Zeitschriftenreferate

European Journal of Wood and Wood Products -     

Measuring and mitigating inhibition during quantitative real time PCR analysis of viral nucleic acid extracts from large-volume environmental water samples

Naturally-occurring inhibitory compounds are a major concern during qPCR and RT-qPCR analysis of environmental samples, particularly large volume water samples. Here, a standardized method for measuring and mitigating sample inhibition in environmental water concentrates is described. Specifically, the method 1) employs a commercially available standard RNA control; 2) defines inhibition by the change in the quantification cycle (C_q) of the standard RNA control when added to the sample concentrate; and 3) calculates a dilution factor using a mathematical formula applied to the change in C_q to indicate the specific volume of nuclease-free water necessary to dilute the effect of inhibitors. The standardized inhibition method was applied to 3,193 large-volume water (surface, groundwater, drinking water, agricultural runoff, sewage) concentrates of which 1,074 (34%) were inhibited. Inhibition level was not related to sample volume. Samples collected from the same locations over a one to two year period had widely variable inhibition levels. The proportion of samples that could have been reported as false negatives if inhibition had not been mitigated was between 0.3% and 71%, depending on water source. These findings emphasize the importance of measuring and mitigating inhibition when reporting qPCR results for viral pathogens in environmental waters to minimize the likelihood of reporting false negatives and under-quantifying virus concentration.     

Deep learning for photoacoustic tomography from sparse data

The development of fast and accurate image reconstruction algorithms is a central aspect of computed tomography. In this paper, we investigate this issue for the sparse data problem in photoacoustic tomography (PAT). We develop a direct and highly efficient reconstruction algorithm based on deep learning. In our approach, image reconstruction is performed with a deep convolutional neural network (CNN), whose weights are adjusted prior to the actual image reconstruction based on a set of training data. The proposed reconstruction approach can be interpreted as a network that uses the PAT filtered backprojection algorithm for the first layer, followed by the U-net architecture for the remaining layers. Actual image reconstruction with deep learning consists in one evaluation of the trained CNN, which does not require time-consuming solution of the forward and adjoint problems. At the same time, our numerical results demonstrate that the proposed deep learning approach reconstructs images with a quality comparable to state of the art iterative approaches for PAT from sparse data.     

Studying the role of vision in cycling: Critique on restricting research to fixation behaviour

In a recent study published in Accident Analysis & Prevention, Vansteenkiste et al. (2013) – as one of the first in this field – investigated the visual control of bicycle steering. They undertook the interesting task of testing cyclists’ eye fixation behaviour against Donges’ two-level model of steering, i.e. the guidance level to anticipate alternations in the course of the road and the stabilization level for lane keeping. Although the laboratory experiment itself is well conducted, we believe that its results cannot be used to test the two-level model of steering as developed for driving. The test track was only 15 m long, was completely straight and was known in advance. Accordingly, it did not provide adequate conditions for testing the guidance level. Furthermore, as the experimental lanes were much narrower than real-world cycling lanes, the stabilization level differed considerably from that in the real world. The study by Vansteenkiste et al. (2013) may provide valuable insight into the role of vision in ‘precision steering’, but, as we discuss in the paper, more elaborate research paradigms are needed to achieve more comprehensive knowledge of the role of vision in real-world cycling and cycling safety.     

Vacuum Insulation Panels – Exciting Thermal Properties and Most Challenging Applications

Vacuum insulation panels (VIPs) have a thermal resistance that is about a factor of 10 higher than that of equally thick conventional polystyrene boards. VIPs nowadays mostly consist of a load-bearing kernel of fumed silica. The kernel is evacuated to below 1 mbar and sealed in a high- barrier laminate, which consists of several layers of Al-coated polyethylene (PE) or polyethylene terephthalate (PET). The laminate is optimized for extremely low leakage rates for air and moisture and thus for a long service life, which is required especially for building applications. The evacuated kernel has a thermal conductivity of about 4 × 10⁻³ W · m⁻¹ · K⁻¹ at room temperature, which results mainly from solid thermal conduction along the tenuous silica backbone. A U-value of 0.2 W · m⁻² · K⁻¹ results from a thickness of 2 cm. Thus slim, yet highly insulating fa?ade constructions can be realized. As the kernel has nano-size pores, the gaseous thermal conductivity becomes noticeable only for pressures above 10 mbar. Only above 100 mbar the thermal conductivity doubles to about 8 × 10⁻³ W · m⁻¹ · K⁻¹, such a pressure could occur after several decades of usage in a middle European climate. These investigations revealed that the pressure increase is due to water vapor permeating the laminate itself, and to N₂ and O₂, which tend to penetrate the VIP via the sealed edges. An extremely important innovation is the integration of a thermo-sensor into the VIP to nondestructively measure the thermal performance in situ. A successful “self-trial” was the integration of about 100 hand-made VIPs into the new ZAE-building in Würzburg. Afterwards, several other buildings were super-insulated using VIPs within a large joint R&D project initiated and coordinated by ZAE Bayern and funded by the Bavarian Ministry of Economics in Munich. These VIPs were manufactured commercially and integrated into floorings, the gable fa?ade of an old building under protection, the roof and the facades of a terraced house as well as into an ultra-low-energy “passive house” and the slim balustrade of a hospital. The thermal reliability of these constructions was monitored using an infrared camera.Invited paper presented at the Seventh European Conference on Thermophysical Properties, September 5-8, 2005, Bratislava, Slovak Republic.     

Zeolitic materials with hierarchical porous structures

During the past several years, different kinds of hierarchical structured zeolitic materials have been synthesized due to their highly attractive properties, such as superior mass/heat transfer characteristics, lower restriction of the diffusion of reactants in the mesopores, and low pressure drop. Our contribution provides general information regarding types and preparation methods of hierarchical zeolitic materials and their relative advantages and disadvantages. Thereafter, recent advances in the preparation and characterization of hierarchical zeolitic structures within the crystallites by post-synthetic treatment methods, such as dealumination or desilication; and structured devices by in situ and ex situ zeolite coatings on open-cellular ceramic foams as (non-reactive as well as reactive) supports are highlighted. Specific advantages of using hierarchical zeolitic catalysts/structures in selected catalytic reactions, such as benzene to phenol (BTOP) and methanol to olefins (MTO) are presented.     

MR imaging and localized proton MR spectroscopy in late infantile neuronal ceroid lipofuscinosis

PURPOSE: Late juvenile neuronal ceroid lipofuscinosis (NCL) is a lysosomal neurodegenerative disorder caused by the accumulation of lipopigment in neurons. Our purpose was to characterize the MR imaging and spectroscopic findings in three children with late infantile NCL. METHODS: Three children with late infantile NCL and three age-matched control subjects were examined by MR imaging and by localized MR spectroscopy using echo times of 135 and 5. Normalized peak integral values were calculated for N-acetylaspartate (NAA), choline, creatine, myo-inositol, and glutamate/glutamine. RESULTS: MR imaging revealed volume loss of the CNS, most prominently in the cerebellum. The T2-weighted images showed a hypointense thalamus and hyperintense periventricular white matter. Proton MR spectra revealed progressive changes, with a reduction of NAA and an increase of myo-inositol and glutamate/glutamine. In long-standing late infantile NCL, myo-inositol became the most prominent resonance. Lactate was not detectable. CONCLUSION: MR imaging in combination with proton MR spectroscopy can facilitate the diagnosis of late infantile NCL and help to differentiate NCL from other neurometabolic disorders, such as mitochondrial or peroxisomal encephalopathies.