Stimuli-responsive protamine-based biodegradable nanocapsules for enhanced bioavailability and intracellular delivery of anticancer agents

Enzyme-and pH-responsive polyelectrolyte nanocapsules having diameters in the range of 200 +/- 20 nm were fabricated by means of Layer-by-Layer assembly of biopolymers, protamine, and heparin, and then loaded with anticancer drug doxorubicin. The incorporation of the FDA-approved peptide drug protamine as a wall component rendered the capsules responsive to enzyme stimuli. The stimuli-responsive drug release from these nanocapsules was evaluated, and further modulation of capsule permeability to avoid premature release was demonstrated by crosslinking the wall components. The interaction of the nanocapsules with cancer cells was studied using MCF-7 breast cancer cells. These capsules were readily internalized and disintegrated inside the cells, culminating in the release of the loaded doxorubicin and subsequent cell death as observed by confocal microscopy and MTT Assay. The bioavailability studies performed using BALB/c mice revealed that the encapsulated doxorubicin exhibited enhanced bioavailability compared to free doxorubicin. Our results indicate that this stimuli-responsive system fabricated from clinically used FDA-approved molecules and exhibiting minimal premature release has great potential for drug-delivery applications.

Ellipse Fitting Using the Finite Rate of Innovation Sampling Principle

Standard approaches for ellipse fitting are based on the minimization of algebraic or geometric distance between the given data and a template ellipse. When the data are noisy and come from a partial ellipse, the state-of-the-art methods tend to produce biased ellipses. We rely on the sampling structure of the underlying signal and show that the x- and y-coordinate functions of an ellipse are finite-rate-of-innovation (FRI) signals, and that their parameters are estimable from partial data. We consider both uniform and nonuniform sampling scenarios in the presence of noise and show that the data can be modeled as a sum of random amplitude-modulated complex exponentials. A low-pass filter is used to suppress noise and approximate the data as a sum of weighted complex exponentials. The annihilating filter used in FRI approaches is applied to estimate the sampling interval in the closed form. We perform experiments on simulated and real data, and assess both objective and subjective performances in comparison with the state-of-the-art ellipse fitting methods. The proposed method produces ellipses with lesser bias. Furthermore, the mean-squared error is lesser by about 2 to 10 dB. We show the applications of ellipse fitting in iris images starting from partial edge contours, and to free-hand ellipses drawn on a touch-screen tablet.

Empirical Analysis of Sampling Based Estimators for Evaluating RBMs

The Restricted Boltzmann Machines (RBM) can be used either as classifiers or as generative models. The quality of the generative RBM is measured through the average log-likelihood on test data. Due to the high computational complexity of evaluating the partition function, exact calculation of test log-likelihood is very difficult. In recent years some estimation methods are suggested for approximate computation of test log-likelihood. In this paper we present an empirical comparison of the main estimation methods, namely, the AIS algorithm for estimating the partition function, the CSL method for directly estimating the log-likelihood, and the RAISE algorithm that combines these two ideas.

A strategy to achieve enhanced electromagnetic interference shielding at ultra-low concentration of multiwall carbon nanotubes in P alpha MSAN/PMMA blends in the presence of a random copolymer PS-r-PMMA

A unique strategy was adopted to achieve an ultra-low electrical percolation threshold of multiwall carbon nanotubes (MWNTs) (0.25 wt%) in a classical partially miscible blend of poly-alpha-methylstyrene-co-acrylonitrile and poly(methyl methacrylate) (P alpha MSAN/PMMA), with a lower critical solution temperature. The polymer blend nanocomposite was prepared by standard melt-mixing followed by annealing above the phase separation temperature. In a two-step mixing protocol, MWNTs were initially melt-mixed with a random PS-r-PMMA copolymer and subsequently diluted with 85/15 P alpha MSAN/PMMA blends in the next mixing step. Mediated by the PS-r-PMMA, the MWNTs were mostly localized at the interface and bridged the PMMA droplets. This strategy led to enhanced electromagnetic interference (EMI) shielding effectiveness at 0.25 wt% MWNTs through multiple scattering from MWNT-covered droplets, as compared to the blends without the copolymer, which were transparent to electromagnetic radiation.

