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Molecular-genetic identification of emerged novel invasive pathogens of Asiatic Elm Ulmus pumila L
(2014)
The dwarf elm Ulmus pumila L. (Ulmaceae) is one of indigenous species of flora in Kazakhstan and forms a basis of dendroflora in virtually all settlements of the region. In the past decade, multiple outbreaks of previously unknown diseases of the small-leaved elm have been registered. In our study, by the molecular-genetic analysis it was found that the pathogens responsible for the outbreaks are microfungi belonging to the genus Fusarium – F. solani and F. oxysporum. The nucleotide sequences (ITS regions) isolated from the diseased trees showed very high similarity with the GenBank control numbers EU625403.1 and FJ478128.1 (100.0 and 99.0 % respectively). Oncoming research will focus on the search of natural microbial antagonists of the discovered phytopathogens.
Network theory provides novel concepts that promise an improved characterization of interacting dynamical systems. Within this framework, evolving networks can be considered as being composed of nodes, representing systems, and of time-varying edges, representing interactions between these systems. This approach is highly attractive to further our understanding of the physiological and pathophysiological dynamics in human brain networks. Indeed, there is growing evidence that the epileptic process can be regarded as a large-scale network phenomenon. We here review methodologies for inferring networks from empirical time series and for a characterization of these evolving networks. We summarize recent findings derived from studies that investigate human epileptic brain networks evolving on timescales ranging from few seconds to weeks. We point to possible pitfalls and open issues, and discuss future perspectives.
The scope of this study is the measurement of endotoxin adsorption rate for carbonized rice husk. It showed good adsorption properties for LPS. During the batch experiments, several techniques were used and optimized for improving the material’s adsorption behavior. Also, with the results obtained it was possible to differentiate the materials according to their adsorption capacity and kinetic characteristics.
Background
True date palms (Phoenix dactylifera L.) are impressive trees and have served as an indispensable source of food for mankind in tropical and subtropical countries for centuries. The aim of this study is to differentiate date palm tree varieties by analysing leaflet cross sections with technical/optical methods and artificial neural networks (ANN).
Results
Fluorescence microscopy images of leaflet cross sections have been taken from a set of five date palm tree cultivars (Hewlat al Jouf, Khlas, Nabot Soltan, Shishi, Um Raheem). After features extraction from images, the obtained data have been fed in a multilayer perceptron ANN with backpropagation learning algorithm.
Conclusions
Overall, an accurate result in prediction and differentiation of date palm tree cultivars was achieved with average prediction in tenfold cross-validation is 89.1% and reached 100% in one of the best ANN.
Shakedown analysis of Reissner-Mindlin plates using the edge-based smoothed finite element method
(2014)
This paper concerns the development of a primal-dual algorithm for limit and shakedown analysis of Reissner-Mindlin plates made of von Mises material. At each optimization iteration, the lower bound of the shakedown load multiplier is calculated simultaneously with the upper bound using the duality theory. An edge-based smoothed finite element method (ES-FEM) combined with the discrete shear gap (DSG) technique is used to improve the accuracy of the solutions and to avoid the transverse shear locking behaviour. The method not only possesses all inherent features of convergence and accuracy from ES-FEM, but also ensures that the total number of variables in the optimization problem is kept to a minimum compared with the standard finite element formulation. Numerical examples are presented to demonstrate the effectiveness of the present method.
Two single-incision mini-slings used for treating urinary incontinence in women are compared with respect to the stresses they produce in their surrounding tissue. In an earlier paper we experimentally observed that these implants produce considerably different stress distributions in a muscle tissue equivalent. Here we perform 2D finite element analyses to compare the shear stresses and normal stresses in the tissue equivalent for the two meshes and to investigate their failure behavior. The results clearly show that the Gynecare TVT fails for increasing loads in a zipper-like manner because it gradually debonds from the surrounding tissue. Contrary to that, the tissue at the ends of the DynaMesh-SIS direct may rupture but only at higher loads. The simulation results are in good agreement with the experimental observations thus the computational model helps to interpret the experimental results and provides a tool for qualitative evaluation of mesh implants.
Successful bone sawing requires a high level of skill and experience, which could be gained by the use of Virtual Reality-based simulators. A key aspect of these medical simulators is realistic force feedback. The aim of this paper is to model the bone sawing process in order to develop a valid training simulator for the bilateral sagittal split osteotomy, the most often applied corrective surgery in case of a malposition of the mandible. Bone samples from a human cadaveric mandible were tested using a designed experimental system. Image processing and statistical analysis were used for the selection of four models for the bone sawing process. The results revealed a polynomial dependency between the material removal rate and the applied force. Differences between the three segments of the osteotomy line and between the cortical and cancellous bone were highlighted.
This paper develops a new finite element method (FEM)-based upper bound algorithm for limit and shakedown analysis of hardening structures by a direct plasticity method. The hardening model is a simple two-surface model of plasticity with a fixed bounding surface. The initial yield surface can translate inside the bounding surface, and it is bounded by one of the two equivalent conditions: (1) it always stays inside the bounding surface or (2) its centre cannot move outside the back-stress surface. The algorithm gives an effective tool to analyze the problems with a very high number of degree of freedom. Our numerical results are very close to the analytical solutions and numerical solutions in literature.
A semiconductor field-effect device has been used for an enzymatically catalyzed degradation of biopolymers for the first time. This novel technique is capable to monitor the degradation process of multiple samples in situ and in real-time. As model system, the degradation of the biopolymer poly(D, L-lactic acid) has been monitored in the degradation medium containing the enzyme lipase from Rhizomucor miehei. The obtained results demonstrate the potential of capacitive field-effect sensors for degradation studies of biodegradable polymers.
