530 research outputs found

    Chemoenzymatic Labeling of Proteins for Imaging in Bacterial Cells

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    Reliable methods to determine the subcellular localization of bacterial proteins are needed for the study of prokaryotic cell biology. We describe here a simple and general technique for imaging of bacterial proteins in situ by fluorescence microscopy. The method uses the eukaryotic enzyme N-myristoyltransferase to modify the N-terminus of the protein of interest with an azido fatty acid. Subsequent strain-promoted azide–alkyne cycloaddition allows conjugation of dyes and imaging of tagged proteins by confocal fluorescence microscopy. We demonstrate the method by labeling the chemotaxis proteins Tar and CheA and the cell division proteins FtsZ and FtsA in Escherichia coli. We observe distinct spatial patterns for each of these proteins in both fixed and live cells. The method should prove broadly useful for protein imaging in bacteria

    Land surface phenological response to decadal climate variability across Australia using satellite remote sensing

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    © 2014 Author(s). Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative spatial information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually recurring patterns. However, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e., drylands) received much less attention, despite the fact that they cover more than 30% of the global land surface. Here, we focused on Australia, a continent with one of the most variable rainfall climates in the world and vast areas of dryland systems, where a detailed phenological investigation and a characterization of the relationship between phenology and climate variability are missing. To fill this knowledge gap, we developed an algorithm to characterize phenological cycles, and analyzed geographic and climate-driven variability in phenology from 2000 to 2013, which included extreme drought and wet years. We linked derived phenological metrics to rainfall and the Southern Oscillation Index (SOI). We conducted a continent-wide investigation and a more detailed investigation over the Murray-Darling Basin (MDB), the primary agricultural area and largest river catchment of Australia. Results showed high inter-and intra-annual variability in phenological cycles across Australia. The peak of phenological cycles occurred not only during the austral summer, but also at any time of the year, and their timing varied by more than a month in the interior of the continent. The magnitude of the phenological cycle peak and the integrated greenness were most significantly correlated with monthly SOI within the preceding 12 months. Correlation patterns occurred primarily over northeastern Australia and within the MDB, predominantly over natural land cover and particularly in floodplain and wetland areas. Integrated greenness of the phenological cycles (surrogate of vegetation productivity) showed positive anomalies of more than 2 standard deviations over most of eastern Australia in 2009-2010, which coincided with the transition from the El Niño-induced decadal droughts to flooding caused by La Niña

    Design space exploration and optimization of path oblivious RAM in secure processors

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    Keeping user data private is a huge problem both in cloud computing and computation outsourcing. One paradigm to achieve data privacy is to use tamper-resistant processors, inside which users' private data is decrypted and computed upon. These processors need to interact with untrusted external memory. Even if we encrypt all data that leaves the trusted processor, however, the address sequence that goes off-chip may still leak information. To prevent this address leakage, the security community has proposed ORAM (Oblivious RAM). ORAM has mainly been explored in server/file settings which assume a vastly different computation model than secure processors. Not surprisingly, naïvely applying ORAM to a secure processor setting incurs large performance overheads. In this paper, a recent proposal called Path ORAM is studied. We demonstrate techniques to make Path ORAM practical in a secure processor setting. We introduce background eviction schemes to prevent Path ORAM failure and allow for a performance-driven design space exploration. We propose a concept called super blocks to further improve Path ORAM's performance, and also show an efficient integrity verification scheme for Path ORAM. With our optimizations, Path ORAM overhead drops by 41.8%, and SPEC benchmark execution time improves by 52.4% in relation to a baseline configuration. Our work can be used to improve the security level of previous secure processors.National Science Foundation (U.S.). Graduate Research Fellowship Program (Grant 1122374)American Society for Engineering Education. National Defense Science and Engineering Graduate FellowshipUnited States. Defense Advanced Research Projects Agency (Clean-slate design of Resilient, Adaptive, Secure Hosts Contract N66001-10-2-4089

    Wireless sensor networks for in-situ image validation for water and nutrient management

