Statistical Analysis of Diabetes Mellitus

Diabetes mellitus is a disease where the glucosis-content of the blood does not automatically decrease to a ”normal” value between 70 mg/dl and 120 mg/dl (3,89 mmol/l and 6,67 mmol/l) between perhaps one hour (or two hours) after eating. Several instruments can be used to arrive at a relative low increase of the glucosis-content. Besides drugs (oral antidiabetica, insulin) the blood-sugar content can mainly be influenced by (i) eating, i.e., consumption of the right amount of food at the right time (ii) physical training (walking, cycling, swimming). In a recent paper the author has performed a regression analysis on the influence of eating during the night. The result was that one ”bread-unit” (12g carbon-hydrats) increases the blood-sugar by about 50 mg/dl, while one hour after eating the blood-sugar decreases by about 10 mg/dl per hour. By applying this result-assuming its correctness - it is easy to eat the right amount during the night and to arrive at a fastening blood-sugar (glucosis-content) in the morning of about 100 mg/dl (5,56 mmol/l). In this paper we try to incorporate some physical exercise into the model.

Semantic network analysis of ontologies

A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, beside consistency checking, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as (labeled, directed) graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures in general currently receive high attention in the Semantic Web community, there are only very few SNA applications up to now, and virtually none for analyzing the structure of ontologies. We illustrate in this paper the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality based on Hermitian matrices, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size.

Characterization of Lipid Droplets and Functional Analysis of Lipid Droplet-Associated Proteins in Dictyostelium discoideum

Lipid droplets (LDs) are the universal storage form of fat as a reservoir of metabolic energy in animals, plants, bacteria and single celled eukaryotes. Dictyostelium LD formation was investigated in response to the addition of different nutrients to the growth medium. LDs were induced by adding exogenous cholesterol, palmitic acid (PA) as well as growth in bacterial suspension, while glucose addition fails to form LDs. Among these nutrients, PA addition is most effective to stimulate LD formation, and depletion of PA from the medium caused LD degradation. The neutral lipids incorporated into the LD-core are composed of triacylglycerol (TAG), steryl esters, and an unknown neutral lipid (UKL) species when the cells were loaded simultaneously with cholesterol and PA. In order to avoid the contamination with other cellular organelles, the LD-purification method was modified. The isolated LD fraction was analysed by mass spectrometry and 100 proteins were identified. Nineteen of these appear to be directly involved in lipid metabolism or function in regulating LD morphology. Together with a previous study, a total of 13 proteins from the LD-proteome were confirmed to localize to LDs after the induction with PA. Among the identified LD-proteins, the localization of Ldp (lipid droplet membrane protein), GPAT3 (glycerol-3-phosphate acyltransferase 3) and AGPAT3 (1-acylglycerol-3-phosphate-acyltransferase 3) were further verified by GFP-tagging at the N-termini or C-termini of the respective proteins. Fluorescence microscopy demonstrated that PA-treatment stimulated the translocation of the three proteins from the ER to LDs. In order to clarify DGAT (diacylglycerol acyltransferase) function in Dictyostelium, the localization of DGAT1, that is not present in LD-proteome, was also investigated. GFP-tagged DGAT1 localized to the ER both, in the presence and absence of PA, which is different from the previously observed localization of GFP-tagged DGAT2, which almost exclusively binds to LDs. The investigation of the cellular neutral lipid level helps to elucidate the mechanism responsible for LD-formation in Dictyostelium cells. Ldp and two short-chain dehydrogenases, ADH (alcohol dehydrogenase) and Ali (ADH-like protein), are not involved in neutral lipid biosynthesis. GPAT, AGPAT and DGAT are three transferases responsible for the three acylation steps of de novo TAG synthesis. Knock-out (KO) of AGPAT3 and DGAT2 did not affect storage-fat formation significantly, whereas cells lacking GPAT3 or DGAT1 decreased TAG and LD accumulation dramatically. Furthermore, DGAT1 is responsible for the accumulation of the unknown lipid UKL. Overexpression of DGAT2 can rescue the reduced TAG content of the DGAT1-KO mutant, but fails to restore UKL content in these cells, indicating that of DGAT1 and DGAT2 have overlapping functions in TAG synthesis, but the role in UKL formation is unique to DGAT1. Both GPAT3 and DGAT1 affect phagocytic activity. Mutation of GPAT3 increases it but a DGAT1-KO decreases phagocytosis. The double knockout of DGAT1 and 2 also impairs the ability to grow on a bacterial lawn, which again can be rescued by overexpression of DGAT2. These and other results are incorporated into a new model, which proposes that up-regulation of phagocytosis serves to replenish precursor molecules of membrane lipid synthesis, whereas phagocytosis is down-regulated when excess fatty acids are used for storage-fat formation.