Thermosensitive molecularly imprinted poly(1‐vinyl‐2‐pyrrolidone/methyl methacrylate/N‐vinylcaprolactam) for selective extraction of imatinib mesylate in human biological fluid

The efficiency of a molecularly imprinted polymer as a selective packing material for the solid‐phase extraction of imatinib mesylate sorption was investigated. The molecularly imprinted polymer was prepared using N,N′‐methylenebisacrylamide as a cross‐linker agent, N‐vinylcaprolactam as a thermo‐sensitive monomer, 1‐vinyl‐2‐pyrrolidone and methyl methacrylate as functional monomers, azobisisobutyronitrile as an initiator and imatinib mesylate as a template. The drug‐imprinted polymer was identified by Fourier transform infrared spectroscopy, thermogravimetric analysis, elemental analysis, and scanning electron microscopy. It was found that this polymer can be used for determination of trace levels of imatinib mesylate with a recovery percentage that could reach over 90%. Furthermore, the synthesized molecularly imprinted polymer indicated higher selectivity towards imatinib mesylate than other compounds. From isotherm study, the equilibrium adsorption data of imatinib mesylate by imprinted polymer were analyzed by Langmuir, Freundlich, and Temkin isotherm models. The developed method was used for determination of imatinib mesylate in human fluid samples by high performance liquid chromatography with excellent results.     

Electrospun polyethylene terephthalate (PET) nanofibrous conduit for biomedical application

Nanostructured biomaterials have great potential in the field of biomedical engineering. Efforts for treatment of cardiovascular diseases focused on introducing vascular substitutes that are nonthrombogenic and have long‐term patency, but still there is not any perfect replacement for clinical use. In this study, nanostructure tubes of a commonly known biocompatible polymer, polyethylene terephthalate (PET), were prepared via electrospinning process using small diameter mandrel as a collector with two different speeds. The nanofibers (NFs) morphologies' physical and mechanical properties were investigated according to scanning electron microscope (SEM), water contact angle (WCA), porosity measurement, differential scanning calorimetry (DSC), and tensile test. Finer NFs, more percentage of crystallinity, and superior mechanical properties were observed for samples prepared by higher speed mandrel. Since both samples stimulated platelet adhesion and activation, further surface modification with sodium nitrate as nitric oxide (NO) donor was done using two different approaches: dip‐coating and electrospraying. The modified NFs were evaluated via SEM, WCA, tensile test, platelets, and cell adhesion. The results showed more hydrophilicity, reduction in platelet adhesion, and improved blood compatibility for eNO‐HS (electrosprayed NO for higher collector speed) compared with other samples implying the promising potential of this fabrication and modification technique for improving PET‐based cardiovascular substitutes.     

Estimating complicated baselines in analytical signals using the iterative training of Bayesian regularized artificial neural networks

The present work deals with the development of a new baseline correction method based on the comparative learning capabilities of artificial neural networks. The developed method uses the Bayes probability theorem for prevention of the occurrence of the over-fitting and finding a generalized baseline. The developed method has been applied on simulated and real metabolomic gas-chromatography (GC) and Raman data sets. The results revealed that the proposed method can be used to handle different types of baselines with cave, convex, curvelinear, triangular and sinusoidal patterns. For further evaluation of the performances of this method, it has been compared with benchmarking baseline correction methods such as corner-cutting (CC), morphological weighted penalized least squares (MPLS), adaptive iteratively-reweighted penalized least squares (airPLS) and iterative polynomial fitting (iPF). In order to compare the methods, the projected difference resolution (PDR) criterion has been calculated for the data before and after the baseline correction procedure. The calculated values of PDR after the baseline correction using iBRANN, airPLS, MPLS, iPF and CC algorithms for the GC metabolomic data were 4.18, 3.64, 3.88, 1.88 and 3.08, respectively. The obtained results in this work demonstrated that the developed iterative Bayesian regularized neural network (iBRANN) method in this work thoroughly detects the baselines and is superior over the CC, MPLS, airPLS and iPF techniques. A graphical user interface has been developed for the suggested algorithm and can be used for easy implementation of the iBRANN algorithm for the correction of different chromatography, NMR and Raman data sets.     

Global optimization of the difference of affine increasing and positively homogeneous functions

The theory of increasing and positively homogeneous (IPH) functions defined on a real topological vector space X has well been developed. In this paper, we first give various characterizations for maximal elements of the support set of this class of functions. As an application, we present various characterizations for maximal elements of the support set of affine IPH functions. Finally, we investigate necessary and sufficient conditions for the global minimum of the difference of two strictly affine IPH functions.     

