Segmentation, Reconstruction, and Analysis of Blood Thrombus Formation in 3D 2-Photon Microscopy Images

We study the problem of segmenting, reconstructing, and analyzing the structure growth of thrombi (clots) in blood vessels in vivo based on 2-photon microscopic image data. First, we develop an algorithm for segmenting clots in 3D microscopic images based on density-based clustering and methods for dealing with imaging artifacts. Next, we apply the union-of-balls (or alpha-shape) algorithm to reconstruct the boundary of clots in 3D. Finally, we perform experimental studies and analysis on the reconstructed clots and obtain quantitative data of thrombus growth and structures. We conduct experiments on laser-induced injuries in vessels of two types of mice (the wild type and the type with low levels of coagulation factor VII) and analyze and compare the developing clot structures based on their reconstructed clots from image data. The results we obtain are of biomedical significance. Our quantitative analysis of the clot composition leads to better understanding of the thrombus development, and is valuable to the modeling and verification of computational simulation of thrombogenesis

The Dynamics of Sustained Reentry in a Loop Model with Discrete Gap Junction Resistance

Dynamics of reentry are studied in a one dimensional loop of model cardiac cells with discrete intercellular gap junction resistance ($R$). Each cell is represented by a continuous cable with ionic current given by a modified Beeler-Reuter formulation. For $R$ below a limiting value, propagation is found to change from period-1 to quasi-periodic ($QP$) at a critical loop length ($L_{crit}$) that decreases with $R$. Quasi-periodic reentry exists from $L_{crit}$ to a minimum length ($L_{min}$) that is also shortening with $R$. The decrease of $L_{crit}(R)$ is not a simple scaling, but the bifurcation can still be predicted from the slope of the restitution curve giving the duration of the action potential as a function of the diastolic interval. However, the shape of the restitution curve changes with $R$.Comment: 6 pages, 7 figure

Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation

Abstract Segmentation of 3D images is a fundamental problem in biomedical image analysis. Deep learning (DL) approaches have achieved state-of-the-art segmentation performance. To exploit the 3D contexts using neural networks, known DL segmentation methods, including 3D convolution, 2D convolution on planes orthogonal to 2D image slices, and LSTM in multiple directions, all suffer incompatibility with the highly anisotropic dimensions in common 3D biomedical images. In this paper, we propose a new DL framework for 3D image segmentation, based on a combination of a fully convolutional network (FCN) and a recurrent neural network (RNN), which are responsible for exploiting the intra-slice and inter-slice contexts, respectively. To our best knowledge, this is the first DL framework for 3D image segmentation that explicitly leverages 3D image anisotropism. Evaluating using a dataset from the ISBI Neuronal Structure Segmentation Challenge and in-house image stacks for 3D fungus segmentation, our approach achieves promising results comparing to the known DL-based 3D segmentation approaches

An in vitro-identified high-affinity nucleosome-positioning signal is capable of transiently positioning a nucleosome in vivo

<p>Abstract</p> <p>Background</p> <p>The physiological function of eukaryotic DNA occurs in the context of nucleosomal arrays that can expose or obscure defined segments of the genome. Certain DNA sequences are capable of strongly positioning a nucleosome <it>in vitro</it>, suggesting the possibility that favorable intrinsic signals might reproducibly structure chromatin segments. As high-throughput sequencing analyses of nucleosome coverage <it>in vitro </it>and <it>in vivo </it>have become possible, a vigorous debate has arisen over the degree to which intrinsic DNA:nucleosome affinities orchestrate the <it>in vivo </it>positions of nucleosomes, thereby controlling physical accessibility of specific sequences in DNA.</p> <p>Results</p> <p>We describe here the <it>in vivo </it>consequences of placing a synthetic high-affinity nucleosome-positioning signal, the 601 sequence, into a DNA plasmid vector in mice. Strikingly, the 601 sequence was sufficient to position nucleosomes during an early phase after introduction of the DNA into the mice (when the plasmid vector transgene was active). This positioning capability was transient, with a loss of strong positioning at a later time point when the transgenes had become silent.</p> <p>Conclusions</p> <p>These results demonstrate an ability of DNA sequences selected solely for nucleosome affinity to organize chromatin <it>in vivo</it>, and the ability of other mechanisms to overcome these interactions in a dynamic nuclear environment.</p

