Cryptic AUG is important for 48S ribosomal assembly during internal initiation of translation of coxsackievirus B3 RNA

We have investigated the possible role of a conserved cis-acting element, the cryptic AUG, present in the 5' UTR of coxsackievirus B3 (CVB3) RNA. CVB3 5' UTR contains multiple AUG codons upstream of the initiator AUG, which are not used for the initiation of translation. The 48S ribosomal assembly takes place upstream of the cryptic AUG. We show here that mutation in the cryptic AUG results in reduced efficiency of translation mediated by the CVB3 IRES; mutation also reduces the interaction of mutant IRES with a well characterized IRES trans-acting factor, the human La protein. Furthermore, partial silencing of the La gene showed a decrease in IRES activity in the case of both the wild-type and mutant. We have demonstrated here that the interaction of the 48S ribosomal complex with mutant RNA was weaker compared with wild-type RNA by ribosome assembly analysis. We have also investigated by chemical and enzymic modifications the possible alteration in secondary structure in the mutant RNA. Results suggest that the secondary structure of mutant RNA was only marginally altered. Additionally, we have demonstrated by generating compensatory and non-specific mutations the specific function of the cryptic AUG in internal initiation. Results suggest that the effect of the cryptic AUG is specific and translation could not be rescued. However, a possibility of tertiary interaction of the cryptic AUG with other cis-acting elements cannot be ruled out. Taken together, it appears that the integrity of the cryptic AUG is important for efficient translation initiation by the CVB3 IRES RNA.

Effective thermal conductivity of a heat generating rod bundle dissipating heat by natural convection and radiation

A numerical study of conjugate natural convection and surface radiation in a horizontal hexagonal sheath housing 19 solid heat generating rods with cladding and argon as the fill gas, is performed. The natural convection in the sheath is driven by the volumetric heat generation in the solid rods. The problem is solved using the FLUENT CFD code. A correlation is obtained to predict the maximum temperature in the rod bundle for different pitch-to-diameter ratios and heat generating rates. The effective thermal conductivity is related to the heat generation rate, maximum temperature and the sheath temperature. Results are presented for the dimensionless maximum temperature, Rayleigh number and the contribution of radiation with changing emissivity, total wattage and the pitch-to-diameter ratio. In the simulation of a larger system that contains a rod bundle, the effective thermal conductivity facilitates simplified modelling of the rod bundle by treating it as a solid of effective thermal conductivity. The parametric studies revealed that the contribution of radiation can be 38-65% of the total heat generation, for the parameter ranges chosen. Data for critical Rayleigh number above which natural convection comes into effect is also presented. (C) 2011 Elsevier B.V. All rights reserved.

Chimeras of Escherichia coli and Mycobacterium tuberculosis Single-Stranded DNA Binding Proteins: Characterization and Function in Escherichia coli

Single stranded DNA binding proteins (SSBs) are vital for the survival of organisms. Studies on SSBs from the prototype, Escherichia coli (EcoSSB) and, an important human pathogen, Mycobacterium tuberculosis (MtuSSB) had shown that despite significant variations in their quaternary structures, the DNA binding and oligomerization properties of the two are similar. Here, we used the X-ray crystal structure data of the two SSBs to design a series of chimeric proteins (m beta 1, m beta 1'beta 2, m beta 1-beta 5, m beta 1-beta 6 and m beta 4-beta 5) by transplanting beta 1, beta 1'beta 2, beta 1-beta 5, beta 1-beta 6 and beta 4-beta 5 regions, respectively of the N-terminal (DNA binding) domain of MtuSSB for the corresponding sequences in EcoSSB. In addition, m beta 1'beta 2(ESWR) SSB was generated by mutating the MtuSSB specific `PRIY' sequence in the beta 2 strand of m beta 1'beta 2 SSB to EcoSSB specific `ESWR' sequence. Biochemical characterization revealed that except for m beta 1 SSB, all chimeras and a control construct lacking the C-terminal domain (Delta C SSB) bound DNA in modes corresponding to limited and unlimited modes of binding. However, the DNA on MtuSSB may follow a different path than the EcoSSB. Structural probing by protease digestion revealed that unlike other SSBs used, m beta 1 SSB was also hypersensitive to chymotrypsin treatment. Further, to check for their biological activities, we developed a sensitive assay, and observed that m beta 1-beta 6, MtuSSB, m beta 1'beta 2 and m beta 1-beta 5 SSBs complemented E. coli Delta ssb in a dose dependent manner. Complementation by the m beta 1-beta 5 SSB was poor. In contrast, m beta 1'beta 2(ESWR) SSB complemented E. coli as well as EcoSSB. The inefficiently functioning SSBs resulted in an elongated cell/filamentation phenotype of E. coli. Taken together, our observations suggest that specific interactions within the DNA binding domain of the homotetrameric SSBs are crucial for their biological function.

