Cytotoxic agent containment kit

A cytotoxic agent containment kit is disclosed which has a top enclosure member and bottom enclosure member that are hingedly connected much like a brief case. The bottom enclosure member has a sealable, nonpermeable container for drugs and another for holding waste such as empty drug containers and used hypodermic needles. A removable tray is provided which acts as a work surface for preparing the drugs for administration. The contents of the kit including the tray and containers can be disposed of after use, and the outer case reused. The kit's nonpermeable construction helps insure that persons handling it will not be accidentally exposed to the cytotoxic agents that it contains.Board of Regents, University of Texas Syste

Improving Navy recruiting with data farming

Proceedings of the 2016 Winter Simulation Conference T. M. K. Roeder, P. I. Frazier, R. Szechtman, E. Zhou, T. Huschka, and S. E. Chick, eds.Secretary of the Navy Ray Mabus states that people provide “the Navy and Marine Corps’ greatest edge” (Mabus, 2015). To help recruit and manage this dynamic workforce of more than 300,000 active duty Sailors, the Navy uses mathematical models and simulation to assess the potential impacts and risks of changes to force structure, budgets, policies, and the economy. One important model is the Planned Re-source Optimization (PRO) model. PRO is currently being used to inform recruiting resourcing decisions. The decisions may involve, for example, advertising, enlistment bonuses, number of production recruiters, etc. A limitation of PRO is the lack of an interface to facilitate extensive experimentation. This paper summarizes an effort underway to enhance the analytic utility of the PRO model by embedding it in a data farming environment. This enhanced tool is called the “Planned Resource Optimization Model with Ex-perimental Design” (PROM-WED)

X-Ray Luminous Supernovae: Threats to Terrestrial Biospheres

The spectacular outbursts of energy associated with supernovae (SNe) have long motivated research into their potentially hazardous effects on Earth and analogous environments. Much of this research has focused primarily on the atmospheric damage associated with the prompt arrival of ionizing photons within days or months of the initial outburst, and the high-energy cosmic rays that arrive thousands of years after the explosion. In this study, we turn the focus to persistent X-ray emission, arising in certain SNe that have interactions with a dense circumstellar medium, and observed months and/or years after the initial outburst. The sustained high X-ray luminosity leads to large doses of ionizing radiation out to formidable distances. We provide an assessment of the threat posed by these X-ray luminous SNe by analyzing the collective X-ray observations from Chandra, Swift-XRT, XMM-Newton, NuSTAR, and others. We find that this threat is particularly acute for SNe showing evidence of strong circumstellar interaction, such as Type IIn explosions, which have significantly larger ranges of influence than previously expected, and lethal consequences up to $\sim$ 50 pc away. Furthermore, X-ray bright SNe could pose a substantial and distinct threat to terrestrial biospheres, and tighten the Galactic habitable zone. We urge follow-up X-ray observations of interacting SNe for months and years after the explosion to shed light on the physical nature of the emission and its full time evolution, and to clarify the danger that these events pose for life in our Galaxy and other star-forming regions.Comment: 24 pages, 6 figures. Now includes a more detailed analysis of X-ray effectiveness for ozone destruction; conclusions unchanged. Matches version to appear in Ap

A structure-based nomenclature for Bacillus thuringiensis and other bacteria-derived pesticidal proteins

In 1998 a nomenclature for the growing list of pesticidal proteins from Bacillus thuringiensis (Bt) was derived based solely on protein sequence comparisons. This nomenclature was widely adopted and provided a robust framework for the naming and classification of the proteins. The success of these proteins in integrated pest management schemes prompted an increased effort to find others with improved or more diverse activities. These discovery activities led to the characterization of proteins from a wider range of bacteria and with a variety of different protein folds. Since most of these new proteins were grouped together as Cry proteins it became apparent that the existing nomenclature had limitations in representing the diverse range of proteins that had been identified. This revised nomenclature retains the basic principles of the 1998 version but provides specific mnemonics to represent different structural groups. For the purposes of consistency, the vast majority of the proteins have either retained their name or have a new name that clearly references the previous one. Other pesticidal proteins not previously included in the nomenclature have been incorporated into this version

Assessing the reliability of eBURST using simulated populations with known ancestry

