Functional regulation of PVBV Nuclear Inclusion protein-a protease activity upon interaction with Viral Protein genome-linked and phosphorylation

Regulation of NIa-Pro is crucial for polyprotein processing and hence, for successful infection of potyviruses. We have examined two novel mechanisms that could regulate NIa-Pro activity. Firstly, the influence of VPg domain on the proteolytic activity of NIa-Pro was investigated. It was shown that the turnover number of the protease increases when these two domains interact (as: two-fold; trans: seven-fold) with each other. Secondly, the protease activity of NIa-Pro could also be modulated by phosphorylation at Ser129. A mutation of this residue either to aspartate (phosphorylation-mimic) or alanine (phosphorylation-deficient) drastically reduces the protease activity. Based on these observations and molecular modeling studies, we propose that interaction with VPg as well as phosphorylation of Ser129 could relay a signal through Trp143 present at the protein surface to the active site pocket by subtle conformational changes, thus modulating protease activity of NIa-Pro. (C) 2011 Elsevier Inc. All rights reserved.

Error, Confidence, and Cost in Engineering Computations

The questions that one should answer in engineering computations - deterministic, probabilistic/randomized, as well as heuristic - are (i) how good the computed results/outputs are and (ii) how much the cost in terms of amount of computation and the amount of storage utilized in getting the outputs is. The absolutely errorfree quantities as well as the completely errorless computations done in a natural process can never be captured by any means that we have at our disposal. While the computations including the input real quantities in nature/natural processes are exact, all the computations that we do using a digital computer or are carried out in an embedded form are never exact. The input data for such computations are also never exact because any measuring instrument has inherent error of a fixed order associated with it and this error, as a matter of hypothesis and not as a matter of assumption, is not less than 0.005 per cent. Here by error we imply relative error bounds. The fact that exact error is never known under any circumstances and any context implies that the term error is nothing but error-bounds. Further, in engineering computations, it is the relative error or, equivalently, the relative error-bounds (and not the absolute error) which is supremely important in providing us the information regarding the quality of the results/outputs. Another important fact is that inconsistency and/or near-consistency in nature, i.e., in problems created from nature is completely nonexistent while in our modelling of the natural problems we may introduce inconsistency or near-inconsistency due to human error or due to inherent non-removable error associated with any measuring device or due to assumptions introduced to make the problem solvable or more easily solvable in practice. Thus if we discover any inconsistency or possibly any near-inconsistency in a mathematical model, it is certainly due to any or all of the three foregoing factors. We do, however, go ahead to solve such inconsistent/near-consistent problems and do get results that could be useful in real-world situations. The talk considers several deterministic, probabilistic, and heuristic algorithms in numerical optimisation, other numerical and statistical computations, and in PAC (probably approximately correct) learning models. It highlights the quality of the results/outputs through specifying relative error-bounds along with the associated confidence level, and the cost, viz., amount of computations and that of storage through complexity. It points out the limitation in error-free computations (wherever possible, i.e., where the number of arithmetic operations is finite and is known a priori) as well as in the usage of interval arithmetic. Further, the interdependence among the error, the confidence, and the cost is discussed.

Minimal unsatisfiable sets: Classification and bounds

Proving the unsatisfiability of propositional Boolean formulas has applications in a wide range of fields. Minimal Unsatisfiable Sets (MUS) are signatures of the property of unsatisfiability in formulas and our understanding of these signatures can be very helpful in answering various algorithmic and structural questions relating to unsatisfiability. In this paper, we explore some combinatorial properties of MUS and use them to devise a classification scheme for MUS. We also derive bounds on the sizes of MUS in Horn, 2-SAT and 3-SAT formulas.

Gap model of one-way cyclic lateral load on vertical files in soft clay

For the analysis and design of pile foundation used for coastal structures the prediction of cyclic response, which is influenced by the nonlinear behavior, gap (pile soil separation) and degradation (reduction in strength) of soil becomes necessary. To study the effect of the above parameters a nonlinear cyclic load analysis program using finite element method is developed, incorporating the proposed gap and degradation model and adopting an incremental-iterative procedure. The pile is idealized using beam elements and the soil by number of elastoplastic sub-element springs at each node. The effect of gap and degradation on the load-deflection behavior. elasto-plastic sub-element and resistance of the soil at ground-line have been clearly depicted in this paper.

