Mapping of assembled epitopes with microgram quantities of antigen: Identification of an epitope at the receptor binding region of human follicle stimulating hormone

Identification of epitopes by modification studies has been reported by us recently. The method requires milligram quantities of antigen and since several proteins are not available in large quantities they are not amenable for such an investigation. One such protein is human follicle stimulating hormone (hFSH) whose mapping of epitopes is of importance in reproductive biology. Here we report a method that uses microgram quantities of hFSH to map a beta-specific epitope located at the receptor binding region. This identification has also been validated by the chemical modification method using heterologous antigen ovine follicle stimulating hormone (oFSH).

Mapping the common antigenic determinants in avidin and streptavidin

An epitope scan analysis of the whole sequence of avidin and core streptavidin using polyclonal antibodies to these two antigens reveal the presence of multiple common epitopes in both the proteins. These antigenic determinants consist mostly of either identical or similar residues. The antibody recognition sites in both antigens are shown to be localized to homologous regions.

Numerical integration over arbitrary polygonal domains based on Schwarz-Christoffel conformal mapping

This paper presents a new numerical integration technique oil arbitrary polygonal domains. The polygonal domain is mapped conformally to the unit disk using Schwarz-Christoffel mapping and a midpoint quadrature rule defined oil this unit disk is used. This method eliminates the need for a two-level isoparametric mapping Usually required. Moreover, the positivity of the Jacobian is guaranteed. Numerical results presented for a few benchmark problems in the context of polygonal finite elements show that the proposed method yields accurate results.

Fine-tuning of the signalling network controlling morphogenesis and stem cell development in teeth

Tooth development is regulated by sequential and reciprocal interactions between epithelium and mesenchyme. The molecular mechanisms underlying this regulation are conserved and most of the participating molecules belong to several signalling families. Research focusing on mouse teeth has uncovered many aspects of tooth development, including molecular and evolutionary specifi cs, and in addition offered a valuable system to analyse the regulation of epithelial stem cells. In mice the spatial and temporal regulation of cell differentiation and the mechanisms of patterning during development can be analysed both in vivo and in vitro. Follistatin (Fst), a negative regulator of TGFβ superfamily signalling, is an important inhibitor during embryonic development. We showed the necessity of modulation of TGFβ signalling by Fst in three different regulatory steps during tooth development. First we showed that tinkering with the level of TGFβ signalling by Fst may cause variation in the molar cusp patterning and crown morphogenesis. Second, our results indicated that in the continuously growing mouse incisors asymmetric expression of Fst is responsible for the labial-lingual patterning of ameloblast differentiation and enamel formation. Two TGFβ superfamily signals, BMP and Activin, are required for proper ameloblast differentiation and Fst modulates their effects. Third, we identifi ed a complex signalling network regulating the maintenance and proliferation of epithelial stem cells in the incisor, and showed that Fst is an essential modulator of this regulation. FGF3 in cooperation with FGF10 stimulates proliferation of epithelial stem cells and transit amplifying cells in the labial cervical loop. BMP4 represses Fgf3 expression whereas Activin inhibits the repressive effect of BMP4 on the labial side. Thus, Fst inhibits Activin rather than BMP4 in the cervical loop area and limits the proliferation of lingual epithelium, thereby causing the asymmetric maintenance and proliferation of epithelial stem cells. In addition, we detected Lgr5, a Wnt target gene and an epithelial stem cell marker in the intestine, in the putative epithelial stem cells of the incisor, suggesting that Lgr5 is a marker of incisor stem cells but is not regulated by Wnt/β-catenin signalling in the incisor. Thus the epithelial stem cells in the incisor may not be directly regulated by Wnt/β-catenin signalling. In conclusion, we showed in the mouse incisors that modulating the balance between inductive and inhibitory signals constitutes a key mechanism regulating the epithelial stem cells and ameloblast differentiation. Furthermore, we found additional support for the location of the putative epithelial stem cells and for the stemness of these cells. In the mouse molar we showed the necessity of fi ne-tuning the signalling in the regulation of the crown morphogenesis, and that altering the levels of an inhibitor can cause variation in the crown patterning.

Strategies for efficient disruption of metabolism in Mycobacterium tuberculosis from network analysis

Tuberculosis continues to be a major health challenge, warranting the need for newer strategies for therapeutic intervention and newer approaches to discover them. Here, we report the identification of efficient metabolism disruption strategies by analysis of a reactome network. Protein-protein dependencies at a genome scale are derived from the curated metabolic network, from which insights into the nature and extent of inter-protein and inter-pathway dependencies have been obtained. A functional distance matrix and a subsequent nearness index derived from this information, helps in understanding how the influence of a given protein can pervade to the metabolic network. Thus, the nearness index can be viewed as a metabolic disruptability index, which suggests possible strategies for achieving maximal metabolic disruption by inhibition of the least number of proteins. A greedy approach has been used to identify the most influential singleton, and its combination with the other most pervasive proteins to obtain highly influential pairs, triplets and quadruplets. The effect of deletion of these combinations on cellular metabolism has been studied by flux balance analysis. An obvious outcome of this study is a rational identification of drug targets, to efficiently bring down mycobacterial metabolism.

