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A national need is to prepare for and respond to accidental or intentional disasters categorized as chemical, biological, radiological, nuclear, or explosive (CBRNE). These incidents require specific subject-matter expertise, yet have commonalities. We identify 7 core elements comprising CBRNE science that require integration for effective preparedness planning and public health and medical response and recovery. These core elements are (1) basic and clinical sciences, (2) modeling and systems management, (3) planning, (4) response and incident management, (5) recovery and resilience, (6) lessons learned, and (7) continuous improvement. A key feature is the ability of relevant subject matter experts to integrate information into response operations. We propose the CBRNE medical operations science support expert as a professional who (1) understands that CBRNE incidents require an integrated systems approach, (2) understands the key functions and contributions of CBRNE science practitioners, (3) helps direct strategic and tactical CBRNE planning and responses through first-hand experience, and (4) provides advice to senior decision-makers managing response activities. Recognition of both CBRNE science as a distinct competency and the establishment of the CBRNE medical operations science support expert informs the public of the enormous progress made, broadcasts opportunities for new talent, and enhances the sophistication and analytic expertise of senior managers planning for and responding to CBRNE incidents.
We describe the investigation of two temporally coincident illness clusters involving salmonella and Staphylococcus aureus in two states. Cases were defined as gastrointestinal illness following two meal events. Investigators interviewed ill persons. Stool, food and environmental samples underwent pathogen testing. Alabama: Eighty cases were identified. Median time from meal to illness was 5·8 h. Salmonella Heidelberg was identified from 27 of 28 stool specimens tested, and coagulase-positive S. aureus was isolated from three of 16 ill persons. Environmental investigation indicated that food handling deficiencies occurred. Colorado: Seven cases were identified. Median time from meal to illness was 4·5 h. Five persons were hospitalised, four of whom were admitted to the intensive care unit. Salmonella Heidelberg was identified in six of seven stool specimens and coagulase-positive S. aureus in three of six tested. No single food item was implicated in either outbreak. These two outbreaks were linked to infection with Salmonella Heidelberg, but additional factors, such as dual aetiology that included S. aureus or the dose of salmonella ingested may have contributed to the short incubation periods and high illness severity. The outbreaks underscore the importance of measures to prevent foodborne illness through appropriate washing, handling, preparation and storage of food.
No standard exists for provision of care following catastrophic natural disasters. Host nations, funders, and overseeing agencies need a method to identify the most effective interventions when allocating finite resources. Measures of effectiveness are real-time indicators that can be used to link early action with downstream impact.
Group consensus methods can be used to develop measures of effectiveness detailing the major functions of post natural disaster acute phase medical response.
A review of peer-reviewed disaster response publications (2001-2011) identified potential measures describing domestic and international medical response. A steering committee comprised of six persons with publications pertaining to disaster response, and those serving in leadership capacity for a disaster response organization, was assembled. The committee determined which measures identified in the literature review had the best potential to gauge effectiveness during post-disaster acute-phase medical response. Using a modified Delphi technique, a second, larger group (Expert Panel) evaluated these measures and novel measures suggested (or “free-texted”) by participants for importance, validity, usability, and feasibility. After three iterations, the highest rated measures were selected.
The literature review identified 397 measures. The steering committee approved 116 (29.2%) of these measures for advancement to the Delphi process. In Round 1, 25 (22%) measures attained >75% approval and, accompanied by 77 free-text measures, graduated to Round 2. There, 56 (50%) measures achieved >75% approval. In Round 3, 37 (66%) measures achieved median scores of 4 or higher (on a 5-point ordinal scale). These selected measures describe major aspects of disaster response, including: Evaluation, Treatment, Disposition, Public Health, and Team Logistics. Of participants from the Expert Panel, 24/39 (63%) completed all rounds. Thirty-three percent of these experts represented international agencies; 42% represented US government agencies.
