Chronically Elevated Exogenous Glucose Elicits Antipodal Effects on the Proteome Signature of Differentiating Human iPSC-Derived Pancreatic Progenitors

The past decade revealed that cell identity changes, such as dedifferentiation or transdifferentiation, accompany the insulin-producing β-cell decay in most diabetes conditions. Mapping and controlling the mechanisms governing these processes is, thus, extremely valuable for managing the disease progression. Extracellular glucose is known to influence cell identity by impacting the redox balance. Here, we use global proteomics and pathway analysis to map the response of differentiating human pancreatic progenitors to chronically increased in vitro glucose levels. We show that exogenous high glucose levels impact different protein subsets in a concentration-dependent manner. In contrast, regardless of concentration, glucose elicits an antipodal effect on the proteome landscape, inducing both beneficial and detrimental changes in regard to achieving the desired islet cell fingerprint. Furthermore, we identified that only a subgroup of these effects and pathways are regulated by changes in redox balance. Our study highlights a complex effect of exogenous glucose on differentiating pancreas progenitors characterized by a distinct proteome signature.     

Bioenergetic Alterations of Metabolic Redox Coenzymes as NADH,FAD and FMN by Means of Fluorescence Lifetime Imaging Techniques

Metabolic FLIM (fluorescence lifetime imaging) is used to image bioenergetic status in cells and tissue. Whereas an attribution of the fluorescence lifetime of coenzymes as an indicator for cell metabolism is mainly accepted, it is debated whether this is valid for the redox state of cells. In this regard, an innovative algorithm using the lifetime characteristics of nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavin adenine dinucleotide (FAD) to calculate the fluorescence lifetime induced redox ratio (FLIRR) has been reported so far. We extended the FLIRR approach and present new results, which includes FLIM data of the various enzymes, such as NAD(P)H, FAD, as well as flavin mononucleotide (FMN). Our algorithm uses a two-exponential fitting procedure for the NAD(P)H autofluorescence and a three-exponential fit of the flavin signal. By extending the FLIRR approach, we introduced FLIRR1 as protein-bound NAD(P)H related to protein-bound FAD, FLIRR2 as protein-bound NAD(P)H related to free (unbound) FAD and FLIRR3 as protein-bound NAD(P)H related to protein-bound FMN. We compared the significance of extended FLIRR to the metabolic index, defined as the ratio of protein-bound NAD(P)H to free NAD(P)H. The statistically significant difference for tumor and normal cells was found to be highest for FLIRR1.     

Matching ultrasonic transducer using two matching layers where one of them is glue

The aim of this work is to propose an original solution to the acoustic impedance mismatch between a PZT transducer and a water load. The characteristic acoustic impedance of the PZT is around 33 MRayl. Theoretically, a quarter-wave layer with characteristic acoustic impedance equal to 7 MRayl is necessary to match the transducer to water. In practice, it is difficult to find a material with this particular impedance. Two or more quarter-wave layers may also be used. The following proposed solution consists in using two matching layers where one of them is the glue. Moreover, their thicknesses are not equal to a quarter of their individual wavelength. Once the glue is taken as the first matching layer, the specific material of the second layer can easily be found. In this work, the second layer, which is also the front layer, is made of glass. The thickness of each matching layer is then calculated as a function of the characteristic acoustic impedance of the two layers. The influence of the thickness of these layers is discussed. The proposed matching configuration is analyzed and theoretical results have been carefully and successfully compared with measurements.     

Temporal Hydrologic Alterations Coupled with Climate Variability and Drought for Transboundary River Basins

Climate change (CC) and drought episode impacts linked with anthropogenic pressure have become an increasing concern for policy makers and water resources managers. The current research presents a comprehensive methodology but simple approach for predicting the annual streamflow alteration based on drought indices and hydrological alteration indicators. This has been achieved depending on the evaluation of drought severity and CC impacts during the human intervention periods to separate the influence of climatic abnormality and measure the hydrologic deviations as a result of streamflow regulation configurations. As a representative case study, the Lesser Zab River Basin in northern Iraq has been chosen. In order to analyse the natural flow regime, 34 hydrological years of streamflow (1931–1965) prior to the main dam construction were assessed. The Indicators of Hydrologic Alteration (IHA) method has been applied to quantify the hydrological alterations of various flow characteristics. In addition, an easy approach for hydrological drought prediction in relatively small basins grounded on meteorological parameters during the early months of the hydrological year has been presented. The prediction was accomplished by implementing the one-dimensional drought examination and the reconnaissance drought index (RDI) for evaluating the severity of meteorological drought. The proposed methodology is founded on linear regression relations connecting the RDI of 3, 6, and 12 months and the streamflow drought index (SDI). The results are critical for circumstances where an early exploration of meteorological drought is obtainable. Outcomes assist water resources managers, engineers, policy makers and decision-makers responsible for mitigating the effects of CC.     

Development and characterization of a biocompatible OH-modified copolymer based on polyurethane

Different polyurethanes were synthesized by varying the diol as well as the diisocyanate components and chain extenders. Polyurethanes with OH-groups were obtained by photo- and thermoinitiation of the radical polymerization of hydroxy alkyl acrylates in the presence of the polyurethanes. The polymers were evaluated with respect to their biocompatibility by measuring the cell spreading, the rates of DNA- and protein synthesis and the swelling behaviour. The differences in the surfaces and the bulks between the selected basic polyurethane and the functionalized modification were determined and characterized by XPS, FTIR-ATR and ¹³C-FT-NMR-spectroscopy. The mechanical data of Tecoflex EG 60D® and Pellethane 2363–80AE® were compared with the data of the synthesized polyurethanes.     

