Traveling Waves in Spatial SIRS Models

We study traveling wavefront solutions for two reaction–diffusion systems, which are derived respectively as diffusion approximations to two nonlocal spatial SIRS models. These solutions characterize the propagating progress and speed of the spatial spread of underlying epidemic waves. For the first diffusion system, we find a lower bound for wave speeds and prove that the traveling waves exist for all speeds bigger than this bound. For the second diffusion system, we find the minimal wave speed and show that the traveling waves exist for all speeds bigger than or equal to the minimal speed. We further prove the uniqueness (up to translation) of these solutions for sufficiently large wave speeds. The existence of these solutions are proved by a shooting argument combining with LaSalle’s invariance principle, and their uniqueness by a geometric singular perturbation argument.     

Swelling and Network Parameters of 1-Hexadecene-Co-Trimethylolpropane Distearate Monoacrylate Sorbers

Linear and crosslinked copolymers with different compositions of 1-hexadecene and trimethylolpropane distearate monoacrylate monomers were synthesized and evaluated for oil-absorbency application. Different concentrations of ethylene glycol diacrylate (EGDA) and ethylene glycol dimethacrylate (EGDMA) crosslinkers were used. The concentration of both crosslinkers was varied from 0.5% to 2%. Copolymer compositions were determined from ¹H NMR spectroscopy. Monomer reactivity ratios were calculated using Fineman-Ross and Kelen-Tudos techniques at low conversions. The oil absorbency and swelling rate constant were measured and influenced mainly by the degree of crosslinking and the hydrophobicity of copolymer units. The final equilibrium oil content, volume fraction of polymer and swelling capacity were determined at 298 K. The effective crosslinking density V_e, theoretical crosslink density V_t, the average molecular weight between the crosslinks M_c and the polymer-toluene interaction parameter χ were determined from swelling measurements. The efficiencies of EGDA and EGDMA crosslinking agents toward copolymers were determined.     

Identification of ligands that target the HCV-E2 binding site on CD81

Hepatitis C is a global health problem. While many drug companies have active R&D efforts to develop new drugs for treating Hepatitis C virus (HCV), most target the viral enzymes. The HCV glycoprotein E2 has been shown to play an essential role in hepatocyte invasion by binding to CD81 and other cell surface receptors. This paper describes the use of AutoDock to identify ligand binding sites on the large extracellular loop of the open conformation of CD81 and to perform virtual screening runs to identify sets of small molecule ligands predicted to bind to two of these sites. The best sites selected by AutoLigand were located in regions identified by mutational studies to be the site of E2 binding. Thirty-six ligands predicted by AutoDock to bind to these sites were subsequently tested experimentally to determine if they bound to CD81-LEL. Binding assays conducted using surface Plasmon resonance revealed that 26 out of 36 (72 %) of the ligands bound in vitro to the recombinant CD81-LEL protein. Competition experiments performed using dual polarization interferometry showed that one of the ligands predicted to bind to the large cleft between the C and D helices was also effective in blocking E2 binding to CD81-LEL.     

Isoshamixanthone: a new pyrano xanthone from endophytic Aspergillus sp. ASCLA and absolute configuration of epiisoshamixanthone

Abstract

Isoshamixanthone (1), a new stereoisomeric pyrano xanthone together with the previously known fungal metabolites, epiisoshamixanthone (2), sterigmatocystin (3), arugosin C (4), norlichexanthone (5), diorcinol (6), ergosterol and methyllinoleate, were obtained from the endophytic fungal strain Aspergillus sp. ASCLA isolated from leaf tissues of the medicinal plant Callistemon subulatus. The chemical structure of the new xanthone (1) was elucidated by extensive 1D, 2D NMR, and ESI HR mass measurements, and by comparison with literature data. The constitutions and absolute configurations of 1 and epiisoshamixanthone (2) were additionally confirmed by X-ray crystallography. Compounds 1,2 were evaluated for their potential anticancer activity using the human cervix carcinoma cell line (KB-3-1). The antimicrobial activities of the fungal extract and compounds 1,2 were studied using a panel of pathogenic microorganisms as well.     

A Bootstrap Framework for Aggregating within and between Feature Selection Methods

In the past decade, big data has become increasingly prevalent in a large number of applications. As a result, datasets suffering from noise and redundancy issues have necessitated the use of feature selection across multiple domains. However, a common concern in feature selection is that different approaches can give very different results when applied to similar datasets. Aggregating the results of different selection methods helps to resolve this concern and control the diversity of selected feature subsets. In this work, we implemented a general framework for the ensemble of multiple feature selection methods. Based on diversified datasets generated from the original set of observations, we aggregated the importance scores generated by multiple feature selection techniques using two methods: the Within Aggregation Method (WAM), which refers to aggregating importance scores within a single feature selection; and the Between Aggregation Method (BAM), which refers to aggregating importance scores between multiple feature selection methods. We applied the proposed framework on 13 real datasets with diverse performances and characteristics. The experimental evaluation showed that WAM provides an effective tool for determining the best feature selection method for a given dataset. WAM has also shown greater stability than BAM in terms of identifying important features. The computational demands of the two methods appeared to be comparable. The results of this work suggest that by applying both WAM and BAM, practitioners can gain a deeper understanding of the feature selection process.     

