Uniqueness theorems for an impulsive Sturm-Liouville boundary value problem

In this study, an impulsive boundary value problem, generated by Sturm-Liouville differential equation with the eigenvalue parameter contained in one boundary condition is considered. It is shown that the coefficients of the problem are uniquely determined either by the Weyl function or by two given spectra.     

Correlations of Bond and Breakage Parameters of Some Ores with the Corresponding Point Load Index

This paper presents significant correlations of the Bond parameter (work index, W_i and grindability, G) and the breakage parameters (specific rate of breakage, S_i and the fineness value, γ) with the point load index (I_s(50)). The experimental results obtained from calcite, barite, colemanite and bauxite samples have demonstrated that the Bond and breakage parameters were closely correlated with the point load index. That is, the values of G, S_i and a_T parameters decreased with the increase in the values of the point load index; however, the γ parameter of B_i,j increased with increasing I_s(50) values.     

Potential energy surfaces for rearrangements of Berson trimethylenemethanes

In this research, thermal rearrangements of the Berson trimethylenemethanes (Berson-TMMs) have been investigated by employing density functional theory (DFT) and high-level ab initio methods, such as the complete active space self-consistent field (CASSCF), multireference second-order M?ller-Plesset perturbation theory (MRMP2), multireference configuration interaction singles and doubles (MRCISD), and coupled-cluster singles and doubles with perturbative triples [CCSD(T)]. In all computations Pople's polarized triple-ζ split valence basis set, 6-311G(d,p), is utilized. The relevant portions of the lowest-energy, singlet-spin potential energy surface of the C(4)H(6) (parent TMM), C(6)H(8) (Berson-TMMa), and C(8)H(12) (Berson-TMMc) chemical systems have been explored in order to determine the reaction energies and activation parameters accurately, with the ultimate objective of providing a theoretical account of experiments by Berson on TMMc. The nature of the orthogonal and the planar structures of the parent TMM have been clarified in this study. We have concluded that the orthogonal TMM (1)B(1) minimum has a C(2v) symmetry structure, and there is no pyramidalization in the unique methylene group. It lies at 13.9 kcal mol(-1) above the triplet minimum (3)B(2) at MRCISD level. The closed-shell (1)A(1) state of the planar TMM is not a true minimum but a transition structure (TS) for 180° rotation of the unique methylene group in the orthogonal TMM minimum. It lies at 3.0 kcal mol(-1) above (1)B(1). The planar structures are also involved in the interchange of equivalent orthogonal TMMs (o(1), o(2), o(3)). Many features of the parent TMM are retained in TMMa and TMMc, despite the constraints imposed by the five-membered ring in the latter species. Thus, ring closure to the bicyclic molecules 3a (3c) and 5a (5c) takes place similarly to that in the parent TMM. Likewise, planar TMMa (TMMc) structures are TSs, while orthogonal ones are true minima. The adiabatic singlet-triplet gaps are also similar, being 14.7 (13.0) and 16.5 (16.2) kcal mol(-1) in the orthogonal (o(1)) and planar TMMa (TMMc), respectively. It has been shown here that the substantial reductions in the ring-opening barriers of MCP derivatives 3a (3c) and 5a (5c) can be largely attributed to ring strain in the former and π-bond strain in the latter species.     

Nano-oncology: drug delivery, imaging, and sensing

Innovation in the last decade has endowed nanotechnology with an assortment of tools for delivery, imaging, and sensing in cancer research—stealthy nanoparticle vectors circulating in vivo, assembled with exquisite molecular control, capable of selective tumor targeting and potent delivery of therapeutics; intense and photostable quantum dot-based tumor imaging, enabling multicolor detection of cell receptors with a single optical excitation source; arrays of semiconducting nanowire and carbon nanotube sensor elements for selective multiplexed sensing of cancer markers without the need for probe labeling. These rapidly emerging tools are indicative of a burgeoning field ready to expand into medical applications. This review attempts to outline most of the current nanoparticle toolset for therapeutic release by liposomes, dendrimers, smart polymers, and virus-based systems. Advantages of nanoparticle-based imaging and targeting by use of nanoshells and quantum dots are also explored. Finally, emerging nanoelectronics-based sensing and a global discussion on the utility of each nanoparticle system addresses their fundamental advantages and shortcomings in cancer research.     

Sampling hazelnuts for aflatoxin: uncertainty associated with sampling, sample preparation, and analysis

The variability associated with the aflatoxin test procedure used to estimate aflatoxin levels in bulk shipments of hazelnuts was investigated. Sixteen 10 kg samples of shelled hazelnuts were taken from each of 20 lots that were suspected of aflatoxin contamination. The total variance associated with testing shelled hazelnuts was estimated and partitioned into sampling, sample preparation, and analytical variance components. Each variance component increased as aflatoxin concentration (either B1 or total) increased. With the use of regression analysis, mathematical expressions were developed to model the relationship between aflatoxin concentration and the total, sampling, sample preparation, and analytical variances. The expressions for these relationships were used to estimate the variance for any sample size, subsample size, and number of analyses for a specific aflatoxin concentration. The sampling, sample preparation, and analytical variances associated with estimating aflatoxin in a hazelnut lot at a total aflatoxin level of 10 ng/g and using a 10 kg sample, a 50 g subsample, dry comminution with a Robot Coupe mill, and a high-performance liquid chromatographic analytical method are 174.40, 0.74, and 0.27, respectively. The sampling, sample preparation, and analytical steps of the aflatoxin test procedure accounted for 99.4, 0.4, and 0.2% of the total variability, respectively.     

