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At least 1,009 records · Page 56

The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19

This study analyzed the risk factors for patients with COVID-19 developing severe illnesses and explored the value of applying the logistic model combined with ROC curve analysis to predict the risk of severe illnesses at COVID-19 patients’ admissions. The clinical data of 1046 COVID-19 patients admitted to a designated hospital in a certain city from July to September 2020 were retrospectively analyzed, the clinical characteristics of the patients were collected, and a multivariate unconditional logistic regression analysis was used to determine the risk factors for severe illnesses in COVID-19 patients during hospitalization. Based on the analysis results, a prediction model for severe conditions and the ROC curve were constructed, and the predictive value of the model was assessed. Logistic regression analysis showed that age (OR = 3.257, 95% CI 10.466–18.584), complications with chronic obstructive pulmonary disease (OR = 7.337, 95% CI 0.227–87.021), cough (OR = 5517, 95% CI 0.258–65.024), and venous thrombosis (OR = 7322, 95% CI 0.278–95.020) were risk factors for COVID-19 patients developing severe conditions during hospitalization. When complications were not taken into consideration, COVID-19 patients’ ages, number of diseases, and underlying diseases were risk factors influencing the development of severe illnesses. The ROC curve analysis results showed that the AUC that predicted the severity of COVID-19 patients at admission was 0.943, the optimal threshold was −3.24, and the specificity was 0.824, while the sensitivity was 0.827. The changes in the condition of severe COVID-19 patients are related to many factors such as age, clinical symptoms, and underlying diseases. This study has a certain value in predicting COVID-19 patients that develop from mild to severe conditions, and this prediction model is a useful tool in the quick prediction of the changes in patients’ conditions and providing early intervention for those with risk factors.

Lian, Zhichuang↗

Analysis of the first ten years of FDA’s rare pediatric disease priority review voucher program: designations, diseases, and drug development

Abstract Background The Rare Pediatric Disease (RPD) Priority Review Voucher (PRV) Program was enacted in 2012 to support the development of new products for children. Prior to requesting a voucher, applicants can request RPD designation, which confirms their product treats or prevents a rare disease in which the serious manifestations primarily affect children. This study describes the trends and characteristics of these designations. Details of RPD designations are not publicly disclosable; this research represents the first analysis of the RPD designation component of the program. Results We used an internal US Food and Drug Administration database to analyze all RPD designations between 2013 and 2022. Multiple characteristics were analyzed, including the diseases targeted by RPD designation, whether the product targeted a neonatal disease, product type (drug/biologic), and the level of evidence (preclinical/clinical) to support designation. There were 569 RPD designations during the study period. The top therapeutic areas were neurology (26%, n = 149), metabolism (23%, n = 131), oncology (18%, n = 105). The top diseases targeted by RPD designation were Duchenne muscular dystrophy, neuroblastoma, and sickle cell disease. Neonatology products represented 6% (n = 33), over half were for drug products and 38% were supported by clinical data. Conclusions The RPD PRV program was created to encourage development of new products for children. The results of this study establish that a wide range of diseases have seen development—from rare pediatric cancers to rare genetic disorders. Continued support of product development for children with rare diseases is needed to find treatments for all children with unmet needs.

Mease, Catherine (ORCID:000900050156198X)↗

Development of genetic tools for the thermophilic filamentous fungus Thermoascus aurantiacus

Abstract Background Fungal enzymes are vital for industrial biotechnology, including the conversion of plant biomass to biofuels and bio-based chemicals. In recent years, there is increasing interest in using enzymes from thermophilic fungi, which often have higher reaction rates and thermal tolerance compared to currently used fungal enzymes. The thermophilic filamentous fungus Thermoascus aurantiacus produces large amounts of highly thermostable plant cell wall-degrading enzymes. However, no genetic tools have yet been developed for this fungus, which prevents strain engineering efforts. The goal of this study was to develop strain engineering tools such as a transformation system, a CRISPR/Cas9 gene editing system and a sexual crossing protocol to improve the enzyme production. Results Here, we report Agrobacterium tumefaciens -mediated transformation (ATMT) of T. aurantiacus using the hph marker gene, conferring resistance to hygromycin B. The newly developed transformation protocol was optimized and used to integrate an expression cassette of the transcriptional xylanase regulator xlnR , which led to up to 500% increased xylanase activity. Furthermore, a CRISPR/Cas9 gene editing system was established in this fungus, and two different gRNAs were tested to delete the pyrG orthologue with 10% and 35% deletion efficiency, respectively. Lastly, a sexual crossing protocol was established using a hygromycin B- and a 5-fluoroorotic acid-resistant parent strain. Crossing and isolation of progeny on selective media were completed in a week. Conclusion The genetic tools developed for T. aurantiacus can now be used individually or in combination to further improve thermostable enzyme production by this fungus.

