171 research outputs found
JWalk: a tool for lazy, systematic testing of java classes by design introspection and user interaction
Popular software testing tools, such as JUnit, allow frequent retesting of modified code; yet the manually created test scripts are often seriously incomplete. A unit-testing tool called JWalk has therefore been developed to address the need for systematic unit testing within the context of agile methods. The tool operates directly on the compiled code for Java classes and uses a new lazy method for inducing the changing design of a class on the fly. This is achieved partly through introspection, using Java’s reflection capability, and partly through interaction with the user, constructing and saving test oracles on the fly. Predictive rules reduce the number of oracle values that must be confirmed by the tester. Without human intervention, JWalk performs bounded exhaustive exploration of the class’s method protocols and may be directed to explore the space of algebraic constructions, or the intended design state-space of the tested class. With some human interaction, JWalk performs up to the equivalent of fully automated state-based testing, from a specification that was acquired incrementally
Low-Cost High-Throughput Genotyping for Diagnosing Familial Hypercholesterolemia
BACKGROUND: Familial hypercholesterolemia (FH) is a common but underdiagnosed genetic disorder characterized by high low-density lipoprotein cholesterol levels and premature cardiovascular disease. Current sequencing methods to diagnose FH are expensive and time-consuming. In this study, we evaluated the accuracy of a low-cost, high-throughput genotyping array for diagnosing FH. METHODS: An Illumina Global Screening Array was customized to include probes for 636 variants, previously classified as FH-causing variants. First, its theoretical coverage was assessed in all FH variant carriers diagnosed through next-generation sequencing between 2016 and 2022 in the Netherlands (n=1772). Next, the performance of the array was validated in another sample of FH variant carriers previously identified in the Dutch FH cascade screening program (n=1268). RESULTS: The theoretical coverage of the array for FH-causing variants was 91.3%. Validation of the array was assessed in a sample of 1268 carriers of whom 1015 carried a variant in LDLR, 250 in APOB, and 3 in PCSK9. The overall sensitivity was 94.7% and increased to 98.2% after excluding participants with variants not included in the array design. Copy number variation analysis yielded a 89.4% sensitivity. In 18 carriers, the array identified a total of 19 additional FH-causing variants. Subsequent DNA analysis confirmed 5 of the additionally identified variants, yielding a false-positive result in 16 subjects (1.3%).CONCLUSIONS: The FH genotyping array is a promising tool for genetically diagnosing FH at low costs and has the potential to greatly increase accessibility to genetic testing for FH. Continuous customization of the array will further improve its performance.</p
Asynchronous Testing of Synchronous Components in GALS Systems
International audienceGALS (Globally Asynchronous Locally Synchronous) systems, such as the Internet of Things or autonomous cars, integrate reactive synchronous components that interact asynchronously. The complexity induced by combining synchronous and asynchronous aspects makes GALS systems difficult to develop and debug. Ensuring their functional correctness and reliability requires rigorous design methodologies, based on formal methods and assisted by validation tools. In this paper we propose a testing methodology for GALS systems integrating: (1) synchronous and asynchronous concurrent models; (2) functional unit testing and behavioral conformance testing; and (3) various formal methods and their tool equipments. We leverage the conformance test generation for asynchronous systems to automatically derive realistic scenarios (input constraints and oracle), which are necessary ingredients for the unit testing of individual synchronous components, and are difficult and error-prone to design manually. We illustrate our approach on a simple, but relevant example inspired by autonomous cars
Intra-city Differences in Cardiac Expression of Inflammatory Genes and Inflammasomes in Young Urbanites: A Pilot Study
Southwest Mexico City (SWMC) air pollution is characterized by high concentrations of ozone and particulate matter < 10 μm (PM10) containing lipopolysaccharides while in the North PM2.5 is high. These intra-city differences are likely accounting for higher CD14 and IL-1β in SWMC v NMC mice myocardial expression. This pilot study was designed to investigate whether similar intra-city differences exist in the levels of myocardial inflammatory genes in young people. Inflammatory mediator genes and inflammasome arrays were measured in right and left autopsy ventricles of 6 southwest/15 north (18.5 ± 2.6 years) MC residents after fatal sudden accidental deaths. There was a significant S v N right ventricle up-regulation of IL-1β (p=0.008), TNF-α (p=0.001), IL-10 (p=0.001), and CD14 (p=0.002), and a left ventricle difference in TNF-α (p=0.007), and IL-10 (p=0.02). SW right ventricles had significant up-regulation of NLRC1, NLRP3 and of 29/84 inflammasome genes, including NOD factors and caspases. There was significant degranulation of mast cells both in myocardium and epicardial nerve fibers. Differential expression of key inflammatory myocardial genes and inflammasomes are influenced by the location of residence. Myocardial inflammation and inflammasome activation in young hearts is a plausible pathway of heart injury in urbanites and adverse effects on the cardiovascular system are expected
Multicomponent fractionation of Saccharina latissima brown algae using chelating salt solutions
Valorisation to biogas of macroalgal waste streams: a circular approach to bioproducts and bioenergy in Ireland
© 2016 The Author(s) Seaweeds (macroalgae) have been recently attracting more and more interest as a third generation feedstock for bioenergy and biofuels. However, several barriers impede the deployment of competitive seaweed-based energy. The high cost associated to seaweed farming and harvesting, as well as their seasonal availability and biochemical composition currently make macroalgae exploitation too expensive for energy production only. Recent studies have indicated a possible solution to aforementioned challenges may lay in seaweed integrated biorefinery, in which a bioenergy and/or biofuel production step ends an extractions cascade of high-value bioproducts. This results in the double benefit of producing renewable energy while adopting a zero waste approach, as fostered by recent EU societal challenges within the context of the Circular Economy development. This study investigates the biogas potential of residues from six indigenous Irish seaweed species while discussing related issues experienced during fermentation. It was found that Laminaria and Fucus spp. are the most promising seaweed species for biogas production following biorefinery extractions producing 187–195 mL CH4 gVS−1 and about 100 mL CH4 gVS−1 , respectively, exhibiting overall actual yields close to raw un-extracted seaweed
Robust estimation of bacterial cell count from optical density
Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
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