An assessment of biopolymer‐ and synthetic polymer‐based scaffolds for bone and vascular tissue engineering

The promise of tissue engineering is the combination of a scaffold with cells to initiate the regeneration of tissues or organs. Engineering of scaffolds is critical for success and tailoring of polymer properties is essential for their good performance. Many different materials of natural and synthetic origins have been investigated, but the challenge is to find those that have the right mix of mechanical performance, biodegradability and biocompatibility for biological applications. This article reviews key polymeric properties for bone and vascular scaffold eligibility with focus on biopolymers, synthetic polymers and their blends. The limitations of these polymeric systems and ways and means to improve scaffold performance specifically for bone and vascular tissue engineering are discussed. © 2013 Society of Chemical Industry     

Potent‐By‐Design: Amino Acids Mimicking Porous Nanotherapeutics with Intrinsic Anticancer Targeting Properties

Exogenous sources of amino acids are essential nutrients to fuel cancer growth. Here, the increased demand for amino acid displayed by cancer cells is unconventionally exploited as a design principle to replete cancer cells with apoptosis inducing nanoscopic porous amino acid mimics (Nano‐PAAM). A small library consisting of nine essential amino acids nanoconjugates (30 nm) are synthesized, and the in vitro anticancer activity is evaluated. Among the Nano‐PAAMs, l ‐phenylalanine functionalized Nano‐PAAM (Nano‐pPAAM) has emerged as a novel nanotherapeutics with excellent intrinsic anticancer and cancer‐selective properties. The therapeutic efficacy of Nano‐pPAAM against a panel of human breast, gastric, and skin cancer cells could be ascribed to the specific targeting of the overexpressed human large neutral amino acid transporter SLC7A5 (LAT‐1) in cancer cells, and its intracellular reactive oxygen species (ROS) inducing properties of the nanoporous core. At the mechanistic level, it is revealed that Nano‐pPAAM could activate both the extrinsic and intrinsic apoptosis pathways to exert a potent “double‐whammy” anticancer effect. The potential clinical utility of Nano‐pPAAM is further investigated using an MDA‐MB‐231 xenograft in NOD scid gamma mice, where an overall suppression of tumor growth by 60% is achieved without the aid of any drugs or application of external stimuli.     

Stability indicating HPTLC determination of linezolid as bulk drug and in pharmaceutical dosage form

A simple, selective, precise, and stability-indicating high-performance thin layer chromatographic method of analysis of Linezolid both as a bulk drug and in formulations was developed and validated in pharmaceutical dosage form. The method employed TLC aluminium plates precoated with silica gel 60F-254 as the stationary phase. The solvent system consisted of toluene-acetone (5:5, v/v). This system was found to give compact spots for Linezolid (R_f value of 0.29 ± 0.01). Linezolid was subjected to acidic, alkali hydrolysis, oxidation, and photodegradation. The degraded products also were well separated from the pure drug. Densitometric analysis of Linezolid was conducted in the absorbance mode at 254 nm. The linear regression data for the calibration plots showed good linear relationship with r² = 0.997 ± 0.001 in the concentration range of 300-800 ng/spot. The mean value of correlation coefficient, slope, and intercept were 0.998 ± 0.003, 0.15 ± 0.009, and 19.52 ± 1.66 respectively. The method was validated for precision, accuracy, ruggedness, and recovery. The limits of detection and quantification were 20 ng/spot and 50 ng/spot, respectively. The drug undergoes degradation under acidic and basic conditions, oxidation and photo degradation. All the peaks of degraded product were resolved from the standard drug with significantly different R_f values. This indicates that the drug is susceptible to acid-base hydrolysis, oxidation, and photo degradation. Statistical analysis proves that the method is reproducible and selective for the estimation of the said drug. Because the method could effectively separate the drug from its degradation products, it can be used as a stability indicating one.     

Spherical crystallization of celecoxib

Celecoxib exhibits poor flow properties and compressibility. Spherical crystallization of celecoxib was carried out using the solvent change method. An acetone:dichloromethane (DCM):water system was used where DCM acted as a bridging liquid and acetone and water as good and bad solvent, respectively. Hydroxypropylmethylcellulose (HPMC) was used to impart strength and sphericity to the agglomerates. The effect of amount of bridging liquid and speed of agitation was studied using 3² factorial design. Primary properties of the agglomerates were evaluated by infrared spectroscopy, powder X-ray diffraction, and differential scanning calorimetry. The effect of variables on micromeritic, mechanical, compressional, and dissolution behavior was evaluated by response surface methodology. Particle size, bulk density, mean yield pressure (MYP), and drug release were found to be significantly affected by either of the two variables. Interaction of variables significantly affected the MYP.     

Catalytic degradation of methylene blue by biosynthesised copper nanoflowers using F. benghalensis leaf extract