Distributed Function Computation over Fields and Rings via Linear Compression of Sources

The setting considered in this paper is one of distributed function computation. More specifically, there is a collection of N sources possessing correlated information and a destination that would like to acquire a specific linear combination of the N sources. We address both the case when the common alphabet of the sources is a finite field and the case when it is a finite, commutative principal ideal ring with identity. The goal is to minimize the total amount of information needed to be transmitted by the N sources while enabling reliable recovery at the destination of the linear combination sought. One means of achieving this goal is for each of the sources to compress all the information it possesses and transmit this to the receiver. The Slepian-Wolf theorem of information theory governs the minimum rate at which each source must transmit while enabling all data to be reliably recovered at the receiver. However, recovering all the data at the destination is often wasteful of resources since the destination is only interested in computing a specific linear combination. An alternative explored here is one in which each source is compressed using a common linear mapping and then transmitted to the destination which then proceeds to use linearity to directly recover the needed linear combination. The article is part review and presents in part, new results. The portion of the paper that deals with finite fields is previously known material, while that dealing with rings is mostly new.Attempting to find the best linear map that will enable function computation forces us to consider the linear compression of source. While in the finite field case, it is known that a source can be linearly compressed down to its entropy, it turns out that the same does not hold in the case of rings. An explanation for this curious interplay between algebra and information theory is also provided in this paper.

Abstract Characteristic Function

The characteristic function for a contraction is a classical complete unitary invariant devised by Sz.-Nagy and Foias. Just as a contraction is related to the Szego kernel k(S)(z, w) = ( 1 - z(w)over bar)- 1 for |z|, |w| < 1, by means of (1/k(S))( T, T *) = 0, we consider an arbitrary open connected domain Omega in C(n), a kernel k on Omega so that 1/k is a polynomial and a tuple T = (T(1), T(2), ... , T(n)) of commuting bounded operators on a complex separable Hilbert spaceHsuch that (1/k)( T, T *) >= 0. Under some standard assumptions on k, it turns out that whether a characteristic function can be associated with T or not depends not only on T, but also on the kernel k. We give a necessary and sufficient condition. When this condition is satisfied, a functional model can be constructed. Moreover, the characteristic function then is a complete unitary invariant for a suitable class of tuples T.

Structure-function relationship in serine hydroxymethyltransferase

Serine hydroxymethyltransferase (SHMT), a pyridoxal-5V-phosphate (PLP)-dependent enzyme catalyzes thetetrahydrofolate (H4-folate)- dependent retro-aldol cleavage of serine to form 5,10-methylene H4-folate and glycine. The structure–function relationship of SHMT wasstudied in our laboratory initially by mutation of residues that are conserved in all SHMTs and later by structure-based mutagenesis of residues located in the active site. The analysis of mutants showed that K71, Y72, R80, D89, W110, S202, C203, H304, H306 and H356 residues are involved in maintenance of the oligomeric structure. The mutation of D227, a residue involved in charge relay system, led to the formation of inactive dimers, indicating that this residue has a role in maintaining the tetrameric structure and catalysis. E74, a residue appropriately positioned in the structure of the enzyme to carry out proton abstraction, was shown by characterization of E74Q and E74K mutants to be involved in conversion of the enzyme from an ‘open’ to ‘closed’ conformation rather than proton abstraction from the hydroxylgroup of serine. K256, the residue involved in the formation of Schiffs base with PLP, also plays a crucial role in the maintenance of the tetrameric structure. Mutation of R262 residue established the importance of distal interactions in facilitating catalysis and Y82 is not involved in the formaldehyde transfer via the postulated hemiacetal intermediate but plays a role in stabilizing the quinonoid intermediate.The mutational analysis of scSHMT along with the structure of recombinant Bacillus stearothermophilus SHMT and its substrate(s)complexes was used to provide evidence for a direct transfer mechanism rather than retro-aldol cleavage for the reaction catalyzed by SHMT.

A neural network based automatic generation control design through reinforcement learning

This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.

