Topological-Pattern-Based Recommendation of UMLS Concepts for National Cancer Institute Thesaurus.

The National Cancer Institute Thesaurus (NCIt) is a reference terminology used to support clinical, translational and basic research as well as administrative activities. As medical knowledge evolves, concepts that might be missing from a particular needed subdomain are regularly added to the NCIt. However, terminology development is known to be labor-intensive and error-prone. Therefore, cost-effective semi-automated methods for identifying potentially missing concepts would be useful to terminology curators. Previously, we have developed a structural method leveraging the native term mappings of the Unified Medical Language System to identify potential concepts in several of its source vocabularies to enrich the SNOMED CT. In this paper, we tested an analogous method for NCIt. Concepts from eight UMLS source terminologies were identified as possibilities to enrich NCIt's conceptual content.

Non-invasive physiology in conscious mice.

Linking gene defect to disease phenotypes in mice has become an essential step in the development of new drugs. Yet, many in vitro and in vivo assays require anaesthetic and surgery or do not reflect physiologically relevant phenomena. The effects of genes or diseases may only become apparent with stressors. Here, we apply non-invasive ECG monitoring and gait imaging systems to describe changes in the electrocardiogram and in gait dynamics resulting from a doubling of the ambulatory speed of mice. We found that B6C3H mice (n = 5) take 3.6 +/- 0.1 strides/second to walk 18cm/second and have a heart rate of 750 +/- 2bpm after 1 minute of walking at this speed. These mice significantly increase stride frequency to 5.2 +/- 0.1 strides/second in order to increase their speed to 36cm/second. The heart rate increased significantly (814 +/- 9bpm, p < 0.05) after trotting at the higher speed for 90 seconds, and the QRS interval duration significantly decreased (9.4 +/- 0.3ms vs. 10.4 +/- 0.3ms, p < 0.05). We discuss the application of the ECG screening and gait imaging systems to mouse models of Duchenne muscular dystrophy, Down syndrome and amyotrophic lateral sclerosis, diseases in humans that are known to affect the heart and neuromuscular systems.