BACKGROUND: The program eBURST uses multilocus sequence typing data to divide bacterial populations into groups of closely related strains (clonal complexes), predicts the founding genotype of each group, and displays the patterns of recent evolutionary descent of all other strains in the group from the founder. The reliability of eBURST was evaluated using populations simulated with different levels of recombination in which the ancestry of all strains was known. RESULTS: For strictly clonal simulations, where all allelic change is due to point mutation, the groups of related strains identified by eBURST were very similar to those expected from the true ancestry and most of the true ancestor-descendant relationships (90–98%) were identified by eBURST. Populations simulated with low or moderate levels of recombination showed similarly high performance but the reliability of eBURST declined with increasing recombination to mutation ratio. Populations simulated under a high recombination to mutation ratio were dominated by a single large straggly eBURST group, which resulted from the incorrect linking of unrelated groups of strains into the same eBURST group. The reliability of the ancestor-descendant links in eBURST diagrams was related to the proportion of strains in the largest eBURST group, which provides a useful guide to when eBURST is likely to be unreliable. CONCLUSION: Examination of eBURST groups within populations of a range of bacterial species showed that most were within the range in which eBURST is reliable, and only a small number (e.g. Burkholderia pseudomallei and Enterococcus faecium) appeared to have such high rates of recombination that eBURST is likely to be unreliable. The study also demonstrates how three simple tests in eBURST v3 can be used to detect unreliable eBURST performance and recognise populations in which there appears to be a high rate of recombination relative to mutation

Evaluation of methods for detecting human reads in microbial sequencing datasets

Sequencing data from host-associated microbes can often be contaminated by the body of the investigator or research subject. Human DNA is typically removed from microbial reads either by subtractive alignment (dropping all reads that map to the human genome) or by using a read classification tool to predict those of human origin, and then discarding them. To inform best practice guidelines, we benchmarked eight alignment-based and two classification-based methods of human read detection using simulated data from 10 clinically prevalent bacteria and three viruses, into which contaminating human reads had been added. While the majority of methods successfully detected >99 % of the human reads, they were distinguishable by variance. The most precise methods, with negligible variance, were Bowtie2 and SNAP, both of which misidentified few, if any, bacterial reads (and no viral reads) as human. While correctly detecting a similar number of human reads, methods based on taxonomic classification, such as Kraken2 and Centrifuge, could misclassify bacterial reads as human, although the extent of this was species-specific. Among the most sensitive methods of human read detection was BWA, although this also made the greatest number of false positive classifications. Across all methods, the set of human reads not identified as such, although often representing 300 bp) bacterial reads, the highest performing approaches were classification-based, using Kraken2 or Centrifuge. For shorter (c. 150 bp) bacterial reads, combining multiple methods of human read detection maximized the recovery of human reads from contaminated short read datasets without being compromised by false positives. A particularly high-performance approach with shorter bacterial reads was a two-stage classification using Bowtie2 followed by SNAP. Using this approach, we re-examined 11 577 publicly archived bacterial read sets for hitherto undetected human contamination. We were able to extract a sufficient number of reads to call known human SNPs, including those with clinical significance, in 6 % of the samples. These results show that phenotypically distinct human sequence is detectable in publicly archived microbial read datasets

Study of Beauty Hadron Decays into Pairs of Charm Hadrons

First observations of the decays Λ[0 over b] → Λ[+ over c]D[− over (s)] are reported using data corresponding to an integrated luminosity of 3  fb[superscript −1] collected at 7 and 8 TeV center-of-mass energies in proton-proton collisions with the LHCb detector. In addition, the most precise measurement of the branching fraction B(B[0 over s] → D[superscript +]D[− over s]) is made and a search is performed for the decays B[0 over (s)] → Λ[+ over c]Λ[− over c]. The results obtained are B(Λ[0 over b] → Λ[+ over c]D[superscript −])/B(Λ[0 over b] → Λ[+ over c]D[− over s]) = 0.042 ± 0.003(stat) ± 0.003(syst), ⎡⎣B(Λ[0 over b] → Λ[+ over c]D[− over s]) over B([¯ over B[superscript 0] → D[superscript +]D[− over s])⎤⎦/⎡⎣B(Λ[0 over b] → Λ[+ over c]π[superscript −]) over B([¯ over B[superscript 0] → D[superscript +]π[superscript −])⎤⎦ = 0.96 ± 0.02(stat) ± 0.06(syst), B(B[0 over s] → D[superscript +]D[− over s])/B([¯ over B][superscript 0] → D[superscript +]D[− over s]) = 0.038 ± 0.004(stat) ± 0.003(syst), B([¯ over B][superscript 0] → Λ[+ over c]Λ[− over c])/B([¯ over B][superscript 0] → D[superscript +]D[− over s]) < 0.0022[95%  C.L.], B(B[0 over s] → Λ[+ over c]Λ[− over c])/B(B[0 over s] → D[superscript +]D[− over s]) < 0.30[95%  C.L.]. Measurement of the mass of the Λ[0 over b] baryon relative to the [¯ over B][superscript 0] meson gives M(Λ[0 over b]) − M([¯ over B][superscript 0]) = 339.72 ± 0.24(stat) ± 0.18(syst)  MeV/c[superscript 2]. This result provides the most precise measurement of the mass of the Λ[0 over b] baryon to date.National Science Foundation (U.S.