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    Water and Nitrogen (N) are critical inputs for crop production. Remote sensing data collected from multiple scales, including ground-based, aerial, and satellite, can be used for the formulation of an efficient and cost effective algorithm for the detection of N and water stress. Formulation and validation of such techniques require continuous acquisition of ground based spectral data over the canopy enabling field measurements to coincide exactly with aerial and satellite observations. In this context, a wireless sensor in situ network was developed and this paper describes the results of the first phase of the experiment along with the details of sensor development and instrumentation set up. The sensor network was established based on different spatial sampling strategies and each sensor collected spectral data in seven narrow wavebands (470, 550, 670, 700, 720, 750, 790 nm) critical for monitoring crop growth. Spectral measurements recorded at required intervals (up to 30 seconds) were relayed through a multi-hop wireless network to a base computer at the field site. These data were then accessed by the remote sensing centre computing system through broad band internet. Comparison of the data from the WSN and an industry standard ground based hyperspectral radiometer indicated that there were no significant differences in the spectral measurements for all the wavebands except for 790nm. Combining sensor and wireless technologies provides a robust means of aerial and satellite data calibration and an enhanced understanding of issues of variations in the scale for the effective water and nutrient management in wheat.<br /

    Sequential application of hyperspectral indices for delineation of stripe rust infection and nitrogen deficiency in wheat

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    © 2015, Springer Science+Business Media New York. Nitrogen (N) fertilization is crucial for the growth and development of wheat crops, and yet increased use of N can also result in increased stripe rust severity. Stripe rust infection and N deficiency both cause changes in foliar physiological activity and reduction in plant pigments that result in chlorosis. Furthermore, stripe rust produce pustules on the leaf surface which similar to chlorotic regions have a yellow color. Quantifying the severity of each factor is critical for adopting appropriate management practices. Eleven widely-used vegetation indices, based on mathematic combinations of narrow-band optical reflectance measurements in the visible/near infrared wavelength range were evaluated for their ability to discriminate and quantify stripe rust severity and N deficiency in a rust-susceptible wheat variety (H45) under varying conditions of nitrogen status. The physiological reflectance index (PhRI) and leaf and canopy chlorophyll index (LCCI) provided the strongest correlation with levels of rust infection and N-deficiency, respectively. When PhRI and LCCI were used in a sequence, both N deficiency and rust infection levels were correctly classified in 82.5 and 55 % of the plots at Zadoks growth stage 47 and 75, respectively. In misclassified plots, an overestimation of N deficiency was accompanied by an underestimation of the rust infection level or vice versa. In 18 % of the plots, there was a tendency to underestimate the severity of stripe rust infection even though the N-deficiency level was correctly predicted. The contrasting responses of the PhRI and LCCI to stripe rust infection and N deficiency, respectively, and the relative insensitivity of these indices to the other parameter makes their use in combination suitable for quantifying levels of stripe rust infection and N deficiency in wheat crops under field conditions

    Analysis of CT Brain Images using Radial Basis Function Neural Network

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    Medical image processing and analysis is the tool to assist radiologists in the diagnosis process to obtain a moreaccurate and faster diagnosis. In this work, we have developed a neural network to classify the computer tomography(CT) brain tumor image for automatic diagnosis. This system is divided into four steps namely enhancement, segmentation, feature extraction and classification. In the first phase, an edge-based selective median filter is usedto improve the visibility of the loss of the gray-white matter interface in CT brain tumor images. Second phaseuses a modified version of shift genetic algorithm for the segmentation. Next phase extracts the textural featuresusing statistical texture analysis method. These features are fed into classifiers like BPN, Fuzzy k-NN, and radialbasis function network. The performances of these classifiers are analyzed in the final phase with receiver operating characteristic and precision-recall curve. The result shows that the CAD system is only to develop the tool for braintumor and proposed method is very accurate and computationally more efficient and less time consuming.Defence Science Journal, 2012, 62(4), pp.212-218, DOI:http://dx.doi.org/10.14429/dsj.62.183

