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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

ML-based calibration and control of the GlueX Central Drift Chamber

The GlueX Central Drift Chamber (CDC) in Hall D at Jefferson Lab, used for detecting and tracking charged particles, is calibrated and controlled during data taking using a Gaussian process. The system dynamically adjusts the high voltage applied to the anode wires inside the chamber in response to changing environmental and experimental conditions such that the gain is stabilized. Control policies have been established to manage the CDC's behavior. These policies are activated when the model's uncertainty exceeds a configurable threshold or during human-initiated tests during normal production running. Finally, we demonstrate the system reduces the time detector experts dedicate to calibration of the data offline, leading to a marked decrease in computing resource usage without compromising detector performance.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Guidance on the Use of Hand-Held Survey Meters for radiological Triage: Time-Dependent Detector Count Rates Corresponding to 50, 250, and 500 mSv Effective Dose for Adult Males and Adult Females

In June 2006, the Radiation Studies Branch of the Centers for Disease Control and Prevention held a workshop to explore rapid methods of facilitating radiological triage of large numbers of potentially contaminated individuals following detonation of a radiological dispersal device. Two options were discussed. The first was the use of traditional gamma cameras in nuclear medicine departments operated as makeshift wholebody counters. Guidance on this approach is currently available from the CDC. This approach would be feasible if a manageable number of individuals were involved, transportation to the relevant hospitals was quickly provided, and the medical staff at each facility had been previously trained in this non-traditional use of their radiopharmaceutical imaging devices. If, however, substantially larger numbers of individuals (100 s to 1,000 s) needed radiological screening, other options must be given to first responders, first receivers, and health physicists providing medical management. In this study, the second option of the workshop was investigated by the use of commercially available portable survey meters (either NaI or GM based) for assessing potential ranges of effective dose (G50, 50Y250, 250Y500, and 9500 mSv). Two hybrid computational phantoms were used to model an adult male and an adult female subject internally contaminated with 241Am, 60Cs, 137Cs, 131I, or 192Ir following an acute inhalation or ingestion intake. As a function of time following the exposure, the net count rates corresponding to committed effective doses of 50, 250, and 500 mSv were estimated via Monte Carlo radiation transport simulation for each of four different detector types, positions, and screening distances. Measured net count rates can be compared to these values, and an assignment of one of four possible effective dose ranges could be made. The method implicitly assumes that all external contamination has been removed prior to screening and that the measurements be conducted in a low background, and possibly mobile, facility positioned at the triage location. Net count rate data are provided in both tabular and graphical format within a series of eight handbooks available at the CDC website (http://www.bt.cdc.gov/radiation/clinicians/evaluation).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Use of Adaptive Injection Strategies to Increase the Full Load Limit of RCCI Operation

Dual-fuel combustion using port-injection of low reactivity fuel combined with direct injection (DI) of a higher reactivity fuel, otherwise known as reactivity controlled compression ignition (RCCI), has been shown as a method to achieve low-temperature combustion with moderate peak pressure rise rates, low engine-out soot and NO x emissions, and high indicated thermal efficiency. A key requirement for extending to high-load operation is moderating the reactivity of the premixed charge prior to the diesel injection. One way to accomplish this is to use a very low reactivity fuel such as natural gas. In this work, experimental testing was conducted on a 13 l multicylinder heavy-duty diesel engine modified to operate using RCCI combustion with port injection of natural gas and DI of diesel fuel. Engine testing was conducted at an engine speed of 1200 rpm over a wide variety of loads and injection conditions. The impact on dual-fuel engine performance and emissions with respect to varying the fuel injection parameters is quantified within this study. The injection strategies used in the work were found to affect the combustion process in similar ways to both conventional diesel combustion (CDC) and RCCI combustion for phasing control and emissions performance. As the load is increased, the port fuel injection (PFI) quantity was reduced to keep peak cylinder pressure (PCP) and maximum pressure rise rate (MPRR) under the imposed limits. Overall, the peak load using the new injection strategy was shown to reach 22 bar brake mean effective pressure (BMEP) with a peak brake thermal efficiency (BTE) of 47.6%.