Time-Instant Sampling Based Encoding of Time-Varying Acoustic Spectrum

The inner ear has been shown to characterize an acoustic stimuli by transducing fluid motion in the inner ear to mechanical bending of stereocilia on the inner hair cells (IHCs). The excitation motion/energy transferred to an IHC is dependent on the frequency spectrum of the acoustic stimuli, and the spatial location of the IHC along the length of the basilar membrane (BM). Subsequently, the afferent auditory nerve fiber (ANF) bundle samples the encoded waveform in the IHCs by synapsing with them. In this work we focus on sampling of information by afferent ANFs from the IHCs, and show computationally that sampling at specific time instants is sufficient for decoding of time-varying acoustic spectrum embedded in the acoustic stimuli. The approach is based on sampling the signal at its zero-crossings and higher-order derivative zero-crossings. We show results of the approach on time-varying acoustic spectrum estimation from cricket call signal recording. The framework gives a time-domain and non-spatial processing perspective to auditory signal processing. The approach works on the full band signal, and is devoid of modeling any bandpass filtering mimicking the BM action. Instead, we motivate the approach from the perspective of event-triggered sampling by afferent ANFs on the stimuli encoded in the IHCs. Though the approach gives acoustic spectrum estimation but it is shallow on its complete understanding for plausible bio-mechanical replication with current mammalian auditory mechanics insights.

Investigations into enhanced wax production with combustion synthesized Fischer-Tropsch catalysts

Combustion synthesized (CS) cobalt catalysts deposited over two supports, alumina and silica doped alumina (SDA), were characterized and tested for its Fischer-Tropsch (FT) activity. The properties of CS catalysts were compared to catalysts synthesized by conventional impregnation method (IWI). The CS catalysts resulted in 40-70% increase in the yield of C6+ hydrocarbons compared to MI catalysts. The FT activity for CS catalysts showed formation of long chain hydrocarbon waxes (C24+) compared to the formation of middle distillates (C-10-C-20) for IWI synthesized catalysts, indicating higher hydrocarbon chain growth probability for CS catalysts. This is ascribed to the smaller crystallite sizes, increased degree of cobalt reduction and consequentially, a higher number of active metal sites, exposed over the catalyst surface. Additionally, 12-13% increase in the overall C6+ hydrocarbon yield is realized for SDA-CS catalysts, compared to Al2O3-CS catalysts. The improved performance of CS-SDA catalysts is attributed to 48% increase in cobalt dispersion compared to Al2O3 supported CS catalysts, which is again caused by the decrease in the cobalt -support interaction for SDA supports. The metal support interactions were analyzed using XPS and H-2 TPR-TPD experiments. Combustion method produced catalysts with smaller crystallite size (17-18 nm), higher degree of reduction (similar to 92%) and higher metal dispersion (16.1%) compared to the IWI method. Despite its enhanced properties, the CS catalysts require prominently higher reduction temperatures (similar to 1100-1200 K). The hydrocarbon product analysis for Al2O3 supported catalyst showed higher paraffin wax concentrations compared to SDA supported catalysts, due to the lower surface basicity of Al2O3. This work reveals the impact of the CS catalysts and the nature of support on FT activity and hydrocarbon product spectrum. (C) 2016 Elsevier Ltd. All rights reserved.

Enhanced photocatalytic activity of ultra-high aspect ratio ZnO nanowires due to Cu induced defects

We report the synthesis of ZnO nanowires in ambient air at 650 degrees C by a single-step vapor transport method using two different sources Zn (ZnO nanowires-I) and Zn:Cu (ZnO nanowires-II). The Zn:Cu mixed source co-vaporize Zn with a small amount of Cu at temperatures where elemental Cu source does not vaporize. This method provides us a facile route for Cu doping into ZnO. The aspect ratio of the grown ZnO nanowires-II was found to be higher by more than five times compared ZnO nanowires-I. Photocatalytic activity was measured by using a solar simulator and its ultraviolet-filtered light. The ZnO nanowires-II shows higher catalytic activity due to increased aspect ratio and higher content of surface defects because of incorporation of Cu impurities.