Functional analysis of disulfide linkages clustered within the amino terminus of human apolipoprotein B

We tested the involvement of N-terminal six disulfide bonds (Cys-1 through Cys-12) of human apolipoprotein (apo) B in the assembly and secretion of lipoproteins using two C-terminal-truncated apoB variants, namely B50 and B18. In transfected rat hepatoma McA-RH7777 cells, B50 could assemble very low density lipoproteins (VLDL), and B18 was secreted as high density lipoproteins. When all 12 cysteine residues were substituted with alanines in B50, the mutant protein (B50C1-12) lost its ability to assemble lipid and was degraded intracellularly. However, mutation had no effect on B50C1-12 translation or translocation across the microsomal membrane. Post-translational degradation of B50C1-12 was partially inhibited by the proteasome inhibitor MG132. To determine which cysteines were critical in VLDL assembly and secretion, we prepared three additional mutant B50s, each containing four selected Cys-to-Ala substitutions in tandem (i.e. Cys-1 to Cys-4, Cys-5 to Cys-8, and Cys-9 to Cys-12). Expression of these mutants showed that disruption of disulfide bond formation within Cys-5 to Cys-8 diminished apoB secretion, whereas within Cys-1 to Cys-4 or Cys-9 to Cys-12 had lesser or no effect. In another two mutants in which only one disulfide bond (i.e. between Cys-5 and Cys-6 or between Cys-7 and Cys-8) was eliminated, only secretion of B50 with mutations at Cys-7 and Cys-8 was decreased. Thus, the disulfide bond involving Cys-7 and Cys-8 is most important for VLDL assembly and secretion. In addition, assembly and secretion of VLDL containing endogenous B100 or B48 were impaired in cells transfected with B50s containing Cys-7 and Cys-8 mutation. The Cys-to-Ala substitution abolished recognition of B50 by MB19, a conformational antibody with an epitope at the N terminus of human apoB. The Cys-to-Ala substitution also attenuated secretion of B18, but the effect of the mutation on B18 secretion was less evident than on B50.     

Methotrexate-grafted-oligochitosan micelles as drug carriers: synthesis and biological evaluations

The novel amphiphilic derivatives of Methotrexate–chitosan oligosaccharide (MTX–CHO) with different molar feeding ratios of MTX were synthesized. The degree of MTX substitution ranged from 4.47 to 13.5 %. MTX–CHO copolymer formed micelles with an average size of 134.6 ± 14.52 to 236.6 ± 30.01 nm, and zeta potential of 20 ± 5 to 16.8 ± 7.74 mV. The critical micelle concentration was found to range from 125 to 0.56 mg/l. Analysis of micelles with different degree of substitutions (DSs) revealed that the size of micelles decreased by increasing DS while zeta potential was reduced. Release study indicated that drug content had effect on the release rate. With increasing amount of loaded drug in the micelle, release rate was decreased. Drug loaded and unloaded MTX–CHO micelles showed significant cytotoxicity on MDA-MB-231. Loaded micelle was more effective than unloaded one which indicated that conjugation could reduce efficacy of MTX. The viability of MDA-MB-231 in presence of drug loaded micelles was significantly decreased and cell viability at 1 µg/ml was 45.17 ± 9 % while the viability of unloaded micelles was 91.86 ± 9.88. These phenomena make MTX–CHO micelles as a good candidate for hydrophobic anticancer drug carrier.     

Extraction optimization of a hydrocolloid extract from cress seed (Lepidium sativum) using response surface methodology

Extraction conditions for maximum values of yield, viscosity and minimum protein content of hydrocolloid extract from Lepidium sativum seed were investigated using response surface methodology. A Central Composite Face Design (CCFD) with four independent variables: temperature (25–85 °C); pH (3–10); extraction time (10–25 min) and water to seed ratio (10:1–80:1) was used to study the response variables (yield, viscosity and protein content). Data analysis showed that all the variables significantly (p < 0.05) affected the extraction yield and viscosity, whereas the effect of water to seed ratio on protein content was not significant (p > 0.05). Applying a desirability function method the optimum parameters were: extraction temperature 35 °C, pH 10, water to seed ratio of 30:1 and an extraction time of 15 min. At this optimum point, apparent viscosity, yield and protein content were 0.2 Pa s, 6.46% and 0.57%, respectively. The experimental values were very close to the predicted values and were not statistically different (p > 0.05).     

