Prediction of protein-protein interactions between human host and a pathogen and its application to three pathogenic bacteria

Molecular understanding of disease processes can be accelerated if all interactions between the host and pathogen are known. The unavailability of experimental methods for large-scale detection of interactions across host and pathogen organisms hinders this process. Here we apply a simple method to predict protein-protein interactions across a host and pathogen organisms. We use homology detection approaches against the protein-protein interaction databases. DIP and iPfam in order to predict interacting proteins in a host-pathogen pair. In the present work, we first applied this approach to the test cases involving the pairs phage T4 - Escherichia coli and phage lambda - E. coli and show that previously known interactions could be recognized using our approach. We further apply this approach to predict interactions between human and three pathogens E. coli, Salmonella enterica typhimurium and Yersinia pestis. We identified several novel interactions involving proteins of host or pathogen that could be thought of as highly relevant to the disease process. Serendipitously, many interactions involve hypothetical proteins of yet unknown function. Hypothetical proteins are predicted from computational analysis of genome sequences with no laboratory analysis on their functions yet available. The predicted interactions involving such proteins could provide hints to their functions. (C) 2011 Elsevier B.V. All rights reserved.

Parasite abundance and diversity in mammals: correlates with host ecology

Fecally dispersed parasites of 12 wild mammal species in Mudumalai Sanctuary, southern India, were studied, Fecal propagule densities and parasite diversity measures were correlated with host ecological variables. Host species with higher predatory pressure had lower parasite loads and parasite diversity. Host body weight, home range, population density, gregariousness, and diet did not show predicted effects on parasite loads. Measures of a! diversity were positively correlated with parasite abundance and were negatively correlated with beta diversity, Based on these data, hypotheses regarding determinants of parasite community are discussed.

Secretion of endocrine signals by the primate embryo during the peri-implantation period

Development of preimplantation embryos and blastocyst implantation are critical early events in the establishment of pregnancy. In primates, embryonic signals, secreted during the peri-implantation period, are believed to play a major role in the regulation of embryonic differentiation and implantation. However, only limited progress has been made in the molecular and functional characterization of embryonic signals, partly due to severe paucity of primate embryos and the lack of optimal culture conditions to obtain viable embryo development. Two embryonic (endocrine) secretions, i.e. chorionic gonadotrophin (CG) and gonadotrophin releasing hormone (GnRH) are being studied. This article reviews the current status of knowledge on the recovery and culture of embryos, their secretion of CG, GnRH and other potential endocrine signals and their regulation and physiological role(s) during the peri-implantation period in primates, including humans.

Use of finite wordlength FIR digital filter structures with improved magnitude and phase characteristics for reduction of muscle noise in EEG signals

One of the main disturbances in EEG signals is EMG artefacts generated by muscle movements. In the paper, the use of a linear phase FIR digital low-pass filter with finite wordlength precision coefficients is proposed, designed using the compensation procedure, to minimise EMG artefacts in contaminated EEG signals. To make the filtering more effective, different structures are used, i.e. cascading, twicing and sharpening (apart from simple low-pass filtering) of the designed FIR filter Modifications are proposed to twicing and sharpening structures to regain the linear phase characteristics that are lost in conventional twicing and sharpening operations. The efficacy of all these transformed filters in minimising EMG artefacts is studied, using SNR improvements as a performance measure for simulated signals. Time plots of the signals are also compared. Studies show that the modified sharpening structure is superior in performance to all other proposed methods. These algorithms have also been applied to real or recorded EMG-contaminated EEG signal. Comparison of time plots, and also the output SNR, show that the proposed modified sharpened structure works better in minimising EMG artefacts compared with other methods considered.

Unusual charged Higgs boson signals at CERN LEP 2

We have made a detailed study of the signals expected at CERN LEP 2 from charged scalar bosons whose dominant decay channels are into four fermions. The event rates as well as kinematics of the final states are discussed when such scalars are either pair produced or are generated through a tree-level interaction involving a charged scalar, the W, and the Z. The backgrounds in both cases are discussed. We also suggest the possibility of reconstructing the mass of such a scalar at LEP 2.

