Poly(Caprolactone)‐Poly(N‐Isopropyl Acrylamide)‐Fe3O4 Magnetic Nanofibrous Structure with Stimuli Responsive Drug Release

Poly(caprolactone; PCL)—poly(N‐isopropylacrylamie; PNIPAAm)—Fe₃O₄ fiber, that can be magnetically actuated, is reported. Here, a structure is engineered that can be utilized as a smart carrier for the release of chemotherapeutic drug via magneto‐thermal activation, with the aid of magnetic nanoparticles (MNPs). The magnetic measurement of the fibers revealed saturation magnetization values within the range of 1.2–2.2 emu g^?1. The magnetic PCL‐PNIPAAm‐Fe₃O₄ scaffold shows a specific loss power value of 4.19 W g^?1 at 20 wt% MNPs. A temperature increase of 40 °C led to a 600% swelling after only 3 h. Doxorubicin (DOX) as a model drug, demonstrates a controllable drug release profile. 39% ± 0.92 of the total drug loaded is released after 96 h at 37 °C, while 25% drug release in 3 h at 40 °C is detected. Cytotoxicity results show no significant difference in cell attachment efficiency between the MNP‐loaded fibers and control while the DOX‐loaded fibers effectively inhibited cell proliferation at 24 h matching the drug release profile. The noncytotoxic effect, coupled with the magneto‐thermal property and controlled drug release, renders excellent potential for these fibers to be used as a smart drug‐release agent for localized cancer therapy.     

Antibacterial activity of Artemisia persica Boiss essential oil against Escherichia coli O157: H7 and Listeria monocytogenes in probiotic Doogh

This study was conducted to assess the antibacterial efficacy of Artemisia persica Boiss essential oil (APBEO) at a concentration of 75 and 150 ppm with probiotic bacterium Lactobacillus paracasei in preserving the microbial and organoleptic quality of Doogh during storage at 4°C. The results indicated a gradual increase in acidity, whereas a decline in pH was noted in all the samples (p < .05). The addition of APBEO (150 ppm) and probiotics in doogh exhibited a synergistic effect and increased death rate of L. monocytogenes and E. coli O157: H7 in Doogh samples after 15 days. Also, the high score of overall acceptability was associated with the sample with 75 ppm APBEO. The incorporation of APBEO and probiotics in the sample exhibited a synergistic trend to ensure the safety of doogh and keep the quality of products.     

Progesterone Release from PDMS-Modified Silica Xerogels Containing Ag Nanoparticles

Silicon - The objective of this study is to investigate the effects of adding PDMS and Ag nanoparticles on chemical and physical properties of silica xerogels as well as release behavior of...     

Solving a category of two-dimensional fractional optimal control problems using discrete Legendre polynomials

In this paper, we formulate a numerical method to approximate the solution of two-dimensional optimal control problem with a fractional parabolic partial differential equation (PDE) constraint in the Caputo type. First, the optimal conditions of the optimal control problems are derived. Then, we discretize the spatial derivatives and time derivatives terms in the optimal conditions by using shifted discrete Legendre polynomials and collocations method. The main idea is simplifying the optimal conditions to a system of algebraic equations. In fact, the main privilege of this new type of discretization is that the numerical solution is directly and globally obtained by solving one efficient algebraic system rather than step-by-step process which avoids accumulation and propagation of error. Several examples are tested and numerical results show a good agreement between exact and approximate solutions.     

Application of Markov Chain Analysis and Tanks-in-Series Model in Mathematical Modeling of Impinging Stream Dryers

In spite of the fact that the principles of impinging stream reactors have been developed for more than half a century, the performance analysis of such devices, from a viewpoint of the mathematical modeling, has not been investigated extensively. In this study two models are proposed to describe the drying performance of particulate materials in two-impinging stream dryers. The models are developed based on the Markov chain analysis and the tanks-in-series model. The required parameters for each model are determined by using RTD data obtained in a two-impinging stream dryer and the governing equations are solved numerically. Comparison of the results of the models with available experimental data shows that the stirred tanks-in-series model successfully explains the drying behavior in impinging stream dryers. Nevertheless, the results of the model that is developed based on the Markov chain analysis are not in exact agreement with corresponding experimental data because of the extremely short residence time of the particles inside the dryer. Also, the effects of some operating parameters on the performance of such dryers are investigated. The results indicate that the drying efficiency of the dryer increases when solid-to-gas flow rate ratio, initial moisture content, and diameter of the particles decrease and when the temperature of the carrier gas increases.     

A Study of a High-Throughput Plasmid DNA Purification System

An automated process that incorporates Millipore's Plasmid Miniprep₉₆ Montáge™ Kit with the Apogent Discoveries PlateMate Plus® and Tango™ automated high-throughput dispensing systems has been developed for purifying plasmid DNA. To test the efficacy of this process, parameters such as the reproducibility and consistency of the purified DNA quantity and quality as well as the purification speed were analyzed. The purification time for two plates of the Plasmid Miniprep₉₆ Kit (192 samples) was approximately 60 minutes using a PlateMate Plus equipped with 96 disposable tips and the Tango system equipped with 96 RB (resin bead) syringes. High uniformity and consistency in DNA yields (determined by spectrophotometric analysis) and quality (determined by gel electrophoresis analysis) among the different wells were observed. The purified plasmid DNA samples sequenced at an exceptional level with an average PHRED Q > 20 of 819 ± 25.*Millipore and Montage are the trademarks of Millipore Corporation     

Mathematical modeling of polyethylene terephthalate pyrolysis in a spouted bed

A model has been developed for pyrolysis of polyethylene terephthalate (PET) in a spouted bed reactor based on the conservation equations for heat, mass, and momentum transports. A spouted bed has been constructed and the kinetic parameters have been obtained within the temperature range of 723–833 K, using two particle size ranges, (0.1–1.0) × 10^?3 and (1.0–3.0) × 10^?3 m. The model' predictions for the radial distributions of temperature and concentration confirm the excellent mixing of particles. Thus, spouted beds are appropriate equipments for performing kinetic studies of PET pyrolysis. The inlet gas temperature and the mass of PET highly affect PET conversion. The amount of inert particles has a negligible effect on the conversion and it can be reduced as far as a stable spouting is preserved. The gas flow suffices to eliminate the external heat and mass‐transfer limitations. It can be reduced to the minimum value to decrease the energy consumption. © 2015 American Institute of Chemical Engineers AIChE J, 61: 1900–1911, 2015     

A distributed algorithm for fitting generalized additive models

Generalized additive models are an effective regression tool, popular in the statistics literature, that provides an automatic extension of traditional linear models to nonlinear systems. We present a distributed algorithm for fitting generalized additive models, based on the alternating direction method of multipliers (ADMM). In our algorithm the component functions of the model are fit independently, in parallel; a simple iteration yields convergence to the optimal generalized additive model. This is in contrast to the traditional approach of backfitting, where the component functions are fit sequentially. We illustrate the method on different classes of problems such as generalized additive, logistic, and piecewise constant models, with various types of regularization, including those that promote smoothness and sparsity.