Engraftment of Prevascularized,Tissue Engineered Constructs in a Novel Rabbit Segmental Bone Defect Model

The gold standard treatment of large segmental bone defects is autologous bone transfer, which suffers from low availability and additional morbidity. Tissue engineered bone able to engraft orthotopically and a suitable animal model for pre-clinical testing are direly needed. This study aimed to evaluate engraftment of tissue-engineered bone with different prevascularization strategies in a novel segmental defect model in the rabbit humerus. Decellularized bone matrix (Tutobone) seeded with bone marrow mesenchymal stromal cells was used directly orthotopically or combined with a vessel and inserted immediately (1-step) or only after six weeks of subcutaneous “incubation” (2-step). After 12 weeks, histological and radiological assessment was performed. Variable callus formation was observed. No bone formation or remodeling of the graft through TRAP positive osteoclasts could be detected. Instead, a variable amount of necrotic tissue formed. Although necrotic area correlated significantly with amount of vessels and the 2-step strategy had significantly more vessels than the 1-step strategy, no significant reduction of necrotic area was found. In conclusion, the animal model developed here represents a highly challenging situation, for which a suitable engineered bone graft with better prevascularization, better resorbability and higher osteogenicity has yet to be developed.     

Allele-Specific Inhibition of Histone Demethylases

Histone demethylases play a critical role in mammalian gene expression by removing methyl groups from lysine residues in degree- and site-specific manner. To specifically interrogate members and isoforms of this class of enzymes, we have developed demethylase variants with an expanded active site. The mutant enzymes are capable of performing lysine demethylation with wild-type proficiency, but are sensitive to inhibition by cofactor-competitive molecules embellished with a complementary steric “bump”. The selected inhibitors show more than 20-fold selectivity over the wild-type demethylase, thus overcoming issues typical to pharmacological and genetic approaches. The mutant–inhibitor pairs are shown to act on a physiologically relevant full-length substrate. By engineering a conserved amino acid to achieve member-specific perturbation, this study provides a general approach for studying histone demethylases in diverse cellular processes.     

A two-dimensional material for high capacity supercapacitors: S-doped graphene

In this work, sulfur-doped graphene-coated electrodes are prepared by cyclic voltammetry in different potential ranges and different cycles (from 10 to 50) for selective modification of electrodes by different functional groups. The prepared electrodes are characterized by spectroscopic, microscopic and electrochemical methods. In scanning electron microscopic analysis, formation of graphene layers and their porous structure have been determined. Electrochemical impedance spectroscopic and cyclic voltammetric analyses are also used in electrochemical characterization of the electrodes. Then, the prepared sulfur-doped graphene-coated electrodes by using cyclic voltammetry in one-step and low cost are used as electrode materials of supercapacitor for the first time in the literature. Since the mesoporous structure of the electrodes prepared in lower potential ranges increases, specific capacitance of the electrodes increases from 74 to 1833 mF cm⁻² with 10 mA cm⁻² current density. This result shows that specific capacitances of prepared electrodes are higher than those of the electrodes prepared with metal-doped in the literature.     

Cancer‐Targeting Graphene Quantum Dots: Fluorescence Quantum Yields,Stability, and Cell Selectivity

Folic acid, due to its high affinity toward folate receptors (FR), is recognized as one of the most promising cancer targeting vectors. However, the inherent defects of low water solubility (1.6 µg mL^?1), high sensitivity toward photo‐bleaching, low fluorescent quantum yields (QYs, <0.5%) seriously limit its practical application. Herein, ultrastable, highly luminescent graphene quantum dots (GQDs) that selectively target diverse cancer cells are prepared and tested. The new GQDs present step changes compared to common folic acid through an ≈6250 times increase in water solubility (to ≈10 mg mL^?1), more than 150 times in QYs (up to ≈77%), while maintaining luminescence stability up to 98% when subjected to UV, visible light, and heating over 360 min. It is shown that the suppression of nonradiative transitions by amino groups pyrolyzed from pterin plays a key role in the mechanism of high QYs and excellent stability. The functional groups that are likely responsible for the selective targeting of cancer cells with different levels of folate receptor expression on the surface are identified. Collectively with these promising properties, the new functional graphene quantum dots may open a new avenue for cancer diagnosis, drug delivery, and therapies.     

