Titanium promoted reduction of imines with Grignards, silanes, and zinc: identification of a new mechanism with silanes

Aldimines react with reducing agents, such as Grignards, phenylsilane or zinc in the presence of titanium(IV) isopropoxide to form amines and reductively coupled imines (diamines). Using deuterium labeled reagents, the mechanism of reduction to form amines is described. Reducing agents, such as the Grignard and zinc result in the formation of low valent titanium (LVT), which in turn reduces the imine. On the other hand, phenylsilane reacts by a distinctly different mechanism and where a hydrogen atom from silicon is directly transferred to the titanium coordinated imine. (c) 2014 Elsevier Ltd. All rights reserved.

Identification of miRNAs from French bean (Phaseolus vulgaris) under low nitrate stress

Objective: In this study, we report the role of miRNAs involved under nitrogen starvation from widely grown vegetable crop, French bean. In recent years, a great deal of attention has been paid to the elucidation of miRNAs involved in low nitrate stress. Methods: To identify miRNAs expressed under stress, cDNA libraries were analyzed. Results: We reported the nine potential miRNAs with 67 targets involved in nutrient transporters and other stress specific genes. Among the miRNA sequences obtained 6 sequences belong to miR172 family, one with miR169. RT-PCR analysis of expression of miR172 family was induced upon low nitrate stress while miR169 family was repressed. In addition, Pvu-SN7b and Pvu-miR16 may be new members of miRNA172 and miR169 families, respectively. Conclusion: The targets of Pvu-SN7b were major protein kinases, one among which is the Protein Kinase CK2. CK2 Kinase is found to involve in transcription-directed signaling, gene control and cell-cycle regulation. Other targets of Pvu-SN7b were involved in DNA-dependent transcription regulation, photo-periodism, calcium-mediated signaling. Pvu-miR16 targets Thymidine kinase, the key enzyme of deoxy-nucleotide synthesis. The cleavage of these targets affects cell proliferation there by affecting nodule formation. Pvu-miR8 inhibits translation of its target protein Pre-protein translocase, a membrane-bound protein transporter involved in trans-membrane protein transportation. Together these results denote the response and role of miRNAs to nitrate-limiting conditions in French bean.

Automatic Tonic Identification in Indian Art Music: Approaches and Evaluation

The tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist chooses in order to construct the melodies during a rg(a) rendition, and all accompanying instruments are tuned using the tonic pitch. Consequently, tonic identification is a fundamental task for most computational analyses of Indian art music, such as intonation analysis, melodic motif analysis and rg recognition. In this paper we review existing approaches for tonic identification in Indian art music and evaluate them on six diverse datasets for a thorough comparison and analysis. We study the performance of each method in different contexts such as the presence/absence of additional metadata, the quality of audio data, the duration of audio data, music tradition (Hindustani/Carnatic) and the gender of the singer (male/female). We show that the approaches that combine multi-pitch analysis with machine learning provide the best performance in most cases (90% identification accuracy on average), and are robust across the aforementioned contexts compared to the approaches based on expert knowledge. In addition, we also show that the performance of the latter can be improved when additional metadata is available to further constrain the problem. Finally, we present a detailed error analysis of each method, providing further insights into the advantages and limitations of the methods.

Role of Vertex Index in Substructure Identification and Activity Prediction: A Study on Antitubercular Activity of a Series of Acid Alkyl Ester Derivatives

Tuberculosis (TB) is a life threatening disease caused due to infection from Mycobacterium tuberculosis (Mtb). That most of the TB strains have become resistant to various existing drugs, development of effective novel drug candidates to combat this disease is a need of the day. In spite of intensive research world-wide, the success rate of discovering a new anti-TB drug is very poor. Therefore, novel drug discovery methods have to be tried. We have used a rule based computational method that utilizes a vertex index, named `distance exponent index (D-x)' (taken x = -4 here) for predicting anti-TB activity of a series of acid alkyl ester derivatives. The method is meant to identify activity related substructures from a series a compounds and predict activity of a compound on that basis. The high degree of successful prediction in the present study suggests that the said method may be useful in discovering effective anti-TB compound. It is also apparent that substructural approaches may be leveraged for wide purposes in computer-aided drug design.

