Degree Of Repulsion Research Articles

In Vitro Characterization and Evaluation of Silver Nanoparticles Cytotoxicity on Human “Liver and Breast” Cancer Cells Versus Normal Melanocytes

Introduction: In the field of medicine, silver nanoparticles (Ag NPs) with their distinctive characteristics represent an interesting new cancer therapy. Cancer is a serious disease, despite the recent advances in its treatment; there are still some cases that are resistant to the current therapy.Aim of the work: This study aimed at examining the characteristics of 2 forms of silver nanomaterial (Ag NPs 1 and Ag NPs 2) and investigating their effect on breast cancer (MCF7) and liver cancer (HEP-G2) as well as on human normal melanocytes cell lines (HBF4).Materials and methods: It was found that both samples of nanoparticles have negative surface charge and their mean sizes were 9.02 nm and 24.6 nm respectively. Both Ag NPs 1 and Ag NPs 2 had a dose- dependent cytotoxicity on MCF7 and HEP-G2 with negligible effect on normal cell line (HBF4) measured by MTT assay.Results: Inhibitory Concentration 50 of Ag NPs1 and Ag NPs2 were 20.06 and 16.03 nmol/ml respectively. The resultant cell death was via apoptosis as illustrated by the inverted light microscopy. RT-PCR assessment revealed significant upregulation in Caspase 3 gene expression in the malignant cell lines exposed to each silver nanomaterials and remarkable downregulation VEGF and upregulation in TNF-α in either cancer cell line exposed to Ag NPs2 only. Meanwhile, the change in these cellular markers was minimal in normal human melanocyte cell line.Conclusion: This study indicates that silver nanoparticles can be used as anticancer agent with minimal effect on normal tissues. The cell viability depends not only on the size of Ag NPs but also their shape, surface charge and degree of repulsion between particles and aggregation.

Spatial stochastic models for analysis of heterogeneous cellular networks with repulsively deployed base stations

We consider spatial stochastic models of downlink heterogeneous cellular networks (HCNs) with multiple tiers, where the base stations (BSs) of each tier have a particular spatial density, transmission power and path-loss exponent. Prior works on such spatial models of HCNs assume, due to its tractability, that the BSs are deployed according to homogeneous Poisson point processes. This means that the BSs are located independently of each other and their spatial correlation is ignored. In the current paper, we propose two spatial models for the analysis of downlink HCNs, in which the BSs are deployed according to α-Ginibre point processes. The α-Ginibre point processes constitute a class of determinantal point processes and account for the repulsion between the BSs. Besides, the degree of repulsion is adjustable according to the value of α∈(0,1]. In one proposed model, the BSs of different tiers are deployed according to mutually independent α-Ginibre processes, where the α can take different values for the different tiers. In the other model, all the BSs are deployed according to an α-Ginibre point process and they are classified into multiple tiers by mutually independent marks. For these proposed models, we derive computable representations for the coverage probability of a typical user—the probability that the downlink signal-to-interference-plus-noise ratio for the typical user achieves a target threshold. We exhibit the results of some numerical experiments and compare the proposed models and the Poisson based model.

Thermo- and Mesostabilizing Protein Interactions Identified by Temperature-Dependent Statistical Potentials

The goal of controlling protein thermostability is tackled here through establishing, by in silico analyses, the relative weight of residue-residue interactions in proteins as a function of temperature. We have designed for that purpose a (melting-) temperature-dependent, statistical distance potential, where the interresidue distances are computed between the side-chain geometric centers or their functional centers. Their separate derivation from proteins of either high or low thermal resistance reveals the interactions that contribute most to stability in different temperature ranges. Thermostabilizing interactions include salt bridges and cation- π interactions (especially those involving arginine), aromatic interactions, and H-bonds between negatively charged and some aromatic residues. In contrast, H-bonds between two polar noncharged residues or between a polar noncharged residue and a negatively charged residue are relatively less stabilizing at high temperatures. An important observation is that it is necessary to consider both repulsive and attractive interactions in overall thermostabilization, as the degree of repulsion may also vary with temperature. These temperature-dependent potentials are not only useful for the identification of meso- and thermostabilizing pair interactions, but also exhibit predictive power, as illustrated by their ability to predict the melting temperature of a protein based on the melting temperature of homologous proteins.

A Theoretical Study on the Electronic Structure of Au−XO(0,-1,+1) (X = C, N, and O) Complexes: Effect of an External Electric Field

A theoretical study on the nature of Au-XO(0,-1,+1) (X=C, N, O) interaction is carried out in order to provide a better understanding on the adsorption process of XO molecules on Au surfaces or Au-supported surfaces. The effect of the total charge as well as the presence of an external electric field on the formation processes of the Au-XO complex are analyzed and discussed using DFT (B3LYP) and high-level ab initio (CCSD(T)//MP2) methods employing a 6-311+G(3df) basis set for X and O atoms and Stuttgart pseudopotentials for Au atom. The presence of an electric field can increase the binding of O2 molecule to Au while weakening the formation of the Au-CO complex. These behaviors are discussed in the context of adsorption or deadsorption of these molecules on Au clusters. The formation of the Au-XO complex, the effect of addition/removal of one electron, and the role of the electric field are rationalized by studying the nature of the bonding interactions by means of the electron localization function (ELF) analysis. The net interaction between Au and XO fragments is governed by the interplay of three factors: (i) the amount of charge transfer from Au to XO, (ii) the sharing of the lone pair from X atom by the Au core (V(X, Au) basin), and (iii) the role of the lone pair of Au (V(Au) basin) mainly formed by 6s electrons. The total charge of the system and the applied electric field determine the population and orientation of the V(Au) basin and, subsequently, the degree of repulsion with the V(X, Au) basin.

