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.

A unified view of the apriori-based algorithms for frequent episode discovery

Frequent episode discovery framework is a popular framework in temporal data mining with many applications. Over the years, many different notions of frequencies of episodes have been proposed along with different algorithms for episode discovery. In this paper, we present a unified view of all the apriori-based discovery methods for serial episodes under these different notions of frequencies. Specifically, we present a unified view of the various frequency counting algorithms. We propose a generic counting algorithm such that all current algorithms are special cases of it. This unified view allows one to gain insights into different frequencies, and we present quantitative relationships among different frequencies. Our unified view also helps in obtaining correctness proofs for various counting algorithms as we show here. It also aids in understanding and obtaining the anti-monotonicity properties satisfied by the various frequencies, the properties exploited by the candidate generation step of any apriori-based method. We also point out how our unified view of counting helps to consider generalization of the algorithm to count episodes with general partial orders.

Dual-Stage Power Management Algorithms for Energy Harvesting Sensors

In this paper, we propose power management algorithms for maximizing the utility of energy harvesting sensors (EHS) that operate purely on the basis of energy harvested from the environment. In particular, we consider communication (i.e., transmission and reception) power management issues for EHS under an energy neutrality constraint. We also consider the fixed power loss effects of the circuitry, the battery inefficiency and its storage capacity, in the design of the algorithms. We propose a two-stage structure that exploits the inherent difference in the timescales at which the energy harvesting and channel fading processes evolve, without loss of optimality of the resulting solution. The outer stage schedules the power that can be used by an inner stage algorithm, so as to maximize the long term average utility and at the same time maintain energy neutrality. The inner stage optimizes the communication parameters to achieve maximum utility in the short-term, subject to the power constraint imposed by the outer stage. We optimize the algorithms for different transmission schemes such as the truncated channel inversion and retransmission strategies. The performance of the algorithms is illustrated via simulations using solar irradiance data, and for the case of Rayleigh fading channels. The results demonstrate the significant performance benefits that can be obtained using the proposed power management algorithms compared to the energy efficient (optimum when there is no storage) and the uniform power consumption (optimum when the battery has infinite capacity and is perfectly efficient) approaches.

Mechanism of Fragility at BCL2 Gene Minor Breakpoint Cluster Region during t(14;18) Chromosomal Translocation

The t(14;18) translocation in follicular lymphoma is one of the most common chromosomal translocations. Breaks in chromosome 18 are localized at the 3'-UTR of BCL2 gene or downstream and are mainly clustered in either the major breakpoint region or the minor breakpoint cluster region (mcr). The recombination activating gene (RAG) complex induces breaks at IgH locus of chromosome 14, whereas the mechanism of fragility at BCL2 mcr remains unclear. Here, for the first time, we show that RAGs can nick mcr; however, the mechanism is unique. Three independent nicks of equal efficiency are generated, when both Mg2+ and Mn2+ are present, unlike a single nick during V(D)J recombination. Further, we demonstrate that RAG binding and nicking at the mcr are independent of nonamer, whereas a CCACCTCT motif plays a critical role in its fragility, as shown by sequential mutagenesis. More importantly, we recapitulate the BCL2 mcr translocation and find that mcr can undergo synapsis with a standard recombination signal sequence within the cells, in a RAG-dependent manner. Further, mutation to the CCACCTCT motif abolishes recombination within the cells, indicating its vital role. Hence, our data suggest a novel, physiologically relevant, nonamer-independent mechanism of RAG nicking at mcr, which may be important for generation of chromosomal translocations in humans.

Ultrasound Assisted Optical Tomography: Estimation of phase Shift experienced by photon on transit through US insonified region for detection of breast tumor