Hanson, Reed↗
DOE OSTI2020

COVID-19 global pandemic planning: Performance and electret charge of N95 respirators after recommended decontamination methods

Shortages of N95 respirators for use by medical personnel have driven consideration of novel conservation strategies, including decontamination for reuse and extended use. Decontamination methods listed as promising by the Centers for Disease Control and Prevention (CDC) (vaporous hydrogen peroxide (VHP), wet heat, ultraviolet irradiation (UVI)) and several methods considered for low resource environments (bleach, isopropyl alcohol and detergent/soap) were studied for two commonly used surgical N95 respirators (3M™ 1860 and 1870+ Aura™). Although N95 filtration performance depends on the electrostatically charged electret filtration layer, the impact of decontamination on this layer is largely unexplored. As such, respirator performance following decontamination was assessed based on the fit, filtration efficiency, and pressure drop, along with the relationship between (1) surface charge of the electret layer, and (2) elastic properties of the straps. Decontamination with VHP, wet heat, UVI, and bleach did not degrade fit and filtration performance or electret charge. Isopropyl alcohol and soap significantly degraded fit, filtration performance, and electret charge. Pressure drop across the respirators was unchanged. Modest degradation of N95 strap elasticity was observed in mechanical fatigue testing, a model for repeated donnings and doffings. CDC recommended decontamination methods including VHP, wet heat, and UV light did not degrade N95 respirator fit or filtration performance in these tests. Extended use of N95 respirators may degrade strap elasticity, but a loss of face seal integrity should be apparent during user seal checks. NIOSH recommends performing user seal checks after every donning to detect loss of appropriate fit. Decontamination methods which degrade electret charge such as alcohols or detergents should not be used on N95 respirators. The loss of N95 performance due to electret degradation would not be apparent to a respirator user or evident during a negative pressure user seal check.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge

Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013–14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013–2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013–March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts.

Infectious Diseases↗
DOE OSTI2019

Clinical Importance of Sputum in the Respiratory Tract as a Predictive Marker of Postoperative Morbidity After Esophagectomy for Esophageal Cancer

Background: Respiratory morbidity is common after esophagectomy and can be a major cause of surgery-related mortality. Thus, it is important to identify novel predictors that can preoperatively estimate the incidence of postoperative respiratory morbidity. Asymptomatic sputum in the respiratory tract is sometimes observed on preoperative computed tomography (CT). This study aimed to determine the clinical importance of sputum in the respiratory tract as a predictor of postoperative morbidity after esophagectomy for esophageal cancer. Patients and Methods: The study included 609 consecutive patients who underwent three-incisional esophagectomy for esophageal cancer between April 2005 and November 2018. Results: Among the patients, 76 (12.5%) had sputum in the respiratory tract on preoperative CT. This finding was significantly associated with older age, more extreme smoking habit, worse performance status, lower forced expiratory volume 1%, and more frequent pulmonary comorbidities. Additionally, the incidence of postoperative pneumonia was higher in these patients than in those without sputum (16 vs 8%, p = 0.028). Sputum in the main bronchus was associated with higher frequencies of morbidity of Clavien–Dindo classification (CDc) ≥ II (p = 0.019), severe morbidity of CDc ≥ IIIb (p = 0.058), pneumonia (p = 0.10), and pulmonary morbidity (p = 0.19) compared with the finding of sputum in the trachea alone. On multivariate analysis, sputum in the respiratory tract was an independent risk factor (hazard ratio, 2.07; 95% confidence interval, 1.019–4.207; p = 0.044) for postoperative pneumonia. Conclusions: Sputum in the respiratory tract is a novel predictor of postesophagectomy pneumonia. Patients with sputum in the more distal respiratory tract might have high risk of postoperative morbidities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Forecasting the 2013–2014 influenza season using Wikipedia

Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Real Time Assays for Quantifying Cytotoxicity with Single Cell Resolution

A new live cell-based assay platform has been developed for the determination of complement dependent cytotoxicity (CDC), antibody dependent cellular cytotoxicity (ADCC), and overall cytotoxicity in human whole blood. In these assays, the targeted tumor cell populations are first labeled with fluorescent Cell Tracker dyes and immobilized using a DNA-based adhesion technique. This allows the facile generation of live cell arrays that are arranged arbitrarily or in ordered rectilinear patterns. Following the addition of antibodies in combination with serum, PBMCs, or whole blood, cell death within the targeted population can be assessed by the addition of propidium iodide (PI) as a viability probe. The array is then analyzed with an automated microscopic imager. The extent of cytotoxicity can be quantified accurately by comparing the number of surviving target cells to the number of dead cells labeled with both Cell Tracker and PI. Excellent batch-to-batch reproducibility has been achieved using this method. In addition to allowing cytotoxicity analysis to be conducted in real time on a single cell basis, this new assay overcomes the need for hazardous radiochemicals. Fluorescently-labeled antibodies can be used to identify individual cells that bear the targeted receptors, but yet resist the CDC and ADCC mechanisms. This new approach also allows the use of whole blood in cytotoxicity assays, providing an assessment of antibody efficacy in a highly relevant biological mixture. Given the rapid development of new antibody-based therapeutic agents, this convenient assay platform is well-poised to streamline the drug discovery process significantly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Conditioning multi-model ensembles for disease forecasting

In this study we investigate how an ensemble of disease models can be conditioned to observational data, in a bid to improve its predictive skill. We use the ensemble of influenza forecasting models gathered by the US Centers for Disease Control and Prevention (CDC) as the exemplar. This ensemble is used every year to forecast the annual influenza outbreak in the United States. The models constituting this ensemble draw on very different modeling assumptions and approximations and are a diverse collection of methods to approximate epidemiological dynamics. Currently, each models' predictions are accorded the same importance, or weight, when compiling the ensemble's forecast. We consider this equally-weighted ensemble as the baseline case which has to be improved upon. In this study, we explore whether an ensemble forecast can be improved by "conditioning" the ensemble to whatever observational data is available from the ongoing outbreak. "Conditioning" can imply according the ensemble's members different weights which evolve over time, or simply perform the forecast using the top k (equally-weighted) models. In the latter case, the composition of the "top-k-see of models evolves over time. This is called "model averaging" in statistics. We explore four methods to perform model-averaging, three of which are new. We find that the CDC ensemble responds best to the "top-k-models" approach to model-averaging. All the new MA methods perform better than the baseline equally-weighted ensemble. The four model-averaging methods treat the models as black-boxes and simply use their forecasts as inputs i.e., one does not need access to the models at all, but rather only their forecasts. The model-averaging approaches reviewed in this report thus form a general framework for model-averaging any model ensemble.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Diagnostic Testing for COVID-19 Bridging Study for QIAamp Viral RNA Extraction vs Beckman RNAdvance vs Thermofisher MagMAX

This report describes testing that was performed by LANL’s Biological Agent Testing Lab (BATL) to validate modifications to the CDC EUA 2019-Novel Coronavirus (2019- nCoV) Real-Time RT-PCR Diagnostic Panel (EUA-CDC-nCoV-IFU). BATL intends to implement the modifications to increase thoughput for daily testing . BATL validated the viral RNA extraction process, using the orignial component, QIAamp Viral RNA Mini Kit (Cat # 52906) and the new components, Beckman Coulter magnetic 96-well plate RNAdvance Viral kit (Cat # C63510), Thermofisher MagMAX Viral/Pathogen Nucleic Acid Isolation Kit (Cat # A48310). Equivalency was demonstrated between the original component and the Beckman Coulter magnetic 96-well plate RNAdvance Viral kit (Cat # C63510). Equivalency was also demonstrated between the original component and the Thermofisher MagMAX Viral/Pathogen Nucleic Acid Isolation Kit (Cat # A48310). Subsequently, substitution of the original component with either of these kits for viral RNA extraction increased BATL’s extraction capability from 100 samples per day to 279 samples per day.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Evaluation of Three RNA Extraction Kits with a 2019-nCoV Assay

