Detection and characterisation of circulating cysticercal antigens in human cerebrospinal fluid

With biotin labelled and unlabelled immunoglobulin fraction of anticysticercal antibodies raised in rabbits, tandem-enzyme linked immunosorbent assay (T-ELISA), capture-dot immunobinding assay (C-DIA) and reverse passive haemagglutination (RPHA) tests were developed for the detection of cysticercal antigens. The sensitivity levels were respectively, 9 ng ml−1, 2 ng ml−1 and 45 ng ml−1. All three methods were of equal specificity as none of the antigens of Mycobacterium tuberculosis, Japanese encephalitis virus and Echinococcus granulosus reacted with anticysticercal IgG. Cysticercal antigens were detected in the cerebrospinal fluid (CSF) of confirmed neurocysticercosis at sensitivity levels of 91·6% by T-ELISA, 83·33% by C-DIA and 75% by RPHA and specificity levels of >93%. Western analysis of these antigens in CSF showed mainly antigens of 64–68 kDa and 24–28 kDA. By crossed immunoelectrophoresis (CIE) with an intermediate gel technique, five circulating antigens were found to be released from scolex and fluid.

Microbial identification by detection of ligation probes on DNA microarray

Microbes in natural and artificial environments as well as in the human body are a key part of the functional properties of these complex systems. The presence or absence of certain microbial taxa is a correlate of functional status like risk of disease or course of metabolic processes of a microbial community. As microbes are highly diverse and mostly notcultivable, molecular markers like gene sequences are a potential basis for detection and identification of key types. The goal of this thesis was to study molecular methods for identification of microbial DNA in order to develop a tool for analysis of environmental and clinical DNA samples. Particular emphasis was placed on specificity of detection which is a major challenge when analyzing complex microbial communities. The approach taken in this study was the application and optimization of enzymatic ligation of DNA probes coupled with microarray read-out for high-throughput microbial profiling. The results show that fungal phylotypes and human papillomavirus genotypes could be accurately identified from pools of PCR amplicons generated from purified sample DNA. Approximately 1 ng/μl of sample DNA was needed for representative PCR amplification as measured by comparisons between clone sequencing and microarray. A minimum of 0,25 amol/μl of PCR amplicons was detectable from amongst 5 ng/μl of background DNA, suggesting that the detection limit of the test comprising of ligation reaction followed by microarray read-out was approximately 0,04%. Detection from sample DNA directly was shown to be feasible with probes forming a circular molecule upon ligation followed by PCR amplification of the probe. In this approach, the minimum detectable relative amount of target genome was found to be 1% of all genomes in the sample as estimated from 454 deep sequencing results. Signal-to-noise of contact printed microarrays could be improved by using an internal microarray hybridization control oligonucleotide probe together with a computational algorithm. The algorithm was based on identification of a bias in the microarray data and correction of the bias as shown by simulated and real data. The results further suggest semiquantitative detection to be possible by ligation detection, allowing estimation of target abundance in a sample. However, in practise, comprehensive sequence information of full length rRNA genes is needed to support probe design with complex samples. This study shows that DNA microarray has the potential for an accurate microbial diagnostic platform to take advantage of increasing sequence data and to replace traditional, less efficient methods that still dominate routine testing in laboratories. The data suggests that ligation reaction based microarray assay can be optimized to a degree that allows good signal-tonoise and semiquantitative detection.

Coordination-Driven Self-Assembly of M3L2 Trigonal Cages from Preorganized Metalloligands Incorporating Octahedral Metal Centers and Fluorescent Detection of Nitroaromatics

The design and preparation of novel M3L2 trigonal cages via the coordination-driven self-assembly of preorganized metalloligands containing octahedral aluminum(III), gallium(III), or ruthenium(II) centers is described. When tritopic or dinuclear linear metalloligands and appropriate complementary subunits are employed, M3L2 trigonal-bipyramidal and trigonal-prismatic cages are self-assembled under mild conditions. These three-dimensional cages were characterized with multinuclear NMR spectroscopy (H-1 and P-31) and high-resolution electrospray ionization mass spectrometry. The structure of one such trigonal-prismatic cage, self-assembled from an arene ruthenium metalloligand, was confirmed via single-crystal X-ray crystallography. The fluorescent nature of these prisms, due to the presence of their electron-rich ethynyl functionalities, prompted photophysical studies, which revealed that electron-deficient nitroaromatics are effective quenchers of the cages' emission. Excited-state charge transfer from the prisms to the nitroaromatic substrates can be used as the basis for the development of selective and discriminatory turn-off fluorescent sensors for nitroaromatics.

