Insights into stabilizing interactions in the distorted domain-swapped dimer of Salmonella typhimurium survival protein

The survival protein SurE from Salmonella typhimurium (StSurE) is a dimeric protein that functions as a phosphatase. SurE dimers are formed by the swapping of a loop with a pair of beta-strands and a C-terminal helix between two protomers. In a previous study, the Asp230 and His234 residues were mutated to Ala to abolish a hydrogen bond that was thought to be crucial for C-terminal helix swapping. These mutations led to functionally inactive and distorted dimers in which the two protomers were related by a rotation of 167 degrees. New salt bridges involving Glu112 were observed in the dimeric interface of the H234A and D230A/H234A mutants. To explore the role of these salt bridges in the stability of the distorted structure, E112A, E112A/D230A, E112A/H234A, E112A/D230A/H234A, R179L/H180A/H234A and E112A/R179L/H180A/H234A mutants were constructed. X-ray crystal structures of the E112A, E112A/H234A and E112A/D230A mutants could be determined. The dimeric structures of the E112A and E112A/H234A mutants were similar to that of native SurE, while the E112A/D230A mutant had a residual rotation of 11 degrees between the B chains upon superposition of the A chains of the mutant and native dimers. The native dimeric structure was nearly restored in the E112A/H234A mutant, suggesting that the new salt bridge observed in the H234A and D230A/H234A mutants was indeed responsible for the stability of their distorted structures. Catalytic activity was also restored in these mutants, implying that appropriate dimeric organization is necessary for the activity of SurE.

Human action recognition in H.264/AVC compressed domain using meta-cognitive radial basis function network

In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

Optimum Parameter Selection in Sparse Reconstruction of Frequency-Domain Optical-Coherence Tomography Signals

For a multilayered specimen, the back-scattered signal in frequency-domain optical-coherence tomography (FDOCT) is expressible as a sum of cosines, each corresponding to a change of refractive index in the specimen. Each of the cosines represent a peak in the reconstructed tomogram. We consider a truncated cosine series representation of the signal, with the constraint that the coefficients in the basis expansion be sparse. An l(2) (sum of squared errors) data error is considered with an l(1) (summation of absolute values) constraint on the coefficients. The optimization problem is solved using Weiszfeld's iteratively reweighted least squares (IRLS) algorithm. On real FDOCT data, improved results are obtained over the standard reconstruction technique with lower levels of background measurement noise and artifacts due to a strong l(1) penalty. The previous sparse tomogram reconstruction techniques in the literature proposed collecting sparse samples, necessitating a change in the data capturing process conventionally used in FDOCT. The IRLS-based method proposed in this paper does not suffer from this drawback.

Compressed domain human action recognition in H.264/AVC video streams

This paper discusses a novel high-speed approach for human action recognition in H.264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of the proposed work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can result in reduced hardware utilization and faster recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust to outdoor as well as indoor testing scenarios. We have evaluated the performance of the proposed method on two benchmark action datasets and achieved more than 85 % accuracy. The proposed algorithm classifies actions with speed (> 2,000 fps) approximately 100 times faster than existing state-of-the-art pixel-domain algorithms.

Study of wrist pulse signals using time domain spatial features

Blood travels throughout the body and thus its flow is modulated by changes in body condition. As a consequence, the wrist pulse signal contains important information about the status of the human body. In this work we have employed signal processing techniques to extract important information from these signals. Radial artery pulse pressure signals are acquired at wrist position noninvasively for several subjects for two cases of interest, viz. before and after exercise, and before and after lunch. Further analysis is performed by fitting a bi-modal Gaussian model to the data and extracting spatial features from the fit. The spatial features show statistically significant (p < 0.001) changes between the groups for both the cases, which indicates that they are effective in distinguishing the changes taking place due to exercise or food intake. Recursive cluster elimination based support vector machine classifier is used to classify between the groups. A high classification accuracy of 99.71% is achieved for the exercise case and 99.94% is achieved for the lunch case. This paper demonstrates the utility of certain spatial features in studying wrist pulse signals obtained under various experimental conditions. The ability of the spatial features in distinguishing changing body conditions can be potentially used for various healthcare applications. (C) 2015 Elsevier Ltd. All rights reserved.

