Molecular dynamics simulation of the sliding of distamycin anticancer drug along DNA: interactions and sequence selectivity

Molecular dynamics simulations and umbrella sampling have been used to investigate the sliding of distamycin anticancer drug along the DNA minor groove. The potential energy surface calculated for the sliding of drug shows three minima. The global minimum corresponds to the binding of drug to the AT-rich region, which is the origin of sequence selectivity of distamycin. This selectivity originates from both structural factors and energy contributions. The analysis of energy contributions of binding was performed by the MM–PBSA method. The analysis of hydrogen bonds and van der Waals, electrostatic, and solvation interactions show that structural or steric factors are more important in the selectivity of distamycin than energetic factors. The results of this study can be applied in the design of new derivatives of distamycin anticancer drug with improved properties.     

Magnetic solid-phase extraction of Zineb by C18-functionalised paramagnetic nanoparticles and determination by first-derivative spectrophotometry

Fe₃O₄-SiO₂-C₁₈ paramagnetic nanoparticles have been synthesised and used as magnetic solid-phase extraction (MSPE) sorbent for the extraction of Zineb from agricultural aqueous samples under ultrasonic condition and quantified through a first-derivative spectrophotometric method. The produced magnetic nanoparticles were characterised by using scanning electron microscopy, X-ray diffraction spectroscopy, Fourier transform infrared spectroscopy and zeta potential reader. The Fe₃O₄-SiO₂-C₁₈ paramagnetic nanoparticles had spherical structures with diameters in the range of 198–201 nm. Further, MSPE was performed by dispersion of Fe₃O₄-SiO₂-C₁₈ paramagnetic nanoparticles in a buffered aqueous solution accompanied by sonication. Next, the sorbents were accumulated by applying an external magnetic field and were washed with 4-(2-pyridylazo) resorcinol-dimethyl sulfoxide solution, for the purpose of desorbing the analyte. The extraction conditions (sample pH, washing and elution solutions, amount of sorbents, time of extraction, sample volume and effect of diverse ions), as well as Zineb-PAR first-order derivative spectra, were also evaluated. The calibration curve of the method was linear in the concentration range of 0.055–24.3 mg L^?1 with a correlation coefficient of 0.991. The limit of detection and limit of quantification values were 0.022 and 0.055 mg L^?1, respectively. The precision of the method for 0.27 mg L^?1 solution of the analyte was found to be less than 3.2%. The recoveries of three different concentrations (0.27, 1.37 and 13.7 mg L^?1) obtained 98.3%, 98.5% and 96.0%, respectively. The proposed Fe₃O₄-SiO₂-C₁₈ paramagnetic nanoparticles were found to have the capability of reusing for 7.0 times.     

Joint replenishment model with substitution

When products are coupled to the same cycle, the joint replenishment model (JRM) is used to determine optimal inventory levels, where the amount to order (for each item) is designed to minimize the joint holding and ordering costs based on a given demand. JRM studies assume that there is no substitution between items. However, this assumption is unrealistic in some settings where substitution cannot be ignored. This paper combines the separate works on substitution and joint replenishment and proposes a solution procedure for solving the joint replenishment model with substitution (JRMS) for two products within the framework of the classical economic order quantity model. We determine the optimal order quantities for each product taking into consideration substitution between them so that demand is partially met and the total cost associated with the delivery, holding, and shortage of the products is minimized. We also provide an extensive scenario analysis and draw insights. In particular, we shed some light on the role of substitution in reducing the fixed cost. We show that JRMS can result in substantial cost savings compared to the ordinary JRM.     

Reserve stock models: Deterioration and preventive replenishment

Reserve stocks are needed in a wide spectrum of industries from strategic oil reserves to tactical (machine buffer) reserves in manufacturing. One important aspect under-looked in research is the effect of deterioration, where a reserve stock, held for a long time, may be depleted gradually due to factors such as spoilage, evaporation, and leakage. We consider the common framework of a reserve stock that is utilized only when a supply interruption occurs. Supply outage occurs randomly and infrequently, and its duration is random. During the down time the reserve is depleted by demand, diverted from its main supply. We develop optimal stocking policies, for a reserve stock which deteriorates exponentially. These policies balance typical economic costs of ordering, holding, and shortage, as well as additional costs of deterioration and preventive measures. Our main results are showing that (i) deterioration significantly increases cost (up to 5%) and (ii) a preventive replenishment policy, with periodic restocking, can offset some of these additional costs. One side contribution is refining a classical reserve stock model (Hansmann, 1962).     

Lot sizing with random yield and different qualities

This paper considers a production/inventory system where items produced/purchased are of different qualities: Types A and B. Type A items are of perfect quality, and Type B items are of imperfect quality; but not necessarily defective; and have a lower selling price. The percentage of Type A (the yield rate) is assumed to be a random variable with known probability distribution. The electronics industry gives good examples of such situations. We extend the classical single period (newsvendor) and the economic order quantity (EOQ) models by accounting for random supply and for imperfect quality (Type B) items which are assumed to have their own demand and cost structure. We develop mathematical models and prove concavity of the expected profit function for both situations. We also present detailed analysis and numerical results. We focus on comparing the profitability of the novel proposed models with models from the literature (and derivatives of these models) that develop the optimal order quantity based on the properties of Type A items only (and ignore Type B items). We find that accounting for Type B items can significantly improve profitability.     

Spectrophotometric determination of aqueous acidity constants of three azo dyes

The two successive steps acidity constants of three azo dye derivatives D1–D3, were determined by a spectrophotometric method using 0.10 M KNO₃ as supporting electrolyte in water solvent. The electronic spectra of the compounds were recorded in the course of their pH-metric titration with a standard base solution. The protolytic equilibrium constants can be solved very satisfactorily from absorbance data, by combining the data obtained in the spectrometric determinations with graphic methods as the absorbance diagrams. An A-diagram shows the relative absorbance changes at two wavelengths as a function of the pH. For a one-step system, the absorbance at any wavelength must be proportional to the absorbance at any other wavelength, so an A-diagram for all wavelength combinations for such a system must be linear (rank, s=1). However, if a system is governed by two or more equilibria, the A-diagrams corresponding to multi-step titrations will change direction every time a new equilibrium becomes dominant in the system. Analysis of the each uniform sub-region can then be used in evaluating of the corresponding equilibrium. A-diagrams for all wavelength combinations suggest that these systems have the rank two(s=2). The results revealed that the K_a(1) and K_a(2) values of different azo dyes follow the order D3>D2>D1.