Crassostrea Ariakensis In Chesapeake Bay: Growth, Disease And Mortality In Shallow Subtidal Environments

In April 2004, triploid native (Crassostrea virginica) and nonnative (Crassostrea ariakensis) oysters were deployed in cages at four sites along a salinity gradient in Chesapeake Bay. In Maryland, the lowest salinity site was located in the Severn River and two low to mid-salinity sites were located in the Choptank and Patuxent Rivers. The highest salinity site was located in the York River in Virginia. Growth, disease acquisition, and mortality were measured in the deployed oysters through August 2006. Although ANOVA revealed that the nonnative oysters were significantly larger at the end of the experiment than the native oysters at all sites, the differences were much greater at the Virginia site (59 mm) than in Maryland waters (9-23 mm). With the exception of C. ariakensis in the Severn River, Perkinsus marinus infected both species at all sites. Prevalences and weighted prevalences in both species remained relatively low throughout the experiment, but native oysters consistently acquired higher prevalences and weighted prevalences than C. ariakensis by August 2006. With the exception of several mortality-inducing events including winter freezing and hypoxic exposure, mortality was generally low in both species. No disease-related mortality was suspected in either species given the low weighted prevalences observed. In the York River, where a substantial natural spatfall occurred in 2004, more native spat were found on C. ariakensis than on C. virginica. To our knowledge, this is the first comparison of triploid C. ariakensis to triploid C. virginica conducted in the field. Because we did not observe substantial disease-related mortality, it is too soon to draw conclusions regarding the disease tolerance of C. ariakensis in the field or its viability as a replacement for the native species

A cluster randomized trial evaluating electronic prescribing in an ambulatory care setting

<p>Abstract</p> <p>Background</p> <p>Medication errors, adverse drug events and potential adverse drug events are common and serious in terms of the harms and costs that they impose on the health system and those who use it. Errors resulting in preventable adverse drug events have been shown to occur most often at the stages of ordering and administration. This paper describes the protocol for a pragmatic trial of electronic prescribing to reduce prescription error. The trial was designed to overcome the limitations associated with traditional study design.</p> <p>Design</p> <p>This study was designed as a 65-week, cluster randomized, parallel study.</p> <p>Methods</p> <p>The trial was conducted within ambulatory outpatient clinics in an academic tertiary care centre in Ontario, Canada. The electronic prescribing software for the study is a Canadian electronic prescribing software package which provides physician prescription entry with decision support at the point of care. Using a handheld computer (PDA) the physician selects medications using an error minimising menu-based pick list from a comprehensive drug database, create specific prescription instructions and then transmit the prescription directly and electronically to a participating pharmacy via facsimile or to the physician's printer using local area wireless technology. The unit of allocation and randomization is by 'week', i.e. the system is "on" or "off" according to the randomization scheme and the unit of analysis is the prescription, with adjustment for clustering of patients within practitioners.</p> <p>Discussion</p> <p>This paper describes the protocol for a pragmatic cluster randomized trial of point-of-care electronic prescribing, which was specifically designed to overcome the limitations associated with traditional study design.</p> <p>Trial Registration</p> <p>This trial has been registered with clinicaltrials.gov (ID: NCT00252395)</p

Games, Simulations, Immersive Environments, and Emerging Technologies

International audienceThis entry presents an overview of advanced technologies to support teaching and learning. The use of innovative interactive systems for education has never been higher. Far from being just a trend, the objective is to use the current technology to cover educational needs and create relevant pedagogical situations. The arguments in their favor are generally their positive effects on learners’ motivation and the necessity to provide learning methods adapted to our growing digital culture. The new learning technologies and emerging trends are first reviewed hereunder. We thus define and discuss learning games, gamification, simulation, immersive environments and other emerging technologies. Then, the current limits and remaining scientific challenges are highlighted

Use of attribute association error probability estimates to evaluate quality of medical record geocodes