A Monte Carlo model of ultrasound modulation of multiply scattered coherent light in a highly scattering media has been carried out for estimating the phase shift experienced by a photon beam on its transit through US insonified region. The phase shift is related to the tissue stiffness, thereby opening an avenue for possible breast tumor detection. When the scattering centers in the tissue medium is exposed to a deterministic forcing with the help of a focused ultrasound (US) beam, due to the fact that US-induced oscillation is almost along particular direction, the direction defined by the transducer axis, the scattering events increase, thereby increasing the phase shift experienced by light that traverses through the medium. The phase shift is found to increase with increase in anisotropy g of the medium. However, as the size of the focused region which is the region of interest (ROI) increases, a large number of scattering events take place within the ROI, the ensemble average of the phase shift (Delta phi) becomes very close to zero. The phase of the individual photon is randomly distributed over 2 pi when the scattered photon path crosses a large number of ultrasound wavelengths in the focused region. This is true at high ultrasound frequency (1 MHz) when mean free path length of photon l(s) is comparable to wavelength of US beam. However, at much lower US frequencies (100 Hz), the wavelength of sound is orders of magnitude larger than l(s), and with a high value of g (g 0.9), there is a distinct measurable phase difference for the photon that traverses through the insonified region. Experiments are carried out for validation of simulation results.

Thermo-physical and structural studies of sodium zinc borovanadate glasses in the region of high concentration of modifier oxides

This paper reports investigation of Na2O and ZnO modified borovanadate glasses in the highly modified regime of compositions. These glasses have been prepared by microwave route. Ultraviolet (UV) and visible, infrared (IR), Magic Angle Spinning Nuclear Magnetic Resonance (MAS NMR) and Electron Paramagnetic Resonance (EPR) spectroscopies have been used to characterize the speciation in the glasses. Together with the variation of properties such as molar volume and glass transition temperatures, spectroscopic data indicate that at high levels of modification, ZnO tends to behave like network former. It is proposed that the observed variation of all the properties can be reasonably well understood with a structural model. The model considers that the modification and speciation in glasses are strongly determined by the hierarchy of group electronegativities. Further, it is proposed that the width of the transitions of glasses obtained under same condition reflects the fragility of the glasses. An empirical expression has been suggested to quantify fragility on the basis of width of the transition regions. (C) 2012 Elsevier Ltd. All rights reserved.

Practical fully three-dimensional reconstruction algorithms for diffuse optical tomography

We have developed an efficient fully three-dimensional (3D) reconstruction algorithm for diffuse optical tomography (DOT). The 3D DOT, a severely ill-posed problem, is tackled through a pseudodynamic (PD) approach wherein an ordinary differential equation representing the evolution of the solution on pseudotime is integrated that bypasses an explicit inversion of the associated, ill-conditioned system matrix. One of the most computationally expensive parts of the iterative DOT algorithm, the reevaluation of the Jacobian in each of the iterations, is avoided by using the adjoint-Broyden update formula to provide low rank updates to the Jacobian. In addition, wherever feasible, we have also made the algorithm efficient by integrating along the quadratic path provided by the perturbation equation containing the Hessian. These algorithms are then proven by reconstruction, using simulated and experimental data and verifying the PD results with those from the popular Gauss-Newton scheme. The major findings of this work are as follows: (i) the PD reconstructions are comparatively artifact free, providing superior absorption coefficient maps in terms of quantitative accuracy and contrast recovery; (ii) the scaling of computation time with the dimension of the measurement set is much less steep with the Jacobian update formula in place than without it; and (iii) an increase in the data dimension, even though it renders the reconstruction problem less ill conditioned and thus provides relatively artifact-free reconstructions, does not necessarily provide better contrast property recovery. For the latter, one should also take care to uniformly distribute the measurement points, avoiding regions close to the source so that the relative strength of the derivatives for measurements away from the source does not become insignificant. (c) 2012 Optical Society of America

Applying Genetic Algorithms to Optimize Power in Tiled SNUCA Chip Multicore Architectures

We propose a novel technique for reducing the power consumed by the on-chip cache in SNUCA chip multicore platform. This is achieved by what we call a "remap table", which maps accesses to the cache banks that are as close as possible to the cores, on which the processes are scheduled. With this technique, instead of using all the available cache, we use a portion of the cache and allocate lesser cache to the application. We formulate the problem as an energy-delay (ED) minimization problem and solve it offline using a scalable genetic algorithm approach. Our experiments show up to 40% of savings in the memory sub-system power consumption and 47% savings in energy-delay product (ED).