Among the variety of transducer concepts proposed for label-free detection of biomolecules, the semiconductor field-effect device (FED) is one of the most attractive platforms. As medical techniques continue to progress towards diagnostic and therapies based on biomarkers, the ability of FEDs for a label-free, fast and real-time detection of multiple pathogenic and physiologically relevant molecules with high specificity and sensitivity offers very promising prospects for their application in point-of-care and personalized medicine for an early diagnosis and treatment of diseases. The presented paper reviews recent advances and current trends in research and development of different FEDs for label-free, direct electrical detection of charged biomolecules by their intrinsic molecular charge. The authors are mainly focusing on the detection of the DNA hybridization event, antibody-antigen affinity reaction as well as clinically relevant biomolecules such as cardiac and cancer biomarkers.
It is well known that the degradation environment can strongly influence the biodegradability and kinetics of biodegradation processes of polymers. Therefore, besides the monitoring of the degradation process, it is also necessary to control the medium in which the degradation takes place. In this work, a micromachined multi-parameter sensor chip for the control of the polymer-degradation medium has been developed. The chip combines a capacitive field-effect pH sensor, a four-electrode electrolyte-conductivity sensor and a thin-film Pt-temperature sensor. The results of characterization of individual sensors are presented. In addition, the multi-parameter sensor chip together with an impedimetric polymer-degradation sensor was simultaneously characterized in degradation solutions with different pH and electrolyte conductivity. The obtained results demonstrate the feasibility of the multi-parameter sensor chip for the control of the polymer-degradation medium.
Planar and three-dimensional (3D) interdigitated electrodes (IDE) with electrode digits separated by an insulating barrier of different heights were electrochemically characterized and compared in terms of their sensing properties. Due to the impact of the surface resistance, both types of IDE structures display a non-linear behavior in low-ionic strength solutions. The experimental data were fitted to an electrical equivalent circuit and interpreted taking into account the surface-charge-governed properties. The effect of a charged polyelectrolyte layer electrostatically assembled onto the sensor surface on the surface resistance in solutions with different KCl concentration is studied. In case of the same electrode footprint, 3D-IDEs show a larger cell constant and a higher sensitivity to molecular adsorption than that of planar IDEs. The obtained results demonstrate the potential of 3D-IDEs as a new transducer structure for a direct label-free sensing of charged molecules.
An enzyme system organized in a flow device was used to mimic a reversible Controlled NOT (CNOT) gate with two input and two output signals. Reversible conversion of NAD⁺ and NADH cofactors was used to perform a XOR logic operation, while biocatalytic hydrolysis of p-nitrophenyl phosphate resulted in an Identity operation working in parallel. The first biomolecular realization of a CNOT gate is promising for integration into complex biomolecular networks and future biosensor/biomedical applications.
High-k perovskite oxide of barium strontium titanate (BST) represents a very attractive multi-functional transducer material for the development of (bio-)chemical sensors for liquids. In this work, BST films have been applied as a sensitive transducer material for a label-free detection of adsorbed charged macromolecules (positively charged polyelectrolytes) and concentration of hydrogen peroxide vapor as well as protection insulator layer for a contactless electrolyte-conductivity sensor. The experimental results of characterization of individual sensors are presented. Special emphasis is devoted towards the development of a capacitively-coupled contactless electrolyte-conductivity sensor.
It is well known that biochemical and biotechnological processes are strongly dependent and affected by a variety of physico-chemical parameters such as pH value, temperature, pressure and electrolyte conductivity. Therefore, these quantities have to be monitored or controlled in order to guarantee a stable process operation, optimization and high yield. In this work, a sensor chip for the multiparameter detection of three physico-chemical parameters such as electrolyte conductivity, pH and temperature is realized using barium strontium titanate (BST) as multipurpose material. The chip integrates a capacitively coupled four-electrode electrolyte-conductivity sensor, a capacitive field-effect pH sensor and a thin-film Pt-temperature sensor. Due to the multifunctional properties of BST, it is utilized as final outermost coating layer of the processed sensor chip and serves as passivation and protection layer as well as pH-sensitive transducer material at the same time. The results of testing of the individual sensors of the developed multiparameter sensor chip are presented. In addition, a quasi-simultaneous multiparameter characterization of the sensor chip in buffer solutions with different pH value and electrolyte conductivity is performed. To study the sensor behavior and the suitability of BST as multifunctional material under harsh environmental conditions, the sensor chip was exemplarily tested in a biogas digestate.
A multi-spot (4 × 4 spots) light-addressable potentiometric sensor (MLAPS) consisting of an Al–p-Si–SiO2 structure has been applied for the label-free electrical detection of DNA (deoxyribonucleic acid) immobilization and hybridization by the intrinsic molecular charge for the first time. Single-stranded probe ssDNA molecules (20 bases) were covalently immobilized onto the silanized SiO2 gate surface. The unspecific adsorption of mismatch ssDNA on the MLAPS gate surface was blocked by bovine serum albumin molecules. To reduce the screening effect and to achieve a high sensor signal, the measurements were performed in a low ionic-strength solution. The photocurrent–voltage (I–V) curves were simultaneously recorded on all 16 spots after each surface functionalization step. Large shifts of I–V curves of 25 mV were registered after the DNA immobilization and hybridization event. In contrast, a small potential shift (∼5 mV) was observed in case of mismatch ssDNA, revealing good specificity of the sensor. The obtained results demonstrate the potential of the MLAPS as promising transducer platform for the multi-spot label-free electrical detection of DNA molecules by their intrinsic molecular charge.