Identification of a novel AMPK-PEA15 axis in the anoikis-resistant growth of mammary cells

Introduction: Matrix detachment triggers anoikis, a form of apoptosis, in most normal epithelial cells, while acquisition of anoikis resistance is a prime requisite for solid tumor growth. Of note, recent studies have revealed that a small population of normal human mammary epithelial cells (HMECs) survive in suspension and generate multicellular spheroids termed `mammospheres'. Therefore, understanding how normal HMECs overcome anoikis may provide insights into breast cancer initiation and progression. Methods: Primary breast tissue-derived normal HMECs were grown as adherent monolayers or mammospheres. The status of AMP-activated protein kinase (AMPK) and PEA15 signaling was investigated by immunoblotting. Pharmacological agents and an RNA interference (RNAi) approach were employed to gauge their roles in mammosphere formation. Immunoprecipitation and in vitro kinase assays were undertaken to evaluate interactions between AMPK and PEA15. In vitro sphere formation and tumor xenograft assays were performed to understand their roles in tumorigenicity. Results: In this study, we show that mammosphere formation by normal HMECs is accompanied with an increase in AMPK activity. Inhibition or knockdown of AMPK impaired mammosphere formation. Concomitant with AMPK activation, we detected increased Ser(116) phosphorylation of PEA15, which promotes its anti-apoptotic functions. Inhibition or knockdown of AMPK impaired PEA15 Ser(116) phosphorylation and increased apoptosis. Knockdown of PEA15, or overexpression of the nonphosphorylatable S116A mutant of PEA15, also abrogated mammosphere formation. We further demonstrate that AMPK directly interacts with and phosphorylates PEA15 at Ser(116) residue, thus identifying PEA15 as a novel AMPK substrate. Together, these data revealed that AMPK activation facilitates mammosphere formation by inhibition of apoptosis, at least in part, through Ser(116) phosphorylation of PEA15. Since anoikis resistance plays a critical role in solid tumor growth, we investigated the relevance of these findings in the context of breast cancer. Significantly, we show that the AMPK-PEA15 axis plays an important role in the anchorage-independent growth of breast cancer cells both in vitro and in vivo. Conclusions: Our study identifies a novel AMPK-PEA15 signaling axis in the anchorage-independent growth of both normal and cancerous mammary epithelial cells, suggesting that breast cancer cells may employ mechanisms of anoikis resistance already inherent within a subset of normal HMECs. Thus, targeting the AMPK-PEA15 axis might prevent breast cancer dissemination and metastasis.

Iterated stochastic filters with additive updates for dynamic system identification: Annealing-type iterations and the filter bank

A nonlinear stochastic filtering scheme based on a Gaussian sum representation of the filtering density and an annealing-type iterative update, which is additive and uses an artificial diffusion parameter, is proposed. The additive nature of the update relieves the problem of weight collapse often encountered with filters employing weighted particle based empirical approximation to the filtering density. The proposed Monte Carlo filter bank conforms in structure to the parent nonlinear filtering (Kushner-Stratonovich) equation and possesses excellent mixing properties enabling adequate exploration of the phase space of the state vector. The performance of the filter bank, presently assessed against a few carefully chosen numerical examples, provide ample evidence of its remarkable performance in terms of filter convergence and estimation accuracy vis-a-vis most other competing filters especially in higher dimensional dynamic system identification problems including cases that may demand estimating relatively minor variations in the parameter values from their reference states. (C) 2014 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.

Bayesian parameter identification in dynamic state space models using modified measurement equations

When Markov chain Monte Carlo (MCMC) samplers are used in problems of system parameter identification, one would face computational difficulties in dealing with large amount of measurement data and (or) low levels of measurement noise. Such exigencies are likely to occur in problems of parameter identification in dynamical systems when amount of vibratory measurement data and number of parameters to be identified could be large. In such cases, the posterior probability density function of the system parameters tends to have regions of narrow supports and a finite length MCMC chain is unlikely to cover pertinent regions. The present study proposes strategies based on modification of measurement equations and subsequent corrections, to alleviate this difficulty. This involves artificial enhancement of measurement noise, assimilation of transformed packets of measurements, and a global iteration strategy to improve the choice of prior models. Illustrative examples cover laboratory studies on a time variant dynamical system and a bending-torsion coupled, geometrically non-linear building frame under earthquake support motions. (C) 2015 Elsevier Ltd. All rights reserved.

