Geometrical features of the protein folding mechanism are a robust property of the energy landscape: a detailed investigation of several reduced models

The concept of a funneled energy landscape and the principle of minimal frustration are the theoretical foundation justifying the applicability of structure-based models. In simulations, a protein is commonly reduced to a C(alpha)-bead representation. These simulations are sufficient to predict the geometrical features of the folding mechanism observed experimentally utilizing a concise formulation of the Hamiltonian with low computational costs. Toward a better understanding of the interplay between energetic and geometrical features in folding, the side chain is now explicitly included in the simulations. The simplest choice is the addition of C(beta)-beads at the center-of-mass position of the side chains. While one varies the energetic parameters of the model, the geometric aspects of the folding mechanism remain robust for a broad range of parameters. Energetic properties like folding barriers and protein stability are sensitive to the details of simulations. This robustness to geometry and sensitivity to energetic properties provide flexibility in choosing different parameters to represent changes in sequences, environments, stability or folding rate effects. Therefore, minimal frustration and the funnel concept guarantee that the geometrical features are robust properties of the folding landscape, while mutations and/or changes in the environment easily influence energy-dependent properties like folding rates or stability.     

Al(III) and Fe(III) Balance in Hemodialysis Treatment Assessed via Fluid Analysis by Adsorptive Stripping Voltammetry and UV Sample Digestion

Simultaneous determination of Al(III) and Fe(III) in posthemodialysis fluids was investigated by the Adsorptive stripping voltammetry of solochrome violet metal complexes. The adsorption of the complexes on the mercury electrode (HMDE) was investigated by out of phase altenating current voltammetry in presence of the main matrix interfering species. Sample digestion by UV irradiation was investigated to overcome the matrix interference. The proposed method was valid for real posthemodialysis samples containing or not Desferrioxamine B. Detection limits of 1.4 and 1.8 μg L^?1 were calculated for Al(III) and Fe(III), respectively. Recoveries ranging from 88.1 to 106.3% were obtained from spiking experiments.     

Phase equilibrium data and thermodynamic modeling of the system (CO2 + biodiesel + methanol) at high pressures

The main objective of this work was to investigate the high pressure phase behavior of the binary systems {CO₂(1) + methanol(2)} and {CO₂(1) + soybean methyl esters (biodiesel)(2)} and the ternary system {CO₂(1) + biodiesel(2) + methanol(3)} were determined. Biodiesel was produced from soybean oil, purified, characterized and used in this work. The static synthetic method, using a variable-volume view cell, was employed to obtain the experimental data in the temperature range of (303.15 to 343.15) K and pressures up to 21 MPa. The mole fractions of carbon dioxide were varied according to the systems as follows: (0.2383 to 0.8666) for the binary system {CO₂(1) + methanol(2)}; (0.4201 to 0.9931) for the binary system {CO₂(1) + biodiesel(2)}; (0.4864 to 0.9767) for the ternary system {CO₂(1) + biodiesel(2) + methanol(3)} with a biodiesel to methanol molar ratio of (1:3); and (0.3732 to 0.9630) for the system {CO₂ + biodiesel + methanol} with a biodiesel to methanol molar ratio of (8:1). For these systems, (vapor + liquid), (liquid + liquid), (vapor + liquid + liquid) transitions were observed. The phase equilibrium data obtained for the systems were modeled using the Peng–Robinson equation of state with the classical van der Waals (PR-vdW2) and Wong-Sandler (PR–WS) mixing rules. Both thermodynamic models were able to satisfactorily correlate the phase behavior of the systems investigated and the PR–WS presented the best performance.     

