Identification of mycobacterial lectins from genomic data

Sixty-four sequences containing lectin domains with homologs of known three-dimensional structure were identified through a search of mycobacterial genomes. They appear to belong to the -prism II, the C-type, the Microcystis virdis (MV), and the -trefoil lectin folds. The first three always occur in conjunction with the LysM, the PI-PLC, and the -grasp domains, respectively while mycobacterial -trefoil lectins are unaccompanied by any other domain. Thirty heparin binding hemagglutinins (HBHA), already annotated, have also been included in the study although they have no homologs of known three-dimensional structure. The biological role of HBHA has been well characterized. A comparison between the sequences of the lectin from pathogenic and nonpathogenic mycobacteria provides insights into the carbohydrate binding region of the molecule, but the structure of the molecule is yet to be determined. A reasonable picture of the structural features of other mycobacterial proteins containing one or the other of the four lectin domains can be gleaned through the examination of homologs proteins, although the structure of none of them is available. Their biological role is also yet to be elucidated. The work presented here is among the first steps towards exploring the almost unexplored area of the structural biology of mycobacterial lectins. Proteins 2013. (c) 2012 Wiley Periodicals, Inc.

Variance-Reduced Particle Filters for Structural System Identification Problems

A few variance reduction schemes are proposed within the broad framework of a particle filter as applied to the problem of structural system identification. Whereas the first scheme uses a directional descent step, possibly of the Newton or quasi-Newton type, within the prediction stage of the filter, the second relies on replacing the more conventional Monte Carlo simulation involving pseudorandom sequence with one using quasi-random sequences along with a Brownian bridge discretization while representing the process noise terms. As evidenced through the derivations and subsequent numerical work on the identification of a shear frame, the combined effect of the proposed approaches in yielding variance-reduced estimates of the model parameters appears to be quite noticeable. DOI: 10.1061/(ASCE)EM.1943-7889.0000480. (C) 2013 American Society of Civil Engineers.

Synthon identification in co-crystals and polymorphs with IR spectroscopy. Primary amides as a case study

IR spectroscopy has been widely employed to distinguish between different crystal forms such as polymorphs, clathrates, hydrates and co-crystals. IR has been used to monitor co-crystal formation and single synthon detection. In this work, we have developed a strategy to identify multiple supramolecular synthons in polymorphs and co-crystals with this technique. The identification of multiple synthons in co-crystals with IR is difficult for several reasons. In this paper, a four step method involving well assigned IR spectral markers that correspond to bonds in a synthon is used. IR spectra of three forms of the co-crystal system, 4-hydroxybenzoic acid: 4,4'-bipyridine (2 : 1), show clear differences that may be attributed to differences in the synthon combinations existing in the forms (synthon polymorphism). These differences were picked out from the three IR spectra and the bands analysed and assigned to synthons. Our method first identifies IR marker bands corresponding to (covalent) bonds in known/model crystals and then the markers are mapped in known co-crystals having single synthons. Thereafter, the IR markers are queried in known co-crystals with multiple synthons. Finally they are queried in unknown co-crystals with multiple synthons. In the last part of the study, the N-H stretching absorptions of primary amides that crystallize with the amide dimers linked in a ladder like chain show two specific absorptions which are used as marker absorptions and all variations of this band structure have been used to provide details on the environment around the dimer. The extended dimer can accordingly be easily distinguished from the isolated dimer.

A novel filtering framework through Girsanov correction for the identification of nonlinear dynamical systems

Using a Girsanov change of measures, we propose novel variations within a particle-filtering algorithm, as applied to the inverse problem of state and parameter estimations of nonlinear dynamical systems of engineering interest, toward weakly correcting for the linearization or integration errors that almost invariably occur whilst numerically propagating the process dynamics, typically governed by nonlinear stochastic differential equations (SDEs). Specifically, the correction for linearization, provided by the likelihood or the Radon-Nikodym derivative, is incorporated within the evolving flow in two steps. Once the likelihood, an exponential martingale, is split into a product of two factors, correction owing to the first factor is implemented via rejection sampling in the first step. The second factor, which is directly computable, is accounted for via two different schemes, one employing resampling and the other using a gain-weighted innovation term added to the drift field of the process dynamics thereby overcoming the problem of sample dispersion posed by resampling. The proposed strategies, employed as add-ons to existing particle filters, the bootstrap and auxiliary SIR filters in this work, are found to non-trivially improve the convergence and accuracy of the estimates and also yield reduced mean square errors of such estimates vis-a-vis those obtained through the parent-filtering schemes.