Synthesis, growth, and characterization of a new NLO material 3-(2,3-dimethoxyphenyl)-1-(pyridin-2-yl)prop-2-en-1-one

3-(2,3-Dimethoxyphenyl)-1-(pyridin-2-yl)prop-2-en-1-one (DMPP) a potential second harmonic generating (SHG) has been synthesized and grown as a single crystal by the slow evaporation technique at ambient temperature. The structure determination of the grown crystal was done by single crystal X-ray diffraction study. DMPP crystallizes with orthorhombic system with cell parameters a = 20.3106(8)angstrom, b = 4.9574(2)angstrom, c = 13.4863(5)angstrom, alpha = 90 degrees, beta = 90 degrees, gamma = 90 degrees and space group Pca2(1). The crystals were characterized by FT-IR, thermal analysis, UV-vis-NIR spectroscopy and SHG measurements. Various functional groups present in DMPP were ascertained by FTIR analysis. DMPP is thermally stable up to 80 degrees C and optically transparent in the visible region. The crystal exhibits SHG efficiency comparable to that of KDP. (C) 2011 Elsevier B.V. All rights reserved.

A pseudo-time EnKF incorporating shape based reconstruction for diffuse optical tomography

Purpose: The authors aim at developing a pseudo-time, sub-optimal stochastic filtering approach based on a derivative free variant of the ensemble Kalman filter (EnKF) for solving the inverse problem of diffuse optical tomography (DOT) while making use of a shape based reconstruction strategy that enables representing a cross section of an inhomogeneous tumor boundary by a general closed curve. Methods: The optical parameter fields to be recovered are approximated via an expansion based on the circular harmonics (CH) (Fourier basis functions) and the EnKF is used to recover the coefficients in the expansion with both simulated and experimentally obtained photon fluence data on phantoms with inhomogeneous inclusions. The process and measurement equations in the pseudo-dynamic EnKF (PD-EnKF) presently yield a parsimonious representation of the filter variables, which consist of only the Fourier coefficients and the constant scalar parameter value within the inclusion. Using fictitious, low-intensity Wiener noise processes in suitably constructed ``measurement'' equations, the filter variables are treated as pseudo-stochastic processes so that their recovery within a stochastic filtering framework is made possible. Results: In our numerical simulations, we have considered both elliptical inclusions (two inhomogeneities) and those with more complex shapes (such as an annular ring and a dumbbell) in 2-D objects which are cross-sections of a cylinder with background absorption and (reduced) scattering coefficient chosen as mu(b)(a)=0.01mm(-1) and mu('b)(s)=1.0mm(-1), respectively. We also assume mu(a) = 0.02 mm(-1) within the inhomogeneity (for the single inhomogeneity case) and mu(a) = 0.02 and 0.03 mm(-1) (for the two inhomogeneities case). The reconstruction results by the PD-EnKF are shown to be consistently superior to those through a deterministic and explicitly regularized Gauss-Newton algorithm. We have also estimated the unknown mu(a) from experimentally gathered fluence data and verified the reconstruction by matching the experimental data with the computed one. Conclusions: The PD-EnKF, which exhibits little sensitivity against variations in the fictitiously introduced noise processes, is also proven to be accurate and robust in recovering a spatial map of the absorption coefficient from DOT data. With the help of shape based representation of the inhomogeneities and an appropriate scaling of the CH expansion coefficients representing the boundary, we have been able to recover inhomogeneities representative of the shape of malignancies in medical diagnostic imaging. (C) 2012 American Association of Physicists in Medicine. [DOI: 10.1118/1.3679855]

Loading of single-walled carbon nanotubes in cationic cholesterol suspensions significantly improves gene transfection efficiency in serum