Nanocrystalline CoCrFeNiMn high-entropy alloy with tunable ferromagnetic properties

A nanocrystalline CoCrFeNiMn high-entropy alloy(nc-HEA)with nano-multiphase structure was pre-pared by inert gas condensation(IGC)using a laser evaporation source.Encouragingly,the laser-IGC nc-HEA exhibits unexpected ferromagnetic behavior and the Curie temperature(Tc)increased nearly 10 times compared to any CoCrFeNiMn HEAs prepared by various other methods.In addition,the saturation magnetization(Ms)and Tc of the laser-IGC nc-HEA can be controlled via heat treatment,which is result-ing from the formation and structural evolution of magnetic nanophases during annealing.This work widens the design toolbox for high-performance nc-HEAs based upon laser-IGC technique.     

Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model

The design and sustainability of reinforced concrete deep beam are still the main issues in the sector of structural engineering despite the existence of modern advancements in this area. Proper understanding of shear stress characteristics can assist in providing safer design and prevent failure in deep beams which consequently lead to saving lives and properties. In this investigation, a new intelligent model depending on the hybridization of support vector regression with bio-inspired optimization approach called genetic algorithm (SVR-GA) is employed to predict the shear strength of reinforced concrete (RC) deep beams based on dimensional, mechanical and material parameters properties. The adopted SVR-GA modelling approach is validated against three different well established artificial intelligent (AI) models, including classical SVR, artificial neural network (ANN) and gradient boosted decision trees (GBDTs). The comparison assessments provide a clear impression of the superior capability of the proposed SVR-GA model in the prediction of shear strength capability of simply supported deep beams. The simulated results gained by SVR-GA model are very close to the experimental ones. In quantitative results, the coefficient of determination (R²) during the testing phase (R² = 0.95), whereas the other comparable models generated relatively lower values of R² ranging from 0.884 to 0.941. All in all, the proposed SVR-GA model showed an applicable and robust computer aid technology for modelling RC deep beam shear strength that contributes to the base knowledge of material and structural engineering perspective.

     

Improving of Wavelength Division Multiplexing Based on Free Space Optical Communication via Power Comparative System

Wireless Personal Communications - The names of the second and third authors in the initial online publication were not correctly typeset. The original article has been corrected.     

Study on optimization of the circumferential and axial wavy geometrical configuration of hydrodynamic journal bearing

This paper is focused on using GA genetic algorithm to find the optimal performance with respect to shape optimization in three dimensions for the hydrodynamic journal bearing. The mathematical model for film thickness was drawn using Fourier series function and axial waviness value ( $\bar \Delta $ ) D to represent the journal bearing in circumferential and axial direction, respectively. The objective was then to determine the Fourier coefficients and axial waviness value ( $\bar \Delta $ ) D that maximized the load capacity subjected to a given set of constraint. Optimized results show that the presence of cos wave in axial direction, with a positive dimensionless amplitude (+A) and waviness number m = 0.633, improves the load capacity by (8–10) % over the cylindrical plain bearing with the same arbitrary shape and size; in general, the increasing order of Fourier series (n), an axial dimensionless amplitude and L/D ratio cause the change in load capacity to become more evident.     

Mannose based polymeric nanoparticles for lectin separation

The aim of this work is to synthesize the original, new polymeric nanoparticles for concanavalin A (Con A) purification. Nanoparticles were synthesized by surfactant free emulsion polymerization. In the polymerization prosedure, 1-O-(2′-hydroxy-3′-acryloyloxypropyl)-2,3:5,6-di-O-isopropylidene-α-D-mannofuranose (Man-OPA) was used as co-monomer and 2-hydroxyethylmethacrylate (HEMA) was used as a monomer. Man-OPA was characterized by Fourier Transform Infrared Spectroscopy (FTIR), nuclear magnetic resonance and elemental analysis techniques. Poly(HEMA-Man-OPA) nanoparticles were characterized by scanning electron microscopy, FTIR and Zeta Sizer. In adsorption?desorption experiments, maximum Con A adsorption capacity of poly(HEMA-Man-OPA) nanoparticles was found 630.6 mg/g nanoparticle (pH 7.5, 1.0 mg/mL). Adsorption?desorption experiments were repeated in four times. According to results, these nanoparticles could be used several times without significant decrease in Con A adsorption capacity.