Physicochemical aspects of hydrocolloid extract from the seeds of Lepidium sativum

Acid equivalent weight, intrinsic viscosity and FT‐IR measurements have demonstrated a polyelectrolyte nature to Lepidium sativum seed extract. The polyelectrolyte nature relates to the carboxyl groups carried by galacturonic acid and glucuronic acid unit. The seed extract exhibited pronounced shear thinning in steady shear rheology and a weak gel type behaviour in dynamic rheology when the concentration is high i.e. > 1%. Such behaviour suggests the ability of L. sativum seed extract to structure a liquid, thus showing the possibility of applying it as a novel thickener and stabiliser in aqueous systems. The characteristic could be due to a strong tendency of molecular association of L. sativum seed extract as found for high M/G ratio galactomannans, and possibly also the enhanced macromolecular entanglement due to relatively rigid chain conformation. Temperature dependence study showed that the rheological properties of L. sativum structured solution is stable against temperature variation.     

Effect of fabrication process parameters on the apex‐radius of STM tungsten nanotip

Scanning tunneling microscope (STM) has found a wide application in nanoscience and nanotechnology. This microscope uses an ultra‐sharp metallic tip for image acquisition. Resolution of STM images depends largely on the radius of the tip apex; the smaller the radius the higher the resolution. In the present research, an experimental set‐up was designed and implemented for fabrication of STM tungsten nanotip using electrochemical‐etching method with the aim of optimization of nanotip fabrication process parameters by using Taguchi method. These parameters are electrolyte concentration, immersion length of the tungsten wire, inner diameter of the cathode tube, and the process voltage. It was found that the optimum level of the process parameters for gaining minimum radius of the nanotip apex is electrolyte concentration of 2 M/lit, wire immersion length of 4 mm, cathode tube inner diameter of 55 mm, and voltage of 3.5 V within the range of experiments. By setting the process parameters on the optimum level, the radius of the nanotip apex was decreased by five times in comparison to the mean value of the experimental results. The radius of the nanotip apex was improved down to about 10 nm under the optimum conditions. SCANNING 31: 65–74, 2009. © 2009 Wiley Periodicals, Inc.     

Bilevel Parallel Genetic Algorithms for Optimization of Large Steel Structures

This article is concerned with optimization of very large steel structures subjected to the actual constraints of the American Institute of Steel Construction ASD and LRFD specifications on high-performance multiprocessor machines using biologically inspired genetic algorithms. First, parallel fuzzy genetic algorithms (GAs) are presented for optimization of steel structures using a distributed memory Message Passing Interface (MPI) with two different schemes: the processor farming scheme and the migration scheme. Next, two bilevel parallel GAs are presented for large-scale structural optimization through judicious combination of shared memory data parallel processing using the OpenMP Application Programming Interface (API) and distributed memory message passing parallel processing using MPI. Speedup results are presented for parallel algorithms.     

Time-Frequency Signal Analysis of Earthquake Records Using Mexican Hat Wavelets

Abstract:   A method is presented for time-frequency signal analysis of earthquake records using Mexican hat wavelets. Ground motions in earthquakes are postulated as a sequence of simple penny-shaped ruptures at different locations along a fault line and occurring at different times. The single point source displacement of ground motion is idealized by a Gaussian function. For the purpose of signal analysis of accelerograms, the ground motion record generated by a simple penny-shaped rupture is used to form the basis wavelet function. After a careful study of the characteristics of various wavelet functions, the Mexican hat wavelet was found to be the most appropriate wavelet basis function to represent the acceleration of a single point source rupture. The result of the signal processing of an accelerogram is presented in the form of a scalogram using the coefficients of the continuous Mexican hat wavelet transform to describe the signal energy in the time-scale domain. The proposed signal processing methodology can be used to investigate the characteristics of accelerograms recorded on various types of sites and their effects on different types of structures.     

A novel machine learning‐based algorithm to detect damage in high‐rise building structures

A novel model is presented for global health monitoring of large structures such as high‐rise building structures through adroit integration of 2 signal processing techniques, synchrosqueezed wavelet transform and fast Fourier transform, an unsupervised machine learning technique, the restricted Boltzmann machine, and a recently developed supervised classification algorithm called neural dynamics classification (NDC) algorithm. The model extracts hidden features in the frequency domain of the denoised measured response signals recorded by sensors on different elevations or floors of a structure. The extracted features are used as an input of the NDC to detect and classify the global health of the structure into categories such as healthy, light damage, moderate damage, severe damage, and near collapse. The proposed model is validated using the data obtained from a 3D 1:20 scaled 38‐story reinforced concrete building structure. The results are compared with 3 other supervised classification algorithms: k‐nearest neighbor (KNN), probabilistic neural networks (PNN), and enhanced PNN (EPNN). NDC, EPNN, PNN, and KNN yield maximum average accuracies of 96%, 94%, 92%, and 82%, respectively.