2,692 research outputs found
Advantages and Limitations of Anticipating Laboratory Test Results from Regression- and Tree-Based Rules Derived from Electronic Health-Record Data
Laboratory testing is the single highest-volume medical activity, making it useful to ask how well one can anticipate whether a given test result will be high, low, or within the reference interval (ânormalâ). We analyzed 10 years of electronic health recordsâa total of 69.4 million blood testsâto see how well standard rule-mining techniques can anticipate test results based on patient age and gender, recent diagnoses, and recent laboratory test results. We evaluated rules according to their positive and negative predictive value (PPV and NPV) and area under the receiver-operator characteristic curve (ROC AUCs). Using a stringent cutoff of PPV and/or NPVâ„0.95, standard techniques yield few rules for sendout tests but several for in-house tests, mostly for repeat laboratory tests that are part of the complete blood count and basic metabolic panel. Most rules were clinically and pathophysiologically plausible, and several seemed clinically useful for informing pre-test probability of a given result. But overall, rules were unlikely to be able to function as a general substitute for actually ordering a test. Improving laboratory utilization will likely require different input data and/or alternative methods
Resistance to Wheat streak mosaic virus generated by expression of an artificial polycistronic microRNA in wheat
Wheat streak mosaic virus (WSMV) is a persistent threat to wheat production, necessitating novel approaches for protection. We developed an artificial miRNA strategy against WSMV, incorporating five amiRNAs within one polycistronic amiRNA precursor. Using miRNA sequence and folding rules, we chose five amiRNAs targeting conserved regions of WSMV but avoiding off-targets in wheat. These replaced the natural miRNA in each of five arms of the polycistronic rice miR395, producing amiRNA precursor, FanGuard (FGmiR395), which was transformed into wheat behind a constitutive promoter. Splinted ligation detected all five amiRNAs being processed in transgenic leaves. Resistance was assessed over two generations. Three types of response were observed in T 1 plants of different transgenic families: completely immune; initially resistant with resistance breaking down over time; and initially susceptible followed by plant recovery. Deep sequencing of small RNAs from inoculated leaves allowed the virus sequence to be assembled from an immune transgenic, susceptible transgenic, and susceptible non-transgenic plant; the amiRNA targets were fully conserved in all three isolates, indicating virus replication on some transgenics was not a result of mutational escape by the virus. For resistant families, the resistance segregated with the transgene. Analysis in the T 2 generation confirmed the inheritance of immunity and gave further insights into the other phenotypes. Stable resistant lines developed no symptoms and no virus by ELISA; this resistance was classified as immunity when extracts failed to transmit from inoculated leaves to test plants. This study demonstrates the utility of a polycistronic amiRNA strategy in wheat against WSMV
AbsIDconvert: An absolute approach for converting genetic identifiers at different granularities
KNH2 - KH: a metal amide - hydride solid solution
We report for the first time the formation of a metal amide-hydride solid solution. The dissolution of KH into KNH2 leads to an anionic substitution, which decreases the interaction among NH2 - ions. The rotational properties of the high temperature polymorphs of KNH2 are thereby retained down to room temperature.Fil: Santoru, Antonio. Helmholtz-zentrum Geesthacht; Alemania. UniversitĂ di Torino; ItaliaFil: Pistidda, Claudio. Helmholtz-zentrum Geesthacht; AlemaniaFil: SĂžrby, Magnus H.. Institute for Energy Technology. Physics Department; NoruegaFil: Chierotti, Michele R.. UniversitĂ di Torino; ItaliaFil: Garroni, Sebastian. University of Sassari; ItaliaFil: Pinatel, Eugenio. UniversitĂ di Torino; ItaliaFil: Karimi, Fahim. Helmholtz-zentrum Geesthacht; AlemaniaFil: Cao, Hujun. Helmholtz-zentrum Geesthacht; AlemaniaFil: Bergemann, Nils. Helmholtz-zentrum Geesthacht; AlemaniaFil: Le, Thi T.. Helmholtz-zentrum Geesthacht; AlemaniaFil: Puszkiel, JuliĂĄn Atilio. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - Patagonia Norte; Argentina. ComisiĂłn Nacional de EnergĂa AtĂłmica. Gerencia del Ărea de EnergĂa Nuclear. Instituto Balseiro; ArgentinaFil: Gobetto, Roberto. UniversitĂ di Torino; ItaliaFil: Baricco, Marcello. UniversitĂ di Torino; ItaliaFil: Hauback, Bjorn C.. Institute for Energy Technology. Physics Department; NoruegaFil: Klassen, Thomas. Helmholtz-zentrum Geesthacht; AlemaniaFil: Dornheim, MartĂn. Helmholtz-zentrum Geesthacht; Alemani
categoryCompare, an analytical tool based on feature annotations