Identification and characterization of starvation induced msdgc-1 promoter involved in the c-di-GMP turnover

C-di-GMP Bis-(3'-5')-cyclic-dimeric-guanosine monophosphate], a second messenger is involved in intracellular communication in the bacterial species. As a result several multi-cellular behaviors in both Gram-positive and Gram-negative bacteria are directly linked to the intracellular level of c-di-GMP. The cellular concentration of c-di-GMP is maintained by two opposing activities, diguanylate cyclase (DGC) and phosphodiesterase (PDE-A). In Mycobacterium smegmatis, a single bifunctional protein MSDGC-1 is responsible for the cellular concentration of c-di-GMP. A better understanding of the regulation of c-di-GMP at the genetic level is necessary to control the function of above two activities. In this work, we have characterized the promoter element present in msdgc-1 along with the + 1 transcription start site and identified the sigma factors that regulate the transcription of msdgc-1. Interestingly, msdgc-1 utilizes SigA during the initial phase of growth, whereas near the stationary phase SigB containing RNA polymerase takes over the expression of msdgc-1. We report here that the promoter activity of msdgc-1 increases during starvation or depletion of carbon source like glucose or glycerol. When msdgc-1 is deleted, the numbers of viable cells are similar to 10 times higher in the stationary phase in comparison to that of the wild type. We propose here that msdgc-1 is involved in the regulation of cell population density. (C) 2013 Elsevier B.V. All rights reserved.

A scaled unscented transformation based directed Gaussian sum filter for nonlinear dynamic system identification

Impoverishment of particles, i.e. the discretely simulated sample paths of the process dynamics, poses a major obstacle in employing the particle filters for large dimensional nonlinear system identification. A known route of alleviating this impoverishment, i.e. of using an exponentially increasing ensemble size vis-a-vis the system dimension, remains computationally infeasible in most cases of practical importance. In this work, we explore the possibility of unscented transformation on Gaussian random variables, as incorporated within a scaled Gaussian sum stochastic filter, as a means of applying the nonlinear stochastic filtering theory to higher dimensional structural system identification problems. As an additional strategy to reconcile the evolving process dynamics with the observation history, the proposed filtering scheme also modifies the process model via the incorporation of gain-weighted innovation terms. The reported numerical work on the identification of structural dynamic models of dimension up to 100 is indicative of the potential of the proposed filter in realizing the stated aim of successfully treating relatively larger dimensional filtering problems. (C) 2013 Elsevier Ltd. All rights reserved.

On Whitespace Identification Using Randomly Deployed Sensors

This work considers the identification of the available whitespace, i.e., the regions that do not contain any existing transmitter within a given geographical area. To this end, n sensors are deployed at random locations within the area. These sensors detect for the presence of a transmitter within their radio range r(s) using a binary sensing model, and their individual decisions are combined to estimate the available whitespace. The limiting behavior of the recovered whitespace as a function of n and r(s) is analyzed. It is shown that both the fraction of the available whitespace that the nodes fail to recover as well as their radio range optimally scale as log(n)/n as n gets large. The problem of minimizing the sum absolute error in transmitter localization is also analyzed, and the corresponding optimal scaling of the radio range and the necessary minimum transmitter separation is determined.

Identification of dominant modes in random dynamical and aeroelastic systems

Identification of dominant modes is an important step in studying linearly vibrating systems, including flow-induced vibrations. In the presence of uncertainty, when some of the system parameters and the external excitation are modeled as random quantities, this step becomes more difficult. This work is aimed at giving a systematic treatment to this end. The ability to capture the time averaged kinetic energy is chosen as the primary criterion for selection of modes. Accordingly, a methodology is proposed based on the overlap of probability density functions (pdf) of the natural and excitation frequencies, proximity of the natural frequencies of the mean or baseline system, modal participation factor, and stochastic variation of mode shapes in terms of the modes of the baseline system - termed here as statistical modal overlapping. The probabilistic descriptors of the natural frequencies and mode shapes are found by solving a random eigenvalue problem. Three distinct vibration scenarios are considered: (i) undamped arid damped free vibrations of a bladed disk assembly, (ii) forced vibration of a building, and (iii) flutter of a bridge model. Through numerical studies, it is observed that the proposed methodology gives an accurate selection of modes. (C) 2015 Elsevier Ltd. All rights reserved.

Potential source identification for aerosol concentrations over a site in Northwestern India

The collocated measurements of aerosols size distribution (ASD) and aerosol optical thickness (AOT) are analyzed simultaneously using Grimm aerosol spectrometer and MICROTOP II Sunphotometer over Jaipur, capital of Rajasthan in India. The contrast temperature characteristics during winter and summer seasons of year 2011 are investigated in the present study. The total aerosol number concentration (TANC, 0.3-20 mu m) during winter season was observed higher than in summer time and it was dominated by fine aerosol number concentration (FANC < 2 mu m). Particles smaller than 0.8 mu m (at aerodynamic size) constitute similar to 99% of all particles in winter and similar to 90% of particles in summer season. However, particles greater than 2 mu m contribute similar to 3% and similar to 0.2% in summer and winter seasons respectively. The aerosols optical thickness shows nearly similar AOT values during summer and winter but corresponding low Angstrom Exponent (AE) values during summer than winter, respectively. In this work, Potential Source Contribution Function (PSCF) analysis is applied to identify locations of sources that influenced concentrations of aerosols over study area in two different seasons. PSCF analysis shows that the dust particles from That Desert contribute significantly to the coarse aerosol number concentration (CANC). Higher values of the PSCF in north from Jaipur showed the industrial areas in northern India to be the likely sources of fine particles. The variation in size distribution of aerosols during two seasons is clearly reflected in the log normal size distribution curves. The log normal size distribution curves reveals that the particle size less than 0.8 pm is the key contributor in winter for higher ANC. (C) 2015 Elsevier B.V. All rights reserved.