BACKGROUND: The utility of patient attributes associated with the spatiotemporal analysis of medical records lies not just in their values but also the strength of association between them. Estimating the extent to which a hierarchy of conditional probability exists between patient attribute associations such as patient identifying fields, patient and date of diagnosis, and patient and address at diagnosis is fundamental to estimating the strength of association between patient and geocode, and patient and enumeration area. We propose a hierarchy for the attribute associations within medical records that enable spatiotemporal relationships. We also present a set of metrics that store attribute association error probability (AAEP), to estimate error probability for all attribute associations upon which certainty in a patient geocode depends. METHODS: A series of experiments were undertaken to understand how error estimation could be operationalized within health data and what levels of AAEP in real data reveal themselves using these methods. Specifically, the goals of this evaluation were to (1) assess if the concept of our error assessment techniques could be implemented by a population-based cancer registry; (2) apply the techniques to real data from a large health data agency and characterize the observed levels of AAEP; and (3) demonstrate how detected AAEP might impact spatiotemporal health research. RESULTS: We present an evaluation of AAEP metrics generated for cancer cases in a North Carolina county. We show examples of how we estimated AAEP for selected attribute associations and circumstances. We demonstrate the distribution of AAEP in our case sample across attribute associations, and demonstrate ways in which disease registry specific operations influence the prevalence of AAEP estimates for specific attribute associations. CONCLUSIONS: The effort to detect and store estimates of AAEP is worthwhile because of the increase in confidence fostered by the attribute association level approach to the assessment of uncertainty in patient geocodes, relative to existing geocoding related uncertainty metrics

EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

<p>Abstract</p> <p>Background</p> <p>Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management.</p> <p>Results</p> <p>EMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms.</p> <p>Conclusion</p> <p>EMAAS enables users to track and perform microarray data management and analysis tasks through a single easy-to-use web application. The system architecture is flexible and scalable to allow new array types, analysis algorithms and tools to be added with relative ease and to cope with large increases in data volume.</p

Decadal changes of the Western Arabian sea ecosystem

Historical data from oceanographic expeditions and remotely sensed data on outgoing longwave radiation, temperature, wind speed and ocean color in the western Arabian Sea (1950–2010) were used to investigate decadal trends in the physical and biochemical properties of the upper 300 m. 72 % of the 29,043 vertical profiles retrieved originated from USA and UK expeditions. Increasing outgoing longwave radiation, surface air temperatures and sea surface temperature were identified on decadal timescales. These were well correlated with decreasing wind speeds associated with a reduced Siberian High atmospheric anomaly. Shoaling of the oxycline and nitracline was observed as well as acidification of the upper 300 m. These physical and chemical changes were accompanied by declining chlorophyll-a concentrations, vertical macrofaunal habitat compression, declining sardine landings and an increase of fish kill incidents along the Omani coast

Identifier mapping performance for integrating transcriptomics and proteomics experimental results

Background\ud Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit.\ud \ud Results\ud We compared three freely available internet-based identifier mapping resources for mapping UniProt accessions (ACCs) to Affymetrix probesets identifications (IDs): DAVID, EnVision, and NetAffx. Liquid chromatography-tandem mass spectrometry analyses of 91 endometrial cancer and 7 noncancer samples generated 11,879 distinct ACCs. For each ACC, we compared the retrieval sets of probeset IDs from each mapping resource. We confirmed a high level of discrepancy among the mapping resources. On the same samples, mRNA expression was available. Therefore, to evaluate the quality of each ACC-to-probeset match, we calculated proteome-transcriptome correlations, and compared the resources presuming that better mapping of identifiers should generate a higher proportion of mapped pairs with strong inter-platform correlations. A mixture model for the correlations fitted well and supported regression analysis, providing a window into the performance of the mapping resources. The resources have added and dropped matches over two years, but their overall performance has not changed.\ud \ud Conclusions\ud The methods presented here serve to achieve concrete context-specific insight, to support well-informed decisions in choosing an ID mapping strategy for "omic" data merging

Difficulty Accessing Syringes Mediates the Relationship Between Methamphetamine Use and Syringe Sharing Among Young Injection Drug Users

Injection drug users (IDU) who use methamphetamine (MA) are at an increased risk of HIV infection due to engagement in injection-related risk behavior including syringe sharing. In this cohort study of young IDU aged 18-30, we investigated the relationship between injection MA use and syringe sharing, and whether difficulty accessing sterile syringes mediated this association. Behavioral questionnaires were completed by 384 IDU in Vancouver, Canada between October 2005 and May 2008. Generalized estimating equations were used to estimate direct and indirect effects. The median age of participants was 24 (IQR: 22–27) and 214 (55.7%) were male. Injecting MA was independently associated with syringe sharing. Mediation analyses revealed that difficulty accessing sterile syringes partially mediated the association between injecting MA and syringe sharing. Interventions to reduce syringe sharing among young methamphetamine injectors must address social and structural barriers to accessing HIV prevention programs