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Molecular dissection of the roles of the SOD genes in mammalian response to low dose irradiation
It has been long recognized that a significant fraction of the radiation-induced genetic damage to cells are caused by secondary oxidative species. Internal cellular defense systems against oxidative stress play significant roles in countering genetic damage induced by ionizing radiation. The role of the detoxifying enzymes may be even more prominent in the case of low-dose, low-LET irradiation, as the majority of genetic damage may be caused by secondary oxidative species. In this study we have attempted to decipher the roles of the superoxide dismutase (SOD) genes, which are responsible for detoxifying the superoxide anions. We used adenovirus vectors to deliver RNA interference (RNAi or siRNA) technology to down-regulate the expression levels of the SOD genes. We have also over-expressed the SOD genes by use of recombinant adenovirus vectors. Cells infected with the vectors were then subjected to low dose γ-irradiation. Total RNA were extracted from the exposed cells and the expression of 9000 genes were profiled by use of cDNA microarrays. The result showed that low dose radiation had clear effects on gene expression in HCT116 cells. Both over-expression and down-regulation of the SOD1 gene can change the expression profiles of sub-groups of genes. Close to 200 of the 9000 genes examined showed over two-fold difference in expression under various conditions. Genes with changed expression pattern belong to many categories that include: early growth response, DNA-repair, ion transport, apoptosis, and cytokine response
Thermal and Athermal Swarms of Self-Propelled Particles
Swarms of self-propelled particles exhibit complex behavior that can arise
from simple models, with large changes in swarm behavior resulting from small
changes in model parameters. We investigate the steady-state swarms formed by
self-propelled Morse particles in three dimensions using molecular dynamics
simulations optimized for GPUs. We find a variety of swarms of different
overall shape assemble spontaneously and that for certain Morse potential
parameters coexisting structures are observed. We report a rich "phase diagram"
of athermal swarm structures observed across a broad range of interaction
parameters. Unlike the structures formed in equilibrium self-assembly, we find
that the probability of forming a self-propelled swarm can be biased by the
choice of initial conditions. We investigate how thermal noise influences swarm
formation and demonstrate ways it can be exploited to reconfigure one swarm
into another. Our findings validate and extend previous observations of
self-propelled Morse swarms and highlight open questions for predictive
theories of nonequilibrium self-assembly.Comment: 21 pages, 7 figure
A model-based circular binary segmentation algorithm for the analysis of array CGH data
<p>Abstract</p> <p>Background</p> <p>Circular Binary Segmentation (CBS) is a permutation-based algorithm for array Comparative Genomic Hybridization (aCGH) data analysis. CBS accurately segments data by detecting change-points using a maximal-<it>t </it>test; but extensive computational burden is involved for evaluating the significance of change-points using permutations. A recent implementation utilizing a hybrid method and early stopping rules (hybrid CBS) to improve the performance in speed was subsequently proposed. However, a time analysis revealed that a major portion of computation time of the hybrid CBS was still spent on permutation. In addition, what the hybrid method provides is an approximation of the significance upper bound or lower bound, not an approximation of the significance of change-points itself.</p> <p>Results</p> <p>We developed a novel model-based algorithm, extreme-value based CBS (eCBS), which limits permutations and provides robust results without loss of accuracy. Thousands of aCGH data under null hypothesis were simulated in advance based on a variety of non-normal assumptions, and the corresponding maximal-<it>t </it>distribution was modeled by the Generalized Extreme Value (GEV) distribution. The modeling results, which associate characteristics of aCGH data to the GEV parameters, constitute lookup tables (eXtreme model). Using the eXtreme model, the significance of change-points could be evaluated in a constant time complexity through a table lookup process.</p> <p>Conclusions</p> <p>A novel algorithm, eCBS, was developed in this study. The current implementation of eCBS consistently outperforms the hybrid CBS 4× to 20× in computation time without loss of accuracy. Source codes, supplementary materials, supplementary figures, and supplementary tables can be found at <url>http://ntumaps.cgm.ntu.edu.tw/eCBSsupplementary</url>.</p
Gene Regulation, Modulation, and Their Applications in Gene Expression Data Analysis
Common microarray and next-generation sequencing data analysis concentrate on tumor subtype classification, marker detection, and transcriptional regulation discovery during biological processes by exploring the correlated gene expression patterns and their shared functions. Genetic regulatory network (GRN) based approaches have been employed in many large studies in order to scrutinize for dysregulation and potential treatment controls. In addition to gene regulation and network construction, the concept of the network modulator that has significant systemic impact has been proposed, and detection algorithms have been developed in past years. Here we provide a unified mathematic description of these methods, followed with a brief survey of these modulator identification algorithms. As an early attempt to extend the concept to new RNA regulation mechanism, competitive endogenous RNA (ceRNA), into a modulator framework, we provide two applications to illustrate the network construction, modulation effect, and the preliminary finding from these networks. Those methods we surveyed and developed are used to dissect the regulated network under different modulators. Not limit to these, the concept of "modulation" can adapt to various biological mechanisms to discover the novel gene regulation mechanisms
Radionuclide Analysis on Bamboos following the Fukushima Nuclear Accident
In response to contamination from the recent Fukushima nuclear accident, we conducted radionuclide analysis on bamboos sampled from six sites within a 25 to 980 km radius of the Fukushima Daiichi nuclear power plant. Maximum activity concentrations of radiocesium 134Cs and 137Cs in samples from Fukushima city, 65 km away from the Fukushima Daiichi plant, were in excess of 71 and 79 kBq/kg, dry weight (DW), respectively. In Kashiwa city, 195 km away from the Fukushima Daiichi, the sample concentrations were in excess of 3.4 and 4.3 kBq/kg DW, respectively. In Toyohashi city, 440 km away from the Fukushima Daiichi, the concentrations were below the measurable limits of up to 4.5 Bq/kg DW. In the radiocesium contaminated samples, the radiocesium activity was higher in mature and fallen leaves than in young leaves, branches and culms
The Expression and Localization of N-Myc Downstream-Regulated Gene 1 in Human Trophoblasts
The protein N-Myc downstream-regulated gene 1 (NDRG1) is implicated in the regulation of cell proliferation, differentiation, and cellular stress response. NDRG1 is expressed in primary human trophoblasts, where it promotes cell viability and resistance to hypoxic injury. The mechanism of action of NDRG1 remains unknown. To gain further insight into the intracellular action of NDRG1, we analyzed the expression pattern and cellular localization of endogenous NDRG1 and transfected Myc-tagged NDRG1 in human trophoblasts exposed to diverse injuries. In standard conditions, NDRG1 was diffusely expressed in the cytoplasm at a low level. Hypoxia or the hypoxia mimetic cobalt chloride, but not serum deprivation, ultraviolet (UV) light, or ionizing radiation, induced the expression of NDRG1 in human trophoblasts and the redistribution of NDRG1 into the nucleus and cytoplasmic membranes associated with the endoplasmic reticulum (ER) and microtubules. Mutation of the phosphopantetheine attachment site (PPAS) within NDRG1 abrogated this pattern of redistribution. Our results shed new light on the impact of cell injury on NDRG1 expression patterns, and suggest that the PPAS domain plays a key role in NDRG1's subcellular distribution. © 2013 Shi et al
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