Ring Resonators and Micro Fluidics: Novel Design for Drug/Disease Detection

MEMS systems are technologically developed from integrated circuit industry to create miniature sensors and actuators. Originally these semiconductor processes and materials were used to build electrical and mechanical systems, but expanded to include biological, optical fluidic magnetic and other systems 12]. Here a novel approach is suggested where in two different fields are integrated via moems, micro fluidics and ring resonators. It is well known at any preliminary stage of disease onset, many physiological changes occur in the body fluids like saliva, blood, urine etc. The drawback till now was that current calibrations are not sensitive enough to detect the minor physiological changes. This is overcome using optical detector techniques 1]. The basic concepts of ring resonators, with slight variations can be used for optical detection of these minute disease markers. A well known fact of ring resonators is that a change in refractive index will trigger a shift in the resonant wavelength 5]. The trigger for the wavelength shift in the case discussed will be the presence of disease agents. To trap the disease agents specific antibody has to be used (e. g. BSA).

Development and characterization of monoclonal antibodies against WbSXP-1 for the detection of circulating filarial antigens

The importance of developing effective assays to diagnose, monitor and evaluate human lymphatic filariasis has been emphasized by the World Health Organization. Presently, few immunodiagnostics are available for filarial monitoring programmes. The Wuchereria bancrofti (Wb) SXP-1 parasite protein, with 84% homology to Brugia malayi (Bm) SXP-1, was found to be highly immunogenic. WbSXP-1 is one among the diagnostic candidate molecules that were used for developing a rapid-antibody-flow-through diagnostic kit for filariasis. Studies were initiated with the aim of developing monoclonal antibodies against recombinant WbSXP-1 and prospective applications for the detection of both circulating Wb and Bm antigens in serum samples from infected individuals. The monoclones 1A6C2 of subclass IgG1k, and 2A12F8 of class IgM, specifically detected Wb and Bm microfilaria isolated from patients and did not show cross-reactivity with other filarial recombinant antigens. We anticipate that this work will address the problems faced in the rapid diagnosis of human lymphatic filariasis in endemic areas in developing countries.

Improving fault detection and reliability in FDDI networks

FDDI (Fibre Distributed Data Interface) is a 100 Mbit/s token ring network with two counter rotating optical rings. In this paper various possible faults (like lost token, link failures, etc.) are considered, and fault detection and the ring recovery process in case of a failure and the reliability mechanisms provided are studied. We suggest a new method to improve the fault detection and ring recovery process. The performance improvement in terms of station queue length and the average delay is compared with the performance of the existing fault detection and ring recovery process through simulation. We also suggest a modification for the physical configuration of the FDDI networks within the guidelines set by the standard to make the network more reliable. It is shown that, unlike the existing FDDI network, full connectivity is maintained among the stations even when multiple single link failures occur. A distributed algorithm is proposed for link reconfiguration of the modified FDDI network when many successive as well as simultaneous link failures occur. The performance of the modified FDDI network under link failures is studied through simulation and compared with that of the existing FDDI network.

High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Performance

Large MIMO systems with tens of antennas in each communication terminal using full-rate non-orthogonal space-time block codes (STBC) from Cyclic Division Algebras (CDA) can achieve the benefits of both transmit diversity as well as high spectral efficiencies. Maximum-likelihood (ML) or near-ML decoding of these large-sized STBCs at low complexities, however, has been a challenge. In this paper, we establish that near-ML decoding of these large STBCs is possible at practically affordable low complexities. We show that the likelihood ascent search (LAS) detector, reported earlier by us for V-BLAST, is able to achieve near-ML uncoded BER performance in decoding a 32x32 STBC from CDA, which employs 32 transmit antennas and sends 32(2) = 1024 complex data symbols in 32 time slots in one STBC matrix (i.e., 32 data symbols sent per channel use). In terms of coded BER, with a 16x16 STBC, rate-3/4 turbo code and 4-QAM (i.e., 24 bps/Hz), the LAS detector performs close to within just about 4 dB from the theoretical MIMO capacity. Our results further show that, with LAS detection, information lossless (ILL) STBCs perform almost as good as full-diversity ILL (FD-ILL) STBCs. Such low-complexity detectors can potentially enable implementation of high spectral efficiency large MIMO systems that could be considered in wireless standards.

