123,256 research outputs found

    Glycosylases and AP-cleaving enzymes as a general tool for probe-directed cleavage of ssDNA targets

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    The current arsenal of molecular tools for site-directed cleavage of single-stranded DNA (ssDNA) is limited. Here, we describe a method for targeted DNA cleavage that requires only the presence of an A nucleotide at the target position. The procedure involves hybridization of a complementary oligonucleotide probe to the target sequence. The probe is designed to create a deliberate G:A mismatch at the desired position of cleavage. The DNA repair enzyme MutY glycosylase recognizes the mismatch structure and selectively removes the mispaired A from the duplex to create an abasic site in the target strand. Addition of an AP-endonuclease, such as Endonuclease IV, subsequently cleaves the backbone dividing the DNA strand into two fragments. With an appropriate choice of an AP-cleaving enzyme, the 3ā€²- and 5ā€²-ends of the cleaved DNA are suitable to take part in subsequent enzymatic reactions such as priming for polymerization or joining by DNA ligation. We define suitable standard reaction conditions for glycosylase/AP-cleaving enzyme (G/AP) cleavage, and demonstrate the use of the method in an improved scheme for in situ detection using target-primed rolling-circle amplification of padlock probes

    Three-Dimensional Spectral-Domain Optical Coherence Tomography Data Analysis for Glaucoma Detection

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    Purpose: To develop a new three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) data analysis method using a machine learning technique based on variable-size super pixel segmentation that efficiently utilizes full 3D dataset to improve the discrimination between early glaucomatous and healthy eyes. Methods: 192 eyes of 96 subjects (44 healthy, 59 glaucoma suspect and 89 glaucomatous eyes) were scanned with SD-OCT. Each SD-OCT cube dataset was first converted into 2D feature map based on retinal nerve fiber layer (RNFL) segmentation and then divided into various number of super pixels. Unlike the conventional super pixel having a fixed number of points, this newly developed variable-size super pixel is defined as a cluster of homogeneous adjacent pixels with variable size, shape and number. Features of super pixel map were extracted and used as inputs to machine classifier (LogitBoost adaptive boosting) to automatically identify diseased eyes. For discriminating performance assessment, area under the curve (AUC) of the receiver operating characteristics of the machine classifier outputs were compared with the conventional circumpapillary RNFL (cpRNFL) thickness measurements. Results: The super pixel analysis showed statistically significantly higher AUC than the cpRNFL (0.855 vs. 0.707, respectively, p = 0.031, Jackknife test) when glaucoma suspects were discriminated from healthy, while no significant difference was found when confirmed glaucoma eyes were discriminated from healthy eyes. Conclusions: A novel 3D OCT analysis technique performed at least as well as the cpRNFL in glaucoma discrimination and even better at glaucoma suspect discrimination. This new method has the potential to improve early detection of glaucomatous damage. Ā© 2013 Xu et al

    Fast and Accurate Algorithm for Eye Localization for Gaze Tracking in Low Resolution Images

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    Iris centre localization in low-resolution visible images is a challenging problem in computer vision community due to noise, shadows, occlusions, pose variations, eye blinks, etc. This paper proposes an efficient method for determining iris centre in low-resolution images in the visible spectrum. Even low-cost consumer-grade webcams can be used for gaze tracking without any additional hardware. A two-stage algorithm is proposed for iris centre localization. The proposed method uses geometrical characteristics of the eye. In the first stage, a fast convolution based approach is used for obtaining the coarse location of iris centre (IC). The IC location is further refined in the second stage using boundary tracing and ellipse fitting. The algorithm has been evaluated in public databases like BioID, Gi4E and is found to outperform the state of the art methods.Comment: 12 pages, 10 figures, IET Computer Vision, 201

    Magnetic pattern at supergranulation scale: the Void Size Distribution

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    The large-scale magnetic pattern of the quiet sun is dominated by the magnetic network. This network, created by photospheric magnetic fields swept into convective downflows, delineates the boundaries of large scale cells of overturning plasma and exhibits voids in magnetic organization. Such voids include internetwork fields, a mixed-polarity sparse field that populate the inner part of network cells. To single out voids and to quantify their intrinsic pattern a fast circle packing based algorithm is applied to 511 SOHO/MDI high resolution magnetograms acquired during the outstanding solar activity minimum between 23 and 24 cycles. The computed Void Distribution Function shows a quasi-exponential decay behavior in the range 10-60 Mm. The lack of distinct flow scales in such a range corroborates the hypothesis of multi-scale motion flows at the solar surface. In addition to the quasi-exponential decay we have found that the voids reveal departure from a simple exponential decay around 35 Mm.Comment: 6 pages, 8 figures, to appear in Astronomy and Astrophysic
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