High-sensitivity and high-resolution low-energy ion scattering

Low-Energy Ion Scattering (LEIS or ISS) is used to selectively analyze the atomic composition of the outer atomic layer of surfaces. In addition, the spectrum gives (non-destructively) the in-depth distribution. Using a double toroidal energy analyzer with parallel energy detection and time-of-flight filtering a high sensitivity and mass resolution of LEIS is achieved. This is demonstrated for a highly dispersed catalyst of Pt/Au on γ-alumina. The improved depth resolution is illustrated for self-assembled monolayers of alkanethiols (12-20 carbon atoms) on gold. Even for these low Z carbon atoms a clear shift of 8 eV/carbon atom is observed (using 1.5 keV ⁴He⁺ ion scattering). This opens many new possibilities for studies of ultra-thin diffusion barriers, high-k dielectrics and biosensors.     

Daily dietary lithium intake in Belgium using duplicate portion sampling

 For the first time, daily dietary lithium intake for adults in Belgium has been evaluated by duplicate portion sampling, the heating of the samples in a microwave oven and atomic absorption spectrometric determination of the element. The mean intake value for adults (8.6±4.6 μg/day) is very low compared to the scarce literature data. Since the lithium requirement of humans and animals is still unknown, no comparison could be made with RDA values.     

Learning directed probabilistic logical models: ordering-search versus structure-search

We discuss how to learn non-recursive directed probabilistic logical models from relational data. This problem has been tackled before by upgrading the structure-search algorithm initially proposed for Bayesian networks. In this paper we show how to upgrade another algorithm for learning Bayesian networks, namely ordering-search. For Bayesian networks, ordering-search was found to work better than structure-search. It is non-obvious that these results carry over to the relational case, however, since there ordering-search needs to be implemented quite differently. Hence, we perform an experimental comparison of these upgraded algorithms on four relational domains. We conclude that also in the relational case ordering-search is competitive with structure-search in terms of quality of the learned models, while ordering-search is significantly faster.     

An FFT-based signal identification approach for obtaining the propagation constants of the leaky modes in layered media

We propose to find the propagation constants of modes in layered media by means of signal identification methods. To this effect we employ Cauchy's theorem, conformal mapping and Fast Fourier Transform (FFT) techniques to generate relevant Hankel moments, afterwards to be processed with selected signal identification algorithms. The method, terminated by a few Newton steps, provides a batch of highly accurate roots in appropriate disks or half-disks.     

Functionalized gold nanoparticles: a detailed in vivo multimodal microscopic brain distribution study

In the present study, the in vivo distribution of polyelectrolyte multilayer coated gold nanoparticles is shown, starting from the living animal down to cellular level. The coating was designed with functional moieties to serve as a potential nano drug for prion disease. With near infrared time-domain imaging we followed the biodistribution in mice up to 7 days after intravenous injection of the nanoparticles. The peak concentration in the head of mice was detected between 19 and 24 h. The precise particle distribution in the brain was studied ex vivo by X-ray microtomography, confocal laser and fluorescence microscopy. We found that the particles mainly accumulate in the hippocampus, thalamus, hypothalamus, and the cerebral cortex.     

On the optimum mass transfer of flat absorbing falling films

The coupled heat- and mass-transfer of the absorbing falling film is considered in the flat-film approximation. We study the influence of the operating conditions on the absorption efficiency in a fully non-dimensional framework and find an optimal Reynolds number, which can be interpreted as an optimal film thickness. We also test various thermal wall boundary conditions to select the best approximation compared to a realistic test case.     

High Versatility of IPP and DMAPP Methyltransferases Enables Synthesis of C6, C7 and C8 Terpenoid Building Blocks

The natural substance class of terpenoids covers an extremely wide range of different structures, although their building block repertoire is limited to the C₅ compounds DMAPP and IPP. This study aims at the characterization of methyltransferases (MTases) that modify these terpene precursors and the demonstration of their suitability for biotechnological purposes. All seven enzymes tested accepted IPP as substrate and altogether five C₆ compounds and six C₇ compounds were formed within the reactions. A high selectivity for the deprotonation site as well as high stereoselectivity could be observed for most of the biocatalysts. Only the enzyme from Micromonospora humi also accepted DMAPP as substrate, converting it into (2R)-2-methyl-IPP in vitro. In vivo studies demonstrated the production of a C₈ compound and a hydride shift step within the MTase-catalyzed reaction. Our study presents IPP/DMAPP MTases with very different catalytic properties, which provide biosynthetic access to many novel terpene-derived structures.     

Feasibility of glioblastoma tissue response mapping with physiologic BOLD imaging using precise oxygen and carbon dioxide challenge

Magnetic Resonance Materials in Physics, Biology and Medicine - Innovative physiologic MRI development focuses on depiction of heterogenous vascular and metabolic features in glioblastoma. For this...