Sensitive voltammetric assay of etoposide using modified glassy carbon electrode with a dispersion of multi-walled carbon nanotube

A sensitive electroanalytical method for the determination of anticancer drug etoposide (ETP) using adsorptive stripping differential pulse voltammetry (AdSDPV) at a multi-walled carbon nanotube-modified glassy carbon electrode (MWCNT-modified GCE) is presented. The surface morphology of modified electrode was characterized by scanning electron microscopy. The effects of accumulation time and potential, pH, scan rate, and amount of MWCNT suspension were investigated. The calibration curve was linear in the concentration range of 2.0?×?10^?8–2.0?×?10^?6 M with the detection limit of 5.4?×?10^?9 M. The reproducibility of the peak current was found at 1.55 % (n?=?5) RSD value in pH 6.0 Britton–Robinson buffer for the MWCNT-modified GCE. The method was then successfully utilized for the determination of ETP in pharmaceutical dosage form, and a recovery of 99.55 % was obtained. The possible oxidation mechanism of ETP was also discussed. The proposed electroanalytical method using MWCNT-modified GCE is the most sensitive method for the determination of ETP with lowest limit of detection in the previously published electrochemical methods.     

Effects of Lipid-Based Encapsulation on the Bioaccessibility and Bioavailability of Phenolic Compounds

Phenolic compounds (quercetin, rutin, cyanidin, tangeretin, hesperetin, curcumin, resveratrol, etc.) are known to have health-promoting effects and they are accepted as one of the main proposed nutraceutical group. However, their application is limited owing to the problems related with their stability and water solubility as well as their low bioaccessibility and bioavailability. These limitations can be overcome by encapsulating phenolic compounds by physical, physicochemical and chemical encapsulation techniques. This review focuses on the effects of encapsulation, especially lipid-based techniques (emulsion/nanoemulsion, solid lipid nanoparticles, liposomes/nanoliposomes, etc.), on the digestibility characteristics of phenolic compounds in terms of bioaccessibility and bioavailability.     

Simultaneous Estimation of Ceftazidime and Ceftizoxime in Pharmaceutical Formulations by HPLC Method

The aim of the present study was to develop a fast, sensitive and reliable method for rapid screening of cephalosporin injectable dosage forms namely ceftazidime and ceftizoxime to the detection of counterfeit and substandard drugs that might be illegally commercialized. Ceftazidime, ceftizoxime and cefixime (IS) were separated in a X-Terra RP-18 column (250 × 4.60 mm ID × 5 ??) and DAD detector set at 290 and 260 nm. The mobile phase consisted of a mixture of methanol:water 20:80 (v/v) at a flow rate of 1.0 mL min^?1. Additionally, in order to find the optimum pH value of separation the pK _a values of studied compounds were determined by using two different methodologies. Aqueous pK _a values of studied compounds have been determined by UV-spectrophotometry and liquid chromatography were used for the determination and direct characterization of the dissociation constants by using the dependence of the capacity factor on the pH of the mobile phase in 20% (v/v) methanol?Cwater binary mixture in which separation was performed. The pH of the mobile phase was adjusted with 25 mM H₃PO₄ to 3.2. The method was shown to be linear, sensible, accurate, and reproducible over the range of analysis and it can be used to pharmaceutical formulations containing a single active ingredient within a short analysis time.     

Compressed images for affinity prediction (CIFAP): a study on predicting binding affinities for checkpoint kinase 1 protein inhibitors

Analyses of known protein–ligand interactions play an important role in designing novel and efficient drugs, contributing to drug discovery and development. Recently, machine learning methods have proven useful in the design of novel drugs, which utilize intelligent techniques to predict the outcome of unknown protein–ligand interactions by learning from the physical and geometrical properties of known protein–ligand interactions. The aim of this study is to work through a specific example of a novel computational method, namely compressed images for affinity prediction (CIFAP), in which binding affinities for structurally related ligands in complexes with human checkpoint kinase 1 (CHK1) are predicted. The CIFAP algorithm presented here relates published pIC ₅₀ values of 57 compounds, derived from a thienopyridine pharmacophore, in complexes with CHK1 to their two‐dimensional (2D) electrostatic potential images compressed in orthogonal dimensions. Patterns obtained from the 2D images are then used as inputs in regression and learning algorithms such as support vector regression (SVR) and adaptive neuro‐fuzzy inference system (ANFIS) methods to validate the experimental pIC ₅₀ values. This study revealed that the 2D image pixels in the vicinity of bound ligand surfaces provide more relevant information to make correlations with the empirical pIC ₅₀ values. As compared with ANFIS, SVR gave rise to the lowest root mean square errors and the greatest correlations, suggesting that SVR could be a plausible choice of machine learning methods in predicting binding affinities by CIFAP. Copyright © 2013 John Wiley & Sons, Ltd.