Oxidative Stress Detection With Escherichia Coli Harboring A katG\u27::lux Fusion

A plasmid containing a transcriptional fusion of the Escherichia coli katG promoter to a truncated Vibrio fischeri lux operon (luxCDABE) was constructed. An E. coli strain bearing this plasmid (strain DPD2511) exhibited low basal levels of luminescence, which increased up to 1,000-fold in the presence of hydrogen peroxide, organic peroxides, redox-cycling agents (methyl viologen and menadione), a hydrogen peroxide-producing enzyme system (xanthine and xanthine oxidase), and cigarette smoke. An oxyR deletion abolished hydrogen peroxide-dependent induction, confirming that oxyR controlled katG\u27::lux luminescence. Light emission was also induced by ethanol by an unexplained mechanism. A marked synergistic response was observed when cells were exposed to both ethanol and hydrogen peroxide; the level of luminescence measured in the presence of both inducers was much higher than the sum of the level of luminescence observed with ethanol and the level of luminescence observed with hydrogen peroxide. It is suggested that this construction or similar constructions may be used as a tool for assaying oxidant and antioxidant properties of chemicals, as a biosensor for environmental monitoring and as a tool for studying cellular responses to oxidative hazards

Detection Of DNA Damage By Use Of Escherichia Coli Carrying recA\u27::lux, uvrA\u27::lux, And alkA\u27::lux Reporter Plasmids

Plasmids were constructed in which DNA damage-inducible promoters recA, uvrA, and alkA from Escherichia coli were fused to the Vibrio fischeri luxCDABE operon. Introduction of these plasmids into E. coli allowed the detection of a dose-dependent response to DNA-damaging agents, such as mitomycin and UV irradiation. Bioluminescence was measured in real time over extended periods. The fusion of the recA promoter to luxCDABE showed the most dramatic and sensitive responses. lexA dependence of the bioluminescent SOS response was demonstrated, confirming that this biosensor\u27s reports were transmitted by the expected regulatory circuitry. Comparisons were made between luxCDABE and lacZ fusions to each promoter. It is suggested that the lux biosensors may have use in monitoring chemical, physical, and genotoxic agents as well as in further characterizing the mechanisms of DNA repair

Fourier PCA and Robust Tensor Decomposition

Fourier PCA is Principal Component Analysis of a matrix obtained from higher order derivatives of the logarithm of the Fourier transform of a distribution.We make this method algorithmic by developing a tensor decomposition method for a pair of tensors sharing the same vectors in rank-$1$ decompositions. Our main application is the first provably polynomial-time algorithm for underdetermined ICA, i.e., learning an $n \times m$ matrix $A$ from observations $y=Ax$ where $x$ is drawn from an unknown product distribution with arbitrary non-Gaussian components. The number of component distributions $m$ can be arbitrarily higher than the dimension $n$ and the columns of $A$ only need to satisfy a natural and efficiently verifiable nondegeneracy condition. As a second application, we give an alternative algorithm for learning mixtures of spherical Gaussians with linearly independent means. These results also hold in the presence of Gaussian noise.Comment: Extensively revised; details added; minor errors corrected; exposition improve

Negative Link Prediction in Social Media

Signed network analysis has attracted increasing attention in recent years. This is in part because research on signed network analysis suggests that negative links have added value in the analytical process. A major impediment in their effective use is that most social media sites do not enable users to specify them explicitly. In other words, a gap exists between the importance of negative links and their availability in real data sets. Therefore, it is natural to explore whether one can predict negative links automatically from the commonly available social network data. In this paper, we investigate the novel problem of negative link prediction with only positive links and content-centric interactions in social media. We make a number of important observations about negative links, and propose a principled framework NeLP, which can exploit positive links and content-centric interactions to predict negative links. Our experimental results on real-world social networks demonstrate that the proposed NeLP framework can accurately predict negative links with positive links and content-centric interactions. Our detailed experiments also illustrate the relative importance of various factors to the effectiveness of the proposed framework

Nonparametric Regression on a Graph

The 'Signal plus Noise' model for nonparametric regression can be extended to the case of observations taken at the vertices of a graph. This model includes many familiar regression problems. This article discusses the use of the edges of a graph to measure roughness in penalized regression. Distance between estimate and observation is measured at every vertex in the L2 norm, and roughness is penalized on every edge in the L1 norm. Thus the ideas of total variation penalization can be extended to a graph. The resulting minimization problem presents special computational challenges, so we describe a new and fast algorithm and demonstrate its use with examples. The examples include image analysis, a simulation applicable to discrete spatial variation, and classification. In our examples, penalized regression improves upon kernel smoothing in terms of identifying local extreme values on planar graphs. In all examples we use fully automatic procedures for setting the smoothing parameters. Supplemental materials are available online. © 2011 American Statistical Association