Block Copolymer Assembly via Kinetic Control

Block copolymers consist of two or more chemically different polymer segments, or blocks, connected by a covalent linkage. In solution, amphiphilic blocks can self-assemble as a result of energetic repulsion effects between blocks. The degree of repulsion, the lengths of the block segments, and the selectivity of the solvent primarily control the resultant assembled morphology. In an ideal situation, one would like to be able to alter the morphology that forms without having to change the chemistry of the block copolymer. Through the kinetic manipulation of charged, amphiphilic block copolymers in solution, we are able to generate different nanoscale structures with simple block copolymer chemistry. The technique relies on divalent organic counter ions and solvent mixtures to drive the organization of the block copolymers down specific pathways into complex one-dimensional structures. Block copolymers are increasingly used as templating materials; thus, the ability to control the formation of specific patterns and structures is of growing interest and applicability.

Slow fiber cluster pattern in pig longissimus thoracis muscle: implications for myogenesis.

Recent evidence implicates fiber type proportions as playing a role in meat eating quality, and in pigs it has been suggested that the slow oxidative fibers contribute to both juiciness and tenderness. The fiber distribution in pigs is different from that found in most other species, in which the various types of skeletal muscle fiber are distributed in a "checkerboard" pattern, because in pigs the slow oxidative fibers have a clustered distribution. The initial processes leading to fiber clustering are likely to occur during myogenesis, but the precise mechanistic aetiology of this patterning and whether the slow oxidative fiber clusters occur in a random or ordered fashion is unknown. In the present study longissimus thoracis muscle from Large White crossbred pigs was sampled at the 10th rib, 48 h postmortem. Transverse cryo-sections were cut and histochemically stained to allow the identification of the main muscle fiber types: slow oxidative, fast glycolytic, and fast oxidative glycolytic. Images of the sections were captured and analyzed using point processes and Voronoi Tesselations to examine the randomness and spatial distribution of the clusters of slow oxidative fibers found in pig longissimus thoracis muscle. The results showed that an assumption of complete spatial randomness can be rejected and that a mathematical model incorporating a minimum distance of 1.7 to 2.0 microm between cluster centers produced fiber patterns similar to those observed in the original transverse sections of the muscle. In addition, if it assumed that the central fiber in each cluster is derived from primary myoblast progenitors, these results suggest that there may be some degree of repulsion between the primary fibers during the initial stages of cluster formation. The mechanistic basis of such repulsion is not clear, but it is speculated that secreted factors, such as sonic hedgehog or myostatin may play a role.

Pulsed-laser flash and continuous photolysis of ion-pair complexes of methyl viologen and ethylenediamine tetra-acetic acid in aqueous solution

Methyl viologen (MV2+) and EDTA form ion-pair complexes in aqueous solution that exhibit enhanced tail absorption in the u.v.-visible spectral region. Continuous photolysis of the system yields MV˙+ with values of ϕ(MV˙+) that are dependent on pH, the concentrations of the various species in solution, temperature and the wavelength of excitation. Pulsed-laser excitation at 355 mm generates initially a spectrum that is not that of free MV˙+; its enhanced absorption in the 440–540 nm region is reminiscent of that displayed by reduced viologen dimers and aggregates. The conversion of the initial absorption to that of free MV˙+ occurs via[MV2+]-independent first-order kinetics in the µs time frame; kobs increases as [EDTA] is decreased and the pH of the solution is increased. It is suggested that the ion-pair complexes of MV2+ exist as ‘pseudo-micellar’ aggregates, so that the absorption of light generates MV˙+ and an oxidized EDTA radical, with the electron localized on an amine moiety, within the aggregate. The reducing EDTA radical, formed via the deprotonation of the extremely strong carbon-acid alpha to the amine radical site and a carboxylate group, causes the generation of another equivalent of MV˙+ within the aggregate in competition with the decay modes of the radical; the MV˙+ species therein are ultimately released into bulk solution as the aggregate structure equilibrates; the rate of equilibration depends on [EDTA] in bulk solution and the degree of repulsion among the anionic species in the outer hydrophilic sheath of the ‘pseudo-micelle’. The observed values of Φ(MV˙+) reflect the competition within the aggregates between geminate-pair back electron transfer (radiationless deactivation in photophysical terms) and radical degradation processes.

Effects of Light on Movements of Herring

Light is apparently an important factor in controlling the distribution of the herring in southern New Brunswick. They swim to the east just before sunrise and to the west just after sunset; the moon, when low in elevation, is also said to have an attractive influence. However, they are repelled by direct sunlight, the degree of repulsion depending upon the intensity of light and size of fish. During moonlight, starlight, cloudy and foggy nights, all sizes extend to the surface.