Noise and outlier removal from jet engine health signals using weighted FIR median hybrid filters

The removal of noise and outliers from measurement signals is a major problem in jet engine health monitoring. Topical measurement signals found in most jet engines include low rotor speed, high rotor speed. fuel flow and exhaust gas temperature. Deviations in these measurements from a baseline 'good' engine are often called measurement deltas and the health signals used for fault detection, isolation, trending and data mining. Linear filters such as the FIR moving average filter and IIR exponential average filter are used in the industry to remove noise and outliers from the jet engine measurement deltas. However, the use of linear filters can lead to loss of critical features in the signal that can contain information about maintenance and repair events that could be used by fault isolation algorithms to determine engine condition or by data mining algorithms to learn valuable patterns in the data, Non-linear filters such as the median and weighted median hybrid filters offer the opportunity to remove noise and gross outliers from signals while preserving features. In this study. a comparison of traditional linear filters popular in the jet engine industry is made with the median filter and the subfilter weighted FIR median hybrid (SWFMH) filter. Results using simulated data with implanted faults shows that the SWFMH filter results in a noise reduction of over 60 per cent compared to only 20 per cent for FIR filters and 30 per cent for IIR filters. Preprocessing jet engine health signals using the SWFMH filter would greatly improve the accuracy of diagnostic systems. (C) 2002 Published by Elsevier Science Ltd.

The effect of host glass on optical absorption and fluorescence of Nd3+ in xNa(2)O-(30-x)K2O-70B(2)O(3) glasses

The effect of host glass composition on the optical absorption and fluorescence spectra of Nd3+ has been studied in mixed alkali borate glasses of the type xNa(2)O-(30-x)K2O-69.5B(2)O(3)-0.5Nd(2)O(3) (X = 5,10,15,20 and 25). Various spectroscopic parameters such as Racah (E-1, E-2 and E-3), spin-orbit (xi(4f)) and configuration interaction (alpha, beta) parameters have been calculated. The Judd-Ofelt intensity parameters (Omega(lambda)) have been calculated and the radiative transition probabilities (A(rad)), radiative lifetimes (tau(r)), branching ratios (beta) and integrated absorption cross sections (Sigma) have been obtained for certain excited states of the Nd3+, ion and are discussed with respect to x. From the fluorescence spectra, the effective fluorescence line widths (Deltalambda(eff)) and stimulated emission cross sections (sigma(p)) have been obtained for the three transitions F-4(3/2) --> I-4(9/2), F-4(3/2) --> I-4(11/2) and F-4(3/2) --> I-4(13/2) of Nd3+. The stimulated emission cross section (sigma(p)) values are found to be in the range (2.0-4.8) x 10(-2)0 cm(2) and they are large enough to indicate that the mixed alkali borate glasses could be potential laser host materials.

Optimal local polynomial regression of noisy time varying signals

We address the problem of local-polynomial modeling of smooth time-varying signals with unknown functional form, in the presence of additive noise. The problem formulation is in the time domain and the polynomial coefficients are estimated in the pointwise minimum mean square error (PMMSE) sense. The choice of the window length for local modeling introduces a bias-variance tradeoff, which we solve optimally by using the intersection-of-confidence-intervals (ICI) technique. The combination of the local polynomial model and the ICI technique gives rise to an adaptive signal model equipped with a time-varying PMMSE-optimal window length whose performance is superior to that obtained by using a fixed window length. We also evaluate the sensitivity of the ICI technique with respect to the confidence interval width. Simulation results on electrocardiogram (ECG) signals show that at 0dB signal-to-noise ratio (SNR), one can achieve about 12dB improvement in SNR. Monte-Carlo performance analysis shows that the performance is comparable to the basic wavelet techniques. For 0 dB SNR, the adaptive window technique yields about 2-3dB higher SNR than wavelet regression techniques and for SNRs greater than 12dB, the wavelet techniques yield about 2dB higher SNR.

Estimation of BT Interference in OFDM Sub Carriers with Training Signals

While wireless LAN (WLAN) is very popular now a days, its performance deteriorates in the presence of other signals like Bluetooth (BT) signal that operate in the same band as WLAN. Present interference mitigation techniques in WLAN due to BT cancel interference in WLAN sub carrier where BT has hopped but do not cancel interference in the adjacent sub carriers. In this paper BT interference signal in all the OFDM sub carriers is estimated. That is, leakage of BT in other sub carriers including the sub carriers in which it has hopped is also measured. BT signals are estimated using the training signals of OFDM system. Simulation results in AWGN noise show that proposed algorithm agrees closely with theoretical results.

