Brochure technojobs

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Technojobs

Technojobs, job portal dedicated to technical profiles. See details in our brochure

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Background: Diabetes education is mainly based on one-on-one patient-health care provider contact. This is costly, time-consuming and gives the patient no room for practice. We want to address these issues by creating the Eindhoven Diabetes Education Simulator, which uses a physiology-based mathematical model to predict glucose and insulin concentrations for patients with diabetes type 1 and 2 over a 2-4 hour time period after intake of food and/or insulin. In our current model food is entered in the form of carbohydrate content. The goal of this study was to incorporate different food products and composite meals for healthy persons, since different food types will elicit different glucose responses. Methods: A literature search was performed for datasets of different food products using (combinations of) the following search terms: healthy, mixed meal, glucose, insulin, glycemic response, glycemic index, and looking for cross-references. We included any dataset for which glucose ánd insulin concentrations were measured on at least 5 time points after food ingestion in healthy subjects. Healthy was defined as normal glucose tolerant, normal insulin sensitive, normotensive, normal HbA1c, non-obese (BMI< 30 kg/m2), no family history of diabetes, not pregnant, and free of apparent diseases and medication. Our model was fitted to the different datasets using a non-linear least squares algorithm. Results: We have fitted our model to 57 separate datasets (from 18 publications including 220 subjects, references available on request). For 35 of these datasets we obtained a model fit that described the dataset well, of which five are shown in Figure 1. In the cases that we could not obtain a good fit, there usually were a limited number of data points available. Conclusion: The Eindhoven Diabetes Education Simulator is able to simulate postprandial glucose and insulin concentrations for healthy persons for 35 different food products and composite meals.

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Part of the Training Course: Data Integration in the Life Sciences. from 2 Feb 2015 through 6 Feb 2015, Lorentz Center, Leiden Organized by ERA-Net program for Systems Biology Applications (ERASysApp, https://www.erasysapp.eu/) and the Dutch systems biology and bioinformatics community (BioSB, http://biosb.nl). http://www.lorentzcenter.nl/lc/web/2015/684/description.php3?wsid=684&venue=Snellius

ADAPT: Analysis of Dynamic Adaptations in Parameter Trajectories

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Due to an aging population and the obesity epidemic, an increasing number of people suffer from the so-called Metabolic Syndrome (MetSyn). Those people have a combination of related disease phenotypes, such as high cholesterol, disturbed sugar metabolism and insulin insensitivity. Moreover, they are at a high risk to develop type 2 diabetes, fatty liver and cardiovascular diseases. We use systems biology to understand how the processes involved in metabolism of cholesterol, lipids and sugars become imbalanced. As an example, a study on the effect of Liver X receptor (LXR) agonists is reported. Systems biology (systems medicine) research also triggers innovation in methods and technology for modelling. The application of a novel computational modeling approach, called Analysis of Dynamic Adaptations in Parameter Trajectories (ADAPT) will be discussed. ADAPT is applied to describe the development and progression of MetSyn over a longer period of time. In combination with model-based experimental validation we study the physiological origin of hepatic steatosis induced by liver X receptor activation.

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Grain Track – is a web-based CTRM-system for commodity trading companies to manage: counterparties, supply chain, logistics, invoices, vessels and documents. We resolve three painful problems of grain traders : - Lack of complete picture of finance and trade situation at the moment: lots of contracts, shipments, invoices and documents at the same time. - Difficult and untimely forecasting of cash flow, trade position and profit and loss - Financial and timing costs on communication, discussions, meetings and accounting by managers and employees Commotrack outputs: - Consolidated information about all counterparties - Statistics of trade operations by each product - Estimated and actual profit and loss by each deal - Physical + derivatives position and mark to market - Accounting and stocks management - Stuff control and KPI

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