We present here a series of cholesterol based cationic lipid suspensions that solubilize single-walled carbon nanotubes (SWCNT) efficiently in water. Each cationic lipid formulation was characterized in terms of their energy minimized molecular structures, bilayer widths of the aggregates based on X-ray diffraction. Then these aggregates were investigated pertaining to their DNA binding and release efficiency, effect of CNT inclusion on the stability of cationic cholesterol lipid-DNA complexes, Zeta potential values and changes in the chiro-optical property of DNA, effect on Raman spectral shift and changes in morphology by SEM and AFM. Each cationic lipid formulation was optimized for the amount of SWCNT solubilized in water, lipid-DNA ratio, amount of the plasmid DNA that can be transfected and the effect on the cellular toxicity. The resulting SWCNT-lipid formulations were then used for in vitro transfection of pEGFP-C3 in A549 (human alveolar basal epithelial) cells and HeLa (human cervical cancer) cells. Advantageously, the CNT-loaded formulations confer an excellent transfection efficiency even in high percentages of blood serum and showed significantly better gene transfer efficiency compared to one of the potent, well-known commercial transfection reagent, Lipofectamine2000.

Partition function for hindered, one-and multi-dimensional rotors

Writing the hindered rotor (hr) partition function as the trace of (rho) over cap = e(-beta(H) over cap hr), we approximate it by the sum of contributions from a set of points in position space. The contribution of the density matrix from each point is approximated by performing a local harmonic expansion around it. The highlight of this method is that it can be easily extended to multidimensional systems. Local harmonic expansion leads to a breakdown of the method a low temperatures. In order to calculate the partition function at low temperatures, we suggest a matrix multiplication procedure. The results obtained using these methods closely agree with the exact partition function at all temperature ranges. Our method bypasses the evaluation of eigenvalues and eigenfunctions and evaluates the density matrix for internal rotation directly. We also suggest a procedure to account for the antisymmetry of the total wavefunction in the same. (C) 2012 Elsevier B.V. All rights reserved.

Smart polymer mediated purification and recovery of active proteins from inclusion bodies

Obtaining correctly folded proteins from inclusion bodies of recombinant proteins expressed in bacterial hosts requires solubilization with denaturants and a refolding step. Aggregation competes with the second step. Refolding of eight different proteins was carried out by precipitation with smart polymers. These proteins have different molecular weights, different number of disulfide bridges and some of these are known to be highly prone to aggregation. A high throughput refolding screen based upon fluorescence emission maximum around 340 nm (for correctly folded proteins) was developed to identify the suitable smart polymer. The proteins could be dissociated and recovered after the refolding step. The refolding could be scaled up and high refolding yields in the range of 8 mg L-1 (for CD4D12, the first two domains of human CD4) to 58 mg L-1 (for malETrx, thioredoxin fused with signal peptide of maltose binding protein) were obtained. Dynamic light scattering (DLS) showed that polymer if chosen correctly acted as a pseuclochaperonin and bound to the proteins. It also showed that the time for maximum binding was about 50 min which coincided with the time required for incubation (with the polymer) before precipitation for maximum recovery of folded proteins. The refolded proteins were characterized by fluorescence emission spectra, circular dichroism (CD) spectroscopy, melting temperature (T-m), and surface hydrophobicity measurement by ANS (8-anilinol-naphthalene sulfonic acid) fluorescence. Biological activity assay for thioredoxin and fluorescence based assay in case of maltose binding protein (MBP) were also carried out to confirm correct refolding. (C) 2012 Elsevier B.V. All rights reserved.

Enantiospecific total synthesis of 15-hydroxy-5-(methoxymethoxy)crinipellin-9-one

Enantiospecific total synthesis of the crinipellin mentioned in the title was accomplished. In the present synthesis cyclopentane ring in campholenaldehyde was identified as the B-ring, two intramolecular rhodium carbenoid CH insertion reactions were employed for the construction of the A and C rings, and an intramolecular Michael addition reaction was utilized for the construction of the D-ring of crinipellin. (C) 2012 Elsevier Ltd. All rights reserved.

Higher spin quasinormal modes and one-loop determinants in the BTZ black hole

We solve the wave equations of arbitrary integer spin fields in the BTZ black hole background and obtain exact expressions for their quasinormal modes. We show that these quasinormal modes precisely agree with the location of the poles of the corresponding two point function in the dual conformal field theory as predicted by the AdS/CFT correspondence. We then use these quasinormal modes to construct the one-loop determinant of the higher spin field in the thermal BTZ background. This is shown to agree with that obtained from the corresponding heat kernel constructed recently by group theoretic methods.

