Pertussis Toxin Inhibits Encephalitogenic T-Cell Infiltration and Promotes a B-Cell-Driven Disease during Th17-EAE

Pertussis toxin (PTX) is a required co-adjuvant for experimental autoimmune encephalomyelitis (EAE) induced by immunization with myelin antigen. However, PTX’s effects on EAE induced by the transfer of myelin-specific T helper cells is not known. Therefore, we investigated how PTX affects the Th17 transfer EAE model (Th17-EAE). We found that PTX significantly reduced Th17-EAE by inhibiting chemokine-receptor-dependent trafficking of Th17 cells. Strikingly, PTX also promoted the accumulation of B cells in the CNS, suggesting that PTX alters the disease toward a B-cell-dependent pathology. To determine the role of B cells, we compared the effects of PTX on Th17-EAE in wild-type (WT) and B-cell-deficient (µMT) mice. Without PTX treatment, disease severity was equivalent between WT and µMT mice. In contrast, with PTX treatment, the µMT mice had significantly less disease and a reduction in pathogenic Th17 cells in the CNS compared to the WT mice. In conclusion, this study shows that PTX inhibits the migration of pathogenic Th17 cells, while promoting the accumulation of pathogenic B cells in the CNS during Th17-EAE. These data provide useful methodological information for adoptive-transfer Th17-EAE and, furthermore, describe another important experimental system to study the pathogenic mechanisms of B cells in multiple sclerosis.     

Effect of the Curvature of a Spherical Flame on Its Speed: Comparison of Two Approaches

Combustion, Explosion, and Shock Waves - Two approaches to describing an expanding spherical flame are compared. Processing of a large amount of experimental data shows that the approach using as a...     

Revamping SiO2 Spheres by Core–Shell Porosity Endowment to Construct a Mazelike Nanoreactor for Enhanced Catalysis in CO2 Hydrogenation to Methanol

Beyond the catalytic activity of nanocatalysts, the support with architectural design and explicit boundary could also promote the overall performance through improving the diffusion process, highlighting additional support for the morphology-dependent activity. To delineate this, herein, a novel mazelike-reactor framework, namely multi-voids mesoporous silica sphere (MVmSiO₂), is carved through a top-down approach by endowing core-shell porosity premade Stöber SiO₂ spheres. The precisely-engineered MVmSiO₂ with peripheral one-dimensional pores in the shell and interconnecting compartmented voids in the core region is simulated to prove combined hierarchical and structural superiority over its analogous counterparts. Supported with CuZn-based alloys, mazelike MVmSiO₂ nanoreactor experimentally demonstrated its expected workability in model gas-phase CO₂ hydrogenation reaction where enhanced CO₂ activity, good methanol yield, and more importantly, a prolonged stable performance are realized. While tuning the nanoreactor composition besides morphology optimization could further increase the catalytic performance, it is accentuated that the morphological architecture of support further boosts the reaction performance apart from comprehensive compositional optimization. In addition to the found morphological restraints and size-confinement effects imposed by MVmSiO₂, active sites of catalysts are also investigated by exploring the size difference of the confined CuZn alloy nanoparticles in CO₂ hydrogenation employing both in-situ experimental characterizations and density functional theory calculations.     

Down-link OFDRMA communications

Wireless Networks - Orthogonal frequency-division multiplexing with random multiple access (OFDRMA) is discussed for down-link communications, whereby a single base-station transmits information...     

Increasing the Efficiency of Projection Models of Strip Lines

Journal of Communications Technology and Electronics - Abstract—The matrix coefficients of projection models of strip lines obtained using the Chebyshev basis are presented as a sum of...     

UPR: deadlock-free dynamic network reconfiguration by exploiting channel dependency graph compatibility

The Journal of Supercomputing - Deadlock-free dynamic network reconfiguration process is usually studied from the routing algorithm restrictions and resource reservation perspective. The dynamic...     

The validation and further development of a multidimensional cognitive load scale for virtual environments

Measuring cognitive load is important in virtual learning environments (VLE). Thus, valid and reliable measures of cognitive load are important to support instructional design in VLE. Through three studies, we investigated the validity and reliability of Leppink's Cognitive Load Scale (CLS) and developed the extraneous cognitive load (EL) dimension into three sub-scales relevant for VLE: EL instructions, EL interaction, and EL environment. We investigated the validity of the measures using the Partial Credit Model (PCM), Confirmatory Factor Analysis (CFA), and correlations with retention tests. Study 1 (n = 73) investigated the adapted version of the CLS. Study 2 describes the development and validation of the Multidimensional Cognitive Load Scale for Virtual Environments (MCLSVE), with 140 students in higher education. Study 3 tested the generalizability of the results with 121 higher education students in a more complicated VLE. The results provide initial evidence for the validity and reliability of the MCLSVE.     

Intraprocedural Analysis Based on Symbolic Execution for Bug Detection

Programming and Computer Software - In this paper, we overview the approaches and techniques employed by the Svace static analysis tool for intraprocedural analysis. This analysis implies the...     

Implementation of periodic boundary conditions for loading of mechanical metamaterials and other complex geometric microstructures using finite element analysis

The implementation of periodic boundary conditions (PBCs) is one of the most important and difficult steps in the computational analysis of structures and materials. This is especially true in cases such as mechanical metamaterials which typically possess intricate geometries and designs which makes finding and implementing the correct PBCs a difficult challenge. In this work, we analyze one of the most common PBCs implementation technique, as well as implement and validate an alternative generic method which is suitable to simulate any possible 2D microstructural geometry with a quadrilateral unit cell regardless of symmetry and mode of deformation. A detailed schematic of how both these methods can be employed to study 3D systems is also presented.

     

ZnO–SnO2 nanocubes for fluorescence sensing and dye degradation applications

ZnO–SnO₂ nanocubes were used as promising material for efficient sensing of p-nitrophenol and faster photocatalytic degradations of dyes like methyl orange (MO), methylene Blue (MB) and acid orange 74 (AO74). ZnO–SnO₂ nanocubes were prepared by the facile solution process at 50 °C using Zn(NO₃)₂·6H₂O and SnCl₂·2H₂O as a precursor in the presence of ethylenediammine. The synthesized material was examined for its morphological, structural, crystalline, optical, vibrational, and compositional studies by using field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), Fourier Transform Infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS) and photoluminescence spectroscopy. FESEM studies revealed the formation of well-defined ZnO–SnO₂ nanocubes where the structural examinations revealed the formation of a crystalline tetragonal rutile phase for SnO₂ with some crystal sites doped with Zn. The as-synthesized nanocubes were explored for their photocatalytic activities towards three different dye viz. MO, MB, and AO74. Practically, complete degradation of AO74 was seen within 4 minutes of photo-irradiation in the presence of 0.05 g ZnO–SnO₂ nanocubes. However, 97.17% and 41.63% degradations were observed for MB and MO within 15 and 60 minutes, respectively. All the dye degradation processes followed the pseudo-first-order kinetic model. Moreover, the as-synthesized nanocubes were utilized to fabricate highly sensitive and selective fluorescent chemical sensor for the detection of p-nitrophenol (PNP). ZnO–SnO₂ nanocubes showed a very low detection limit of 4.09 μM for the detection of PNP as calculated according to the 3σ IUPAC criteria. Further, the as-synthesized ZnO–SnO₂ nanotubes were found to be highly selective for p-nitrophenol as compared to the other two isomers.