PERIODIC CONTROLS IN AN OSCILLATING DOMAIN: CONTROLS VIA UNFOLDING AND HOMOGENIZATION

An optimal control problem in a two-dimensional domain with a rapidly oscillating boundary is considered. The main features of this article are on two points, namely, we consider periodic controls in the thin periodic slabs of period epsilon > 0, a small parameter, and height O(1) in the oscillatory part, and the controls are characterized using unfolding operators. We then do a homogenization analysis of the optimal control problems as epsilon -> 0 with L-2 as well as Dirichlet (gradient-type) cost functionals.

First Structural View of a Peptide Interacting with the Nucleotide Binding Domain of Heat Shock Protein 90

The involvement of Hsp90 in progression of diseases like cancer, neurological disorders and several pathogen related conditions is well established. Hsp90, therefore, has emerged as an attractive drug target for many of these diseases. Several small molecule inhibitors of Hsp90, such as geldanamycin derivatives, that display antitumor activity, have been developed and are under clinical trials. However, none of these tested inhibitors or drugs are peptide-based compounds. Here we report the first crystal structure of a peptide bound at the ATP binding site of the N-terminal domain of Hsp90. The peptide makes several specific interactions with the binding site residues, which are comparable to those made by the nucleotide and geldanamycin. A modified peptide was designed based on these interactions. Inhibition of ATPase activity of Hsp90 was observed in the presence of the modified peptide. This study provides an alternative approach and a lead peptide molecule for the rational design of effective inhibitors of Hsp90 function.

Evidence for N-7 guanine methyl transferase activity encoded within the modular domain of RNA-dependent RNA polymerase L of a Morbillivirus

Post-transcriptional modification of viral mRNA is essential for the translation of viral proteins by cellular translation machinery. Due to the cytoplasmic replication of Paramyxoviruses, the viral-encoded RNA-dependent RNA polymerase (RdRP) is thought to possess all activities required for mRNA capping and methylation. In the present work, using partially purified recombinant RNA polymerase complex of rinderpest virus expressed in insect cells, we demonstrate the in vitro methylation of capped mRNA. Further, we show that a recombinant C-terminal fragment (1717-2183 aa) of L protein is capable of methylating capped mRNA, suggesting that the various post-transcriptional activities of the L protein are located in independently folding domains.

Ultrafast Chemical Dynamics in Time Domain Through Fluorescence Spectroscopy

While absorption and emission spectroscopy have always been used to detect and characterize molecules and molecular complexes, the availability of ultrashort laser pulses and associated computer-aided optical detection techniques allowed study of chemical processes directly in the time domain at unprecedented time scales, through appearance and disappearance of fluorescence from participating chemical species. Application of such techniques to chemical dynamics in liquids, where many processes occur with picosecond and femtosecond time scales lead to the discovery of a host of new phenomena that in turn led to the development of many new theories. Experiment and theory together provided new and valuable insight into many fundamental chemical processes, like isomerization dynamics, electron and proton transfer reactions, vibrational energy and phase relaxation, photosynthesis, to name just a few. In this article, we shall review a few of such discoveries in attempt to provide a glimpse of the fascinating research employing fluorescence spectroscopy that changed the field of chemical dynamics forever.

Electrically driven intracellular and extracellular nanomanipulators evoke neurogenic/cardiomyogenic differentiation in human mesenchymal stem cells