The following characteristics of three RNA extraction kits (Norgen Biotek Total RNA Purification Kit, #17200; Bioneer AccuPrep Viral RNA Extraction Kit, #K-3033; and Promega Maxwell HT Viral TNA Kit, #AX2340) were evaluated: Limits of detection for quantitative synthetic RNA using the Centers for Disease Control and Prevention’s (CDC) 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel and the Applied Biosystems 7500 Fast Dx system; Limits of detection for positive clinical specimen using the Centers for Disease Control and Prevention’s (CDC) 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel and the Applied Biosystems 7500 Fast Dx system; Ability of the lysis buffers in each kit to inactivate the virus as measured by a cell-based infectivity assay.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Ducted Fuel Injection And Cooled Spray Technologies For Particulate Control In Heavy-duty Diesel Engines (Final Report)

Cooled Spray (CS) and Ducted Fuel Injection (DFI) are in-cylinder technologies for diesel engines that can reduce particulate matter and soot emissions and data has been published showing that these technologies can reduce soot emissions by 75-100% for some engines at some operating conditions. However, little is known about scaling the devices for engine size. Additionally, the performance of either technology over the engine duty cycle has not been explored. This project addresses both of these points through single-cylinder engine investigations. The objectives of this project are to provide details about dimensional scaling of these devices and to demonstrate 75% PM reduction over a range of operating conditions on a single-cylinder engine. Two engines were used for this project: a 125mm bore optically accessible engine at Sandia National Laboratories and a 168mm bore metal engine at Southwest Research Institute. The optical engine was used to study the performance of DFI and CS inserts for a large injector orifice diameter injector that is characteristic of a locomotive engine and to perform scaling studies for DFI. The metal engine was used to perform scaling and alignment studies for CS and to evaluate the technology for both EGR and non-EGR engines over the engine operating map. Modifications were required for both engines to accept the prototype inserts being tested. The optical engine required a new fuel injector, cylinder head and piston so that tests could be run at the pressures and engine speeds required. Additionally, a novel rotating stage was designed for the optical engine to simplify alignment of the modules. The metal engine required a modified cylinder head to accept CS inserts and a modified piston to provide additional space around the fuel injector for the CS inserts. Tests on the optical engine showed that DFI reduces PM emissions for both small injector orifices (0.170mm diameter) and large injector orifices (0.290mm). For high load testing, the DFI modules were not as effective as at low load testing, but it was acknowledged that minimal geometric optimization was performed and more improvements may be possible. Comparing DFI to CS and conventional diesel combustion (CDC), DFI performed better than CS or CDC. The CS geometries used in these studies may not be ideal for that engine and additional modifications likely would improve performance. Tests on the metal engine showed PM reductions as high has 80% at some operating conditions with duty-cycle PM reductions of ~50% for EGR and non-EGR configurations. The CS testing on the metal engine showed that chamfering of the fuel passage inlet either through hydro-erosion or mechanical grinding provided significant improvements in the PM reduction capabilities of the insert. Additionally, alignment sensitivities were explored and the data show that the tolerance to misalignment is approximately 0.05 to 0.1mm for the inserts that were studied here. Air-fuel ratio was shown to be important in the effectiveness of the CS inserts. In several tests, it was shown that the CS inserts are more effective at reducing the PM for high-AFR operating conditions compared to low AFR conditions. In summary, multiple designs were evaluated on both engines. It was found that for the conditions and configurations studied here, a fuel passage diameter of ~2.5mm performed best overall. Significant duty-cycle PM reductions are possible using these technologies and sensitivities to AFR, alignment fuel passage diameter and inlet fuel passage shaping were explored and are reported here. More PM reduction may be possible with improved geometric design and attention to alignment practices.