Use of whole-genus genome sequence data to develop a multilocus sequence typing tool that accurately identifies Yersinia isolates to the species and subspecies levels

The genus Yersinia is a large and diverse bacterial genus consisting of human-pathogenic species, a fish-pathogenic species, and a large number of environmental species. Recently, the phylogenetic and population structure of the entire genus was elucidated through the genome sequence data of 241 strains encompassing every known species in the genus. Here we report the mining of this enormous data set to create a multilocus sequence typing-based scheme that can identify Yersinia strains to the species level to a level of resolution equal to that for whole-genome sequencing. Our assay is designed to be able to accurately subtype the important human-pathogenic species Yersinia enterocolitica to whole-genome resolution levels. We also report the validation of the scheme on 386 strains from reference laboratory collections across Europe. We propose that the scheme is an important molecular typing system to allow accurate and reproducible identification of Yersinia isolates to the species level, a process often inconsistent in nonspecialist laboratories. Additionally, our assay is the most phylogenetically informative typing scheme available for Y. enterocolitica

Proteomic analysis of the cerebrospinal fluid of patients with restless legs syndrome/Willis-Ekbom disease

BACKGROUND: Restless Legs Syndrome/Willis-Ekbom Disease (RLS/WED) is a sensorimotor disorder that causes patients to experience overwhelming and distressing sensations in the legs compelling the patient to move their legs to provide relief. The purpose of this study was to determine if biomarkers in the cerebrospinal fluid can distinguish RLS/WED patients from neurological controls. METHODS: We obtained CSF samples by lumbar puncture from 5 early-onset RLS/WED patients and 5 controls. We performed 2-dimensional difference in-gel electrophoresis (2D-DIGE). Proteins that were significantly altered were identified by Student’s t-test. Protein spots that were differentially expressed (p ≤ 0.05, Av. Ratio ≥ 2.0) between RLS/WED and control CSF samples were identified using MALDI-TOF-MS. Statistical analyses of the validation immunoblot assays were performed using Student’s t-test. RESULTS: In this discovery study we identified 6 candidate CSF protein markers for early-onset RLS/WED. Four proteins (Cystatin C, Lipocalin-type Prostaglandin D2 Synthase, Vitamin D binding Protein, and β-Hemoglobin) were increased and 2 proteins (Apolipoprotein A1 and α-1-acid Glycoprotein) were decreased in RLS/WED patients. CONCLUSIONS: Our results reveal a protein profile in the RLS/WED CSF that is consistent with clinical findings of disruptive sleep, cardiovascular dysfunction and painful symptoms. Moreover, protein profiles are consistent with neuropathological findings of activation of hypoxia inducible factor (HIF) pathways and alterations in dopaminergic systems. These data indicate the CSF of RLS/WED patients may provide information relevant to biological basis for RLS/WED, treatment strategies and potential new treatment targets

Radioactive Source Localisation via Projective Linear Reconstruction

Radiation mapping, through the detection of ionising gamma-ray emissions, is an important technique used across the nuclear industry to characterise environments over a range of length scales. In complex scenarios, the precise localisation and activity of radiological sources becomes difficult to determine due to the inability to directly image gamma photon emissions. This is a result of the potentially unknown number of sources combined with uncertainties associated with the source-detector separation&mdash;causing an apparent &lsquo;blurring&rsquo; of the as-detected radiation field relative to the true distribution. Accurate delimitation of distinct sources is important for decommissioning, waste processing, and homeland security. Therefore, methods for estimating the precise, &lsquo;true&rsquo; solution from radiation mapping measurements are required. Herein is presented a computational method of enhanced radiological source localisation from scanning survey measurements conducted with a robotic arm. The procedure uses an experimentally derived Detector Response Function (DRF) to perform a randomised-Kaczmarz deconvolution from robotically acquired radiation field measurements. The performance of the process is assessed on radiation maps obtained from a series of emulated waste processing scenarios. The results demonstrate a Projective Linear Reconstruction (PLR) algorithm can successfully locate a series of point sources to within 2 cm of the true locations, corresponding to resolution enhancements of between 5&times; and 10&times;