Prediction of motion induced magnetic fields for human brain MRI at 3T

Objective Maps of B0 field inhomogeneities are often used to improve MRI image quality, even in a retrospective fashion. These field inhomogeneities depend on the exact head position within the static field but acquiring field maps (FM) at every position is time consuming. Here we explore different ways to obtain B0 predictions at different head positions. Methods FM were predicted from iterative simulations with four field factors: 1) sample induced B0 field, 2) system's spherical harmonic shim field, 3) perturbing field originating outside the field of view, 4) sequence phase errors. The simulation was improved by including local susceptibility sources estimated from UTE scans and position-specific masks. The estimation performance of the simulated FMs and a transformed FM, obtained from the measured reference FM, were compared with the actual FM at different head positions. Results The transformed FM provided inconsistent results for large head movements (>5 degree rotation), while the simulation strategy had a superior prediction accuracy for all positions. The simulated FM was used to optimize B0 shims with up to 22.2% improvement with respect to the transformed FM approach. Conclusion The proposed simulation strategy is able to predict movement induced B0 field inhomogeneities yielding more precise estimates of the ground truth field homogeneity than the transformed FM

Analysis of glycoprotein processing in the endoplasmic reticulum using synthetic oligosaccharides

Protein quality control (QC) in the endoplasmic reticulum (ER) comprises many steps, including folding and transport of nascent proteins as well as degradation of misfolded proteins. Recent studies have revealed that high-mannose-type glycans play a pivotal role in the QC process. To gain knowledge about the molecular basis of this process with well-defined homogeneous compounds, we achieved a convergent synthesis of high-mannose-type glycans and their functionalized derivatives. We focused on analyses of UDP-Glc: glycoprotein glucosyltransferase (UGGT) and ER Glucosidase II, which play crucial roles in glycoprotein QC; however, their specificities remain unclear. In addition, we established an in vitro assay system mimicking the in vivo condition which is highly crowded because of the presence of various biomacromolecules

Service orchestration with priority constraints

Business process management is an operational management approach that focuses on improving business processes. Business processes, i.e., collections of important activities in an organization, are represented in the form of a workflow, an orchestrated and repeatable pattern of activities amenable to automated analysis and control. Priority is an important concept in modeling workflows. We need priority to model cancelable and compensable tasks within transactional business processes. We use the Reo coordination language to model and formally analyze workflows. In this paper, we propose a constraint-based approach to formalize priority in Reo. We introduce special channels to propagate and block priority flows, define their semantics as constraints, and model priority propagation as a constraint satisfaction problem

Structural Analysis to Determine the Core of Hypoxia Response Network

The advent of sophisticated molecular biology techniques allows to deduce the structure of complex biological networks. However, networks tend to be huge and impose computational challenges on traditional mathematical analysis due to their high dimension and lack of reliable kinetic data. To overcome this problem, complex biological networks are decomposed into modules that are assumed to capture essential aspects of the full network's dynamics. The question that begs for an answer is how to identify the core that is representative of a network's dynamics, its function and robustness. One of the powerful methods to probe into the structure of a network is Petri net analysis. Petri nets support network visualization and execution. They are also equipped with sound mathematical and formal reasoning based on which a network can be decomposed into modules. The structural analysis provides insight into the robustness and facilitates the identification of fragile nodes. The application of these techniques to a previously proposed hypoxia control network reveals three functional modules responsible for degrading the hypoxia-inducible factor (HIF). Interestingly, the structural analysis identifies superfluous network parts and suggests that the reversibility of the reactions are not important for the essential functionality. The core network is determined to be the union of the three reduced individual modules. The structural analysis results are confirmed by numerical integration of the differential equations induced by the individual modules as well as their composition. The structural analysis leads also to a coarse network structure highlighting the structural principles inherent in the three functional modules. Importantly, our analysis identifies the fragile node in this robust network without which the switch-like behavior is shown to be completely absent