Glycosphingolipids in microdomain formation and their spatial organization

Plasma membranes regulate the influx and efflux of molecules across themselves and are also responsible for primary signal transduction between cells or within the same cell. Presence of lateral heterogeneity and the ability of reorganization are essential requirements for effective functioning of biomembranes. Lipid rafts are small, heterogeneous, dynamic domains enriched in glycosphingolipids, sphingomyelin and cholesterol, and profoundly influence membrane organization. Glycosphingolipids are inclined towards formation of liquid-ordered phases in membranes, both with and without cholesterol; they are therefore prime players in domain formation. Here, we discuss the role of glycosphingolipids in microdomain formation and their spatial organization within these rafts.

Detection of a periodic structure hidden in random background: the role of signal amplitude in the matched filter detection method

The matched filter method for detecting a periodic structure on a surface hidden behind randomness is known to detect up to (r(0)/Lambda) gt;= 0.11, where r(0) is the coherence length of light on scattering from the rough part and 3 is the wavelength of the periodic part of the surface-the above limit being much lower than what is allowed by conventional detection methods. The primary goal of this technique is the detection and characterization of the periodic structure hidden behind randomness without the use of any complicated experimental or computational procedures. This paper examines this detection procedure for various values of the amplitude a of the periodic part beginning from a = 0 to small finite values of a. We thus address the importance of the following quantities: `(a)lambda) `, which scales the amplitude of the periodic part with the wavelength of light, and (r(0))Lambda),in determining the detectability of the intensity peaks.

Transduction in mycobacterium smegmatis

SEVERAL people have studied lysogeny and lysogenic conversion in the advanced prokaryote, Mycobacterium1-3, and presented evidence for reciprocal genetic exchange from the lysogenic to the non-lysogenic state. Biochemical and physiological changes induced by lysogenization of M. phlei with mycobacteriophage B2 have been demonstrated by Juhasz4. We wish to report the isolation of a mycobacteriophage capable of mediating transduction in Mycobacterium smegmatis strain SN2, thus providing an opportunity to study the genetics of mycobacteria.

Proteomics of Trypanosoma evansi Infection in Rodents

Background: Trypanosoma evansi infections, commonly called 'surra', cause significant economic losses to livestock industry. While this infection is mainly restricted to large animals such as camels, donkeys and equines, recent reports indicate their ability to infect humans. There are no World Animal Health Organization (WAHO) prescribed diagnostic tests or vaccines available against this disease and the available drugs show significant toxicity. There is an urgent need to develop improved methods of diagnosis and control measures for this disease. Unlike its related human parasites T. brucei and T. cruzi whose genomes have been fully sequenced T. evansi genome sequence remains unavailable and very little efforts are being made to develop improved methods of prevention, diagnosis and treatment. With a view to identify potential diagnostic markers and drug targets we have studied the clinical proteome of T. evansi infection using mass spectrometry (MS).Methodology/Principal Findings: Using shot-gun proteomic approach involving nano-lc Quadrupole Time Of Flight (QTOF) mass spectrometry we have identified over 160 proteins expressed by T. evansi in mice infected with camel isolate. Homology driven searches for protein identification from MS/MS data led to most of the matches arising from related Trypanosoma species. Proteins identified belonged to various functional categories including metabolic enzymes; DNA metabolism; transcription; translation as well as cell-cell communication and signal transduction. TCA cycle enzymes were strikingly missing, possibly suggesting their low abundances. The clinical proteome revealed the presence of known and potential drug targets such as oligopeptidases, kinases, cysteine proteases and more.Conclusions/Significance: Previous proteomic studies on Trypanosomal infections, including human parasites T. brucei and T. cruzi, have been carried out from lab grown cultures. For T. evansi infection this is indeed the first ever proteomic study reported thus far. In addition to providing a glimpse into the biology of this neglected disease, our study is the first step towards identification of diagnostic biomarkers, novel drug targets as well as potential vaccine candidates to fight against T. evansi infections.

A non-orthogonal distributed space-time coded protocol - Part 1:Signal model and design criteria

In this two-part series of papers, a generalized non-orthogonal amplify and forward (GNAF) protocol which generalizes several known cooperative diversity protocols is proposed. Transmission in the GNAF protocol comprises of two phases - the broadcast phase and the cooperation phase. In the broadcast phase, the source broadcasts its information to the relays as well as the destination. In the cooperation phase, the source and the relays together transmit a space-time code in a distributed fashion. The GNAF protocol relaxes the constraints imposed by the protocol of Jing and Hassibi on the code structure. In Part-I of this paper, a code design criteria is obtained and it is shown that the GNAF protocol is delay efficient and coding gain efficient as well. Moreover GNAF protocol enables the use of sphere decoders at the destination with a non-exponential Maximum likelihood (ML) decoding complexity. In Part-II, several low decoding complexity code constructions are studied and a lower bound on the Diversity-Multiplexing Gain tradeoff of the GNAF protocol is obtained.

