Reconstruction of 3D Neuronal Structures from Densely Packed Electron Microscopy Data Stacks

The goal of fully decoding how the brain works requires a detailed wiring diagram of the brain network that reveals the complete connectivity matrix. Recent advances in high-throughput 3D electron microscopy (EM) image acquisition techniques have made it possible to obtain high-resolution 3D imaging data that allows researchers to follow axons and dendrites and to identify pre-synaptic and post-synaptic sites, enabling the reconstruction of detailed neural circuits of the nervous system at the level of synapses. However, these massive data sets pose unique challenges to structural reconstruction because the inevitable staining noise, incomplete boundaries, and inhomogeneous staining intensities increase difficulty of 3D reconstruction and visualization. In this dissertation, a new set of algorithms are provided for reconstruction of neuronal morphology from stacks of serial EM images. These algorithms include (1) segmentation algorithms for obtaining the full geometry of neural circuits, (2) interactive segmentation tools for manual correction of erroneous segmentations, and (3) a validation method for obtaining a topologically correct segmentation when a set of segmentation alternatives are available. Experimental results obtained by using EM images containing densely packed cells demonstrate that (1) the proposed segmentation methods can successfully reconstruct full anatomical structures from EM images, (2) the editing tools provide a way for the user to easily and quickly refine incorrect segmentations, (3) and the validation method is effective in combining multiple segmentation results. The algorithms presented in this dissertation are expected to contribute to the reconstruction of the connectome and to open new directions in the development of reconstruction methods

The bid generation problem in combinatorial auctions for transportation service procurement

In this work, a probabilistic bid generation problem with the pricing of a bundle of lanes and carrier’s vehicle routing is considered as it is an importation in transportation service procurement. Depending on the network of the vehicle, there exist multiple lanes for traveling between two locations. To solve the bid generation problem efficiently, a two-phase method approach is presented. At the core of the procedure a feasible vehicle routing problem on a multidigraph is solved by an exhaustive search algorithm to enumerate all routes concerning routing constraints and treat each route as a decision variable in the set partitioning formulation. We examine our model both analytically and empirically using a simulation-based analysis

Head Tracking and Flagellum Tracing for Sperm Motility Analysis

International audienceSperm quality assessment plays an essential role in human fertility and animal breeding. Manual analysis is time-consuming and subject to intra- and inter-observer variability. To automate the analysis process, as well as to offer a means of statistical analysis that may not be achieved by visual inspection, we present a computational framework that tracks the heads and traces the tails for analyzing sperm motility, one of the most important attributes in semen quality evaluation. Our framework consists of 3 modules: head detection, head tracking, and flagellum tracing. The head detection module detects the sperm heads from the image data, and the detected heads are the inputs to the head tracking module for obtaining the head trajectories. Finally, a flagellum tracing algorithm is proposed to obtain the flagellar beat patterns. Our framework aims at providing both the head trajectories and the flagellar beat patterns for quantitatively assessing sperm motility. This distinguishes our work from other existing methods that analyze sperm motility based merely on the head trajectories. We validate our framework using two confocal microscopy image sequences of ram semen samples that were imaged at two different conditions, at which the sperms behave differently. The results show the effectiveness of our framework

Constraining Intra-cluster Gas Models with AMiBA13

Clusters of galaxies have been used extensively to determine cosmological parameters. A major difficulty in making best use of Sunyaev-Zel'dovich (SZ) and X-ray observations of clusters for cosmology is that using X-ray observations it is difficult to measure the temperature distribution and therefore determine the density distribution in individual clusters of galaxies out to the virial radius. Observations with the new generation of SZ instruments are a promising alternative approach. We use clusters of galaxies drawn from high-resolution adaptive mesh refinement (AMR) cosmological simulations to study how well we should be able to constrain the large-scale distribution of the intra-cluster gas (ICG) in individual massive relaxed clusters using AMiBA in its configuration with 13 1.2-m diameter dishes (AMiBA13) along with X-ray observations. We show that non-isothermal beta models provide a good description of the ICG in our simulated relaxed clusters. We use simulated X-ray observations to estimate the quality of constraints on the distribution of gas density, and simulated SZ visibilities (AMiBA13 observations) for constraints on the large-scale temperature distribution of the ICG. We find that AMiBA13 visibilities should constrain the scale radius of the temperature distribution to about 50% accuracy. We conclude that the upgraded AMiBA, AMiBA13, should be a powerful instrument to constrain the large-scale distribution of the ICG.Comment: Accepted for publication in The Astrophysical Journal, 12 pages, 9 figure

Emerged HA and NA Mutants of the Pandemic Influenza H1N1 Viruses with Increasing Epidemiological Significance in Taipei and Kaohsiung, Taiwan, 2009–10

The 2009 influenza pandemic provided an opportunity to observe dynamic changes of the hemagglutinin (HA) and neuraminidase (NA) of pH1N1 strains that spread in two metropolitan areas -Taipei and Kaohsiung. We observed cumulative increases of amino acid substitutions of both HA and NA that were higher in the post–peak than in the pre-peak period of the epidemic. About 14.94% and 3.44% of 174 isolates had one and two amino acids changes, respective, in the four antigenic sites. One unique adaptive mutation of HA2 (E374K) was first detected three weeks before the epidemic peak. This mutation evolved through the epidemic, and finally emerged as the major circulated strain, with significantly higher frequency in the post-peak period than in the pre-peak (64.65% vs 9.28%, p<0.0001). E374K persisted until ten months post-nationwide vaccination without further antigenic changes (e.g. prior to the highest selective pressure). In public health measures, the epidemic peaked at seven weeks after oseltamivir treatment was initiated. The emerging E374K mutants spread before the first peak of school class suspension, extended their survival in high-density population areas before vaccination, dominated in the second wave of class suspension, and were fixed as herd immunity developed. The tempo-spatial spreading of E374K mutants was more concentrated during the post–peak (p = 0.000004) in seven districts with higher spatial clusters (p<0.001). This is the first study examining viral changes during the naïve phase of a pandemic of influenza through integrated virological/serological/clinical surveillance, tempo-spatial analysis, and intervention policies. The vaccination increased the percentage of E374K mutants (22.86% vs 72.34%, p<0.001) and significantly elevated the frequency of mutations in Sa antigenic site (2.36% vs 23.40%, p<0.001). Future pre-vaccination public health efforts should monitor amino acids of HA and NA of pandemic influenza viruses isolated at exponential and peak phases in areas with high cluster cases

Clinical Manifestations, Laboratory Findings, and Treatment Outcomes of SARS Patients

Clinical and laboratory data on severe acute respiratory syndrome (SARS), particularly on the temporal progression of abnormal laboratory findings, are limited. We conducted a prospective study on the clinical, radiologic, and hematologic findings of SARS patients with pneumonia, who were admitted to National Taiwan University Hospital from March 8 to June 15, 2003. Fever was the most frequent initial symptom, followed by cough, myalgia, dyspnea, and diarrhea. Twenty-four patients had various underlying diseases. Most patients had elevated C-reactive protein (CRP) levels and lymphopenia. Other common abnormal laboratory findings included leukopenia, thrombocytopenia, and elevated levels of aminotransferase, lactate dehydrogenase, and creatine kinase. These clinical and laboratory findings were exacerbated in most patients during the second week of disease. The overall case-fatality rate was 19.7%. By multivariate analysis, underlying disease and initial CRP level were predictive of death