Metabolomic Evidence for Peroxisomal Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating disease characterized by unexplained physical fatigue, cognitive and sensory dysfunction, sleeping disturbances, orthostatic intolerance, and gastrointestinal problems. People with ME/CFS often report a prodrome consistent with infections. Using regression, Bayesian and enrichment analyses, we conducted targeted and untargeted metabolomic analysis of plasma from 106 ME/CFS cases and 91 frequency-matched healthy controls. Subjects in the ME/CFS group had significantly decreased levels of plasmalogens and phospholipid ethers (p < 0.001), phosphatidylcholines (p < 0.001) and sphingomyelins (p < 0.001), and elevated levels of dicarboxylic acids (p = 0.013). Using machine learning algorithms, we were able to differentiate ME/CFS or subgroups of ME/CFS from controls with area under the receiver operating characteristic curve (AUC) values up to 0.873. Our findings provide the first metabolomic evidence of peroxisomal dysfunction, and are consistent with dysregulation of lipid remodeling and the tricarboxylic acid cycle. These findings, if validated in other cohorts, could provide new insights into the pathogenesis of ME/CFS and highlight the potential use of the plasma metabolome as a source of biomarkers for the disease.     

Characterization of Biogenic Silica Generated by Thermo Chemical Treatment of Rice Husk

This study presents two routes to produce amorphous silica from an Egyptian rice husk under conditions optimized for least environmental impact and low cost. The first route includes thoroughly washing of the husk sample with water, dry milling and leaching with citric acid. The leaching process was applied in two stages, that is, at 323 K for 180 min and then at 353 K for 60 min. After washing and drying, the leached sample was subjected to a heat treatment in a muffles furnace at four sequential steps. The second route includes all the previously mentioned steps, except the citric acid leaching. The final products were characterized using x-ray fluorescence analysis, carbon content analysis, x-ray diffraction, differential thermal analysis, nitrogen adsorption, mercury intrusion, and scanning electron microscopy. The results show that the citric acid leaching has many advantages with respect to silica yield and porosity as well.     

Product properties of a two-phase magneto-electric composite: Synthesis and numerical modeling

Magneto-electric (ME) materials are of high interest for a variety of advanced applications like in data storage and sensor technology. Due to the low ME coupling in natural materials, composite structures become relevant which generate the effective ME coupling as a strain-mediated product property. In this framework, it seems to be possible to achieve effective ME coefficients that can be exploited technologically. The present contribution investigates the realization of particulate ME composites with a focus on their experimental and computational characterization. We will show that different states of pre-polarizations of the ferroelectric material have a decisive influence on the overall obtainable ME coefficient. Details on the synthesis of two-phase composite microstructures consisting of a barium titanate matrix and cobalt ferrite inclusions will be discussed. Subsequently we will employ computational homogenization in order to determine the effective properties of the experimental composite numerically. We investigate the influence of different states of pre-polarization on the resulting ME-coefficients. For the numerical incorporation of the pre-polarization we use a heuristic method.     

Quantum Confinement of Dirac Quasiparticles in Graphene Patterned with Sub-Nanometer Precision

Quantum confinement of graphene Dirac-like electrons in artificially crafted nanometer structures is a long sought goal that would provide a strategy to selectively tune the electronic properties of graphene, including bandgap opening or quantization of energy levels. However, creating confining structures with nanometer precision in shape, size, and location remains an experimental challenge, both for top-down and bottom-up approaches. Moreover, Klein tunneling, offering an escape route to graphene electrons, limits the efficiency of electrostatic confinement. Here, a scanning tunneling microscope (STM) is used to create graphene nanopatterns, with sub-nanometer precision, by the collective manipulation of a large number of H atoms. Individual graphene nanostructures are built at selected locations, with predetermined orientations and shapes, and with dimensions going all the way from 2 nm up to 1 µm. The method permits the patterns to be erased and rebuilt at will, and it can be implemented on different graphene substrates. STM experiments demonstrate that such graphene nanostructures confine very efficiently graphene Dirac quasiparticles, both in 0D and 1D structures. In graphene quantum dots, perfectly defined energy bandgaps up to 0.8 eV are found that scale as the inverse of the dot’s linear dimension, as expected for massless Dirac fermions.     

Numerical wave optical analysis of microlens array telescopes and comparison with experimental results

We present a numerical wave optical model to describe the complex behavior of coaxial and decentered microlens-array-based telescopes illuminated by an incoherent angular spectrum of plane waves. With the use of this model we have been able to observe major performance differences between Galilean and Keplerian setups, which to our knowledge were not described before. The results of the simulations are compared with experimental results; the images of multimode fiber end faces are characterized with respect to transfer efficiency and intensity distribution. The results are also explained by use of modified existing analytical models.     

A surrogate-based cooperative optimization framework for computationally expensive black-box problems

Optimization and Engineering - Most parallel surrogate-based optimization algorithms focus only on the mechanisms for generating multiple updating points in each cycle, and rather less attention...     

Infrared and carbon dioxide chemisorption study of Mo/ZrO2 catalysts

The interaction of Mo with zirconia has been investigated by infrared spectroscopy (IR) and carbon dioxide chemisorption. Quantitative analysis of the IR results indicated that Mo interacts preferentially with the most basic hydroxyl group (high frequency band at 3775 cm^–1). An approximately 79% decrease in the 3775 cm^–1 band is observed vs. 21% for the low frequency band at 3673 cm^–1, with increasing the Mo loading up to 1 wt%. The relative decrease of the IR band at 3775 cm^–1 was identical to that measured for the CO₂ uptake. The Mo cross-sections estimated from CO₂ chemisorption results were much higher than those typically reported for the Mo system. It was concluded that, as previously reported for the Mo/Al₂o₃ system, CO₂ chemisorption overestimates the surface coverage of Mo/ZrO₂ catalysts.