Transient signal detection using wigner-ville distribution and wavelet denoising

The problem of detecting an unknown transient signal in noise is considered. The SNR of the observed data is first enhanced using wavelet domain filter The output of the wavelet domain filter is then transformed using a Wigner-Ville transform,which separates the spectrum of the observed signal into narrow frequency bands. Each subband signal at the output of the Wigner-ville block is subjected kto wavelet based level dependent denoising (WBLDD)to supress colored noise A weighted sum of the absolute value of outputs of WBLDD is passed through an energy detector, whose output is used as test statistic to take the final decision. By assigning weights proportional to the energy of the corresponding subband signals, the proposed detector approximates a frequency domain matched filter Simulation results are presented to show that the performance of the proposed detector is better than that of the wavelet packet transform based detector.

Coding for Two-User Gaussian MAC with PSK and PAM Signal Sets

Constellation Constrained (CC) capacity regions of a two-user Gaussian Multiple Access Channel(GMAC) have been recently reported. For such a channel, code pairs based on trellis coded modulation are proposed in this paper with MPSK and M-PAM alphabet pairs, for arbitrary values of M,toachieve sum rates close to the CC sum capacity of the GMAC. In particular, the structure of the sum alphabets of M-PSK and M-PAMmalphabet pairs are exploited to prove that, for certain angles of rotation between the alphabets, Ungerboeck labelling on the trellis of each user maximizes the guaranteed squared Euclidean distance of the sum trellis. Hence, such a labelling scheme can be used systematically,to construct trellis code pairs to achieve sum rates close to the CC sum capacity. More importantly, it is shown for the first time that ML decoding complexity at the destination is significantly reduced when M-PAM alphabet pairs are employed with almost no loss in the sum capacity.

Unified large and small signal non-quasi-static model for long channel symmetric DG MOSFET

We propose a unified model for large signal and small signal non-quasi-static analysis of long channel symmetric double gate MOSFET. The model is physics based and relies only on the very basic approximation needed for a charge-based model. It is based on the EKV formalism Enz C, Vittoz EA. Charge based MOS transistor modeling. Wiley; 2006] and is valid in all regions of operation and thus suitable for RF circuit design. Proposed model is verified with professional numerical device simulator and excellent agreement is found. (C) 2010 Elsevier Ltd. All rights reserved.

Composite signal decomposition by digital inverse filtering

Inverse filters are conventionally used for resolving overlapping signals of identical waveshape. However, the inverse filtering approach is shown to be useful for resolving overlapping signals, identical or otherwise, of unknown waveshapes. Digital inverse filter design based on autocorrelation formulation of linear prediction is known to perform optimum spectral flattening of the input signal for which the filter is designed. This property of the inverse filter is used to accomplish composite signal decomposition. The theory has been presented assuming constituent signals to be responses of all-pole filters. However, the approach may be used for a general situation.

ADC Static Characterization Using Nonlinear Ramp Signal

Static characteristics of an analog-to-digital converter (ADC) can be directly determined from the histogram-based quasi-static approach by measuring the ADC output when excited by an ideal ramp/triangular signal of sufficiently low frequency. This approach requires only a fraction of time compared to the conventional dc voltage test, is straightforward, is easy to implement, and, in principle, is an accepted method as per the revised IEEE 1057. However, the only drawback is that ramp signal sources are not ideal. Thus, the nonlinearity present in the ramp signal gets superimposed on the measured ADC characteristics, which renders them, as such, unusable. In recent years, some solutions have been proposed to alleviate this problem by devising means to eliminate the contribution of signal source nonlinearity. Alternatively, a straightforward step would be to get rid of the ramp signal nonlinearity before it is applied to the ADC. Driven by this logic, this paper describes a simple method about using a nonlinear ramp signal, but yet causing little influence on the measured ADC static characteristics. Such a thing is possible because even in a nonideal ramp, there exist regions or segments that are nearly linear. Therefore, the task, essentially, is to identify these near-linear regions in a given source and employ them to test the ADC, with a suitable amplitude to match the ADC full-scale voltage range. Implementation of this method reveals that a significant reduction in the influence of source nonlinearity can be achieved. Simulation and experimental results on 8- and 10-bit ADCs are presented to demonstrate its applicability.