Triggering information by context

With the increased availability of personal computers with attached sensors to capture their environment, there is a big opportunity for context-aware applications; these automatically provide information and/or take actions according to the user's present context, as detected by sensors. When wel l designed, these applications provide an opportunity to tailor the provision of information closely to the user's current needs. A sub-set of context-a ware applications are discrete applications, where discrete pieces of i nformation are attached to individual contexts, to be triggered when the user enters those contexts. The advantage of discrete applications is that authori ng them can be solely a creative process rather than a programming process: it can be a task akin to creating simple web pages. This paper looks at a general system that can be used in any discrete context- aware application. It propounds a general triggering rule, and investigates how this rule applies in practical applications

Bi-stochastic kernels via asymmetric affinity functions

In this short letter we present the construction of a bi-stochastic kernel p for an arbitrary data set X that is derived from an asymmetric affinity function {\alpha}. The affinity function {\alpha} measures the similarity between points in X and some reference set Y. Unlike other methods that construct bi-stochastic kernels via some convergent iteration process or through solving an optimization problem, the construction presented here is quite simple. Furthermore, it can be viewed through the lens of out of sample extensions, making it useful for massive data sets.Comment: 5 pages. v2: Expanded upon the first paragraph of subsection 2.1. v3: Minor changes and edits. v4: Edited comments and added DO

Chevkinite-Group Minerals from Granulite-Facies Metamorphic Rocks and Associated Pegmatites of East Antarctica and South India

Electron microprobe data are presented for chevkinite-group minerals from granulite-facies rocks and associated pegmatities of the Napier Complex and Mawson Station charnockite in East Antarctica and from the Eastern Ghats, South India. Their compositions conform to the general formula for this group, viz. A(4)BC(2)D(2)Si(4)O(22) where, in the analysed specimens A = (rare-earth elements (REE), Ca, Y, Th), B = Fe(2+) Mg, C = (Al, Mg, Ti, Fe(2+), Fe(3+), Zr) and D = Ti and plot within the perrierite field oftlic total Fe (as FeO) (wt.%) vs. CaO (wt.%) discriminator diagram of Macdonald and Belkin (2002). In contrast to most chevkinite-group minerals, the A site shows unusual enrichment in the MREE and HREE relative to the LREE and Ca. In one sample from the Napier Complex, Y is the dominant cation among the total REE + Y in the A site, the first reported case of Y-dominance in the chevkinite group. The minerals include the most Al-rich yet reported in the chevkinite group (\u3c= 9.15 wt.% Al(2)O(3)), sufficient to fill the C site in two samples. Conversely, the amount of Ti in these samples does not fill the D site. and, thus, some of the Al could be making up the deficiency at D, a situation not previously reported in the chevkinite group. Fe abudances are low, requiring Mg to occupy up to 45% of the B site. The chevkinite-group minerals analysed originated from three distinct parageneses: (1) pegmatites containing hornblende and orthopyroxene or garnet; (2) orthopyroxene-bearing gneiss and granulite; (3) highly aluminous paragneisses in which the associated minerals are relatively magnesian or aluminous. Chevkinite-group minerals from the first two parageneses have relatively high FeO content and low MgO and Al(2)O(3) contents; their compositions plot in the field for mafic and intermediate igneous rocks. In contrast, chevkinite-group minerals from the third paragenesis are notably more aluminous and have greater Mg/Fe ratios

Aligning Manifolds of Double Pendulum Dynamics Under the Influence of Noise

This study presents the results of a series of simulation experiments that evaluate and compare four different manifold alignment methods under the influence of noise. The data was created by simulating the dynamics of two slightly different double pendulums in three-dimensional space. The method of semi-supervised feature-level manifold alignment using global distance resulted in the most convincing visualisations. However, the semi-supervised feature-level local alignment methods resulted in smaller alignment errors. These local alignment methods were also more robust to noise and faster than the other methods.Comment: The final version will appear in ICONIP 2018. A DOI identifier to the final version will be added to the preprint, as soon as it is availabl