A tool for developing an automatic insect identification system based on wing outlines.
Ontology highlight
ABSTRACT:
SUBMITTER: Yang HP
PROVIDER: S-EPMC4528224 | biostudies-other | 2015
REPOSITORIES: biostudies-other
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Project description:Gp.Mur is a clinically relevant antigen of the MNS blood group system that is highly prevalent in several Asian populations. Its corresponding antibody, anti-Gp.Mur, has been implicated in hemolytic transfusion reactions and hemolytic disease of the fetus and newborn. Currently, identifying and confirming anti-Gp.Mur antibody presence in sera via agglutination of a panel of red blood cells (RBCs) is inefficient and difficult to quantify. Using a baculovirus expression system to express Gp.Mur antigen on insect cell surfaces, we have developed a quantitative cell-based system to confirm the presence of anti-Gp.Mur antibody in human serum. We obtained 10 serum samples preidentified as having anti-Gp.Mur antibody and another 4 samples containing noncorresponding antibodies from hospital patients. Insect cells displaying Gp.Mur antigen successfully adsorbed anti-Gp.Mur antibody in the sera and inhibited the RBC agglutination mediated by this antibody. By varying the concentration of Gp.Mur-displaying cells, we could grade levels of RBC agglutination by anti-Gp.Mur antibody. Densitometric analysis further enabled quantitative determinations of hemagglutination inhibition by Gp.Mur-displaying cells. We believe that this cell-based hemagglutination inhibition system greatly improves or supplements existing technology and is a convenient means for accurately identifying and quantifying anti-Gp.Mur antibody.
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Project description:IntroductionMedical documentation is applied in various settings including patient care and clinical research. Since procedures of medical documentation are heterogeneous and developed further, secondary use of medical data is complicated. Development of medical forms, merging of data from different sources and meta-analyses of different data sets are currently a predominantly manual process and therefore difficult and cumbersome. Available applications to automate these processes are limited. In particular, tools to compare multiple documentation forms are missing. The objective of this work is to design, implement and evaluate the new system ODMSummary for comparison of multiple forms with a high number of semantically annotated data elements and a high level of usability.MethodsSystem requirements are the capability to summarize and compare a set of forms, enable to estimate the documentation effort, track changes in different versions of forms and find comparable items in different forms. Forms are provided in Operational Data Model format with semantic annotations from the Unified Medical Language System. 12 medical experts were invited to participate in a 3-phase evaluation of the tool regarding usability.ResultsODMSummary (available at https://odmtoolbox.uni-muenster.de/summary/summary.html) provides a structured overview of multiple forms and their documentation fields. This comparison enables medical experts to assess multiple forms or whole datasets for secondary use. System usability was optimized based on expert feedback.DiscussionThe evaluation demonstrates that feedback from domain experts is needed to identify usability issues. In conclusion, this work shows that automatic comparison of multiple forms is feasible and the results are usable for medical experts.
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