Identification of local variations within secondary structures of proteins

Secondary-structure elements (SSEs) play an important role in the folding of proteins. Identification of SSEs in proteins is a common problem in structural biology. A new method, ASSP (Assignment of Secondary Structure in Proteins), using only the path traversed by the C atoms has been developed. The algorithm is based on the premise that the protein structure can be divided into continuous or uniform stretches, which can be defined in terms of helical parameters, and depending on their values the stretches can be classified into different SSEs, namely -helices, 3(10)-helices, -helices, extended -strands and polyproline II (PPII) and other left-handed helices. The methodology was validated using an unbiased clustering of these parameters for a protein data set consisting of 1008 protein chains, which suggested that there are seven well defined clusters associated with different SSEs. Apart from -helices and extended -strands, 3(10)-helices and -helices were also found to occur in substantial numbers. ASSP was able to discriminate non--helical segments from flanking -helices, which were often identified as part of -helices by other algorithms. ASSP can also lead to the identification of novel SSEs. It is believed that ASSP could provide a better understanding of the finer nuances of protein secondary structure and could make an important contribution to the better understanding of comparatively less frequently occurring structural motifs. At the same time, it can contribute to the identification of novel SSEs. A standalone version of the program for the Linux as well as the Windows operating systems is freely downloadable and a web-server version is also available at .

Voice source characterization using pitch synchronous discrete cosine transform for speaker identification

A characterization of the voice source (VS) signal by the pitch synchronous (PS) discrete cosine transform (DCT) is proposed. With the integrated linear prediction residual (ILPR) as the VS estimate, the PS DCT of the ILPR is evaluated as a feature vector for speaker identification (SID). On TIMIT and YOHO databases, using a Gaussian mixture model (GMM)-based classifier, it performs on par with existing VS-based features. On the NIST 2003 database, fusion with a GMM-based classifier using MFCC features improves the identification accuracy by 12% in absolute terms, proving that the proposed characterization has good promise as a feature for SID studies. (C) 2015 Acoustical Society of America

Identification of key amino acid residues in the catalytic mechanism of diaminopropionate ammonialyase from Salmonella typhimurium

Diaminopropionate ammonialyase (DAPAL), a fold-typeII pyridoxal 5-phosphate-dependent enzyme, catalyzes the ,-elimination of diaminopropionate (DAP) to pyruvate and ammonia. DAPAL was able to utilize both d- and l-DAP as substrates with almost equal efficiency. Mutational analysis of functionally important residues such as Thr385, Asp125 and Asp194 was carried out to understand the mechanism by which the isomers are hydrolyzed. Further, the putative residues involved in the formation of disulfide bond Cys271 and Cys299 were also mutated. T385S, T385D sDAPAL were as active with dl-DAP as substrate as sDAPAL, whereas the later exhibited a threefold increase in catalytic efficiency with d-Ser as substrate. Further analysis of these mutants suggested that DAPAL might follow an anti-E-2 mechanism of catalysis that does not involve the formation of a quinonoid intermediate. Of the two mutants of Asp125, D125E showed complete loss of activity with d-DAP as substrate, whereas the reaction with l-DAP was not affected significantly, demonstrating that Asp125 was essential for abstraction of protons from the d-isomer. By contrast, mutational analysis of Asp194 showed that the residue may not be directly involved in proton abstraction from l-DAP. sDAPAL does not form a disulfide bond in solution, although the position of Cys299 and Cys271 in the modeled structure of sDAPAL favored the formation of a disulfide bond. Further, unlike eDAPAL, sDAPAL could be activated by monovalent cations. Mutation of the cysteine residues showed that Cys271 may be involved in coordinating the monovalent cation, as observed in the case of other fold-typeII enzymes.