Synthesis of Plasmonic Group‐4 Nitride Nanocrystals by Solid‐State Metathesis

Ceramic nanoparticles that exhibit a plasmonic response are promising next‐generation photonic materials. In this contribution, a solid‐state metathesis method has been reported for the synthesis of Group 4 nitride (TiN, ZrN, and HfN) nanocrystals. A high‐temperature (1000 °C) reaction between Group 4 metal oxide (TiO₂, ZrO₂, and HfO₂) nanoparticles and magnesium nitride powder yielded nitride nanocrystals that were dispersible in water. A localized surface plasmonic resonance was observed in the near‐infrared region for TiN and in the visible region of light for ZrN and HfN nanocrystals. The frequency of the plasmon resonance was dependent on the refractive index of the solvent and the nanocrystal size.     

Revealing the unexpected promotion effect of EuOx on Pt/CeO2 catalysts for catalytic combustion of toluene

Pt/Eu₂O₃-CeO₂ materials with different Eu concentrations were prepared and applied to toluene destruction, and the remarkable promotion impact of EuO_x on Pt/CeO₂ can be observed. The characterization results reveal that the presence of EuO_x significantly enhances the redox property, lattice O concentration, and Ce³⁺ ratio of the Pt/CeO₂ material, which facilitates the dispersion and activity of Pt active sites and thus accelerates the decomposition process of toluene. Among all catalysts, a sample with an Eu content of 2.5 at.% (Pt/EC-2.5) possesses the best catalytic activity with 0.09 vol% of toluene completely destructed at 200 °C under a relatively high GHSV of 50000 h^?1. The possible reaction pathway and mechanism of toluene combustion over Pt/Eu₂O₃-CeO₂ samples are presented according to in-situ DRIFTS, which confirms that the toluene oxidation process obeys the Mars-van Krevelen mechanism with aldehydes and ketones as primary organic intermediates.     

Platelet-12 lipoxygenase targeting via a newly synthesized curcumin derivative radiolabeled with technetium-99m

Background

One of the most popular techniques for cancer detection is the nuclear medicine technique. The present research focuses on Platelet-12-lipoxygenase (P-12-LOX) as a promising target for treating and radio-imaging tumor tissues. Curcumin was reported to inhibit this enzyme via binding to its active site.

Results

A novel curcumin derivative was successfully synthesized and characterized with yield of 74%. It was radiolabeled with the diagnostic radioisotope technetium-99m with 84% radiochemical yield and in vitro stability up to 6 h. The biodistribution studies in tumor bearing mice confirmed the high affinity predicted by the docking results with a free binding energy value of (ΔG ?50.10 kcal/mol) and affinity (13.64 pki) showing high accumulation in solid tumor with target/non-target ratio >6.

Conclusion

The newly synthesized curcumin derivative, as a result of a computational study on platelet-12 lipoxygenase, showed its excellent free binding energy (?G ?50.10 kcal/mol) and high affinity (13.64 pKi). It could be an excellent radio-imaging agent that targeting tumor cells via targeting of P-12-LOX.

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Graphical abstract This novel curcumin derivative was successfully synthesized and radiolabeled with technetium-99m and biologically evaluated in tumor bearing mice that showed high accumulation in solid tumor with target/non-target ratio >6 confirming the affinity predicted by the docking results. Predicted binding mode of a new curcumin derivative in complex with 12-LOX active site. b Curcumin itself in the 12-LOX active site biological distribution of ^99mTc-curcumin derivative complex in solid tumor bearing Albino mice

     

Overview of Synthetic Methods to Prepare Plasmonic Transition-Metal Nitride Nanoparticles

The search for new plasmonic materials that are low-cost, chemically and thermally stable, and exhibit low optical losses has garnered significant attention among researchers. Recently, metal nitrides have emerged as promising alternatives to conventional, noble-metal-based plasmonic materials, such as silver and gold. Many of the initial studies on metal nitrides have focused on computational prediction of the plasmonic properties of these materials. In recent years, several synthetic methods have been developed to enable empirical analysis. This review highlights synthetic techniques for the preparation of plasmonic metal nitride nanoparticles, which are predominantly free-standing, by using solid-state and solid–gas phase reactions, nonthermal and arc plasma methods, and laser ablation. The physical properties of the nanoparticles, such as shape, size, crystallinity, and optical response, obtained with such synthetic methods are also summarized.