09 BIOMASS FUELS↗

A rapid methods development workflow for high-throughput quantitative proteomic applications

Recent improvements in the speed and sensitivity of liquid chromatography-mass spectrometry systems have driven significant progress toward system-wide characterization of the proteome of many species. These efforts create large proteomic datasets that provide insight into biological processes and identify diagnostic proteins whose abundance changes significantly under different experimental conditions. Yet, these system-wide experiments are typically the starting point for hypothesis-driven, follow-up experiments to elucidate the extent of the phenomenon or the utility of the diagnostic marker, wherein many samples must be analyzed. Transitioning from a few discovery experiments to quantitative analyses on hundreds of samples requires significant resources both to develop sensitive and specific methods as well as analyze them in a high-throughput manner. To aid these efforts, we developed a workflow using data acquired from discovery proteomic experiments, retention time prediction, and standard-flow chromatography to rapidly develop targeted proteomic assays. We demonstrated this workflow by developing MRM assays to quantify proteins of multiple metabolic pathways from multiple microbes under different experimental conditions. With this workflow, one can also target peptides in scheduled/dynamic acquisition methods from a shotgun proteomic dataset downloaded from online repositories, validate with appropriate control samples or standard peptides, and begin analyzing hundreds of samples in only a few minutes.

02 PETROLEUM↗

Quantitative high-throughput screening assays for the discovery and development of SIRPα-CD47 interaction inhibitors

CD47 is an immune checkpoint molecule that downregulates key aspects of both the innate and adaptive anti-tumor immune response via its counter receptor SIRPα, and it is expressed at high levels in a wide variety of tumor types. This has led to the development of biologics that inhibit SIRPα engagement including humanized CD47 antibodies and a soluble SIRPα decoy receptor that are currently undergoing clinical trials. Unfortunately, toxicological issues, including anemia related to on-target mechanisms, are barriers to their clinical advancement. Another potential issue with large biologics that bind CD47 is perturbation of CD47 signaling through its high-affinity interaction with the matricellular protein thrombospondin-1 (TSP1). One approach to avoid these shortcomings is to identify and develop small molecule molecular probes and pretherapeutic agents that would (1) selectively target SIRPα or TSP1 interactions with CD47, (2) provide a route to optimize pharmacokinetics, reduce on-target toxicity and maximize tissue penetration, and (3) allow more flexible routes of administration. As the first step toward this goal, we report the development of an automated quantitative high-throughput screening (qHTS) assay platform capable of screening large diverse drug-like chemical libraries to discover novel small molecules that inhibit CD47-SIRPα interaction. Using time-resolved Förster resonance energy transfer (TR-FRET) and bead-based luminescent oxygen channeling assay formats (AlphaScreen), we developed biochemical assays, optimized their performance, and individually tested them in small-molecule library screening. Based on performance and low false positive rate, the LANCE TR-FRET assay was employed in a ~90,000 compound library qHTS, while the AlphaScreen oxygen channeling assay served as a cross-validation orthogonal assay for follow-up characterization. With this multi-assay strategy, we successfully eliminated compounds that interfered with the assays and identified five compounds that inhibit the CD47- SIRPα interaction; these compounds will be further characterized and later disclosed. Importantly, our results validate the large library qHTS for antagonists of CD47-SIRPα interaction and suggest broad applicability of this approach to screen chemical libraries for other protein-protein interaction modulators.

59 BASIC BIOLOGICAL SCIENCES↗

Development of a Supermarket Prototype Building Model

The U.S. Department of Energy supports the development of commercial building energy codes and standards by participating in industry reviews, update processes, and providing technical analyses to support both published model codes and potential changes. In support of ANSI/ASHRAE/IES Standard 90.1 and the International Energy Conservation Code, 16 commercial prototype building models were developed that cover 80% of the commercial building floor area in the United States for new construction, including both commercial buildings and mid- to high-rise residential buildings, across all U.S. climate zones. However, the current set of commercial prototype building models does not include a supermarket building type, which is one of major building types defined in the Energy Information Administration’s Commercial Building Energy Consumption Survey. As part of an ongoing effort to expand the current Commercial Building Prototype Model suite, this paper presents the procedure used to develop the prototype supermarket building model based on multiple studies as well as a previously developed reference building model. The final set of prototype models includes 68 models for different vintages of ASHRAE Standard 90.1 (i.e., 2004, 2007, 2010, and 2013) and for 17 ASHRAE climate zones.