Pre-Training LiDAR-Based 3D Object Detectors Through Colorization

Accurate 3D object detection and understanding for self-driving cars heavily relies on LiDAR point clouds, necessitating large amounts of labeled data to train. In this work, we introduce an innovative pre-training approach, Grounded Point Colorization (GPC), to bridge the gap between data and labels by teaching the model to colorize LiDAR point clouds, equipping it with valuable semantic cues. To tackle challenges arising from color variations and selection bias, we incorporate color as "context" by providing ground-truth colors as hints during colorization. Experimental results on the KITTI and Waymo datasets demonstrate GPC's remarkable effectiveness. Even with limited labeled data, GPC significantly improves fine-tuning performance; notably, on just 20% of the KITTI dataset, GPC outperforms training from scratch with the entire dataset. In sum, we introduce a fresh perspective on pre-training for 3D object detection, aligning the objective with the model's intended role and ultimately advancing the accuracy and efficiency of 3D object detection for autonomous vehicles

Governing and innovation: the transition to E-mobility - A dutch perspective

This is an essay approach to develop a discussion about the role government can play in stimulating electric vehicle (EV) diffusion, adoption and deployment in support of larger societal goals such as sustainability and urban livability. This reviews governance strategy in support of electric vehicle innovation in a way that integrate many societal actors, including the market to move forward a project with many spillover benefits. It does this by reference to examples and projects in the Netherlands, the EU and the U.S. that articulate these strategies. This is a Dutch perspective because it is written in that context but it has examples and viewpoints that should have a wider appeal

Census 2010 Demographic Profile: Jefferson County

This demographic profile describes characteristics of the local and state population based on results from the 2010 Census. The decennial census is an official enumeration, or count, of all residents on April 1st of the census year. The results of the census provide us with information about basic demographic characteristics of the population, including age, race, ethnicity, household composition, housing occupancy, and housing tenure

Predicted Infrared and Raman Spectra for Neutral Ti_8C_12 Isomers

Using a density-functional based algorithm, the full IR and Raman spectra are calculated for the neutral Ti_8C_12 cluster assuming geometries of Th, Td, D2d and C3v symmetry. The Th pentagonal dodecahedron is found to be dynamically unstable. The calculated properties of the relaxed structure having C3v symmetry are found to be in excellent agreement with experimental gas phase infrared results, ionization potential and electron affinity measurements. Consequently, the results presented may be used as a reference for further experimental characterization using vibrational spectroscopy.Comment: 6 pages, 5 figures. Physical Review A, 2002 (in press

The Peculiar Debris Disk of HD 111520 as Resolved by the Gemini Planet Imager

Using the Gemini Planet Imager (GPI), we have resolved the circumstellar debris disk around HD 111520 at a projected range of ~30-100 AU in both total and polarized $H$-band intensity. The disk is seen edge-on at a position angle of ~165$^{\circ}$ along the spine of emission. A slight inclination or asymmetric warping are covariant and alters the interpretation of the observed disk emission. We employ 3 point spread function (PSF) subtraction methods to reduce the stellar glare and instrumental artifacts to confirm that there is a roughly 2:1 brightness asymmetry between the NW and SE extension. This specific feature makes HD 111520 the most extreme examples of asymmetric debris disks observed in scattered light among similar highly inclined systems, such as HD 15115 and HD 106906. We further identify a tentative localized brightness enhancement and scale height enhancement associated with the disk at ~40 AU away from the star on the SE extension. We also find that the fractional polarization rises from 10 to 40% from 0.5" to 0.8" from the star. The combination of large brightness asymmetry and symmetric polarization fraction leads us to believe that an azimuthal dust density variation is causing the observed asymmetry.Comment: 9 pages, 8 Figures, 1 table, Accepted to Ap