk grains. RESULTS: We show that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling program to detect insects in bulk grains. Our results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. We also demonstrate that the probability of detecting pests in bulk grains increases as the number of sub-samples increases, even when the total volume or mass of grain sampled remains constant. CONCLUSION: This study demonstrates the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models.

DNA technology for the detection of common genetic variants that predispose to thrombophilia

With the identification of common single locus point mutations as risk factors for thrombophilia, many DNA testing methodologies have been described for detecting these variations. Traditionally, functional or immunological testing methods have been used to investigate quantitative anticoagulant deficiencies. However, with the emergence of the genetic variations, factor V Leiden, prothrombin 20210 and, to a lesser extent, the methylene tetrahydrofolate reductase (MTHFR677) and factor V HR2 haplotype, traditional testing methodologies have proved to be less useful and instead DNA technology is more commonly employed in diagnostics. This review considers many of the DNA techniques that have proved to be useful in the detection of common genetic variants that predispose to thrombophilia. Techniques involving gel analysis are used to detect the presence or absence of restriction sites, electrophoretic mobility shifts, as in single strand conformation polymorphism or denaturing gradient gel electrophoresis, and product formation in allele-specific amplification. Such techniques may be sensitive, but are unwielding and often need to be validated objectively. In order to overcome some of the limitations of gel analysis, especially when dealing with larger sample numbers, many alternative detection formats, such as closed tube systems, microplates and microarrays (minisequencing, real-time polymerase chain reaction, and oligonucleotide ligation assays) have been developed. In addition, many of the emerging technologies take advantage of colourimetric or fluorescence detection (including energy transfer) that allows qualitative and quantitative interpretation of results. With the large variety of DNA technologies available, the choice of methodology will depend on several factors including cost and the need for speed, simplicity and robustness. © 2000 Lippincott Williams & Wilkins.

A review of current statistical methodologies for in storage sampling and surveillance in the grains industry

Effective, statistically robust sampling and surveillance strategies form an integral component of large agricultural industries such as the grains industry. Intensive in-storage sampling is essential for pest detection, Integrated Pest Management (IPM), to determine grain quality and to satisfy importing nation’s biosecurity concerns, while surveillance over broad geographic regions ensures that biosecurity risks can be excluded, monitored, eradicated or contained within an area. In the grains industry, a number of qualitative and quantitative methodologies for surveillance and in-storage sampling have been considered. Primarily, research has focussed on developing statistical methodologies for in storage sampling strategies concentrating on detection of pest insects within a grain bulk, however, the need for effective and statistically defensible surveillance strategies has also been recognised. Interestingly, although surveillance and in storage sampling have typically been considered independently, many techniques and concepts are common between the two fields of research. This review aims to consider the development of statistically based in storage sampling and surveillance strategies and to identify methods that may be useful for both surveillance and in storage sampling. We discuss the utility of new quantitative and qualitative approaches, such as Bayesian statistics, fault trees and more traditional probabilistic methods and show how these methods may be used in both surveillance and in storage sampling systems.

Fast and accurate business process drift detection

Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.

Comparison of sampling sites and detection methods for Haemophilus parasuis

Objective To improve the isolation rate and identification procedures for Haemophilus parasuis from pig tissues. Design Thirteen sampling sites and up to three methods were used to confirm the presence of H. parasuis in pigs after experimental challenge. Procedure Colostrum-deprived, naturally farrowed pigs were challenged intratracheally with H parasuis serovar 12 or 4. Samples taken during necropsy were either inoculated onto culture plates, processed directly for PCR or enriched prior to being processed for PCR. The recovery of H parasuis from different sampling sites and using different sampling methods was compared for each serovar. Results H parasuis was recovered from several sample sites for all serovar 12 challenged pigs, while the trachea was the only positive site for all pigs following serovar 4 challenge. The method of solid medium culture of swabs, and confirmation of the identity of cultured bacteria by PCR, resulted in 38% and 14% more positive results on a site basis for serovars 12 and 4, retrospectively, than direct PCR on the swabs. This difference was significant in the serovar 12 challenge. Conclusion Conventional culture proved to be more effective in detecting H parasuis than direct PCR or PCR on enrichment broths. For subacute (serovar 4) infections, the most successful sites for culture or direct PCR were pleural fluid, peritoneal fibrin and fluid, lung and pericardial fluid. For acute (serovar 12) infections, the best sites were lung, heart blood, affected joints and brain. The methodologies and key sampling sites identified in this study will enable improved isolation of H parasuis and aid the diagnosis of Glässer's disease.

Proton NMR studies of dihalogenated phenyl benzamides: two-dimensional higher quantum methodologies

The scalar coupled proton NMR spectra of many organic molecules possessing more than one phenyl ring are generally complex due to degeneracy of transitions arising from the closely resonating protons, in addition to several short- and long- range couplings experienced by each proton. Analogous situations are generally encountered in derivatives of halogenated benzanilides. Extraction of information from such spectra is challenging and demands the differentiation of spectrum pertaining to each phenyl ring and the simplification of their spectral complexity. The present study employs the blend of independent spin system filtering and the spin-state selective detection of single quantum (SO) transitions by the two-dimensional multiple quantum (MQ) methodology in achieving this goal. The precise values of the scalar couplings of very small magnitudes have been derived by double quantum resolved experiments. The experiments also provide the relative signs of heteronuclear couplings. Studies on four isomers of dilhalogenated benzanilides are reported in this work.

Damage Detection Sensitivity, Specificity and Classification Data Analysis for SHM Systems Design, Verification and Validation

In this paper, we consider applying derived knowledge base regarding the sensitivity and specificity of damage(s) to be detected by an SHM system being designed and qualified. These efforts are necessary toward developing capabilities in SHM system to classify reliably various probable damages through sequence of monitoring, i.e., damage precursor identification, detection of damage and monitoring its progression. We consider the particular problem of visual and ultrasonic NDE based SHM system design requirements, where the damage detection sensitivity and specificity data definitions for a class of structural components are established. Methodologies for SHM system specification creation are discussed in details. Examples are shown to illustrate how the physics of damage detection scheme limits particular damage detection sensitivity and specificity and further how these information can be used in algorithms to combine various different NDE schemes in an SHM system to enhance efficiency and effectiveness. Statistical and data driven models to determine the sensitivity and probability of damage detection (POD) has been demonstrated for plate with varying one-sided line crack using optical and ultrasonic based inspection techniques.