Glycomic analysis of human mast cells, eosinophils and basophils

In allergic diseases such as asthma, eosinophils, basophils and mast cells, through release of preformed and newly generated mediators, granule proteins and cytokines, are recognized as key effector cells. While their surface protein phenotypes, mediator release profiles, ontogeny, cell trafficking and genomes have been generally explored and compared, there has yet to be any thorough analysis and comparison of their glycomes. Such studies are critical to understand the contribution of carbohydrates to the induction and regulation of allergic inflammatory responses and are now possible using improved technologies for detecting and characterizing cell-derived glycans. We thus report here the application of high-sensitivity mass spectrometric-based glycomics methodologies to the analysis of N-linked glycans derived from isolated populations of human mast cells, eosinophils and basophils. The samples were subjected to matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) screening analyses and MALDI-TOF/TOF sequencing studies. Results reveal substantive quantities of terminal N-acetylglucosamine containing structures in both the eosinophil and the basophil samples, whereas mast cells display greater relative quantities of sialylated terminal epitopes. For the first time, we characterize the cell surface glycan structures of principal allergic effector cells, which by interaction with glycan-binding proteins (e.g. lectins) have the possibility to dictate cellular functions, and might thus have important implications for the pathogenesis of inflammatory and allergic diseases.

GoCARB in the Context of an Artificial Pancreas

Background: In an artificial pancreas (AP), the meals are either manually announced or detected and their size estimated from the blood glucose level. Both methods have limitations, which result in suboptimal postprandial glucose control. The GoCARB system is designed to provide the carbohydrate content of meals and is presented within the AP framework. Method: The combined use of GoCARB with a control algorithm is assessed in a series of 12 computer simulations. The simulations are defined according to the type of the control (open or closed loop), the use or not-use of GoCARB and the diabetics’ skills in carbohydrate estimation. Results: For bad estimators without GoCARB, the percentage of the time spent in target range (70-180 mg/dl) during the postprandial period is 22.5% and 66.2% for open and closed loop, respectively. When the GoCARB is used, the corresponding percentages are 99.7% and 99.8%. In case of open loop, the time spent in severe hypoglycemic events (<50 mg/dl) is 33.6% without the GoCARB and is reduced to 0.0% when the GoCARB is used. In case of closed loop, the corresponding percentage is 1.4% without the GoCARB and is reduced to 0.0% with the GoCARB. Conclusion: The use of GoCARB improves the control of postprandial response and glucose profiles especially in the case of open loop. However, the most efficient regulation is achieved by the combined use of the control algorithm and the GoCARB.