Hin-mediated DNA knotting and recombining promote replicon dysfunction and mutation

<p>Abstract</p> <p>Background</p> <p>The genetic code imposes a dilemma for cells. The DNA must be long enough to encode for the complexity of an organism, yet thin and flexible enough to fit within the cell. The combination of these properties greatly favors DNA collisions, which can knot and drive recombination of the DNA. Despite the well-accepted propensity of cellular DNA to collide and react with itself, it has not been established what the physiological consequences are.</p> <p>Results</p> <p>Here we analyze the effects of recombined and knotted plasmids in <it>E. coli </it>using the Hin site-specific recombination system. We show that Hin-mediated DNA knotting and recombination (i) promote replicon loss by blocking DNA replication; (ii) block gene transcription; and (iii) cause genetic rearrangements at a rate three to four orders of magnitude higher than the rate for an unknotted, unrecombined plasmid.</p> <p>Conclusion</p> <p>These results show that DNA reactivity leading to recombined and knotted DNA is potentially toxic and may help drive genetic evolution.</p

Quasi-Conformally Flat Mapping the Human Cerebellum

We present a novel approach to creating flat maps of the brain. Our approach attempts to preserve the conformal structure between the original cortical surface in 3-space and the flattened surface. We demonstrate this with data from the human cerebellum. Our maps exhibit quasiconformal behavior and offer several advantages over existing approaches. Introduction l The convoluted surface of the brain, fold complexity and anatomical variability make it difficult to compare anatomical and functional information within and between subjects. l Current visualization techniques (such as projecting functional data onto a rendered cortical surface) make it difficult to compare the location and extent of activated foci. For example, foci buried in deep sulci may appear on the cortical surface and widely separated foci on opposite walls of a sulcus may appear to be close together. Surface Flattening l The surface representing the cortical grey matter is topologically equivalent to a two-dimensi..

Cortical Surface Flattening: A Quasi-Conformal Approach Using Circle Packings

Comparing the location and size of functional brain activity across subjects is di#cult due to individual di#erences in folding patterns and functional foci are often buried within cortical sulci. Cortical flat mapping is a tool which can address these problems by taking advantage of the two-dimensional sheet topology of the cortical surface. Flat mappings of the cortex assist in simplifying complex information and may reveal spatial relationships in functional and anatomical data that were not previously apparent. Metric and areal flattening algorithms have been central to brain flattening e#orts to date. However, it is mathematically impossible to flatten a curved surface in 3-space without introducing metric and areal distortion. Nevertheless, the Riemann Mapping Theorem of complex function theory implies that it is theoretically possible to preserve conformal (angular) information under flattening. In this paper we present a novel approach for creating flat maps of the brain that involves a computer realization of the 150-year-old Riemann Mapping Theorem. This approach uses a circle packing algorithm to compute an essentially unique (i.e. up to Mobius transformations), discrete approximation of a conformal mapping from the cortical surface to the plane or the sphere. Conformal maps are very versatile and o#er a variety of visual presentations and manipulations. Maps can be displayed in three geometries: the Euclidean and hyperbolic planes, and the sphere. A wide variety of Mobius transformations can be used to zoom and focus the maps in a particular region of interest. Conformal maps are mathematically unique and canonical coordinate systems can also be specified on these maps. Although conformal maps do not attempt to preserve linear or areal information, locally t..

Hin-mediated DNA knotting and recombining promote replicon dysfunction and mutation-2

<p><b>Copyright information:</b></p><p>Taken from "Hin-mediated DNA knotting and recombining promote replicon dysfunction and mutation"</p><p>http://www.biomedcentral.com/1471-2199/8/44</p><p>BMC Molecular Biology 2007;8():44-44.</p><p>Published online 25 May 2007</p><p>PMCID:PMC1904230.</p><p></p>tral axis of the double helix). In the roadblock model, the knot (or possibly Hin bound to or cleaving DNA) is impassable and stalls polymerase. Alternatively, in the breakage model, knots may break DNA as a result of forces on the plasmid

Quatitative Comparison and Analysis of Brain Image Registration Using Frequency-Adaptive Wavelet Shrinkage

In the field of template-based medical image analysis, image registration and normalization are frequently used to eval- uate and interpret data in a standard template or reference atlas space. Despite the large number of image-registration (warping) techniques developed recently in the literature, only a few studies have been undertaken to numerically characterize and compare various alignment methods. In this paper, we introduce a new approach for analyzing image registration based on a selective- wavelet reconstruction technique using a frequency-adaptive wavelet shrinkage. We study four polynomial-based and two higher complexity nonaffine warping methods applied to groups of stereotaxic human brain structural (magnetic resonance imaging) and functional (positron emission tomography) data. Depending upon the aim of the image registration, we present several warp classification schemes. Our method uses a concise representation of the native and resliced (pre- and post-warp) data in compressed wavelet space to assess quality of registration. This technique is com- putationally inexpensive and utilizes the image compression, image enhancement, and denoising characteristics of the wavelet-based function representation, as well as the optimality properties of frequency-dependent wavelet shrinkage

Quatitative Comparison and Analysis of Brain Image Registration Using Frequency-Adaptive Wavelet Shrinkage

In the field of template-based medical image analysis, image registration and normalization are frequently used to eval- uate and interpret data in a standard template or reference atlas space. Despite the large number of image-registration (warping) techniques developed recently in the literature, only a few studies have been undertaken to numerically characterize and compare various alignment methods. In this paper, we introduce a new approach for analyzing image registration based on a selective- wavelet reconstruction technique using a frequency-adaptive wavelet shrinkage. We study four polynomial-based and two higher complexity nonaffine warping methods applied to groups of stereotaxic human brain structural (magnetic resonance imaging) and functional (positron emission tomography) data. Depending upon the aim of the image registration, we present several warp classification schemes. Our method uses a concise representation of the native and resliced (pre- and post-warp) data in compressed wavelet space to assess quality of registration. This technique is com- putationally inexpensive and utilizes the image compression, image enhancement, and denoising characteristics of the wavelet-based function representation, as well as the optimality properties of frequency-dependent wavelet shrinkage