Multivariate curve resolution combined with gas chromatography to enhance analytical separation in complex samples: A review

This review describes the major advantages and pitfalls of iterative and non-iterative multivariate curve resolution (MCR) methods combined with gas chromatography (GC) data using literature published since 2000 and highlighting the most important combinations of GC coupled to mass spectrometry (GC–MS) and comprehensive two-dimensional gas chromatography with flame ionization detection (GC × GC-FID) and coupled to mass spectrometry (GC × GC–MS). In addition, a brief summary of some pre-processing strategies will be discussed to correct common issues in GC, such as retention time shifts and baseline/background contributions. Additionally, algorithms such as evolving factor analysis (EFA), heuristic evolving latent projection (HELP), subwindow factor analysis (SFA), multivariate curve resolution-alternating least squares (MCR-ALS), positive matrix factorization (PMF), iterative target transformation factor analysis (ITTFA) and orthogonal projection resolution (OPR) will be described in this paper. Even more, examples of applications to food chemistry, lipidomics and medicinal chemistry, as well as in essential oil research, will be shown. Lastly, a brief illustration of the MCR method hierarchy will also be presented.     

Measuring multipartite concurrence with a single factorizable observable

We show that, for any composite system with an arbitrary number of finite-dimensional subsystems, it is possible to directly measure the multipartite concurrence of pure states by detecting only one single factorizable observable, provided that two copies of the composite state are available. This result can be immediately put into practice in trapped-ion and entangled-photon experiments.     

Tailoring (n,m) structure of single-walled carbon nanotubes by modifying reaction conditions and the nature of the support of CoMo catalysts

The (n,m) population distribution of single-walled carbon nanotubes obtained on supported CoMo catalysts has been determined by photoluminescence and optical absorption. It has been found that the (n,m) distribution can be controlled by varying the gaseous feed composition, the reaction temperature, and the type of catalyst support used. When using CO as a feed over CoMo/SiO2 catalysts, increasing the synthesis temperature results in an increase in nanotube diameter, without a change in the chiral angle. By contrast, by changing the support from SiO2 to MgO, nanotubes with similar diameter but different chiral angles are obtained. Finally, keeping the same reaction conditions but varying the composition of the gaseous feed results in different (n,m) distribution. The clearly different distributions obtained when varying catalysts support and/or reaction conditions demonstrate that the (n,m) distribution is a result of differences in the growth kinetics, which in turn depends on the nanotube cap-metal cluster interaction.     

Voltammetric Determination of Azidothymidine Using Silver Solid Amalgam Electrodes

A new simple and direct electroanalytical method was developed for the determination of azidothymidine in commercial pharmaceutical preparations. It is based on differential pulse voltammetry at silver solid amalgam electrode with polished surface (p‐AgSAE) or surface modified by mercury meniscus (m‐AgSAE). The electroreduction of azidothymidine in basic media at these electrodes gives rise to one irreversible cathodic peak. Its potential in 0.05 mol L^?1 borate buffer, pH 9.3 at ca. ?1050 mV is comparable to that using hanging mercury drop electrode (HMDE). Achieved limits of quantitation are in the 10^?7 mol L^?1 concentration range for both amalgam electrodes. According to the procedure based on the standard addition technique, the recoveries of known amounts of azidothymidine contained in pharmaceutical preparations available in capsules were 101.4±1.8% (m‐AgSAE), 100.3±3.5% (p‐AgSAE) and 102.0±1.0% (HMDE) (n=10). There was no significant difference between the values gained by proposed voltammetric methods and the HPLC‐UV recommended by the United States Pharmacopoeia regarding the mean values and standard deviations.     

Removable singularities for sections of Riemannian submersions of prescribed mean curvature

We will prove that isolated singularities of sections with prescribed mean curvature of a Riemannian submersion fibered by geodesics of a vertical Killing field, are removable. Also we obtain information on the growth of the difference of two sections , having the same prescribed mean curvature and u=v on ∂Ω. This generalizes Theorem 2 of [P. Collin, R. Krust, Le problème de Dirichlet l'équation des surfaces minimales sur des domaines non bornés, Bull. S.M.F. 119 (4) (1991) 443-462].     

A novel chaotic particle swarm optimization approach using Hénon map and implicit filtering local search for economic load dispatch

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the chaotic systems theory, this paper proposed a novel chaotic PSO combined with an implicit filtering (IF) local search method to solve economic dispatch problems. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed PSO introduces chaos mapping using Hénon map sequences which increases its convergence rate and resulting precision. The chaotic PSO approach is used to produce good potential solutions, and the IF is used to fine-tune of final solution of PSO. The hybrid methodology is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. Simulation results are promising and show the effectiveness of the proposed approach.