Experts identified response measures that reflect major functions of an acute medical response. Measures of effectiveness facilitate real-time assessment of performance and can signal where practices should be improved to better aid community preparedness and response. These measures can promote unification of medical assistance, allow for comparison of responses, and bring accountability to post-disaster acute-phase medical care. This is the first consensus-developed reporting tool constructed using objective measures to describe the functions of acute phase disaster medical response. It should be evaluated by agencies providing medical response during the next major natural disaster.
DaftaryRK, CruzAT, ReavesEJ, BurkleFMJr, ChristianMD, FagbuyiDB, GarrettAL, KapurGB, SirbaughPE. Making Disaster Care Count: Consensus Formulation of Measures of Effectiveness for Natural Disaster Acute Phase Medical Response. Prehosp Disaster Med. 2014;29(5):1-7.
We studied the effect of a cross-conjugated bridging group (χC) on charge-transfer in a push-pull chromophore system. The hyperpolarizability of such molecules was found to be comparable to that of a fully π-conjugated molecule (πC) with the same donor and acceptor. The cross-conjugated moiety was then applied as a pendant to a fully π-conjugated chromophore containing a tricyanopyrroline acceptor (TCP). The addition of a χC moiety did not alter the intrinsic hyperpolarizability and provides an avenue for extending and aiding πC systems. The molecules were examined by X-ray diffraction (XRD), hyper-Raleigh scattering (HRS) and UV-visible (UV-vis) spectroscopy. Experimental results were compared with the predictions of density functional theory (DFT). Cross-conjugated molecules have comparable β values, relative to πC molecules, due to reduced spatial overlap between the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO). Thus, the χC architecture could facilitate independent modification of donor and acceptor strengths while minimizing unfavorable effects on electronic transitions and dipole moments.
Civil engineering is a branch of science that covers a broad range of areas where experimental procedures often plays an important role. The research in this field is usually supported by experimental structures able to test physical and mathematical models and to provide measurement results with acceptable accuracy. To assure measurement quality, a metrology probabilistic approach can provide valuable mathematical and computational tools especially suited to the study, evaluation and improvement of measurement processes in its different components (modeling, instrumentation performance, data processing, data validation and traceability), emphasizing measurement uncertainty evaluation as a tool to the analysis of results and to promote the quality and capacity associated with decision-making. This paper presents some of the research held by the metrology division of the Portuguese civil engineering research institutes, focused on the contribution of measurement uncertainty studies to a variety of frameworks, such as testing for metrological characterization and physical and mathematical modeling. Experimental data will be used to illustrate practical cases.
Oxidation of serum proteins can lead to carbonyl formation that alters their function and is often associated with stress-related diseases. As it is recommended that all pigs reared in modern production facilities be given supplemental iron at birth to prevent anemia, and metals can catalyze the carbonylation of proteins, the primary objective of this study was to determine whether standard iron dextran treatment was associated with enhanced serum protein oxidation in newborn piglets. Piglets were treated with 100 mg of iron dextran intramuscularly either on the day of birth, or on the third day after birth. Blood samples were collected from piglets 48 or 96 h after treatment and serum was harvested. For quantification, serum protein carbonyls were converted to hydrazones with dinitrophenyl hydrazine and analyzed spectrophotometrically. To identify and determine relative distribution of carbonylated proteins, serum protein carbonyls were derivatized with biotin hydrazide, separated by two-dimensional polyacrylamide gel electrophoresis, stained with avidin-fluorescein and identified by mass spectrometry. The standard iron dextran treatment was associated with no increase in total oxidized proteins if given either on the first or third day of life. In addition, with a few noted exceptions, the overall distribution and identification of oxidized proteins were similar between control and iron dextran-treated pigs. These results indicate that while iron dextran treatment is associated with a marked increase in circulating iron, it does not appear to specifically induce the oxidation of serum proteins.
