Induction of chromosome damage by ultraviolet light and caffeine: Correlation of cytogenetic evaluation and flow karyotype

Asynchrononously growing cells of a M3-1 Chinese hamster line were ultraviolet (UV) irradiated ( = 254 nm) with UV fluences up to 7.5 J/m2. After irradiation, cells were incubated with or without 2 mM caffeine for 20 hr, then mitotic cells were selected by mechanical shaking. Their chromosomes were isolated, stained with Hoechst 33258 and chromomycin A3, and measured flow cytometrically. While the fluorescence distributions of chromosomes (flow karyotypes) from cells treated with UV alone or with caffeine alone were very similar to those of untreated controls, the flow karyo-types of UV + caffeine-treated cells showed a debris continuum that increased with increasing UV fluence suggesting an increased number of chromosome fragments. Visual evaluation of metaphase plates revealed that the percentage of cells with chromosome damage also increased steadily with increasing UV fluence. A high degree of correlation was observed between the relative magnitude of the debris level from flow karyotypes and the percentage of cells with chromosome damage and with generalized chromosome shattering, respectively, as determined from metaphase spreads

Effect of Different Types of Physical Activity on Activities of Daily Living in Older Adults : Systematic Review and Meta-Analysis

Peer reviewedPostprin

Stratosphere-troposphere transport in a numerical simulation of midlatitude convection

The transport of stratospheric air deep into the troposphere via convection is investigated numerically using the UK Met Office Unified Model. A convective system that formed on 27 June 2004 near southeast England, in the vicinity an upper level potential vorticity anomaly and a lowered tropopause, provides the basis for analysis. Transport is diagnosed using a stratospheric tracer that can either be passed through or withheld from the model’s convective parameterization scheme. Three simulations are performed at increasingly finer resolutions, with horizontal grid lengths of 12, 4, and 1 km. In the 12 and 4 km simulations, tracer is transported deeply into the troposphere by the parameterized convection. In the 1 km simulation, for which the convective parameterization is disengaged, deep transport is still accomplished but with a much smaller magnitude. However, the 1 km simulation resolves stirring along the tropopause that does not exist in the coarser simulations. In all three simulations, the concentration of the deeply transported tracer is small, three orders of magnitude less than that of the shallow transport near the tropopause, most likely because of the efficient dilution of parcels in the lower troposphere

Stability of adversarial Markov chains, with an application to adaptive MCMC algorithms

We consider whether ergodic Markov chains with bounded step size remain bounded in probability when their transitions are modified by an adversary on a bounded subset. We provide counterexamples to show that the answer is no in general, and prove theorems to show that the answer is yes under various additional assumptions. We then use our results to prove convergence of various adaptive Markov chain Monte Carlo algorithms.Comment: Published at http://dx.doi.org/10.1214/14-AAP1083 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Models for UT Inspection of Bolthole Cracks in Layered Structures

Due to the geometrical complexities of bolted, layered airframe structures, the application of Model Assisted Probability of Detection, or MAPOD, is an important tool for helping to assess the ultrasonic inspectability of those components. Of particular importance is the need to inspect for cracks on or near boltholes in those structures. This presentation describes the development and testing of analytical computer models of and their application to bolthole crack inspection. The modeling approach includes approximate, paraxial, bulk-wave models as well as more rigorous, analytical models that include both bulk and surface/plate modes. The simpler models have the flexibility and computational efficiency to handle complex geometries and structures. The more exact, rigorous models apply to simpler, canonical geometries for use in benchmarking and assessing the accuracy of the paraxial models. Previous model results for single layers will be reviewed and application of the models to multiple layers will be highlighted. Extensions of the models to more complex geometries and materials, computational challenges to future model development, and applications of the models to MAPOD, and will also be addressed

Contextual Network Navigation to provide Situational Awareness for Network Administrators

“© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.One of the goals of network administrators is to identify and block sources of attacks from a network steam. Various tools have been developed to help the administrator identify the IP or subnet to be blocked, however these tend to be non-visual. Having a good perception of the wider network can aid the administrator identify their origin, but while network maps of the Internet can be useful for such endeavors, they are difficult to construct, comprehend and even utilize in an attack, and are often referred to as being “hairballs”. We present a visualization technique that displays pathways back to the attacker; we include all potential routing paths with a best-efforts identification of the commercial relationships involved. These two techniques can potentially highlight common pathways and/or networks to allow faster, more complete resolution to the incident, as well as fragile or incomplete routing pathways to/from a network. They can help administrators re-profile their choice of IP transit suppliers to better serve a target audience