Im, Piljae↗

An Agile/XP software development process for modernizing the accelerator control system at Fermilab

Fermilab is undergoing the most ambitious upgrade to its accelerator control system of the 21st century. As part of the ACORN project, hundreds of legacy control system applications written in C/C++ will be re-imagined and developed from the ground up. In addition, applications to support Fermilab’s new super-conducting linear accelerator are already under construction. To manage the development of modern controls applications, the Controls department has adopted an Agile software development process based on eXtreme Programming. In this paper we will describe our process and detail our experience applying it to the development of two case studies.

Diamond, John [Fermilab]↗

Developments in commercial scale farming of microalgae and seaweeds

Expanding markets for microalgae and macroalgae products have led to increased development of commercial farming operations. While microalgae and macroalgae, or seaweed, have historically been harvested in many parts of globe, more recent developments seek to improve productivity, decrease production costs, increase scale, and mitigate environmental impacts of cultivation. Furthermore, this chapter highlights some of those recent developments and identifies future focus areas for research and development.

09 BIOMASS FUELS↗

Electron Storage Ring Development for ICS Sources

There is an increasing world-wide interest in compact light sources based on Inverse Compton Scattering. Development of these types of light sources includes leveraging the investment in accelerator technology first developed at DOE National Laboratories. Although these types of light sources cannot replace the larger user-supported synchrotron facilities, they offer attractive alternatives for many x-ray science applications. Fundamental research at the SLAC National Laboratory in the 1990’s led to the idea of using laser-electron storage rings as a mechanism to generate x-rays with many properties of the larger synchrotron light facilities. This research led to a commercial spin-off of this technology. The SBIR project goal is to understand and improve the performance of the electron storage ring system of the commercially available Compact Light Source. The knowledge gained from studying a low-energy electron storage ring may also benefit other Inverse Compton Scattering (ICS) source development. Better electron storage ring performance is one of the key technologies necessary to extend the utility and breadth of applications of the CLS or related ICS sources. This grant includes a subcontract with SLAC for technical personnel and resources for modeling, feedback development, and related accelerator physics studies.

43 PARTICLE ACCELERATORS↗

Robust Technique for Measuring and Simulating Silicon Wafer Quality Characteristics that Enable the Prediction of Solar Cell Electrical Performance of MEMC Silicon Wafer. Cooperative Research and Development Final Report, CRADA Number CRD-11-438

NREL and MEMC Electronic Materials are interested in developing a robust technique for monitoring material quality of mc-Si and mono-Si wafers -- a technique that can provide relevant data to accurately predict the performance of solar cells fabricated on them. Previous work, performed under two TSAs between NREL and MEMC, has established that dislocation clusters are the dominant performance-limiting factor in MEMC mc-Si solar cells. The work under this CRADA will go further in verifying these results on a larger data set, evaluate possibilities of faster method(s) for mapping dislocations in wafers/ingots, understanding dislocation generation during ingot casting, and helping MEMC to have an internal capability for basic characterization that will provide feedback needed for more accurate crystallization simulations. NREL has already developed dislocation mapping technique and developed a basic electronic model (called Network Model) that uses spatial distribution of dislocations to predict the cell performance. In this CRADA work, we will use these techniques to: (i) establish dislocation, grain size, and grain orientation distributions of the entire ingots (through appropriate DOE) and compare these with theoretical models developed by MEMC, (ii) determine concentrations of some relevant impurities in selected wafers, (iii) evaluate potential of using photoluminescence for dislocation mapping and identification of recombination centers, (iv) evaluate use of diode array analysis as a detailed characterization tool, and (v) establish dislocation mapping as a wafer-quality monitoring tool for commercial mc-Si production.

14 SOLAR ENERGY↗

Recovery Act:Rural Cooperative Geothermal development Electric & Agriculture

Surprise Valley Electric, a small rural electric cooperative serving northeast California and southern Oregon, developed a 3mw binary geothermal electric generating plant on a cooperative member's ranch. The geothermal resource had been discovered in 1980 when the ranch was developing supplemental irrigation water wells. The 240°F resource was used for irrigation until developed through this project for generation of electricity. A portion of the spent geothermal fluid is now used for irrigation in season and is available for other purposes, such as greenhouse agriculture, aquaculture and direct heating of community buildings. Surprise Valley Electric describes many of the challenges a small rural electric cooperative encountered and managed to develop a geothermal generating plant.

