Logical development of the cell ontology.

BACKGROUND: The Cell Ontology (CL) is an ontology for the representation of in vivo cell types. As biological ontologies such as the CL grow in complexity, they become increasingly difficult to use and maintain. By making the information in the ontology computable, we can use automated reasoners to detect errors and assist with classification. Here we report on the generation of computable definitions for the hematopoietic cell types in the CL. RESULTS: Computable definitions for over 340 CL classes have been created using a genus-differentia approach. These define cell types according to multiple axes of classification such as the protein complexes found on the surface of a cell type, the biological processes participated in by a cell type, or the phenotypic characteristics associated with a cell type. We employed automated reasoners to verify the ontology and to reveal mistakes in manual curation. The implementation of this process exposed areas in the ontology where new cell type classes were needed to accommodate species-specific expression of cellular markers. Our use of reasoners also inferred new relationships within the CL, and between the CL and the contributing ontologies. This restructured ontology can be used to identify immune cells by flow cytometry, supports sophisticated biological queries involving cells, and helps generate new hypotheses about cell function based on similarities to other cell types. CONCLUSION: Use of computable definitions enhances the development of the CL and supports the interoperability of OBO ontologies.

A pilot study using flash continuous glucose monitoring in patients with type-2 diabetes on multiple anti-diabetic agents during Ramadan.

BACKGROUND: This study aims to examine the incidence of hypoglycaemia, based on activity, during Ramadan in patients with type 2 diabetes mellitus who were on were on three or more anti-diabetic medications. METHODS: Type 2 diabetes patients who fasted during Ramadan and were on three or more anti-diabetic medications were studied for two weeks using flash glucose monitoring. The patients were asked to document all episodes of hypoglycaemia and were classified as active or sedentary according to their daytime activity. RESULTS: The study included 16 patients of whom 10 were active and 6 were sedentary. There were 13 males and 3 females; mean age was 53.4 ±â€¯6.4 years; mean diabetes duration was 15 ±â€¯5.9 years, and mean HbA1C was 7.9 ±â€¯1.3%. Over the two weeks; there were 7.9 episodes of hypoglycaemia recorded per patient; 50% of which were asymptomatic. There was no difference at baseline in age, BMI, HBA1C, diabetes duration, and anti-diabetic medications between the active and sedentary groups. The active group had better glucose control; median blood glucose was (7.1 (5.1-8.5) vs 10.6 (9.6-11.5) mmol p < 0.01), mean estimated HBA1C was (6.2 ±â€¯1.2% vs 8.3 ±â€¯1.0%; p = 0.047). The active group had more episodes of hypoglycaemia compared to the sedentary group (11.6 vs 1.8 hypo episode per patient/two weeks; p = 0.019); most of which were asymptomatic. CONCLUSION: Patients with type 2 diabetes mellitus who are on three or more anti-diabetic medications should be warned about the increased risk of asymptomatic hypoglycaemia during Ramadan. Anti-diabetic medication adjustments during Ramadan should take into account the degree of activity. Flash glucose monitoring system can help patients to fast safely during Ramadan and detect asymptomatic hypoglycaemia.