A significant amount of uncertainty exists regarding potential human exposure to laboratory biomaterials and organisms in Biosafety Level 2 (BSL-2) research laboratories. Computational fluid dynamics (CFD) modeling is proposed as a way to better understand potential impacts of different combinations of biomaterials, laboratory manipulations, and exposure routes on risks to laboratory workers. Here, in this study, we use CFD models to simulate airborne concentrations of contaminants in an actual BSL-2 laboratory under different configurations. Results show that ventilation configuration, sampling location, and contaminant source location can significantly impact airborne concentrations and exposures. Depending on the source location and airflow patterns, the transient and time-integrated concentrations varied by several orders of magnitude. Contaminant plumes from sources located near a return vent (or exhaust like a fume hood or ventilated biosafety cabinet) are likely to be more contained than sources that are further from the exhaust. Having a direct flow between the source and the exhaust (through-flow condition) may reduce potential exposures to individuals outside the air flow path. Designing a BSL-2 room with ventilation and airflow patterns that maximize through-flow conditions to the return/exhaust vents and minimize dispersion and mixing throughout the room is, therefore, recommended. CFD simulations can also be used to assist in characterizing the impacts of supply and return vent locations, room layout, and source locations on spatial and temporal contaminant concentrations. In addition, proper placement of particle sensors can also be informed by CFD simulations to provide additional characterization and monitoring of potential exposures in BSL-2 facilities.
Sandia National Laboratories' (SNL's) Parametric Choice Model (ParaChoice) supports the U.S. Department of Energy Vehicle Technologies Office (VTO) mission. Using early-stage research as input, ParaChoice supports the informed development of technology that will improve affordability of transportation, while encouraging innovation and reducing dependence on petroleum. Analysis with ParaChoice enables exploration of key factors that influence consumer choice, as well as projecting the effects of technology, fuel, and infrastructure development for the vehicle fleet mix. Because of the distinct differences between requirements, needs, and use patterns for light duty vehicles (LDVs) relative to heavy duty vehicles (HDVs), this project separately models the dynamics of each of these segments to accurately characterize the factors that influence technology adoption.
ParaChoice supports the VTO mission using early-stage research to help in the development of technology that will improve affordability of transportation, while encouraging innovation and reducing dependence on petroleum. Analysis with the ParaChoice model enables exploration of key factors that influence consumer choice, and technology, fuel, and infrastructure development for the vehicle mix. Because of the distinct differences between requirements, needs, and use patterns for light duty vehicles (LDVs) relative to heavy duty vehicles (HDVs), this project models the dynamics of each of these segments to characterize the factors that influence technology adoption.
The purpose of this document is to provide a basic overview and understanding of risk assessment methodologies and tools from the literature and to assess the suitability of these methodologies and tools for cyber risk assessment. Sandia National Laboratories (SNL) performed this review in support of risk modeling activities performed for the Stakeholder Engagement and Cyber Infrastructure Resilience (SECIR) division of the Department of Homeland Security (DHS) Office of Cybersecurity and Communications (CS&C). The set of methodologies and tools covered in this document is not intended to be exhaustive; instead, it focuses on those that are commonly used in the risk assessment community. The classification of methodologies and tools was performed by a group of analysts with experience in risk analysis and cybersecurity, and the resulting analysis of alternatives has been tailored to address the needs of a cyber risk assessment.
Biological imaging and assay technologies rely on fluorescent organic dyes as reporters for a number of interesting targets and processes. However, limitations of organic dyes such as small Stokes shifts, spectral overlap of emission signals with native biological fluorescence background, and photobleaching have all inhibited the development of highly sensitive assays. To overcome the limitations of organic dyes for bioassays, we propose to develop lanthanide-based luminescent dyes and demonstrate them for molecular reporting applications. This relatively new family of dyes was selected for their attractive spectral and chemical properties. Luminescence is imparted by the lanthanide atom and allows for relatively simple chemical structures that can be tailored to the application. The photophysical properties offer unique features such as narrow and non-overlapping emission bands, long luminescent lifetimes, and long wavelength emission, which enable significant sensitivity improvements over organic dyes through spectral and temporal gating of the luminescent signal.Growth in this field has been hindered due to the necessary advanced synthetic chemistry techniques and access to experts in biological assay development. Our strategy for the development of a new lanthanide-based fluorescent reporter system is based on chelation of the lanthanide metal center using absorbing chromophores. Our first strategy involves "Click" chemistry to develop 3-fold symmetric chelators and the other involves use of a new class of tetrapyrrole ligands called corroles. This two-pronged approach is geared towards the optimization of chromophores to enhance light output.
We have developed a novel modular automated processing system (MAPS) that enables reliable, high-throughput analysis as well as sample-customized processing. This system is comprised of a set of independent modules that carry out individual sample processing functions: cell lysis, protein concentration (based on hydrophobic, ion-exchange and affinity interactions), interferent depletion, buffer exchange, and enzymatic digestion of proteins of interest. Taking advantage of its unique capacity for enclosed processing of intact bioparticulates (viruses, spores) and complex serum samples, we have used MAPS for analysis of BSL1 and BSL2 samples to identify specific protein markers through integration with the portable microChemLab{trademark} and MALDI.