Classification of Protein Kinases on the Basis of Both Kinase and Non-Kinase Regions

Background: Protein phosphorylation is a generic way to regulate signal transduction pathways in all kingdoms of life. In many organisms, it is achieved by the large family of Ser/Thr/Tyr protein kinases which are traditionally classified into groups and subfamilies on the basis of the amino acid sequence of their catalytic domains. Many protein kinases are multidomain in nature but the diversity of the accessory domains and their organization are usually not taken into account while classifying kinases into groups or subfamilies. Methodology: Here, we present an approach which considers amino acid sequences of complete gene products, in order to suggest refinements in sets of pre-classified sequences. The strategy is based on alignment-free similarity scores and iterative Area Under the Curve (AUC) computation. Similarity scores are computed by detecting common patterns between two sequences and scoring them using a substitution matrix, with a consistent normalization scheme. This allows us to handle full-length sequences, and implicitly takes into account domain diversity and domain shuffling. We quantitatively validate our approach on a subset of 212 human protein kinases. We then employ it on the complete repertoire of human protein kinases and suggest few qualitative refinements in the subfamily assignment stored in the KinG database, which is based on catalytic domains only. Based on our new measure, we delineate 37 cases of potential hybrid kinases: sequences for which classical classification based entirely on catalytic domains is inconsistent with the full-length similarity scores computed here, which implicitly consider multi-domain nature and regions outside the catalytic kinase domain. We also provide some examples of hybrid kinases of the protozoan parasite Entamoeba histolytica. Conclusions: The implicit consideration of multi-domain architectures is a valuable inclusion to complement other classification schemes. The proposed algorithm may also be employed to classify other families of enzymes with multidomain architecture.

PeptideMine - A webserver for the design of peptides for protein-peptide binding studies derived from protein-protein interactomes

Background: Signal transduction events often involve transient, yet specific, interactions between structurally conserved protein domains and polypeptide sequences in target proteins. The identification and validation of these associating domains is crucial to understand signal transduction pathways that modulate different cellular or developmental processes. Bioinformatics strategies to extract and integrate information from diverse sources have been shown to facilitate the experimental design to understand complex biological events. These methods, primarily based on information from high-throughput experiments, have also led to the identification of new connections thus providing hypothetical models for cellular events. Such models, in turn, provide a framework for directing experimental efforts for validating the predicted molecular rationale for complex cellular processes. In this context, it is envisaged that the rational design of peptides for protein-peptide binding studies could substantially facilitate the experimental strategies to evaluate a predicted interaction. This rational design procedure involves the integration of protein-protein interaction data, gene ontology, physico-chemical calculations, domain-domain interaction data and information on functional sites or critical residues. Results: Here we describe an integrated approach called ``PeptideMine'' for the identification of peptides based on specific functional patterns present in the sequence of an interacting protein. This approach based on sequence searches in the interacting sequence space has been developed into a webserver, which can be used for the identification and analysis of peptides, peptide homologues or functional patterns from the interacting sequence space of a protein. To further facilitate experimental validation, the PeptideMine webserver also provides a list of physico-chemical parameters corresponding to the peptide to determine the feasibility of using the peptide for in vitro biochemical or biophysical studies. Conclusions: The strategy described here involves the integration of data and tools to identify potential interacting partners for a protein and design criteria for peptides based on desired biochemical properties. Alongside the search for interacting protein sequences using three different search programs, the server also provides the biochemical characteristics of candidate peptides to prune peptide sequences based on features that are most suited for a given experiment. The PeptideMine server is available at the URL: http://caps.ncbs.res.in/peptidemine

A Non Quasi-Static Small Signal Model for Long Channel Symmetric DG MOSFET

We propose a compact model for small signal non quasi static analysis of long channel symmetric double gate MOSFET The model is based on the EKV formalism and is valid in all regions of operation and thus suitable for RF circuit design Proposed model is verified with professional numerical device simulator and excellent agreement is found well beyond the cut-off frequency

Signal subspace approach in localization of sound source in shallow water

A new algorithm based on signal subspace approach is proposed for localizing a sound source in shallow water. In the first instance we assumed an ideal channel with plane parallel boundaries and known reflection properties. The sound source is assumed to emit a broadband stationary stochastic signal. The algorithm takes into account the spatial distribution of all images and reflection characteristics of the sea bottom. It is shown that both range and depth of a source can be measured accurately with the help of a vertical array of sensors. For good results the number of sensors should be greater than the number of significant images; however, localization is possible even with a smaller array but at the cost of higher side lobes. Next, we allowed the channel to be stochastically perturbed; this resulted in random phase errors in the reflection coefficients. The most singular effect of the phase errors is to introduce into the spectral matrix an extra term which may be looked upon as a signal generated coloured noise. It is shown through computer simulations that the signal peak height is reduced considerably as a consequence of random phase errors.