02 PETROLEUM↗
DOE OSTI2022

The development and use of decision support framework for informing selection of select agent toxins with modelling studies to inform permissible toxin amounts

Many countries have worked diligently to establish and implement policies and processes to regulate high consequence pathogens and toxins that could have a significant public health impact if misused. In the United States, the Antiterrorism and Effective Death Penalty Act of 1996 (Public Law 104-132, 1996), as amended by the Bioterrorism Preparedness and Response Act of 2002 (Public Law 107-188, 2002) requires that the Department of Health and Human Services (HHS) [through the Centers for Disease Control and Prevention (CDC)] establish a list of bacteria, viruses, and toxins that have the potential to pose a severe threat to public health and safety. Currently, this list is reviewed and updated on a biennial basis using input from subject matter experts (SMEs). We have developed decision support framework (DSF) approaches to facilitate selection of select toxins and, where toxicity data are known, conducted modelling studies to inform selection of toxin amounts that should be excluded from select agent regulations. Exclusion limits allow laboratories to possess toxins under an established limit to support their research or teaching activities without the requirement to register with the Federal Select Agent Program. Fact sheets capturing data from a previously vetted SME workshop convened by CDC, literature review and SME input were developed to assist in evaluating toxins using the DSF approach. The output of the DSF analysis agrees with the current select toxin designations, and no other toxins evaluated in this study were recommended for inclusion on the select agent and toxin list. To inform the selection of exclusion limits, attack scenarios were developed to estimate the amount of toxin needed to impact public health. Scenarios consisted of simulated aerosol releases of a toxin in high-population-density public facilities and the introduction of a toxin into a daily consumable product supply chain. Using published inhalation and ingestion median toxic dose (TD 50 ) and median lethal dose (LD 50 ) values, where available, a range of toxin amounts was examined to estimate the number of people exposed to these amounts in these scenarios. Based on data generated by these models, we proposed toxin exclusion values corresponding to levels below those that would trigger a significant public health response (i.e., amounts estimated to expose up to ten people by inhalation or one hundred people by ingestion to LD 50 or TD 50 levels of toxin in the modeled scenarios).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making

The Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities working with them. Every 2 years the Program reviews the select agent list, utilizing subject matter expert (SME) assessments to rank the agents. In this study, we explore the applicability of multi-criteria decision analysis (MCDA) techniques and logic tree analysis to support the CDC Select Agent Program biennial review process, applying the approach broadly to include non-select agents to evaluate its generality. We conducted a literature search for over 70 pathogens against 15 criteria for assessing public health and bioterrorism risk and documented the findings for archiving. The most prominent data gaps were found for aerosol stability and human infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. Analysis of results obtained from a two-dimensional plot of weighted scores for difficulty of attack (i.e., exposure and production criteria) vs. consequences of an attack (i.e., consequence and mitigation criteria) provided greater fidelity for understanding agent placement compared to a 1-to-n ranking and was used to define a region in the upper right-hand quadrant for identifying pathogens for consideration as select agents. A sensitivity analysis varied the numerical weights attributed to various properties of the pathogens to identify potential quantitative (x and y) thresholds for classifying select agents. The results indicate while there is some clustering of agent scores to suggest thresholds, there are still pathogens that score close to any threshold, suggesting that thresholding “by eye” may not be sufficient. The sensitivity analysis indicates quantitative thresholds are plausible, and there is good agreement of the analytical results with select agent designations. A second analytical approach that applied the data using a logic tree format to rule out pathogens for consideration as select agents arrived at similar conclusions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Healthcare Providers’ Perceptions and Self-Reported Fall Prevention Practices: Findings from a Large New York Health System