Applying Genetic Algorithms to Optimize Power in Tiled SNUCA Chip Multicore Architectures

We propose a novel technique for reducing the power consumed by the on-chip cache in SNUCA chip multicore platform. This is achieved by what we call a "remap table", which maps accesses to the cache banks that are as close as possible to the cores, on which the processes are scheduled. With this technique, instead of using all the available cache, we use a portion of the cache and allocate lesser cache to the application. We formulate the problem as an energy-delay (ED) minimization problem and solve it offline using a scalable genetic algorithm approach. Our experiments show up to 40% of savings in the memory sub-system power consumption and 47% savings in energy-delay product (ED).

Robust solver based on modified particle swarm optimization for improved solution of diffusion transport through containment facilities

Accurate estimation of mass transport parameters is necessary for overall design and evaluation processes of the waste disposal facilities. The mass transport parameters, such as effective diffusion coefficient, retardation factor and diffusion accessible porosity, are estimated from observed diffusion data by inverse analysis. Recently, particle swarm optimization (PSO) algorithm has been used to develop inverse model for estimating these parameters that alleviated existing limitations in the inverse analysis. However, PSO solver yields different solutions in successive runs because of the stochastic nature of the algorithm and also because of the presence of multiple optimum solutions. Thus the estimated mean solution from independent runs is significantly different from the best solution. In this paper, two variants of the PSO algorithms are proposed to improve the performance of the inverse analysis. The proposed algorithms use perturbation equation for the gbest particle to gain information around gbest region on the search space and catfish particles in alternative iterations to improve exploration capabilities. Performance comparison of developed solvers on synthetic test data for two different diffusion problems reveals that one of the proposed solvers, CPPSO, significantly improves overall performance with improved best, worst and mean fitness values. The developed solver is further used to estimate transport parameters from 12 sets of experimentally observed diffusion data obtained from three diffusion problems and compared with published values from the literature. The proposed solver is quick, simple and robust on different diffusion problems. (C) 2012 Elsevier Ltd. All rights reserved.

The Hinge Region of Human Thyroid-Stimulating Hormone (TSH) Receptor Operates as a Tunable Switch between Hormone Binding and Receptor Activation

The mechanism by which the hinge regions of glycoprotein hormone receptors couple hormone binding to activation of downstream effecters is not clearly understood. In the present study, agonistic (311.62) and antagonistic (311.87) monoclonal antibodies (MAbs) directed against the TSH receptor extracellular domain were used to elucidate role of the hinge region in receptor activation. MAb 311.62 which identifies the LRR/Cb-2 junction (aa 265-275), increased the affinity of TSHR for the hormone while concomitantly decreasing its efficacy, whereas MAb 311.87 recognizing LRR 7-9 (aa 201-259) acted as a non-competitive inhibitor of Thyroid stimulating hormone (TSH) binding. Binding of MAbs was sensitive to the conformational changes caused by the activating and inactivating mutations and exhibited differential effects on hormone binding and response of these mutants. By studying the effects of these MAbs on truncation and chimeric mutants of thyroid stimulating hormone receptor (TSHR), this study confirms the tethered inverse agonistic role played by the hinge region and maps the interactions between TSHR hinge region and exoloops responsible for maintenance of the receptor in its basal state. Mechanistic studies on the antibody-receptor interactions suggest that MAb 311.87 is an allosteric insurmountable antagonist and inhibits initiation of the hormone induced conformational changes in the hinge region, whereas MAb 311.62 acts as a partial agonist that recognizes a conformational epitope critical for coupling of hormone binding to receptor activation. The hinge region, probably in close proximity with the alpha-subunit in the hormone-receptor complex, acts as a tunable switch between hormone binding and receptor activation.

Phalangopsidae crickets from the Indian Region (Orthoptera, Grylloidea), with the descriptions of new taxa, diagnoses for genera, and a key to Indian genera