Percolation and connectivity in AB random geometric graphs

Given two independent Poisson point processes Phi((1)), Phi((2)) in R-d, the AB Poisson Boolean model is the graph with the points of Phi((1)) as vertices and with edges between any pair of points for which the intersection of balls of radius 2r centered at these points contains at least one point of Phi((2)). This is a generalization of the AB percolation model on discrete lattices. We show the existence of percolation for all d >= 2 and derive bounds fora critical intensity. We also provide a characterization for this critical intensity when d = 2. To study the connectivity problem, we consider independent Poisson point processes of intensities n and tau n in the unit cube. The AB random geometric graph is defined as above but with balls of radius r. We derive a weak law result for the largest nearest-neighbor distance and almost-sure asymptotic bounds for the connectivity threshold.

Incremental Cycle Detection, Topological Ordering, and Strong Component Maintenance

We present two online algorithms for maintaining a topological order of a directed n-vertex acyclic graph as arcs are added, and detecting a cycle when one is created. Our first algorithm handles m arc additions in O(m(3/2)) time. For sparse graphs (m/n = O(1)), this bound improves the best previous bound by a logarithmic factor, and is tight to within a constant factor among algorithms satisfying a natural locality property. Our second algorithm handles an arbitrary sequence of arc additions in O(n(5/2)) time. For sufficiently dense graphs, this bound improves the best previous bound by a polynomial factor. Our bound may be far from tight: we show that the algorithm can take Omega(n(2)2 root(2lgn)) time by relating its performance to a generalization of the k-levels problem of combinatorial geometry. A completely different algorithm running in Theta (n(2) log n) time was given recently by Bender, Fineman, and Gilbert. We extend both of our algorithms to the maintenance of strong components, without affecting the asymptotic time bounds.

Network properties of protein-decoy structures

Convergence of the vast sequence space of proteins into a highly restricted fold/conformational space suggests a simple yet unique underlying mechanism of protein folding that has been the subject of much debate in the last several decades. One of the major challenges related to the understanding of protein folding or in silico protein structure prediction is the discrimination of non-native structures/decoys from the native structure. Applications of knowledge-based potentials to attain this goal have been extensively reported in the literature. Also, scoring functions based on accessible surface area and amino acid neighbourhood considerations were used in discriminating the decoys from native structures. In this article, we have explored the potential of protein structure network (PSN) parameters to validate the native proteins against a large number of decoy structures generated by diverse methods. We are guided by two principles: (a) the PSNs capture the local properties from a global perspective and (b) inclusion of non-covalent interactions, at all-atom level, including the side-chain atoms, in the network construction accommodates the sequence dependent features. Several network parameters such as the size of the largest cluster, community size, clustering coefficient are evaluated and scored on the basis of the rank of the native structures and the Z-scores. The network analysis of decoy structures highlights the importance of the global properties contributing to the uniqueness of native structures. The analysis also exhibits that the network parameters can be used as metrics to identify the native structures and filter out non-native structures/decoys in a large number of data-sets; thus also has a potential to be used in the protein `structure prediction' problem.

Synthesis of one-dimensional N-doped Ga2O3 nanostructures: different morphologies and different mechanisms

N-doped monoclinic Ga2O3 nanostructures of different morphologies have been synthesized by heating Ga metal in ambient air at 1150 degrees C to 1350 degrees C for 1 to 5 h duration. Neither catalyst nor any gas flow has been used for the synthesis of N-doped Ga2O3 nanostructures. The morphology was controlled by monitoring the curvature of the Ga droplet. Plausible growth mechanisms are discussed to explain the different morphology of the nanostructures. Elemental mapping by electron energy loss spectroscopy of the nanostructures indicate uniform distribution of Ga, O and N. It is interesting to note that we have used neither nitride source nor any gas flow but the synthesis was carried out in ambient air. We believe that ambient nitrogen acts as the source of nitrogen. Unintentional nitrogen doping of the Ga2O3 nanostructures is a straightforward method and such nanostructures could be promising candidates for white light emission.