A Real-time clustering system for spatio-temporal signals from network of neurons

Over past few years, the studies of cultured neuronal networks have opened up avenues for understanding the ion channels, receptor molecules, and synaptic plasticity that may form the basis of learning and memory. The hippocampal neurons from rats are dissociated and cultured on a surface containing a grid of 64 electrodes. The signals from these 64 electrodes are acquired using a fast data acquisition system MED64 (Alpha MED Sciences, Japan) at a sampling rate of 20 K samples with a precision of 16-bits per sample. A few minutes of acquired data runs in to a few hundreds of Mega Bytes. The data processing for the neural analysis is highly compute-intensive because the volume of data is huge. The major processing requirements are noise removal, pattern recovery, pattern matching, clustering and so on. In order to interface a neuronal colony to a physical world, these computations need to be performed in real-time. A single processor such as a desk top computer may not be adequate to meet this computational requirements. Parallel computing is a method used to satisfy the real-time computational requirements of a neuronal system that interacts with an external world while increasing the flexibility and scalability of the application. In this work, we developed a parallel neuronal system using a multi-node Digital Signal processing system. With 8 processors, the system is able to compute and map incoming signals segmented over a period of 200 ms in to an action in a trained cluster system in real time.

Optimizing resolution of signals in a low-IF receiver

The resolution of the digital signal path has a crucial impact on the design, performance and the power dissipation of the radio receiver data path, downstream from the ADC. The ADC quantization noise has been traditionally included with the Front End receiver noise in calculating the SNR as well as BER for the receiver. Using the IEEE 802.15.4 as an example, we show that this approach leads to an over-design for the ADC and the digital signal path, resulting in larger power. More accurate specifications for the front-end design can be obtained by making SNRreg a function of signal resolutions. We show that lower resolution signals provide adequate performance and quantization noise alone does not produce any bit-error. We find that a tight bandpass filter preceding the ADC can relax the resolution requirement and a 1-bit ADC degrades SNR by only 1.35 dB compared to 8-bit ADC. Signal resolution has a larger impact on the synchronization and a 1-bit ADC costs about 5 dB in SNR to maintain the same level of performance as a 8-bit ADC.

Bayesian framework and message passing for joint support and signal recovery of approximately sparse signals

In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly sparse signals from noisy measurements can be viewed as a problem of recovery of approximately sparse signals from noiseless measurements, making the approach applicable to strictly sparse signal recovery from noisy measurements. The support recovery embedded in the approach makes it suitable for recovery of signals with same sparsity profiles, as in the problem of multiple measurement vectors (MMV). Simulation results show that the proposed algorithm, termed as JSSR-MP (joint support and signal recovery via message passing) algorithm, achieves performance comparable to that of sparse Bayesian learning (M-SBL) algorithm in the literature, at one order less complexity compared to the M-SBL algorithm.

Optical diffraction of second-harmonic signals in the LiBO2-Nb2O5 glasses induced by self-organized LiNbO3 crystallites

The nanocrystallites ( ≈ 3 nm) of LiNbO3, evolved in the (100−x)LiBO2-xNb2O5 (5x20, in molar ratio) glass system exhibited intense second-harmonic signals in transmission mode when exposed to infrared (IR) light at λ = 1064 nm. The second-harmonic waves were found to undergo optical diffraction which was attributed to the presence of self-organized submicrometer-sized LiNbO3 crystallites that were grown within the glass matrix along the parallel damage fringes created by the IR laser radiation. Micro-Raman studies carried out on the laser-irradiated samples confirmed the self-organized crystallites to be LiNbO3.

Calculating the Effect of Uneven Terrain on Glide Path Signals

A method for calculating the bends in the glide slope due to uneven terrain is presented. A computer program written for the purpose enables the calculation of the difference in depth of modulation (DDM) at any point, taking into account the effect of uneven terrain. Results are presented for a hypothetical case of a hill in front of the runway. The program enables us to predict the glide slope bends due to irregular terrain, so that proper selection of glide slope antenna location can be made.