Description of Hymenolepis microstoma (Nottingham strain): a classical tapeworm model for research in the genomic era

<p>Abstract</p> <p>Background</p> <p><it>Hymenolepis microstoma </it>(Dujardin, 1845) Blanchard, 1891, the mouse bile duct tapeworm, is a rodent/beetle-hosted laboratory model that has been used in research and teaching since its domestication in the 1950s. Recent characterization of its genome has prompted us to describe the specific strain that underpins these data, anchoring its identity and bringing the 150+ year-old original description up-to-date.</p> <p>Results</p> <p>Morphometric and ultrastructural analyses were carried out on laboratory-reared specimens of the 'Nottingham' strain of <it>Hymenolepis microstoma </it>used for genome characterization. A contemporary description of the species is provided including detailed illustration of adult anatomy and elucidation of its taxonomy and the history of the specific laboratory isolate.</p> <p>Conclusions</p> <p>Our work acts to anchor the specific strain from which the <it>H. microstoma </it>genome has been characterized and provides an anatomical reference for researchers needing to employ a model tapeworm system that enables easy access to all stages of the life cycle. We review its classification, life history and development, and briefly discuss the genome and other model systems being employed at the beginning of a genomic era in cestodology.</p

A Pipeline for Bio-data

Due to the lack of a pipeline that can store and analyze a wide variety of biomedical data, our team built GILBERT. GILBERT is a web application that uses Django and stores its data in PostgreSQL. It contains four main components considered essential elements of a data analysis pipeline: a system that controls which users have access to which studies, an uploader which allows users to add studies to GILBERT’s database, an interface that displays study information and metadata, and a feature that analyzes studies in the database through statistical and graphical means. To evaluate GILBERT, twenty-seven participants responded to two surveys and attended a virtual evaluation session. In the evaluation sessions, a team member read tasks to the participant while another team member scored the participant on their behavior, their ability to complete the tasks, and understanding of the system. Overall, tasks had a high completion rate. Participants rated GILBERT as easy to use and easy to understand. Differences in ratings were insignificant between different majors, amounts of experience with large amounts of data, and experience with other data handling tools such as MATLAB, Python, and SQL. These results show that GILBERT is an effective tool for biomedical data handling. Future work could make GILBERT’s uploader more flexible, allow for easier cross-study analysis, and add more options to create charts