sopB of Salmonella enterica serovar Typhimurium is a potential DNA vaccine candidate in conjugation with live attenuated bacteria

The immune response against Salmonella is multi-faceted involving both the innate and the adaptive immune system. The characterization of specific Salmonella antigens inducing immune response could critically contribute to the development of epitope based vaccines for Salmonella. We have tried to identify a protective T cell epitope(s) of Salmonella, as cell mediated immunity conferred by CD8+ T cells is the most crucial subset conferring protective immunity against Salmonella. It being a proven fact that secreted proteins are better in inducing cell mediated immunity than cell surface and cytosolic antigens, we have analyzed all the genbank annotated Salmonella pathogenicity island 1 and 2 secreted proteins of Salmonella enterica serovar Typhimurium (S. typhimurium) and S. enterica serovar Typhi (S. typhi). They were subjected to BIMAS and SYFPEITHI analysis to map MHC-I and MHC-II binding epitopes. The huge profile of possible T cell epitopes obtained from the two classes of secreted proteins were tabulated and using a scoring system that considers the binding affinity and promiscuity of binding to more than one allele, SopB and SifB were chosen for experimental confirmation in murine immunization model. The entire SopB and SifB genes were cloned into DNA vaccine vectors and were administered along with live attenuated Salmonella and it was found that SopB vaccination reduced the bacterial burden of organs by about 5-fold on day 4 and day 8 after challenge with virulent Salmonella and proved to be a more efficient vaccination strategy than live attenuated bacteria alone.

Assimilation of remote sensing and hydrological data using adaptive filtering techniques for watershed modelling

The knowledge of hydrological variables (e. g. soil moisture, evapotranspiration) are of pronounced importance in various applications including flood control, agricultural production and effective water resources management. These applications require the accurate prediction of hydrological variables spatially and temporally in watershed/basin. Though hydrological models can simulate these variables at desired resolution (spatial and temporal), often they are validated against the variables, which are either sparse in resolution (e. g. soil moisture) or averaged over large regions (e. g. runoff). A combination of the distributed hydrological model (DHM) and remote sensing (RS) has the potential to improve resolution. Data assimilation schemes can optimally combine DHM and RS. Retrieval of hydrological variables (e. g. soil moisture) from remote sensing and assimilating it in hydrological model requires validation of algorithms using field studies. Here we present a review of methodologies developed to assimilate RS in DHM and demonstrate the application for soil moisture in a small experimental watershed in south India.

Functional Analysis of an Acid Adaptive DNA Adenine Methyltransferase from Helicobacter pylori 26695

HP0593 DNA-(N-6-adenine)-methyltransferase (HP0593 MTase) is a member of a Type III restriction-modification system in Helicobacter pylori strain 26695. HP0593 MTase has been cloned, overexpressed and purified heterologously in Escherichia coli. The recognition sequence of the purified MTase was determined as 5'-GCAG-3' and the site of methylation was found to be adenine. The activity of HP0593 MTase was found to be optimal at pH 5.5. This is a unique property in context of natural adaptation of H. pylori in its acidic niche. Dot-blot assay using antibodies that react specifically with DNA containing m6A modification confirmed that HP0593 MTase is an adenine-specific MTase. HP0593 MTase occurred as both monomer and dimer in solution as determined by gel-filtration chromatography and chemical-crosslinking studies. The nonlinear dependence of methylation activity on enzyme concentration indicated that more than one molecule of enzyme was required for its activity. Analysis of initial velocity with AdoMet as a substrate showed that two molecules of AdoMet bind to HP0593 MTase, which is the first example in case of Type III MTases. Interestingly, metal ion cofactors such as Co2+, Mn2+, and also Mg2+ stimulated the HP0593 MTase activity. Preincubation and isotope partitioning analyses clearly indicated that HP0593 MTase-DNA complex is catalytically competent, and suggested that DNA binds to the MTase first followed by AdoMet. HP0593 MTase shows a distributive mechanism of methylation on DNA having more than one recognition site. Considering the occurrence of GCAG sequence in the potential promoter regions of physiologically important genes in H. pylori, our results provide impetus for exploring the role of this DNA MTase in the cellular processes of H. pylori.