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.

Identification of microRNAs and their targets in Finger millet by high throughput sequencing

MicroRNAs are short non-coding RNAs which play an important role in regulating gene expression by mRNA cleavage or by translational repression. The majority of identified miRNAs were evolutionarily conserved; however, others expressed in a species-specific manner. Finger millet is an important cereal crop; nonetheless, no practical information is available on microRNAs to date. In this study, we have identified 95 conserved microRNAs belonging to 39 families and 3 novel microRNAs by high throughput sequencing. For the identified conserved and novel miRNAs a total of 507 targets were predicted. 11 miRNAs were validated and tissue specificity was determined by stem loop RT-qPCR, Northern blot. GO analyses revealed targets of miRNA were involved in wide range of regulatory functions. This study implies large number of known and novel miRNAs found in Finger millet which may play important role in growth and development. (C) 2015 Elsevier B.V. All rights reserved.

A novel index for identification of weak nodes for reactive compensation to improve voltage stability

In this study, a new reactive power loss index (RPLI) is proposed for identification of weak buses in the system. This index is further used for determining the optimal locations for placement of reactive compensation devices in the power system for additional voltage support. The new index is computed from the reactive power support and loss allocation algorithm using Y-bus method for the system under intact condition and as well as critical/severe network contingencies cases. Fuzzy logic approach is used to select the important and critical/severe line contingencies from the contingency list. The inherent characteristics of the reactive power in system operation is properly addressed while determining the reactive power loss allocation to load buses. The proposed index is tested on sample 10-bus equivalent system and 72-bus practical equivalent system of Indian southern region power grid. The validation of the weak buses identification from the proposed index with that from other existing methods in the literature is carried out to demonstrate the effectiveness of the proposed index. Simulation results show that the identification of weak buses in the system from the new RPLI is completely non-iterative, thus requires minimal computational efforts as compared with other existing methods in the literature.

Definition of a serum marker panel for glioblastoma discrimination and identification of Interleukin 1 beta in the microglial secretome as a novel mediator of endothelial cell survival induced by C-reactive protein

Glioblastoma (GBM) is the most common malignant adult primary brain tumor. We profiled 724 cancer-associated proteins in sera of healthy individuals (n = 27) and GBM (n = 28) using antibody microarray. While 69 proteins exhibited differential abundance in GBM sera, a three-marker panel (LYAM1, BHE40 and CRP) could discriminate GBM sera from that of healthy donors with an accuracy of 89.7% and p < 0.0001. The high abundance of C-reactive protein (CRP) in GBM sera was confirmed in 264 independent samples. High levels of CRP protein was seen in GBM but without a change in transcript levels suggesting a non-tumoral origin. Glioma-secreted Interleukin 6 (IL6) was found to induce hepatocytes to secrete CRP, involving JAK-STAT pathway. The culture supernatant from CRP-treated microglial cells induced endothelial cell survival under nutrient-deprivation condition involving CRP-Fc gamma RIII signaling cascade. Transcript profiling of CRP-treated microglial cells identified Interleukin 1 beta (IL1 beta) present in the microglial secretome as the key mediator of CRP-induced endothelial cell survival. IL1 beta neutralization by antibody-binding or siRNA-mediated silencing in microglial cells reduced the ability of the supernatant from CRP-treated microglial cells to induce endothelial cell survival. Thus our study identifies a serum based three-marker panel for GBM diagnosis and provides leads for developing targeted therapies. Biological significance A complex antibody microarray based serum marker profiling identified a three-marker panel - LYAM1, BHE40 and CRP as an accurate discriminator of glioblastoma sera from that of healthy individuals. CRP protein is seen in high levels without a concomitant increase of CRP transcripts in glioblastoma. Glioma-secreted IL6 induced hepatocytes to produce CRP in a JAK-STAT signaling dependent manner. CRP induced microglial cells to release IL1 beta which in turn promoted endothelial cell survival. This study, besides defining a serum panel for glioblastoma discrimination, identified IL1 beta as a potential candidate for developing targeted therapy. (C) 2015 Elsevier B.V. All rights reserved.