Layered Tabu Search Algorithm for Large-MIMO Detection and a Lower Bound on ML Performance

In this paper, we are concerned with low-complexity detection in large multiple-input multiple-output (MIMO) systems with tens of transmit/receive antennas. Our new contributions in this paper are two-fold. First, we propose a low-complexity algorithm for large-MIMO detection based on a layered low-complexity local neighborhood search. Second, we obtain a lower bound on the maximum-likelihood (ML) bit error performance using the local neighborhood search. The advantages of the proposed ML lower bound are i) it is easily obtained for MIMO systems with large number of antennas because of the inherent low complexity of the search algorithm, ii) it is tight at moderate-to-high SNRs, and iii) it can be tightened at low SNRs by increasing the number of symbols in the neighborhood definition. Interestingly, the proposed detection algorithm based on the layered local search achieves bit error performances which are quite close to this lower bound for large number of antennas and higher-order QAM. For e. g., in a 32 x 32 V-BLAST MIMO system, the proposed detection algorithm performs close to within 1.7 dB of the proposed ML lower bound at 10(-3) BER for 16-QAM (128 bps/Hz), and close to within 4.5 dB of the bound for 64-QAM (192 bps/Hz).

Bayesian Learning for Joint Sparse OFDM Channel Estimation and Data Detection

The impulse response of a typical wireless multipath channel can be modeled as a tapped delay line filter whose non-zero components are sparse relative to the channel delay spread. In this paper, a novel method of estimating such sparse multipath fading channels for OFDM systems is explored. In particular, Sparse Bayesian Learning (SBL) techniques are applied to jointly estimate the sparse channel and its second order statistics, and a new Bayesian Cramer-Rao bound is derived for the SBL algorithm. Further, in the context of OFDM channel estimation, an enhancement to the SBL algorithm is proposed, which uses an Expectation Maximization (EM) framework to jointly estimate the sparse channel, unknown data symbols and the second order statistics of the channel. The EM-SBL algorithm is able to recover the support as well as the channel taps more efficiently, and/or using fewer pilot symbols, than the SBL algorithm. To further improve the performance of the EM-SBL, a threshold-based pruning of the estimated second order statistics that are input to the algorithm is proposed, and its mean square error and symbol error rate performance is illustrated through Monte-Carlo simulations. Thus, the algorithms proposed in this paper are capable of obtaining efficient sparse channel estimates even in the presence of a small number of pilots.

Low-Complexity Detection and Performance in Multi-Gigabit High Spectral Efficiency Wireless Systems

Recently, we reported a low-complexity likelihood ascent search (LAS) detection algorithm for large MIMO systems with several tens of antennas that can achieve high spectral efficiencies of the order of tens to hundreds of bps/Hz. Through simulations, we showed that this algorithm achieves increasingly near SISO AWGN performance for increasing number of antennas in Lid. Rayleigh fading. However, no bit error performance analysis of the algorithm was reported. In this paper, we extend our work on this low-complexity large MIMO detector in two directions: i) We report an asymptotic bit error probability analysis of the LAS algorithm in the large system limit, where N-t, N-r -> infinity keeping N-t = N-r, where N-t and N-r are the number of transmit and receive antennas, respectively. Specifically, we prove that the error performance of the LAS detector for V-BLAST with 4-QAM in i.i.d. Rayleigh fading converges to that of the maximum-likelihood (ML) detector as N-t, N-r -> infinity keeping N-t = N-r ii) We present simulated BER and nearness to capacity results for V-BLAST as well as high-rate non-orthogonal STBC from Division Algebras (DA), in a more realistic spatially correlated MIMO channel model. Our simulation results show that a) at an uncoded BER of 10(-3), the performance of the LAS detector in decoding 16 x 16 STBC from DA with N-t = = 16 and 16-QAM degrades in spatially correlated fading by about 7 dB compared to that in i.i.d. fading, and 19) with a rate-3/4 outer turbo code and 48 bps/Hz spectral efficiency, the performance degrades by about 6 dB at a coded BER of 10(-4). Our results further show that providing asymmetry in number of antennas such that N-r > N-t keeping the total receiver array length same as that for N-r = N-t, the detector is able to pick up the extra receive diversity thereby significantly improving the BER performance.