The Indian region is presently the second region after the Neotropics in terms of diversity of phalangopsid crickets. Yet their study is impeded by the lack of necessary taxonomic tools for taxon identification. In the present paper, all generic diagnoses are clarified, using morphological and genitalic characters; female genitalia are described and illustrated for all genera with known females. New taxa are described from southern India: Kempiola flavipunctatus Desutter-Grandcolas n. sp., Opiliosina meridionalis Desutter-Grandcolas n. gen., n. sp., Phalangopsina bolivari Desutter-Grandcolas n. sp., P. chopardi Desutter-Grandcolas n. sp., P. gravelyi Desutter-Grandcolas n. sp., and Speluncasina Desutter-Grandcolas n. gen. The list of phalangopsid crickets from the Indian Region is updated, and a key to phalangopsid genera proposed. A lectotype and a paralectotype are designated to fix the name of Phalangopsina dubia (Bolivar, 1900). Opilionacris annandalei Chopard, 1928, previously transferred to the African genus Phaeophilacris Walker, 1871, is transferred to the genus Speluncasina Desutter-Grandcolas n. gen., while Larandopsis jharnae Bhowmik, 1981 and L. newguineae Bhowmik, 1981 described from New Guinea are transferred to the eneopterine genus Lebinthus Stal, 1877. Finally Luzaropsis confusa Chopard, 1969 is removed from its synonymy with L. ferruginea Walker, 1871.

Computational algorithms inspired by biological processes and evolution

In recent times computational algorithms inspired by biological processes and evolution are gaining much popularity for solving science and engineering problems. These algorithms are broadly classified into evolutionary computation and swarm intelligence algorithms, which are derived based on the analogy of natural evolution and biological activities. These include genetic algorithms, genetic programming, differential evolution, particle swarm optimization, ant colony optimization, artificial neural networks, etc. The algorithms being random-search techniques, use some heuristics to guide the search towards optimal solution and speed-up the convergence to obtain the global optimal solutions. The bio-inspired methods have several attractive features and advantages compared to conventional optimization solvers. They also facilitate the advantage of simulation and optimization environment simultaneously to solve hard-to-define (in simple expressions), real-world problems. These biologically inspired methods have provided novel ways of problem-solving for practical problems in traffic routing, networking, games, industry, robotics, economics, mechanical, chemical, electrical, civil, water resources and others fields. This article discusses the key features and development of bio-inspired computational algorithms, and their scope for application in science and engineering fields.

Efficient Algorithms for Linear Summed Error Structural SVMs

Structural Support Vector Machines (SSVMs) have become a popular tool in machine learning for predicting structured objects like parse trees, Part-of-Speech (POS) label sequences and image segments. Various efficient algorithmic techniques have been proposed for training SSVMs for large datasets. The typical SSVM formulation contains a regularizer term and a composite loss term. The loss term is usually composed of the Linear Maximum Error (LME) associated with the training examples. Other alternatives for the loss term are yet to be explored for SSVMs. We formulate a new SSVM with Linear Summed Error (LSE) loss term and propose efficient algorithms to train the new SSVM formulation using primal cutting-plane method and sequential dual coordinate descent method. Numerical experiments on benchmark datasets demonstrate that the sequential dual coordinate descent method is faster than the cutting-plane method and reaches the steady-state generalization performance faster. It is thus a useful alternative for training SSVMs when linear summed error is used.

Analysis of large-amplitude stratospheric mountain wave event observed from the AIRS and MLS sounders over the western Himalayan region

Mountain waves in the stratosphere have been observed over elevated topographies using both nadir-looking and limb-viewing satellites. However, the characteristics of mountain waves generated over the Himalayan Mountain range and the adjacent Tibetan Plateau are relatively less explored. The present study reports on three-dimensional (3-D) properties of a mountain wave event that occurred over the western Himalayan region on 9 December 2008. Observations made by the Atmospheric Infrared Sounder on board the Aqua and Microwave Limb Sounder on board the Aura satellites are used to delineate the wave properties. The observed wave properties such as horizontal (lambda(x), lambda(y)) and vertical (lambda(z)) wavelengths are 276 km (zonal), 289 km (meridional), and 25 km, respectively. A good agreement is found between the observed and modeled/analyzed vertical wavelength for a stationary gravity wave determined using the Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis winds. The analysis of both the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis and MERRA winds shows that the waves are primarily forced by strong flow across the topography. Using the 3-D properties of waves and the corrected temperature amplitudes, we estimated wave momentum fluxes of the order of similar to 0.05 Pa, which is in agreement with large-amplitude mountain wave events reported elsewhere. In this regard, the present study is considered to be very much informative to the gravity wave drag schemes employed in current general circulation models for this region.