From anomalies in neat liquid to structure, dynamics and function in the biological world

Water brings its remarkable thermodynamic and dynamic anomalies in the pure liquid state to biological world where water molecules face a multitude of additional interactions that frustrate its hydrogen bond network. Yet the water molecules participate and control enormous number of biological processes in manners which are yet to be understood at a molecular level. We discuss thermodynamics, structure, dynamics and properties of water around proteins and DNA, along with those in reverse micelles. We discuss the roles of water in enzyme kinetics, in drug-DNA intercalation and in kinetic-proof reading ( the theory of lack of errors in biosynthesis). We also discuss how water may play an important role in the natural selection of biomolecules. (C) 2011 Elsevier B. V. All rights reserved.

Learning polyhedral classifiers using logistic function

In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimization problem, our method solves an unconstrained optimization problem. Our method is based on a logistic function based model for the posterior probability function. We propose an alternating optimization algorithm, namely, SPLA1 (Single Polyhedral Learning Algorithm1) which maximizes the loglikelihood of the training data to learn the parameters. We also extend our method to make it independent of any user specified parameter (e.g., number of hyperplanes required to form a polyhedral set) in SPLA2. We show the effectiveness of our approach with experiments on various synthetic and real world datasets and compare our approach with a standard decision tree method (OC1) and a constrained optimization based method for learning polyhedral sets.

Construction of equivalent circuit of a transformer winding from driving-point impedance function - analytical approach

Analytical solution is presented to convert a given driving-point impedance function (in s-domain) into a physically realisable ladder network with inductive coupling between any two sections and losses considered. The number of sections in the ladder network can vary, but its topology is assumed fixed. A study of the coefficients of the numerator and denominator polynomials of the driving-point impedance function of the ladder network, for increasing number of sections, led to the identification of certain coefficients, which exhibit very special properties. Generalised expressions for these specific coefficients have also been derived. Exploiting their properties, it is demonstrated that the synthesis method essentially turns out to be an exercise of solving a set of linear, simultaneous, algebraic equations, whose solution directly yields the ladder network elements. The proposed solution is novel, simple and guarantees a unique network. Presently, the formulation can synthesise a unique ladder network up to six sections.

Insights into differential modulation of receptor function by hinge region using novel agonistic lutropin receptor and inverse agonistic thyrotropin receptor antibodies

We report two antibodies, scFv 13B1 and MAb PD1.37, against the hinge regions of LHR and TSHR, respectively, which have similar epitopes but different effects on receptor function. While neither of them affected hormone binding, with marginal effects on hormone response, scFv 13B1 stimulated LHR in a dose-dependent manner, whereas MAb PD1.37 acted as an inverse agonist of TSHR. Moreover, PD1.37 could decrease the basal activity of hinge region CAMs, but had varied effects on those present in ECLs, whereas 13B1 was refractory to any CAMs in LHR. Using truncation mutants and peptide phage display, we compared the differential roles of the hinge region cysteine box-2/3 as well as the exoloops in the activation of these two homologus receptors. (C) 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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.

An Online Actor-Critic Algorithm with Function Approximation for Constrained Markov Decision Processes

We develop an online actor-critic reinforcement learning algorithm with function approximation for a problem of control under inequality constraints. We consider the long-run average cost Markov decision process (MDP) framework in which both the objective and the constraint functions are suitable policy-dependent long-run averages of certain sample path functions. The Lagrange multiplier method is used to handle the inequality constraints. We prove the asymptotic almost sure convergence of our algorithm to a locally optimal solution. We also provide the results of numerical experiments on a problem of routing in a multi-stage queueing network with constraints on long-run average queue lengths. We observe that our algorithm exhibits good performance on this setting and converges to a feasible point.

The force distribution function of an oscillator model of polymer stretching at constant velocity

Recent simulations of the stretching of tethered biopolymers at a constant speed v (Ponmurugan and Vemparala, 2011 Phys. Rev. E 84 060101(R)) have suggested that for any time t, the distribution of the fluctuating forces f responsible for chain deformation is governed by a relation of the form P(+ f)/ P(- f) = expgamma f], gamma being a coefficient that is solely a function of v and the temperature T. This result, which is reminiscent of the fluctuation theorems applicable to stochastic trajectories involving thermodynamic variables, is derived in this paper from an analytical calculation based on a generalization of Mazonka and Jarzynski's classic model of dragged particle dynamics Mazonka and Jarzynski, 1999 arXiv:cond-\textbackslashmat/9912121v1]. However, the analytical calculations suggest that the result holds only if t >> 1 and the force fluctuations are driven by white rather than colored noise; they further suggest that the coefficient gamma in the purported theorem varies not as v(0.15)T-(0.7), as indicated by the simulations, but as vT(-1).