Apyrases (ATP-diphosphohydrolase) comprise a ubiquitous class of glycosylated nucleotidases that hydrolyse extracellular ATP and ADP to orthophosphate and AMP. One class of newly-described, Ca2+-dependent, salivary apyrases known to counteract blood-clotting, has been identified in haematophagous arthropods. Herein, we have identified a gene (Oos-apy-1) encoding a protein that structurally conforms to the Ca2+-activated apyrase from the bed bug, Cimex lectularius, by immunologically screening an Ostertagia L4 cDNA expression library. The expressed protein (rOos-APY-1) was biochemically functional in the presence of Ca2+ only, with greatest activity on ATP, ADP, UTP and UDP. Host antibodies to the fusion protein appeared as early as 14 days post-infection (p.i.) and increased through 30 days p.i. Immunohistochemical and Western blot analyses demonstrated that the native Oos-APY-1 protein is present in the glandular bulb of the oesophagus and is confined to the L4. A putative signal sequence at the N-terminus and near 100% identity with a Teladorsagia circumcincta L4 secreted protein is consistent with the native protein being secreted at the cellular level. Predicated upon substrate specificity, the native protein may be used by the parasite to control the levels of host extracellular nucleotides released by locally-damaged tissues in an effort to modulate immune intervention and inflammation.
Stroke is a leading cause of morbidity and mortality in the US, with secondary damage following the initial insult contributing significantly to overall poor outcome. Prior investigations have shown that the metabolism of certain polyamines such as spermine, spermidine, and putrescine are elevated in ischemic parenchyma, resulting in an increase in their metabolite concentration. Polyamine metabolites tend to be cytotoxic, leading to neuronal injury in the penumbra following stroke and expansion of the area of infarcted tissue. Although the precise mechanism is unclear, the presence of reactive aldehydes produced through polyamine metabolism, such as 3-aminopropanal and acrolein, have been shown to correlate with the incidence of cerebral vasospasm, disruption of oxidative metabolism and mitochondrial functioning, and disturbance of cellular calcium ion channels. Regulation of the polyamine metabolic pathway, therefore, may have the potential to limit injury following cerebral ischemia. To this end, we review this pathway in detail with an emphasis on clinical applicability.
Division X provides a common theme for astronomers using radio techniques to study a vast range of phenomena in the Universe, from exploring the Earth's ionosphere or making radar measurements in the Solar System, via mapping the distribution of gas and molecules in our own Galaxy and in other galaxies, to study the vast explosive processes in radio galaxies and QSOs and the faint afterglow of the Big Bang itself.
MATLAB is exceptionally strong in linear algebra, numerical methods, and graphical interpretation of data. It is easily programmed and relatively easy to learn to use. Hence, it has proven invaluable to engineers and scientists who rely on the scientific techniques and methods at which MATLAB excels. Very often the individuals and groups that so employ MATLAB are primarily interested in the numbers and graphs that emerge from MATLAB commands, processes and programs. Therefore, it is enough for them to work in a MATLAB Command Window, from which they can easily print or export their desired output.
However, other practitioners of mathematical software find themselves with two additional requirements. First, they need a mathematical software package embedded in an interactive environment, in which it is easy to make changes and regenerate results. Second, they need a higher-level presentation mode, which integrates computation and graphics with text, uses different formats for input and output, and communicates effortlessly with other software applications. These additional requirements can be accomplished using either cells and the publish command, or else the M-book interface, both of which were briefly described in Chapter 3. The present chapter goes into more detail and discusses some of the fine points of these methods.
Fine Points of Publishing
As we mentioned Chapter 3, the simplest way to produce a finished presentation with MATLAB is to prepare your work in a script M-file and then publish the result.