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the �Single Network Adaptive Critic (SNAC)� is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Model-following Neuro-adaptive approach for robust control of high performance aircrafts

Based on dynamic inversion, a relatively straightforward approach is presented in this paper for nonlinear flight control design of high performance aircrafts, which does not require the normal and lateral acceleration commands to be first transferred to body rates before computing the required control inputs. This leads to substantial improvement of the tracking response. Promising results are obtained from six degree-offreedom simulation studies of F-16 aircraft, which are found to be superior as compared to an existing approach (which is also based on dynamic inversion). The new approach has two potential benefits, namely reduced oscillatory response (including elimination of non-minimum phase behavior) and reduced control magnitude. Next, a model-following neuron-adaptive design is augmented the nominal design in order to assure robust performance in the presence of parameter inaccuracies in the model. Note that in the approach the model update takes place adaptively online and hence it is philosophically similar to indirect adaptive control. However, unlike a typical indirect adaptive control approach, there is no need to update the individual parameters explicitly. Instead the inaccuracy in the system output dynamics is captured directly and then used in modifying the control. This leads to faster adaptation, which helps in stabilizing the unstable plant quicker. The robustness study from a large number of simulations shows that the adaptive design has good amount of robustness with respect to the expected parameter inaccuracies in the model.

Immunomodulation using agonists and antagonists: potential clinical applications

Introduction: Extensive studies have gone into understanding the differential role of the innate and adaptive arms of the immune system in the context of various diseases. Receptor-ligand interactions are responsible for mediating cross-talk between the innate and adaptive arms of the immune system, so as to effectively counter the pathogenic challenge. While TLRs remain the best studied innate immune receptor, many other receptor families are now coming to the fore for their role in various pathologies. Research has focused on the discovery of novel agonists and antagonists for these receptors as potential therapeutics. Areas covered: In this review, we present an overview of the recent advances in the discovery of drugs targeting important receptors such as G-protein coupled receptors, TRAIL-R, IL-1 beta receptor, PPARs, etc. All these receptors play a critical role in the modulation of the immune response. We focus on the recent paradigms applied for the generation of specific and effective therapeutics for these receptors and their status in clinical trials. Expert opinion: Non-specific activation by antagonist/agonist is a difficult problem to dodge. This demands innovation in ligand designing with the use of strategies such as allosterism and dual-specific ligands. Rigorous preclinical and clinical studies are required in transforming a compound to a therapeutic.

A meshless adaptive multiscale method for fracture

The paper presents a multiscale method for crack propagation. The coarse region is modelled by the differential reproducing kernel particle method. Fracture in the coarse scale region is modelled with the Phantom node method. A molecular statics approach is employed in the fine scale where crack propagation is modelled naturally by breaking of bonds. The triangular lattice corresponds to the lattice structure of the (111) plane of an FCC crystal in the fine scale region. The Lennard-Jones potential is used to model the atom-atom interactions. The coupling between the coarse scale and fine scale is realized through ghost atoms. The ghost atom positions are interpolated from the coarse scale solution and enforced as boundary conditions on the fine scale. The fine scale region is adaptively refined and coarsened as the crack propagates. The centro symmetry parameter is used to detect the crack tip location. The method is implemented in two dimensions. The results are compared to pure atomistic simulations and show excellent agreement. (C) 2014 Elsevier B. V. All rights reserved.

Modeling of Channel Potential and Subthreshold Slope of Symmetric Double-Gate Transistor

A new physically based classical continuous potential distribution model, particularly considering the channel center, is proposed for a short-channel undoped body symmetrical double-gate transistor. It involves a novel technique for solving the 2-D nonlinear Poisson's equation in a rectangular coordinate system, which makes the model valid from weak to strong inversion regimes and from the channel center to the surface. We demonstrated, using the proposed model, that the channel potential versus gate voltage characteristics for the devices having equal channel lengths but different thicknesses pass through a single common point (termed ``crossover point''). Based on the potential model, a new compact model for the subthreshold swing is formulated. It is shown that for the devices having very high short-channel effects (SCE), the effective subthreshold slope factor is mainly dictated by the potential close to the channel center rather than the surface. SCEs and drain-induced barrier lowering are also assessed using the proposed model and validated against a professional numerical device simulator.

A Quasi-Newton Adaptive Algorithm for Generalized Symmetric Eigenvalue Problem

In this paper, we first recast the generalized symmetric eigenvalue problem, where the underlying matrix pencil consists of symmetric positive definite matrices, into an unconstrained minimization problem by constructing an appropriate cost function, We then extend it to the case of multiple eigenvectors using an inflation technique, Based on this asymptotic formulation, we derive a quasi-Newton-based adaptive algorithm for estimating the required generalized eigenvectors in the data case. The resulting algorithm is modular and parallel, and it is globally convergent with probability one, We also analyze the effect of inexact inflation on the convergence of this algorithm and that of inexact knowledge of one of the matrices (in the pencil) on the resulting eigenstructure. Simulation results demonstrate that the performance of this algorithm is almost identical to that of the rank-one updating algorithm of Karasalo. Further, the performance of the proposed algorithm has been found to remain stable even over 1 million updates without suffering from any error accumulation problems.