    Discovery of a Novel Class of Orally Active Trypanocidal N-Myristoyltransferase Inhibitors

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    N-Myristoyltransferase (NMT) represents a promising drug target for human African trypanosomiasis (HAT), which is caused by the parasitic protozoa Trypanosoma brucei. We report the optimization of a high throughput screening hit (1) to give a lead molecule DDD85646 (63), which has potent activity against the enzyme (IC50 = 2 nM) and T. brucei (EC50 = 2 nM) in culture. The compound has good oral pharmacokinetics and cures rodent models of peripheral HAT infection. This compound provides an excellent tool for validation of T. brucei NMT as a drug target for HAT as well as a valuable lead for further optimization.</p

    On the selection and design of proteins and peptide derivatives for the production of photoluminescent, red-emitting gold quantum clusters

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    Novel pathways of the synthesis of photoluminescent gold quantum clusters (AuQCs) using biomolecules as reactants provide biocompatible products for biological imaging techniques. In order to rationalize the rules for the preparation of red-emitting AuQCs in aqueous phase using proteins or peptides, the role of different organic structural units was investigated. Three systems were studied: proteins, peptides, and amino acid mixtures, respectively. We have found that cysteine and tyrosine are indispensable residues. The SH/S-S ratio in a single molecule is not a critical factor in the synthesis, but on the other hand, the stoichiometry of cysteine residues and the gold precursor is crucial. These observations indicate the importance of proper chemical behavior of all species in a wide size range extending from the atomic distances (in the AuI-S semi ring) to nanometer distances covering the larger sizes of proteins assuring the hierarchical structure of the whole self-assembled system

    Characterization and Evaluation of a Rare Orchid Renanthera imschootiana Rolfe from Manipur & Nagaland

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    The orchid Renanthera imschootiana Rolfe is the only species under the genus available in India at Manipur and Nagaland, which is a part of Indo-Burma mega diversity hot-spot. The only collection, NRCO-Coll-77 (1998)/IC 566525 of this species available with us was evaluated and characterized as per 'Common Descriptors of Orchids' developed at this center. Monopodial nature in habit, un-branched raceme with a length of 32.2 cm having attractive dominant red-purple (RHS-60A) flowers and petals coloured grayed orange (RHS-164C) with shade is typical of this species. Broad, lateral sepals with attractive dominant crimson/red purple colour flower having medium-range vase life of 23.7 days, imparts high breeding value to this species for developing new hybrid derivatives

    Interspecific Hybrid Developed in Epidendrum Orchid from the Cross E. radicans Pav. Ex. Lindl. X E. xanthinum Lindl.

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    An interspecific&nbsp;Epidendrum&nbsp;hybrid was developed using&nbsp;E. radicans&nbsp;(known as 'fire star orchid', 'ground-rooted orchid') as female parent and&nbsp;E. xanthinum&nbsp;known as 'yellow orchid' as male parent. The selected line (NRCO&nbsp;Epidendrum&nbsp;cross/2005-01) was characterized for morphological and floral traits. Flower size (3.5 cm x 3.4 cm) of selected line was bigger than both parents, with bright saffron-orange colour (RHS 44A). Dorsal sepal size (1.8 cm x 0.6 cm), lateral sepal size (1.9 cm x 0.7 cm), petal size (1.8 cm x 0.6 cm), lip size (2.3 cm x 2 cm) and column size (1.1 cm x 0.2 cm) were bigger than in parents. Shape and fimbriated side lobes of lip with deep cleft of anterior margins was similar to the male parent (E. xanthinum), except colour. The F1progeny of 'NRCO-Epidendrum&nbsp;cross/2005-01' flowered with different red-orange to yellow shades is categorized broadly into three types: Red-orange, Orangeyellow and Yellow.&nbsp;Epidendrums&nbsp;are popularly known as 'Crucifix orchid' and 'Poor man's orchid', have a long flowering period with 2-3 flowerings in a year, and are easy to multiply. These attributes are ideal for popularizing this plant in India as a potted plant as well garden plant
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