Assessment of high-throughputâomics data initially focuses on relative or raw levels of a particular feature, such as an expression value for a transcript, protein, or metabolite. At a second level, analyses of annotations including known or predicted functions and associations of each individual feature, attempt to distill biological context. Most currently available comparative- and meta-analyses methods are dependent on the availability of identical features across data sets, and concentrate on determining features that are differentially expressed across experiments, some of which may be considered âbiomarkers.â The heterogeneity of measurement platforms and inherent variability of biological systems confounds the search for robust biomarkers indicative of a particular condition. In many instances, however, multiple data sets show involvement of common biological processes or signaling pathways, even though individual features are not commonly measured or differentially expressed between them. We developed a methodology, categoryCompare, for cross-platform and cross-sample comparison of high-throughput data at the annotation level. We assessed the utility of the approach using hypothetical data, as well as determining similarities and differences in the set of processes in two instances: (1) denervated skin vs. denervated muscle, and (2) colon from Crohn's disease vs. colon from ulcerative colitis (UC). The hypothetical data showed that in many cases comparing annotations gave superior results to comparing only at the gene level. Improved analytical results depended as well on the number of genes included in the annotation term, the amount of noise in relation to the number of genes expressing in unenriched annotation categories, and the specific method in which samples are combined. In the skin vs. muscle denervation comparison, the tissues demonstrated markedly different responses. The Crohn's vs. UC comparison showed gross similarities in inflammatory response in the two diseases, with particular processes specific to each disease
A Comparison of Australian and American Medical School Admission Experiences
Attaining admission into medical school has been described as a very competitive process by successful matriculants. The processes that medical schools use to classify applicants can greatly differ among institutions. These systemic differences flow over onto the applicant level, such that individuals from different geographic regions can have varied and diverse application experiences depending on local medical school admissions protocols. This piece compares the medical school admission processes of Australia and the United States of America, in the form of a narrative recount of a successful medical school matriculant in each country, with the individual experiences of matriculants from alternative pathways blended into the piece. The authors discovered significant differences in admissions protocols between the two countries, with the greatest differences revolving around admissions exams, applicant profile (high school students versus college students), degree types, and alternative entrance pathways
SUSTAINING MOROCCAN OASIS AGRICULTURAL SYSTEM through SMALL MECHANIZATION INPUTS
Saharan oases are a highly artificial ecosystem that has proved to be economicallyviable for centuries, despiteitsâfragile equilibrium. The pillar of this ecosystem is the good management of the palm grove, which allows the establishment of a three-layer structure and of a microclimate favourable for agriculture. Nowadays oases ecosystem is at risk, endangered by climate changes and economic and social factors and the poor management of the palm grove,caused by lack of human and material resources,is the main cause of itsâ collapsing. The introduction of small mechanization can provide tools to invigorate this farming system and attract young people in the agricultural sector
Satellite Remote Sensing of Atmospheric SO_2: Volcanic Eruptions and Anthropogenic Emissions
In this article, we present satellite data analysis of atmospheric Sulfur Dioxide (SO_2) from volcanic eruptions and anthropogenic activities. Data from Global Ozone Monitoring Experiment (GOME) on board ERS-2 for the years 1996 to 2002 is analyzed using a DOAS based algorithm with the aim of retrieving SO_2 Slant Column Densities (SCDs). Difficulties in the retrieval of SO_2 SCDs due to instrumental effects are investigated in detail and significantly improved. The retrieved SCDs can be used to identify and monitor several volcanic eruptions. A brief introduction of different volcanic eruptions around the globe is presented Also informations about the anthropogenic SO_2 emissions can be easily achieved from the retrieved data set. A time series of anthropogenic SO_2 emissions over Eastern Europe is presented in this study. The time series showed high SO_2 SCDs over Eastern Europe during the winter months. The results demonstrate a high sensitivity of GOME instrument towards SO_2 emissions
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