Pectic Galactan Polysaccharide-Based Gene Delivery System for Targeting Neuroinflammation

Treating neuroinflammation-related injuries and disorders through manipulation of neuroinflammation functions is being heralded as a new therapeutic strategy. In this study, a novel pectic galactan (PG) polysaccharide based gene therapy approach is developed for targeting reactive gliosis in neuroinflammation. Galectin-3 (Gal-3) is a cell protein with a high affinity to β-galactoside sugars and is highly expressed in reactive gliosis. Since PG carries galactans, it can target reactive gliosis via specific carbohydrate interaction between galactan and Gal-3 on the cell membrane, and therefore can be utilized as a carrier for delivering genes to these cells. The carrier is synthesized by modifying quaternary ammonium groups on the PG. The resulting quaternized PG (QPG) is found to form complexes with plasmid DNA with a mean diameter of 100 nm and have the characteristics required for targeted gene therapy. The complexes efficiently condense large amounts of plasmid per particle and successfully bind to Gal-3. The in vivo study shows that the complexes are biocompatible and safe for administration and can selectively transfect reactive glial cells of an induced cortical lesion. The results confirm that this PG-based delivery system is a promising platform for targeting Gal-3 overexpressing neuroinflammation cells for treating neuroinflammation-related injuries and neurodegenerative diseases.     

Longitudinal permeability determination of dual-scale fibrous materials

In this work, the longitudinal permeability of squarely packed dual-scale fiber preforms is studied theoretically. These fiber preforms are composed of aligned porous tows and the tows are tightly packed. The effective permeability is calculated as a parallel-like network of intra-tow permeability and inter-tow permeability, which are quantified by Darcy’s law and the inscribed radius between tows, respectively. The jump velocity at the interface between inter-tow fluids and porous tows is considered, as derived by substituting Beavers and Joseph’s correlation into Brinkman’s equation. We further examine the effects of intra-tow permeability on the effective permeability of the fibrous system with three interface conditions: (1) interface velocity = 0, (2) interface velocity = mean intra-tow velocity, and (3) interface velocity = jump velocity. The jump-velocity-based model is found to be closest to numerical data. The influence of the fiber volume fraction of tows on the effective permeability is also analyzed.     

Iron(II) Sulfate(VI) from Titania Production as a Raw Material for Preparation of Hydrogen Sulfide Sorbents

A hybrid sorbent material for removal of hydrogen sulfide from air was developed. The material is based on activated carbon and iron compounds obtained from waste iron(II) sulfate(VI) heptahydrate. The iron salt is deposited on the carbonaceous support and subjected to oxidation (Fe²⁺ to Fe³⁺) using atmospheric oxygen under alkaline conditions. An effect of H₂O₂ addition to the process on the composition of the resultant material was also examined. X-ray diffraction (XRD) analyses confirmed easy conversion of waste FeSO₄·7H₂O to iron oxides Fe₃O₄ and FeOOH. The activated carbon supporting iron oxides revealed a higher efficiency in H₂S elimination from air compared to the commercial activated carbon, without any modification.     

{X,Y}-Cyclacene Graphs with Next Nearest Neighbor Interactions

Eigensolutions of {X( = C,B,N),Y( = C,B,N)}-cyclacene graphs with next nearest neighbor (nnn) interactions have been obtained in analytical forms by adapting n-fold rotational symmetry followed by two-fold rotational symmetry (or a plane of symmetry). Expressions of eigensolution indicate the subspectral relationship among such cyclacenes with an even number of hexagonal rings e.g., eigenvalues of {X,Y}-di-cyclacene are found in the eigenspectra of all such even cyclacenes. Total π-electron energies and highest occupied molecular orbital and lowest unoccupied molecular orbital (HOMO–LUMO) gaps are calculated using the analytical expressions obtained and are found to vary negligibly with the variation of nnn interactions in such cyclacenes. Total π-electron energy is found to increase due to increase in restriction intensity of nnn interactions, whereas the HOMO–LUMO gap of polyacenecs having the even number of hexagonal rings and with one electron at each site (atom) decreases with increase in the restriction intensity since such systems contain degenerate half-filled HOMO (bonding or nonbonding) that are much more vulnerable for perturbations imposed through nnn interactions.     