Computational Problem Solving in Spatial Substrates -- A Cognitive Systems Engineering Approach

The ability to perform spatial tasks is crucial for everyday life and of great importance to cognitive agents such as humans, animals, and autonomous robots. A common artificial intelligence approach to accomplish spatial tasks is to represent spatial configurations and tasks in form of detailed knowledge about various aspects of space and time. Suitable algorithms then use the representations to compute solutions to spatial problems. In comparison, natural embodied and situated agents often solve spatial tasks without detailed knowledge about geometric, topological, or mechanical laws; they directly relate actions to effects that are due to spatio-temporal affordances in their bodies and environments. Accordingly, we propose a paradigm that makes the spatio-temporal substrate an integral part of the engine that drives spatial problem solving. We argue that spatial and temporal structures in body and environment can substantially support (and even replace) reasoning effort in computational processes: physical manipulation and perception in spatial environments substitute formal computation. While the approach is well known – for example, we employ diagrams as spatial substrate for geometric problem solving and maps for wayfinding – the underlying principle has not been systematically investigated or formally analyzed as a paradigm of cognitive processing. Topology, distance, and orientation constraints are all integrated and interdependent in truly 2- or 3-dimensional space. Exploiting this fact may not only help overcome the need for acquiring detailed knowledge about the interrelationships between different aspects of space; it also can point to a way of avoiding exploding computational complexity that occurs when we deal with these aspects of space in complex real-world scenarios. Our approach employs affordance-based object-level problem solving to complement knowledge-level formal approaches. We will assess strengths and weaknesses of the new cognitive systems paradigm.     

Five-year experience with setup and implementation of an integrated database system for clinical documentation and research

In radiation oncology, where treatment concepts are elaborated in interdisciplinary collaborations, handling distributed, large heterogeneous amounts of data efficiently is very important, yet challenging, for an optimal treatment of the patient as well as for research itself. This becomes a strong focus, as we step into the era of modern personalized medicine, relying on various quantitative data information, thus involving the active contribution of multiple medical specialties. Hence, combining patient data from all involved information systems is inevitable for analyses. Therefore, we introduced a documentation and data management system integrated in the clinical environment for electronic data capture. We discuss our concept and five-year experience of a precise electronic documentation system, with special focus on the challenges we encountered. We specify how such a system can be designed and implemented to plan, tailor and conduct (multicenter) clinical trials, ultimately reaching the best clinical performance, and enhancing interdisciplinary and clinical research.     

A Distributed O(1)-Approximation Algorithm for the Uniform Facility Location Problem

We investigate a metric facility location problem in a distributed setting. In this problem, we assume that each point is a client as well as a potential location for a facility and that the opening costs for the facilities and the demands of the clients are uniform. The goal is to open a subset of the input points as facilities such that the accumulated cost for the whole point set, consisting of the opening costs for the facilities and the connection costs for the clients, is minimized. We present a randomized distributed algorithm that computes in expectation an ${\mathcal {O}}(1)$ -approximate solution to the metric facility location problem described above. Our algorithm works in a synchronous message passing model, where each point is an autonomous computational entity that has its own local memory and that communicates with the other entities by message passing. We assume that each entity knows the distance to all the other entities, but does not know any of the other pairwise distances. Our algorithm uses three rounds of all-to-all communication with message sizes bounded to $\mathcal{O}(\log(n))$ bits, where n is the number of input points. We extend our distributed algorithm to constant powers of metric spaces. For a metric exponent ?≥1, we obtain a randomized ${\mathcal {O}}(1)$ -approximation algorithm that uses three rounds of all-to-all communication with message sizes bounded to $\mathcal{O}(\log(n))$ bits.     

Unmanned Ground Vehicle Navigation in Coordinate-Free and Localization-Free Wireless Sensor and Actuator Networks

We present a set of algorithms for the navigation of Unmanned Ground Vehicles (UGVs) towards a set of pre-identified target nodes in coordinate-free and localization-free wireless sensor and actuator networks. The UGVs are equipped with a set of wireless listeners that provide sensing information about the potential field generated by the network of actuators. Two main navigation scenarios are considered: single-UGV, single-destination navigation and multi-UGV, multi-destination navigation. For the single-UGV, single-destination case, we present both centralized and distributed navigation algorithms. Both algorithms share a similar two-phase concept. In the first phase, the system assigns level numbers to individual nodes based on their hop distance from the target nodes. In the second phase, the UGV uses the potential field created by the network of actuators to move towards the target nodes, requiring cooperation between triplets of actuator nodes and the UGV. The hop distance to the target nodes is used to control the main moving direction while the potential field, which can be measured by listeners on the UGV, is used to determine the UGV’s movement. For the multi-UGV, multi-destination case, we present a decentralized allocation algorithm such that multiple UGVs avoid converging to the same destination. After each UGV determines its destination, the proposed navigation scheme is applied. The presented algorithms do not attempt to localize UGVs or sensor nodes and are therefore suitable for operating in GPS-free/denied environments. We also present a study of the communication complexity of the algorithms as well as simulation examples that verify the proposed algorithms and compare their performances.