This study reports the unprecedented, novel and eco‐friendly method for the synthesis of three‐dimensional (3D) copper nanostructure having flower like morphology using leaf extract of Ficus benghalensis. The catalytic activity of copper nanoflowers (CuNFs) was investigated against methylene blue (MB) used as a modal dye pollutant. Scanning electron micrograph evidently designated 3D appearance of nanoflowers within a size range from 250 nm to 2.5 μm. Energy‐dispersive X‐ray spectra showed the presence of copper elements in the nanoflowers. Fourier‐transform infrared spectra clearly demonstrated the presence of biomolecules which is responsible for the synthesis of CuNFs. The catalytic activity of the synthesised CuNFs was monitored by ultraviolet–visible spectroscopy. The MB was degraded by 72% in 85 min on addition of CuNFs and the rate constant (k) was found to be 0.77 × 10⁻³ s⁻¹. This method adapted for synthesis of CuNFs offers a valuable contribution in the area of nanomaterial synthesis and in water research by suggesting a sustainable and an alternative route for removal of toxic solvents and waste materials.Inspec keywords: catalysis, dyes, nanostructured materials, nanofabrication, scanning electron microscopy, X‐ray chemical analysis, copper, Fourier transform infrared spectra, visible spectra, ultraviolet spectra, molecular biophysicsOther keywords: catalytic degradation, methylene blue, biosynthesised copper nanoflowers, F. benghalensis leaf extract, three‐dimensional copper nanostructure synthesis, 3D copper nanostructure synthesis, flower like morphology, Ficus benghalensis leaf extract, modal dye pollutant, electron micrograph, 3D appearance, energy‐dispersive X‐ray spectra, copper elements, Fourier‐transform infrared spectra, biomolecules, ultraviolet‐visible spectroscopy, toxic solvent removal, waste materials, size 250 nm to 2.5 mum, Cu     

A state-space search approach for optimizing reliability and cost of execution in distributed sensor networks

Sensor networks are increasingly being used for applications which require fast processing of data, such as multimedia processing and collaboration among sensors to relay observed data to a base station (BS). Distributed computing can be used on a sensor network to reduce the completion time of a task (an application) and distribute the energy consumption equitably across all sensors, so that certain sensors do not die out faster than the others. The distribution of task modules to sensors should consider not only the time and energy savings, but must also improve reliability of the entire task execution. We formulate the above as an optimization problem, and use the A^∗$A^{\ast }$ algorithm with improvements to determine an optimal static allocation of modules among a set of sensors. We also suggest a faster algorithm, called the greedy A^∗$A^{\ast }$ algorithm, if a sub-optimal solution is sufficient. Both algorithms have been simulated, and the results have been compared in terms of energy savings, decrease in completion time of the task, and the deviation of the sub-optimal solution from the optimal one. The sub-optimal solution required 8%–35% less computation, at the cost of 2.5%–15% deviation from the optimal solution in terms of average energy spent per sensor node. Both the A^∗$A^{\ast }$ and greedy A^∗$A^{\ast }$ algorithms have been shown to distribute energy consumption more uniformly across sensors than centralized execution. The greedy A^∗$A^{\ast }$ algorithm is found to be scalable, as the number of evaluations in determining the allocation increases linearly with the number of sensors.     

Optimism and Pessimism as Predictors of Change in Health After Death or Onset of Severe Illness in Family.

The authors prospectively examined changes in health after a major life event (death or onset of severe illness in family) among 5,007 employees (mean age=44.8 years) whose optimism and pessimism levels were assessed in 1997 and major life events in 2000. Health was indicated by sickness absence days during a period covering 36 months prior to the event and 18 months after the event. Increase in sick days after the event was smaller and returned to the preevent level more quickly among highly optimistic individuals than among their counterparts with low optimism. Parallel changes were not observed in relation to pessimism. These findings suggest that optimism may reduce the risk of health problems and may be related to a faster recovery after a major life event. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Visualization of randomly ordered numeric data sets using spherical self-organizing feature maps

Scientific data visualization requires a variety of mathematical techniques to transform multivariate data sets into simple graphical objects, or glyphs, that provide scientists and engineers with a clearer understanding of the underlying system behaviour. The spherical self-organizing feature map (SOFM) described in this paper exploits an unsupervised clustering algorithm to map randomly organized N-dimensional data into a lower three-dimensional (3D) space for visual pattern analysis. Each node on the spherical lattice corresponds to a cluster of input vectors that lie in close spatial proximity within the original feature space, and neighbouring nodes on the lattice represent cluster centres with a high degree of vector similarity. Simple metrics are used to extract associations between the cluster units and the input vectors assigned to them. These are then graphically displayed on the spherical SOFM as either surface elevations or colourized facets. The resulting colourized graphical objects are displayed and manipulated within 3D immersive virtual reality (IVR) environments for interactive data analysis. The ability of the proposed algorithm to transform arbitrarily arranged numeric strings into unique, reproducible shapes is illustrated using chaotic data generated by the Lozi, Hénon, Rössler, and Lorenz attractor functions under varying initial conditions. Implementation of the basic data visualization technique is further demonstrated using the more common Wisconsin breast cancer data and multi-spectral satellite data.     

Dielectric Modulus and Conductivity Scaling Approach to the Analysis of Ion Transport in Solid Polymer Electrolytes

Solid polymer electrolyte films (SPEs) based on poly(methyl methacrylate) are prepared using a solution cast technique. The temperature-dependent behavior of dielectric, modulus spectra and ac conductivity has been investigated. The long tail of the real part of modulus (M′) in the low frequency indicates the capacitive nature of the samples. The frequency dependence of imaginary part of modulus (M″) shows a non-Debye relaxation that has been explained using the Kohlrausch–Williams–Watts stretched exponential function. The activation energy for the relaxation is almost same as the activation energy for the conduction. The relaxation time obtained from the tangent loss graph (τ_δ) is about two orders of magnitude larger than that obtained from the imaginary part of modulus graph (τ_m). The ac conductivity has been found to obey Jonscher's universal power law. Transport parameters show that addition of filler creates additional hopping sites for the charge carriers and also increases the charge carrier density. It is also observed that the higher ionic conductivity at higher temperature is due to increased thermally activated hopping rates accompanied by a significant increase in carrier concentration. The contribution of carrier concentration to the total conductivity is also confirmed from Summerfield scaling. POLYM. ENG. SCI., 60: 297–305, 2019. © 2019 Society of Plastics Engineers