Relative electrical distance concept for evaluation of network reactive power and loss contributions in a deregulated system

With the liberalisation of electricity market it has become very important to determine the participants making use of the transmission network.Transmission line usage computation requires information of generator to load contributions and the path used by various generators to meet loads and losses. In this study relative electrical distance (RED) concept is used to compute reactive power contributions from various sources like generators, switchable volt-amperes reactive(VAR) sources and line charging susceptances that are scattered throughout the network, to meet the system demands. The transmission line charge susceptances contribution to the system reactive flows and its aid extended in reducing the reactive generation at the generator buses are discussed in this paper. Reactive power transmission cost evaluation is carried out in this study. The proposed approach is also compared with other approaches viz.,proportional sharing and modified Y-bus.Detailed case studies with base case and optimised results are carried out on a sample 8-bus system. IEEE 39-bus system and a practical 72-bus system, an equivalent of Indian Southern grid are also considered for illustration and results are discussed.

Inferring neuronal network connectivity from spike data: A temporal data mining approach

Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent d evelopments in electrophysiology and imaging allow one to simultaneously record activities of hundreds of neurons. Inferring the underlying neuronal connectivity patterns from such multi-neuronal spike train data streams is a challenging statistical and computational problem. This task involves finding significant temporal patterns from vast amounts of symbolic time series data. In this paper we show that the frequent episode mining methods from the field of temporal data mining can be very useful in this context. In the frequent episode discovery framework, the data is viewed as a sequence of events, each of which is characterized by an event type and its time of occurrence and episodes are certain types of temporal patterns in such data. Here we show that, using the set of discovered frequent episodes from multi-neuronal data, one can infer different types of connectivity patterns in the neural system that generated it. For this purpose, we introduce the notion of mining for frequent episodes under certain temporal constraints; the structure of these temporal constraints is motivated by the application. We present algorithms for discovering serial and parallel episodes under these temporal constraints. Through extensive simulation studies we demonstrate that these methods are useful for unearthing patterns of neuronal network connectivity.

Modelling heterogeneity of concrete using 2D lattice network for concrete fracture and comparison with AE study

In this paper, numerical modelling of fracture in concrete using two-dimensional lattice model is presented and also a few issues related to lattice modelling technique applicable to concrete fracture are reviewed. A comparison is made with acoustic emission (AE) events with the number of fractured elements. To implement the heterogeneity of the plain concrete, two methods namely, by generating grain structure of the concrete using Fuller's distribution and the concrete material properties are randomly distributed following Gaussian distribution are used. In the first method, the modelling of the concrete at meso level is carried out following the existing methods available in literature. The shape of the aggregates present in the concrete are assumed as perfect spheres and shape of the same in two-dimensional lattice network is circular. A three-point bend (TPB) specimen is tested in the experiment under crack mouth opening displacement (CMOD) control at a rate of 0.0004 mm/sec and the fracture process in the same TPB specimen is modelled using regular triangular 2D lattice network. Load versus crack mouth opening isplacement (CMOD) plots thus obtained by using both the methods are compared with experimental results. It was observed that the number of fractured elements increases near the peak load and beyond the peak load. That is once the crack starts to propagate. AE hits also increase rapidly beyond the peak load. It is compulsory here to mention that although the lattice modelling of concrete fracture used in this present study is very similar to those already available in literature, the present work brings out certain finer details which are not available explicitly in the earlier works.

Random network behaviour of protein structures

Geometric and structural constraints greatly restrict the selection of folds adapted by protein backbones, and yet, folded proteins show an astounding diversity in functionality. For structure to have any bearing on function, it is thus imperative that, apart from the protein backbone, other tunable degrees of freedom be accountable. Here, we focus on side-chain interactions, which non-covalently link amino acids in folded proteins to form a network structure. At a coarse-grained level, we show that the network conforms remarkably well to realizations of random graphs and displays associated percolation behavior. Thus, within the rigid framework of the protein backbone that restricts the structure space, the side-chain interactions exhibit an element of randomness, which account for the functional flexibility and diversity shown by proteins. However, at a finer level, the network exhibits deviations from these random graphs which, as we demonstrate for a few specific examples, reflect the intrinsic uniqueness in the structure and stability, and perhaps specificity in the functioning of biological proteins.

Mapping of fuelwood trees using geoinformatics

Rural population of India constitutes about 70% of the total population and traditional fuels account for 75% of the rural energy needs. Depletion of woodlands coupled with the persistent dependency on fuel wood has posed a serious problem for household energy provision in many parts. This study highlights that the traditional fuels still meet 85-95% of fuel needs in rural areas of Kolar district: people prefer fuel wood for cooking and agriculture residues for water heating and other purposes. However, rapid changes in land cover and land use in recent times have affected these traditional fuels availability necessitating inventorying, mapping and monitoring of bioresources for sustainable management of bioresources. Remote sensing data (Multispectal and Panchromatic), Geographic Information System (GIS), field surveys and non-destructive sampling were used to assess spatially the availability and demand of energy. Field surveys indicate that rural household depends on species such as Prosopis juliflora, Acacia nilotica, Acacia auriculiformis to meet fuel wood requirement for domestic activities. Hence, to take stock of fuel wood availability, mapping was done at species level (with 88% accuracy) considering villages as sampling units using fused multispectral and panchromatic data. (C) 2009 Elsevier Ltd. All rights reserved.