Nanomechanical intervention through electroactuation is an effective strategy to guide stem cell differentiation for tissue engineering and regenerative medicine. In the present study, we elucidate that physical forces exerted by electroactuated gold nanoparticles (GNPs) have a strong influence in regulating the lineage commitment of human mesenchymal stem cells (hMSCs). A novel platform that combines intracellular and extracellular GNPs as nano-manipulators was designed to trigger neurogenic/cardiomyogenic differentiation in hMSCs, in electric field stimulated culture condition. In order to mimic the native microenvironment of nerve and cardiac tissues, hMSCs were treated with physiologically relevant direct current electric field (DC EF) or pulsed electric field (PEF) stimuli, respectively. When exposed to regular intermittent cycles of DC EF stimuli, majority of the GNP actuated hMSCs acquired longer filopodial extensions with multiple branch-points possessing neural-like architecture. Such morphological changes were consistent with higher mRNA expression level for neural-specific markers. On the other hand, PEF elicited cardiomyogenic differentiation, which is commensurate with the tubelike morphological alterations along with the upregulation of cardiac specific markers. The observed effect was significantly promoted even by intracellular actuation and was found to be substrate independent. Further, we have substantiated the participation of oxidative signaling, G0/G1 cell cycle arrest and intracellular calcium Ca2+] elevation as the key upstream regulators dictating GNP assisted hMSC differentiation. Thus, by adopting dual stimulation protocols, we could successfully divert the DC EF exposed cells to differentiate predominantly into neural-like cells and PEF treated cells into cardiomyogenic-like cells, via nanoactuation of GNPs. Such a novel multifaceted approach can be exploited to combat tissue loss following brain injury or heart failure. (C) 2015 Elsevier Ltd. All rights reserved.

Biochemical Characterization of Nonamer Binding Domain of RAG1 Reveals its Thymine Preference with Respect to Length and Position

RAG complex consisting of RAG1 and RAG2 is a site-specific endonuclease responsible for the generation of antigen receptor diversity. It cleaves recombination signal sequence (RSS), comprising of conserved heptamer and nonamer. Nonamer binding domain (NBD) of RAG1 plays a central role in the recognition of RSS. To investigate the DNA binding properties of the domain, NBD of murine RAG1 was cloned, expressed and purified. Electrophoretic mobility shift assays showed that NBD binds with high affinity to nonamer in the context of 12/23 RSS or heteroduplex DNA. NBD binding was specific to thymines when single stranded DNA containing poly A, C, G or T were used. Biolayer interferometry studies showed that poly T binding to NBD was robust and comparable to that of 12RSS. More than 23 nt was essential for NBD binding at homothymidine stretches. On a double-stranded DNA, NBD could bind to A:T stretches, but not G:C or random sequences. Although NBD is indispensable for sequence specific activity of RAGs, external supplementation of purified nonamer binding domain to NBD deleted cRAG1/cRAG2 did not restore its activity, suggesting that the overall domain architecture of RAG1 is important. Therefore, we define the sequence requirements of NBD binding to DNA.

A survey on compressed domain video analysis techniques

Image and video analysis requires rich features that can characterize various aspects of visual information. These rich features are typically extracted from the pixel values of the images and videos, which require huge amount of computation and seldom useful for real-time analysis. On the contrary, the compressed domain analysis offers relevant information pertaining to the visual content in the form of transform coefficients, motion vectors, quantization steps, coded block patterns with minimal computational burden. The quantum of work done in compressed domain is relatively much less compared to pixel domain. This paper aims to survey various video analysis efforts published during the last decade across the spectrum of video compression standards. In this survey, we have included only the analysis part, excluding the processing aspect of compressed domain. This analysis spans through various computer vision applications such as moving object segmentation, human action recognition, indexing, retrieval, face detection, video classification and object tracking in compressed videos.

EXACT INTERNAL CONTROLLABILITY FOR THE WAVE EQUATION IN A DOMAIN WITH OSCILLATING BOUNDARY WITH NEUMANN BOUNDARY CONDITION

In this paper, we study the exact controllability of a second order linear evolution equation in a domain with highly oscillating boundary with homogeneous Neumann boundary condition on the oscillating part of boundary. Our aim is to obtain the exact controllability for the homogenized equation. The limit problem with Neumann condition on the oscillating boundary is different and hence we need to study the exact controllability of this new type of problem. In the process of homogenization, we also study the asymptotic analysis of evolution equation in two setups, namely solution by standard weak formulation and solution by transposition method.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

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.