15 GEOTHERMAL ENERGY↗

Development and Industrialization of InGaN/GaN LEDs on Patterned Sapphire Substrates for Low Cost Emitter Architecture

Patterned sapphire substrate (PSS) technology has proven to be an effective approach to improve efficacy and reduce cost of light-emitting diodes (LEDs). The volume emission from the transparent substrate leads to high package efficiency, while the simple and robust architecture of PSS-based LEDs enables low cost. PSS substrates have gained wide use in mid-power LEDs over the past years. In this project, Lumileds has developed and industrialized PSS and epitaxy technology for high- power flip-chip LEDs to bring these benefits to a broader range of applications and accelerate the adoption of energy-efficient solid-state lighting (SSL). PSS geometries were designed for highly efficient light extraction in a flip-chip architecture and high-volume manufacturability, and corresponding sapphire patterning and epitaxy manufacturing processes were integrally developed. Concurrently, device and package architectures were developed to take advantage of the PSS flip-chip die in different types of products that meet application needs. The developed PSS and epitaxy technology has been fully implemented in manufacturing at Lumileds’ San Jose, CA location, and incorporated in illumination-grade LED products that have been successfully introduced to the market, including LUXEON Q and LUXEON FlipChip White.

36 MATERIALS SCIENCE↗

Regulatory Technology Development Plan - Sodium Fast Reactor. Mechanistic Source Term - Trial Calculation. Work Plan

The overall objective of the SFR Regulatory Technology Development Plan (RTDP) effort is to identify and address potential impediments to the SFR regulatory licensing process. In FY14, an analysis by Argonne identified the development of an SFR-specific MST methodology as an existing licensing gap with high regulatory importance and a potentially long lead-time to closure. This work was followed by an initial examination of the current state-of-knowledge regarding SFR source term development (ANLART-3), which reported several potential gaps. Among these were the potential inadequacies of current computational tools to properly model and assess the transport and retention of radionuclides during a metal fuel pool-type SFR core damage incident. The objective of the current work is to determine the adequacy of existing computational tools, and the associated knowledge database, for the calculation of an SFR MST. To accomplish this task, a trial MST calculation will be performed using available computational tools to establish their limitations with regard to relevant radionuclide release/retention/transport phenomena. The application of existing modeling tools will provide a definitive test to assess their suitability for an SFR MST calculation, while also identifying potential gaps in the current knowledge base and providing insight into open issues regarding regulatory criteria/requirements. The findings of this analysis will assist in determining future research and development needs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development and Validation of a Polarimetric-MCScene 3D Atmospheric Radiation Model

Polarimetric measurements can substantially enhance the ability of both spectrally resolved and single band imagery to detect the proliferation of weapons of mass destruction, providing data for locating and identifying facilities, materials, and processes of undeclared and proliferant nuclear weapons programs worldwide. Unfortunately, models do not exist that efficiently and accurately predict spectral polarized signatures for the materials of interest embedded in complex 3D environments. Having such a model would enable one to test hypotheses and optimize both the enhancement of scene contrast and the signal processing for spectral signature extraction. The Phase I set the groundwork for development of fully validated polarimetric spectral signature and scene simulation models. This has been accomplished 1. by (a) identifying and downloading state-of-the-art surface and atmospheric polarimetric data sources, (b) implementing tools for generating custom polarimetric data, and (c) identifying and requesting US Government funded field measurement data for use in validation; 2. by formulating an approach for upgrading the radiometric spectral signature model MODTRAN to generate polarimetric intensities through (a) ingestion of the polarimetric data, (b) polarimetric vectorization of existing MODTRAN modules, and (c) integration of a newly developed algorithm for computing polarimetric multiple scattering contributions; 3. by generating an initial polarimetric model that demonstrates calculation of polarimetric solar and lunar single scatter intensities arising from the interaction of incoming irradiances with molecules and aerosols; 4. by developing a design and implementation plan to (a) automate polarimetric scene construction and (b) efficiently sample polarimetric scattering and reflection events, for use in a to be developed polarimetric version of the existing first-principles synthetic scene simulation model, MCScene; and 5. by planning a validation field measurement program in collaboration with the Remote Sensing and Exploitation group at Sandia National Laboratories (SNL) in which data from their ongoing polarimetric field and laboratory measurement program will be shared and, to the extent allowed, tailored for model validation in exchange for model predictions under conditions and for geometries outside of their measurement domain.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Multiscale Multiphysics Developments for Accident Tolerant Fuel Concepts