Advanced microsamples: Current applications and considerations for mass spectrometry-based metabolic phenotyping pipelines

Microsamples are collections usually less than 50 µL, although all devices that we have captured as part of this review do not fit within this definition (as some can perform collections of up to 600 µL); however, they are considered microsamples that can be self-administered. These microsamples have been introduced in pre-clinical, clinical, and research settings to overcome obstacles in sampling via traditional venepuncture. However, venepuncture remains the sampling gold standard for the metabolic phenotyping of blood. This presents several challenges in metabolic phenotyping workflows: accessibility for individuals in rural and remote areas (due to the need for trained personnel), the unamenable nature to frequent sampling protocols in longitudinal research (for its invasive nature), and sample collection difficulty in the young and elderly. Furthermore, venous sample stability may be compromised when the temperate conditions necessary for cold-chain transport are beyond control. Alternatively, research utilising microsamples extends phenotyping possibilities to inborn errors of metabolism, therapeutic drug monitoring, nutrition, as well as sport and anti-doping. Although the application of microsamples in metabolic phenotyping exists, it is still in its infancy, with whole blood being overwhelmingly the primary biofluid collected through the collection method of dried blood spots. Research into the metabolic phenotyping of microsamples is limited; however, with advances in commercially available microsampling devices, common barriers such as volumetric inaccuracies and the ‘haematocrit effect’ in dried blood spot microsampling can be overcome. In this review, we provide an overview of the common uses and workflows for microsampling in metabolic phenotyping research. We discuss the advancements in technologies, highlighting key considerations and remaining knowledge gaps for the employment of microsamples in metabolic phenotyping research. This review supports the translation of research from the ‘bench to the community’

Naming treatment and crosslinguistic generalization

Current research on bilingual aphasia has only begun to inform us about the optimal rehabilitation for bilingual aphasic patients and the literature is still sparse in terms of interpreting impairment and recovery in these individuals. Two recent reviews (Faroqi-Shah, Frymark, Mullen, & Wang, 2010; Lorenzen & Murray, 2008) highlight the beneficial effects of rehabilitation in bilingual aphasic patients, however, both reviews underscore the need for theoretically motivated and well controlled rehabilitation studies. There are still several unanswered questions about outcomes in bilingual aphasia rehabilitation, including (a) is it sufficient to rehabilitate only one language, (b) what are the nature of gains in the trained language, and (c) does rehabilitation in one language have beneficial effects in the untreated language? The present experiment attempts to address these questions with a relatively large set of Spanish-English bilinguals with aphasia, all of whom receive therapy in one language at a time. The extent of improvements in the trained language items, semantically related untrained items in the trained language, and between-language transfer to untrained items is examined. In addition to picture naming, changes in the evolution of naming errors and category fluency are also examined in this study

Enabling Scalable Neurocartography: Images to Graphs for Discovery

In recent years, advances in technology have enabled researchers to ask new questions predicated on the collection and analysis of big datasets that were previously too large to study. More specifically, many fundamental questions in neuroscience require studying brain tissue at a large scale to discover emergent properties of neural computation, consciousness, and etiologies of brain disorders. A major challenge is to construct larger, more detailed maps (e.g., structural wiring diagrams) of the brain, known as connectomes. Although raw data exist, obstacles remain in both algorithm development and scalable image analysis to enable access to the knowledge within these data volumes. This dissertation develops, combines and tests state-of-the-art algorithms to estimate graphs and glean other knowledge across six orders of magnitude, from millimeter-scale magnetic resonance imaging to nanometer-scale electron microscopy. This work enables scientific discovery across the community and contributes to the tools and services offered by NeuroData and the Open Connectome Project. Contributions include creating, optimizing and evaluating the first known fully-automated brain graphs in electron microscopy data and magnetic resonance imaging data; pioneering approaches to generate knowledge from X-Ray tomography imaging; and identifying and solving a variety of image analysis challenges associated with building graphs suitable for discovery. These methods were applied across diverse datasets to answer questions at scales not previously explored