Archeal lectins: An identification through a genomic search

Forty-six lectin domains which have homologues among well established eukaryotic and bacterial lectins of known three-dimensional structure, have been identified through a search of 165 archeal genomes using a multipronged approach involving domain recognition, sequence search and analysis of binding sites. Twenty-one of them have the 7-bladed -propeller lectin fold while 16 have the -trefoil fold and 7 the legume lectin fold. The remainder assumes the C-type lectin, the -prism I and the tachylectin folds. Acceptable models of almost all of them could be generated using the appropriate lectins of known three-dimensional structure as templates, with binding sites at one or more expected locations. The work represents the first comprehensive bioinformatic study of archeal lectins. The presence of lectins with the same fold in all domains of life indicates their ancient origin well before the divergence of the three branches. Further work is necessary to identify archeal lectins which have no homologues among eukaryotic and bacterial species. Proteins 2016; 84:21-30. (c) 2015 Wiley Periodicals, Inc.

Identification of a biomarker panel for colorectal cancer diagnosis

Background: Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods: A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60- mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results: After an exhaustive process of pre-processing to ensure data quality–lost values imputation, probes quality, data smoothing and intraclass variability filtering–the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions: We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).

Automatic identification and enumeration of algae

A good understanding of the population dynamics of algal communities is vital in many ecological and pollution studies of freshwater and oceanic systems. Present methods require manual counting and identification of algae and can take up to 90 min to obtain a statistically reliable count on a complex population. Several alternative techniques to accelerate the process have been tried on marine samples but none have been completely successful because insufficient effort has been put into verifying the technique before field trials. The objective of the present study has been to assess the potential of in vivo fluorescence of algal pigments as a means of automatically identifying algae. For this work total fluorescence spectroscopy was chosen as the observation technique.

Identification of the main allergen sensitizers in an Iran asthmatic population by molecular diagnosis

Background: There has been a significant growth in the prevalence of allergy, mainly associated to IgE-mediated disorders such as asthma and rhinitis. The identification of atopy in asthmatic patients through the measurement of specific IgE can help to identify risk factors that cause asthmatic symptoms in patients. The development and use of individualized allergen-based tests by the Component Resolved Diagnosis has been a crucial advance in the accurate diagnosis and control of allergic patients. The objective of this work was to assess the usefulness of molecular diagnosis to identify environmental allergens as possible factors influencing the development and manifestation of asthma in a group of asthmatic patients from Iran. Methods: Studied population: 202 adult asthmatic patients treated at the Loghman Hakim Hospital and Pasteur Institute of Teheran (Iran) from 2011 to 2012. Specific IgE determined by the ImmunoCAP system were used to both evaluate the patients' atopic condition and the molecules involved in the allergic sensitization. SDS-PAGE IgE-immunoblotting associated with mass spectrometry was carried out to study the cockroach IgE-binding sensitizing proteins. Results: Forty-five percent of all patients could be considered atopic individuals. Eighty-two percent of atopic patients were sensitized to pollen allergens. The Salsola kali (Sal k 1) and the Phleum pratense (rPhl p 1 and/or rPhl p 5) major allergens were the most common sensitizers among pollens (71% and 18%, respectively). Thirty-five percent of the atopic population was sensitized to cockroach. Four different allergens, including a previously unknown alpha-amylase, were identified in the cockroach extract. No significant associations could be demonstrated between the severity of asthma and the specific IgE levels in the atopic population. Statistical analysis identified the Sal k 1 as the main protein allergen influencing the development and expression of asthma in the studied population. Conclusions: Pollen and cockroach were the most relevant allergen sources in the asthmatic population. The Salsola kali major allergen was the main cause for sensitization in the atopic patients suffering asthma. Using the Component Resolved Diagnosis, it was possible to identify a new Blattella germanica cockroach allergen (Blattella alpha amylase 53 kDa) that could sensitize a relevant percentage of this population.

Balanced parametrizations and canonical forms for system identification

This paper contains a review of recent results concerning the parametrization of asymptotically stable linear systems using balanced realizations. Particular emphasis is given on the application of these results to system identification. This work is part of a continuing programme aimed at elucidating the role of balanced realization in system identification.

Identification and characterization of novel reptile cathelicidins from elapid snakes

Three cDNA sequences coding for elapid cathelicidins were cloned from constructed venom gland cDNA libraries of Naja atra, Bungarus fasciatus and Ophiophagus hannah. The open reading frames of the cloned elapid cathelicidins were all composed of 576 bp an