U 3 Si 2 and iron-chromium-aluminum (Fe-Cr-Al) alloys are two of many proposed accident-tolerant fuel concepts for the fuel and cladding, respectively. The behavior of these materials under normal operating and accident reactor conditions is not well known. As part of the Department of Energy’s Accident Tolerant Fuel High Impact Problem program significant work has been conducted to investigate the U 3 Si 2 and FeCrAl behavior under reactor conditions. This report presents the multiscale and multiphysics effort completed in fiscal year 2015. The report is split into four major categories including Density Functional Theory Developments, Molecular Dynamics Developments, Mesoscale Developments, and Engineering Scale Developments. The work shown here is a compilation of a collaborative effort between Idaho National Laboratory, Los Alamos National Laboratory, Argonne National Laboratory and Anatech Corp.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Computable general equilibrium model fiscal year 2013 capability development report

This report documents progress made on continued developments of the National Infrastructure Simulation and Analysis Center (NISAC) Computable General Equilibrium Model (NCGEM), developed in fiscal year 2012. In fiscal year 2013, NISAC the treatment of the labor market and tests performed with the model to examine the properties of the solutions computed by the model. To examine these, developers conducted a series of 20 simulations for 20 U.S. States. Each of these simulations compared an economic baseline simulation with an alternative simulation that assumed a 20-percent reduction in overall factor productivity in the manufacturing industries of each State. Differences in the simulation results between the baseline and alternative simulations capture the economic impact of the reduction in factor productivity. While not every State is affected in precisely the same way, the reduction in manufacturing industry productivity negatively affects the manufacturing industries in each State to an extent proportional to the reduction in overall factor productivity. Moreover, overall economic activity decreases when manufacturing sector productivity is reduced. Developers ran two additional simulations: (1) a version of the model for the State of Michigan, with manufacturing divided into two sub-industries (automobile and other vehicle manufacturing as one sub-industry and the rest of manufacturing as the other subindustry); and (2) a version of the model for the United States, divided into 30 industries. NISAC conducted these simulations to illustrate the flexibility of industry definitions in NCGEM and to examine the simulation properties of in more detail.

97 MATHEMATICS AND COMPUTING↗

NREL and DONG Energy Collaboration for Grid Simulator Controls and Testing: Cooperative Research and Development Final Report, CRADA Number CRD-13-527

The National Renewable Energy Laboratory (NREL) and DONG Energy are interested in collaborating for the development of control algorithms, modeling, and grid simulator testing of wind turbine generator systems involving NWTC's advanced Controllable Grid Interface (CGI). NREL and DONG Energy will work together to develop control algorithms, models, test methods, and protocols involving NREL's CGI, as well as appropriate data acquisition systems for grid simulation testing. The CRADA also includes work on joint publication of results achieved from modeling and testing efforts. Further, DONG Energy will send staff to NREL on a long-term basis for collaborative work including modeling and testing. NREL will send staff to DONG Energy on a short-term basis to visit wind power sites and participate in meetings relevant to this collaborative effort. DOE has provided NREL with over 10 years of support in developing custom facilities and capabilities to enable testing of full-scale integrated wind turbine drivetrain systems in accordance with the needs of the US wind industry. NREL currently operates a 2.5MW dynamometer and is in the processes of commissioning a 5MW dynamometer and a grid simulator (referred to as a 'Controllable Grid Interface' or CGI). DONG Energy is the market leader in offshore wind power development, with currently over 1 GW of on- and offshore wind power in operation, and 1.3 GW under construction. DONG Energy has on-going R&D projects involving high voltage DC (HVDC) transmission.

17 WIND ENERGY↗

Advanced Hydrogen Turbine Development

Under the sponsorship of the U.S. Department of Energy (DOE) National Energy Technology Laboratories, Siemens has completed the Advanced Hydrogen Turbine Development Program to develop an advanced gas turbine for incorporation into future coal-based Integrated Gasification Combined Cycle (IGCC) plants. All the scheduled DOE Milestones were completed and significant technical progress was made in the development of new technologies and concepts. Advanced computer simulations and modeling, as well as subscale, full scale laboratory, rig and engine testing were utilized to evaluate and select concepts for further development. Program Requirements of: A 3 to 5 percentage point improvement in overall plant combined cycle efficiency when compared to the reference baseline plant; 20 to 30 percent reduction in overall plant capital cost when compared to the reference baseline plant; and NOx emissions of 2 PPM out of the stack. were all met. The program was completed on schedule and within the allotted budget

42 ENGINEERING↗