28 research outputs found

    Label-free detection of DNA single-base mismatches using a simple reflectance-based optical technique

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    Rapid and quantitative detection of the binding of nucleic acids to surface-immobilized probes remains a challenge in many biomedical applications. We investigated the hybridization of a set of fully complementary and defected 12-base long DNA oligomers by using the Reflective Phantom Interface (RPI), a recently developed multiplexed label-free detection technique. Based on the simple measurement of reflected light intensity, this technology enables to quantify the hybridization directly as it occurs on the surface with a sensitivity of 10 pg mm-2. We found a strong effect of single-base mismatches and of their location on hybridization kinetics and equilibrium binding. In line with previous studies, we found that DNA-DNA binding is weaker on a surface than in the bulk. Our data indicate that this effect is a consequence of weak nonspecific binding of the probes to the surface

    Distributed graph diameter approximation

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    We present an algorithm for approximating the diameter of massive weighted undirected graphs on distributed platforms supporting a MapReduce-like abstraction. In order to be efficient in terms of both time and space, our algorithm is based on a decomposition strategy which partitions the graph into disjoint clusters of bounded radius. Theoretically, our algorithm uses linear space and yields a polylogarithmic approximation guarantee; most importantly, for a large family of graphs, it features a round complexity asymptotically smaller than the one exhibited by a natural approximation algorithm based on the state-of-the-art 06-stepping SSSP algorithm, which is its only practical, linear-space competitor in the distributed setting. We complement our theoretical findings with a proof-of-concept experimental analysis on large benchmark graphs, which suggests that our algorithm may attain substantial improvements in terms of running time compared to the aforementioned competitor, while featuring, in practice, a similar approximation ratio

    Space and Time Efficient Parallel Graph Decomposition, Clustering, and Diameter Approximation

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    We develop a novel parallel decomposition strategy for unweighted, undirected graphs, based on growing disjoint connected clusters from batches of centers progressively selected from yet uncovered nodes. With respect to similar previous decompositions, our strategy exercises a tighter control on both the number of clusters and their maximum radius. We present two important applications of our parallel graph decomposition: (1) kk-center clustering approximation; and (2) diameter approximation. In both cases, we obtain algorithms which feature a polylogarithmic approximation factor and are amenable to a distributed implementation that is geared for massive (long-diameter) graphs. The total space needed for the computation is linear in the problem size, and the parallel depth is substantially sublinear in the diameter for graphs with low doubling dimension. To the best of our knowledge, ours are the first parallel approximations for these problems which achieve sub-diameter parallel time, for a relevant class of graphs, using only linear space. Besides the theoretical guarantees, our algorithms allow for a very simple implementation on clustered architectures: we report on extensive experiments which demonstrate their effectiveness and efficiency on large graphs as compared to alternative known approaches

    Report di monitoraggio 2012 VAS nitrati

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    Il presente documento costituisce il primo rapporto di monitoraggio ambientale che, nell\u2019ambito della procedura di VAS, \ue8 stato prodotto per descrivere l\u2019evoluzione dello stato dell\u2019ambiente, attraverso un insieme di specifici indicatori approvati dal Piano e volti a verificare lo stato di attuazione degli obiettivi prestabiliti, ossia la \u201cperformance di piano\u201d

    Multi-spot, label-free detection of viral infection in complex media by a non-reflecting surface

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    The measurement of the intensity of light reflected by interfaces with extremely low reflectivity in water enables the label-free, multiplex detection of bio-molecular interactions. The binding of targets in solution to surface-immobilized probes (e.g. antibodies) can be quantified using a simple instrumental set-up, comprising a LED source and a camera. The condition of low reflectivity can be achieved by using a perfluorinated plastic substrate with refractive index very close to that of water. Here we show that, despite its simplicity, the method enables label-free detection in complex samples with high absorbance and turbidity. Diagnostic markers of Tomato spotted wilt virus are revealed in crude plant extracts of Datura stramonium leaves at early stage of infection. The measuring procedure requires only the addition of the sample into a cuvette and the acquisition of a series of images for a few minutes. The light reflectivity of the spots of specific antibodies increases more rapidly if the sample is prepared with infected plants
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