This is a short, focused introduction to MATLAB, a comprehensive software system for mathematical and technical computing. It contains concise explanations of essential MATLAB commands, as well as easily understood instructions for using MATLAB's programming features, graphical capabilities, simulation models, and rich desktop interface. Written for MATLAB 7, it can also be used with earlier (and later) versions of MATLAB. This book teaches how to graph functions, solve equations, manipulate images, and much more. It contains explicit instructions for using MATLAB's companion software, Simulink, which allows graphical models to be built for dynamical systems. MATLAB's new "publish" feature is discussed, which allows mathematical computations to be combined with text and graphics, to produce polished, integrated, interactive documents. For the beginner it explains everything needed to start using MATLAB, while experienced users making the switch to MATLAB 7 from an earlier version will also find much useful information here.
MATLAB is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numerical computation. Using MATLAB, you can solve technical computing problems faster than with traditional programming languages, such as C, C++, and Fortran. – The MathWorks, Inc.
That statement encapsulates the view of The MathWorks, Inc., the developer of MATLAB®. MATLAB 7 is an ambitious program. It contains hundreds of commands to do mathematics. You can use it to graph functions, solve equations, perform statistical tests, and much more. It is a high-level programming language that can communicate with its cousins, e.g., Fortran and C. You can produce sound and animate graphics. You can do simulations and modeling (especially if you have access not just to basic MATLAB but also to its accessory Simulink®). You can prepare materials for export to the World Wide Web. In addition, you can use MATLAB to combine mathematical computations with text and graphics in order to produce a polished, integrated, interactive document.
A program this sophisticated contains many features and options. There are literally hundreds of useful commands at your disposal. The MATLAB help documentation contains thousands of entries. The standard references, whether the MathWorks User's Guide for the product, or any of our competitors, contain a myriad of tables describing an endless stream of commands, options, and features that the user might be expected to learn or access.
In this chapter we describe an effective procedure for working with MATLAB, and for preparing and presenting the results of a MATLAB session. In particular we discuss some features of the MATLAB interface and the use of M-files. We introduce a new command in MATLAB 7, publish, which produces formatted output. We also give some simple hints for debugging your M-files.
The MATLAB Interface
Starting with version 6, MATLAB has an interface called the MATLAB Desktop. Embedded inside it is the Command Window that we described in Chapter 2.
By default, the MATLAB Desktop (Figure 1.1 in Chapter 1) contains four windows inside it, the Command Window on the right, the Current Directory Browser and the Workspace Browser in the upper left, and the Command History Window in the lower left. Notice that there are tabs for alternating between the Current Directory and Workspace Browsers. You can change which windows are currently visible with the Desktop menu (in MATLAB 6, the View menu) at the top of the Desktop, and you can adjust the sizes of the windows by dragging their edges with the mouse. The Command Window is where you type the commands and instructions that cause MATLAB to evaluate, compute, draw, and perform all the other wonderful magic that we describe in this book. We will discuss the other windows in separate sections below.
With MATLAB you can create your own Graphical User Interface, or GUI, which consists of a Figure window containing menus, buttons, text, graphics, etc., that a user can manipulate interactively with the mouse and keyboard. There are two main steps in creating a GUI: one is designing its layout, and the other is writing callback functions that perform the desired operations when the user selects different features.
GUI Layout and GUIDE
Specifying the location and properties of various objects in a GUI can be done with commands such as uicontrol, uimenu, and uicontextmenu in an M-file. MATLAB also provides an interactive tool (a GUI itself!) called GUIDE (this stands for Graphical User Interface Development Environment) that greatly simplifies the task of building a GUI. We will describe here how to get started writing GUIs with the MATLAB 7 version of GUIDE, which has some significant enhancements over earlier versions. The version of GUIDE in MATLAB 6 is roughly similar, but some of the menu items and options are different or missing.
✓ One possible drawback of GUIDE is that it equips your GUI with commands that are new in MATLAB 7 and it saves the layout of the GUI in a binary.fig file. If your goal is to create a robust GUI that many different users can use with different versions of MATLAB, you may be better off writing the GUI from scratch as an M-file.