Effect of apple cider vinegar agent on the microstructure,phase evolution,and magnetic properties of CoFe2O4 magnetic nanoparticles

In the present study, spinel structure CoFe₂O₄ nanoparticles were successfully synthesized by the sol-gel auto-combustion technique. The effect of apple cider vinegar (ACV) addition as an organic biocompatible agent on the size, morphology, and magnetic properties of CoFe₂O₄ nanoparticles was investigated in detail. The phase evolution, particle size, and lattice parameter changes of the synthesized phase have been estimated by using Rietveld structure refinement analysis of X-ray powder diffraction data. Also, Fourier transform infrared spectra (FT-IR) of the samples verified the presence of two expected bands correspond to tetrahedral and octahedral metal-oxygen complexes within the spinel structure. Furthermore, microstructural observations revealed that ultrafine particles have a semi-spherical morphology. It was shown that the particles size decreased from ~45 to ~17 nm with an increase in the amount of ACV. Magnetic properties were carried out by vibrating sample magnetometer (VSM) at room temperature. Both the saturation magnetization (M_s) and coercivity (H_c) were found to be significantly dependent on the crystallite size and the amount of ACV.     

Surveying of Na2O3–BaO–PbO–Nb2O5–SiO2–Al2O3 glass-ceramics system in terms of alpha,proton, neutron and gamma protection features by utilizing GEANT4 simulation codes

In this study, nuclear shielding qualities of glass-ceramics with chemical composition Na₂O₃–BaO–PbO–Nb₂O₅–SiO₂–Al₂O₃ containing different amount of BaO and PbO were investigated. The μ_ρ values were simulated using GEANT4 toolkit at 0.015–20 MeV wide energy range and the obtained results were verified by theoretical WinXCOM results. The variables such as μ_ρ, HVL, MFP, Z_eff, N_eff, EBF and EABF were computed to determine the gamma-ray shielding performances of studied glass ceramics. The results revealed that increase in PBO and BaO percentages in glass samples has caused to decrease the HVL, MFP, EBF and EABF values and increase μ_ρ, Z_eff values. It has been seen that N28 and S24 samples own superior protection ability against gamma radiation. In addition, the shielding capacity of these glass ceramics against charged and uncharged particles were predicted by determination of MSP and PR values for alpha, proton and ΣR values for neutrons. It has been concluded that PbO and BaO addition improve radiation shielding competences of glass ceramics. The data obtained from this study will be beneficial for designing glass ceramics shields for radiation protection enforcements.     

大规模多状态计算系统的容错性能分析

针对异构计算节点组成的大规模多状态计算系统的容错性能分析问题，提出了一种计算系统容错性能的评估方法。该方法采用自定义的两级容错性能形式化描述框架进行系统描述，通过构造多值决策图（Multi-value Decision Diagram，MDD）模型对系统进行容错性能建模，并基于构造的模型高效地计算出部件故障的条件下计算系统在特定性能水平上运行的概率，减少了计算的冗余性。实验结果表明，该方法在模型的大小和构建时间上均优于传统方法。该方法的提出将对系统操作员或程序设计者具有重要意义，使其确保系统适合预期应用。     

Flexible Distribution-Based Regression Models for Count Data: Application to Medical Diagnosis

Abstract

Data mining techniques have been successfully utilized in different applications of significant fields, including medical research. With the wealth of data available within the health-care systems, there is a lack of practical analysis tools to discover hidden relationships and trends in data. The complexity of medical data that is unfavorable for most models is a considerable challenge in prediction. The ability of a model to perform accurately and efficiently in disease diagnosis is extremely significant. Thus, the model must be selected to fit the data better, such that the learning from previous data is most efficient, and the diagnosis of the disease is highly accurate. This work is motivated by the limited number of regression analysis tools for multivariate counts in the literature. We propose two regression models for count data based on flexible distributions, namely, the multinomial Beta-Liouville and multinomial scaled Dirichlet, and evaluated the proposed models in the problem of disease diagnosis. The performance is evaluated based on the accuracy of the prediction which depends on the nature and complexity of the dataset. Our results show the efficiency of the two proposed regression models where the prediction performance of both models is competitive to other previously used regression models for count data and to the best results in the literature.