The potential role of a late gene expression factor, lef2, from Bombyx mori nuclear polyhedrosis virus in very late gene transcription and DNA replication

Several late gene expression factors (Lefs) have been implicated in fostering high levels of transcription from the very late gene promoters of polyhedrin and p10 from baculoviruses. We cloned and characterized from Bombyx mori nuclear polyhedrosis virus a late gene expression factor (Bmlef2) that encodes a 209-amino-acid protein harboring a Cys-rich C-terminal domain. The temporal transcription profiles of lef2 revealed a 1.2-kb transcript in both delayed early and late periods after virus infection. Transcription start site mapping identified the presence of an aphidicolin-sensitive late transcript arising from a TAAG motif located at -352 nucleotides and an aphidicolin-insensitive early transcript originating from a TTGT motif located 35 nucleotides downstream to a TATA box at -312 nucleotides, with respect to the +1 ATG of lef2. BmLef2 trans-activated very late gene expression from both polyhedrin and p10 promoters in transient expression assays. Internal deletion of the Cys-rich domain from the C-terminal region abolished the transcriptional activation. Inactivation of Lef2 synthesis by antisense lef2 transcripts drastically reduced the very late gene transcription but showed little effect on the expression from immediate early promoter. Decrease in viral DNA synthesis and a reduction in virus titer were observed only when antisense lef2 was expressed under the immediate early (ie-1) promoter. Furthermore, the antisense experiments suggested that lef2 plays a direct role in very late gene transcription.

Field and potential around local scatterers in thin metal films studied by scanning tunneling potentiometry

We report the direct observation of electrochemical potential and local transport field variations near scatterers like grain boundaries, triple points, and voids in thin platinum films studied by scanning tunneling potentiometry. The field is highest at a void, followed by a triple point and a grain boundary. The local transport field near a void can even be four orders of magnitude higher than the macroscopic field, indicating that the void is the most likely place for an electromigration induced failure. The field build up for a particular type of scatterer depends on the grain connectivity. We estimate an average grain boundary reflection coefficient for the film from the temperature dependence of its resistivity.

A direct adaptive neural command controller design for an unstable helicopter

This paper presents an off-line (finite time interval) and on-line learning direct adaptive neural controller for an unstable helicopter. The neural controller is designed to track pitch rate command signal generated using the reference model. A helicopter having a soft inplane four-bladed hingeless main rotor and a four-bladed tail rotor with conventional mechanical controls is used for the simulation studies. For the simulation study, a linearized helicopter model at different straight and level flight conditions is considered. A neural network with a linear filter architecture trained using backpropagation through time is used to approximate the control law. The controller network parameters are adapted using updated rules Lyapunov synthesis. The off-line trained (for finite time interval) network provides the necessary stability and tracking performance. The on-line learning is used to adapt the network under varying flight conditions. The on-line learning ability is demonstrated through parameter uncertainties. The performance of the proposed direct adaptive neural controller (DANC) is compared with feedback error learning neural controller (FENC).

Transition metal complexes of a potential anticancer quinazoline ligand

A new heterocycle, namely 2-(furyl)-3-(furfuralimino)-1,2-dihydroquinazolin-4(3H)-one (ffdq) was formed by the ondensation of 2-aminobenzoylhydrazide with furfural and characterized by physico-chemical, spectroscopic, and single crystal X-ray diffraction studies. A series of complexes of ffdq have been synthesized and characterized by physico-chemical, spectroscopic, and thermal studies. According to the i.r. and 1H-n.m.r. spectra ffdq behaves as a bidentate ligand coordinating through quinazoline oxygen and azomethine nitrogen. The FAB-mass spectrum of the Cd(II) complex indicates the monomeric nature of this complex. The X-band e.p.r. spectrum of the Cu(II) complex and thermal stabilities of the Co(II) and Ni(II) complexes are discussed.

Approximate potential-distance relationship for clays

The conventional procedure of determining the surface potential of clay platelet and the variation of potential with distance is lengthy and time consuming. Simplified graphical procedures using Gouy theory have been developed and presented. The new procedures are simple, accurate and very much less time consuming.

A pattern adaptive thinning algorithm

A simple sequential thinning algorithm for peeling off pixels along contours is described. An adaptive algorithm obtained by incorporating shape adaptivity into this sequential process is also given. The distortions in the skeleton at the right-angle and acute-angle corners are minimized in the adaptive algorithm. The asymmetry of the skeleton, which is a characteristic of sequential algorithm, and is due to the presence of T-corners in some of the even-thickness pattern is eliminated. The performance (in terms of time requirements and shape preservation) is compared with that of a modern thinning algorithm.