Quantification of sofosbuvir in human serum by liquid chromatography with negative ionization mass spectrometry using the parent peak and its source‐induced fragment: Application to a bioequivalence study

In the mass spectrometry of sofosbuvir, a new orally administered antihepatitis C drug, a weak peak is detected at the m/z value of the parent ion (m/z 530) as a result of in‐source dissociation and current methods to its quantification, is based on monitoring of the parent peak using ultra high‐performance liquid chromatography with tandem mass spectrometry. With these methods serum concentration of the drug is quantifiable only up to 4–5 h postdose. However, the fragmentation of the molecule generates a more stable ion at m/z 287 (base peak) with a signal intensity of about tenfold compared to the parent ion. Our study was aimed to improve sensitivity of analysis by acquisition of the m/z value of the daughter ion from which it originated instead of the parent molecule. This novelty allows us to measure serum concentrations of the drug for a longer time postdose and provides more opportunity for pharmacokinetic studies of sofosbuvir. Our method was linear over the concentration range of 2–2560 ng/mL of sofosbuvir in human serum with a limit of quantification of 2 ng/mL compared to 10 ng/mL reported previously. The coefficient variation values of both inter and intraday analysis were less than 13.8%, and the percentage error was less than 6.3.     

Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case

We have developed a stochastic mathematical formulation for designing a network of multi-product supply chains comprising several capacitated production facilities, distribution centres and retailers in markets under uncertainty. This model considers demand-side and supply-side uncertainties simultaneously, which makes it more realistic in comparison to models in the existing literature. In this model, we consider a discrete set as potential locations of distribution centres and retailing outlets and investigate the impact of strategic facility location decisions on the operational inventory and shipment decisions of the supply chain. We use a path-based formulation that helps us to consider supply-side uncertainties that are possible disruptions in manufacturers, distribution centres and their connecting links. The resultant model, which incorporates the cut-set concept in reliability theory and also the robust optimisation concept, is a mixed integer nonlinear problem. To solve the model to attain global optimality, we have created a transformation based on the piecewise linearisation method. Finally, we illustrate the model outputs and discuss the results through several numerical examples, including a real-life case study from the agri-food industry.     

Catecholthioether derivatives: preliminary study of in-vitro antimicrobial and antioxidant activities

In this research, synthesis, antimicrobial and antioxidant activities of a series of catecholthioethers having benzoxazole and tetrazole moieties are described. Antimicrobial activity was evaluated by minimum inhibitory concentration (MIC) assay. The synthesized compounds were tested in vitro against three Gram-positive bacteria including Staphylococcus aureus (clinical isolated), Staphylococcus aureus ATCC 25922, Enterococcus faecium (clinical isolated), and two Gram-negative bacteria including Klebsiella pneumoniae (clinical isolated) and Pseudomonas aeruginosa 27853 and the yeast Candida albicans in comparison with control drugs. Microbiological results indicated that the synthesized compounds possessed a broad spectrum of activity against the tested microorganisms at MIC values between 4-256 μg/ml. This shows compounds having tetrazole moiety were the most active against Gram-negative strains, whereas compounds having benzoxazole moiety were more active against Gram-positive ones. Also both of them showed significant antifungal activity against Candida albicans and had lower activity than the compared control drugs (Sulfamethoxazole and Fluconazole). The antioxidant activity was assessed using two methods, including, 1,1-biphenyl-2-picrylhydrazyl (DPPH) radical scavenging, and reducing power assays. Some of the catecholthioether derivatives showed antioxidant activity more than Trolox and butylated hydroxyanisole (BHA) as reference antioxidants.     

Bioconjugation of Interferon-alpha Molecules to Lysine-Capped Gold Nanoparticles for Further Drug Delivery Applications

Gold nanoparticles are potentially very attractive components for therapeutic delivery since they can be synthesized with any diameter from 1 to 200 nm to carry a payload of therapeutic molecules into a cell without triggering an immune response. Gold nanoparticles must undergo surface transformations before coupling to therapeutic molecules to become eligible for this purpose. It is now more understood that amine groups can bind to gold nanoparticles strongly, which has enabled surface modification of gold nanoparticles with amino acid lysine through its amine group. These lysine capped gold nanoparticles can further be coupled to therapeutic molecules for delivery purposes. In this study gold nanoparticles were first synthesized and capped with lysine molecules. TEM and FTIR measurements demonstrated the synthesis of lysine-capped gold nanoparticles with an average diameter of 10 nanometers. Interferon alpha molecules-one of the most important therapeutic protein were then chemically bound to lysine-capped gold nanoparticles through a two-step process of diimide-activated amidation. The conjugation of interferon molecules to lysine capped gold nanoparticles was carried out via the reaction between the free amine group of lysine and carboxyl groups of interferon using N-ethyl-N′-13-dimethyl-aminopropyl (EDAC) as a coupling agent. The process of conjugation has also been studied by transmission electron microscopy.