Thermolabile ribonucleases from antarctic psychrotrophic bacteria: detection of the enzyme in various bacteria and purification from Pseudomonas fluorescens

Thirteen terrestrial psychrotrophic bacteria from Antarctica were screened for the presence of a thermolabile ribonuclease (RNAase-HL). The enzyme was detected in three isolates of Pseudomonas fluorescens and one isolate of Pseudomonas syringae. It was purified from one P. Fluorescens isolate and the molecular mass of the enzyme as determined by SDS-PAGE was 16 kDa. RNAase-HL exhibited optimum activity around 40 degrees C at pH 7.4. It could hydrolyse Escherichia coli RNA and the synthetic substrates poly(A), poly(C), poly(U) and poly(A-U). Unlike the crude RNAase from mesophilic P. Fluorescens and pure bovine pancreatic RNAase A which were active even at 65 degrees C, RNAase-HL was totally and irreversibly inactivated at 65 degrees C.

Detection of nif genes in nitrogen-fixing bacterial isolate from tomato (Lycopersicon esculentum Mill cv Pusa ruby)

Nitrogen-fixing bacterial isolate from the intercellular spaces of tomato root cortical cells was studied for the location of nif genes on the chromosomal or plasmid DNA. The bacterial isolate showed two plasmids of approximate molecular sizes of 220 and 120 kb. Klebsiella pneumoniae nif HDK probe hybridized with the chromosomal DNA and not with the plasmid DNA thereby showing that nif genes are localised on the chromosomal DNA.

Leak Detection In Pressure Tubes Of A Pressurized Heavy-Water Reactor By Acoustic-Emission Technique

Leak detection in the fuel channels is one of the challenging problems during the in-service inspection (ISI) of Pressurised Heavy Water Reactors (PHWRs). In this paper, the use of an acoustic emission (AE) technique together with AE signal analysis is described, to detect a leak that was ncountered in one (or more) of the 306 fuel channels of the Madras Atomic Power Station (PHWR), Unit I. The paper describes the problems encountered during the ISI, the experimental methods adopted and the results obtained. Results obtained using acoustic emission signal analysis are compared with those obtained from other leak detection methods used in such cases.

Development of specific DNA probes and their usage in the detection of Plasmodium vivax infection in blood

The application of nucleic acid probes, in the detection of pathogenic micro-organisms, has become an integral part of diagnostic technologies. In this study, Plasmodium vivax-specific DNA probes have been identified by carrying out genomic subtractive hybridization. In this approach, the recombinant clones from a P. vivax genomic library are screened with radiolabelled human and P. falciparum DNA. The colonies which react with labelled P. falciparum and human DNA are eliminated and those which do not produce any autoradiographic signal have been subjected to further screening procedures. Three Fl vivax specific DNA probes have been obtained by these repeated screenings. Further analyses indicate that these probes are specific and sensitive enough to detect P. vivax infection in clinical blood samples when used in a non-radioactive DNA hybridization assay. (C) 1995 Academic Press Limited

Performance of the generalized delta rule in structural damage detection

The paper examines the suitability of the generalized data rule in training artificial neural networks (ANN) for damage identification in structures. Several multilayer perceptron architectures are investigated for a typical bridge truss structure with simulated damage stares generated randomly. The training samples have been generated in terms of measurable structural parameters (displacements and strains) at suitable selected locations in the structure. Issues related to the performance of the network with reference to hidden layers and hidden. neurons are examined. Some heuristics are proposed for the design of neural networks for damage identification in structures. These are further supported by an investigation conducted on five other bridge truss configurations.