Among older adults, falls are the leading cause of injury-related deaths and emergency department visits, and the incidence of falls in the United States is rising as the number of older Americans increases. Research has shown that falls can be reduced by modifying fall-risk factors using multifactorial interventions implemented in clinical settings. However, the literature indicates that many providers feel that they do not know how to conduct fall-risk assessments or do not have adequate knowledge about fall prevention. To help healthcare providers incorporate older adult fall prevention (i.e., falls risk assessment and treatment) into their clinical practice, the Centers for Disease Control and Prevention’s (CDC) Injury Center has developed the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) tool kit. This study was conducted to identify the practice characteristics and providers’ beliefs, knowledge, and fall-related activities before they received training on how to use the STEADI tool kit. Data were collected as part of a larger State Fall Prevention Project funded by CDC’s Injury Center. Completed questionnaires were returned by 38 medical providers from 11 healthcare practices within a large New York health system. Healthcare providers ranked falls as the lowest priority of five conditions, after diabetes, cardiovascular disease, mental health, and musculoskeletal conditions. Less than 40% of the providers asked most or all of their older patients if they had fallen during the past 12 months. Less than a quarter referred their older patients to physical therapists for balance or gait training, and <20% referred older patients to community-based fall prevention programs. Less than 16% reported they conducted standardized functional assessments with their older patients at least once a year. These results suggest that implementing the STEADI tool kit in clinical settings could address knowledge gaps and provide the necessary tools to help providers incorporate fall-risk assessment and treatment into clinical practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Optical Biosensor Platforms Display Varying Sensitivity for the Direct Detection of Influenza RNA

Detection methods that do not require nucleic acid amplification are advantageous for viral diagnostics due to their rapid results. These platforms could provide information for both accurate diagnoses and pandemic surveillance. Influenza virus is prone to pandemic-inducing genetic mutations, so there is a need to apply these detection platforms to influenza diagnostics. Here, we analyzed the Fast Evaluation of Viral Emerging Risks (FEVER) pipeline on ultrasensitive detection platforms, including a waveguide-based optical biosensor and a flow cytometry bead-based assay. The pipeline was also evaluated in silico for sequence coverage in comparison to the U.S. Centers for Disease Control and Prevention’s (CDC) influenza A and B diagnostic assays. The influenza FEVER probe design had a higher tolerance for mismatched bases than the CDC’s probes, and the FEVER probes altogether had a higher detection rate for influenza isolate sequences from GenBank. When formatted for use as molecular beacons, the FEVER probes detected influenza RNA as low as 50 nM on the waveguide-based optical biosensor and 1 nM on the flow cytometer. In addition to molecular beacons, which have an inherently high background signal we also developed an exonuclease selection method that could detect 500 pM of RNA. The combination of high-coverage probes developed using the FEVER pipeline coupled with ultrasensitive optical biosensors is a promising approach for future influenza diagnostic and biosurveillance applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Experimental Characterization of Hydrocarbons and Nitrogen Oxides Production in a Heavy-Duty Diesel–Natural Gas Reactivity-Controlled Compression Ignition Engine

Reactivity-Controlled Compression Ignition (RCCI) combustion is considered one of the most promising Low-Temperature Combustion (LTC) concepts aimed at reducing greenhouse gases for the transportation and power generation sectors. Due to the spontaneous combustion of a lean, nearly homogeneous mixture of air and low-reactivity fuel (LRF), ignited through the direct injection of a small quantity of high-reactivity fuel (HRF), RCCI (dual-fuel) shows higher efficiency and lower pollutants compared to conventional diesel combustion (CDC) if run at very advanced injection timing. Even though a HRF is used, the use of advanced injection timing leads to high ignition delays, compared to CDC, and generates high cycle-to-cycle variability, limited operating range, and high pressure rise rates at high loads. This work presents an experimental analysis performed on a heavy-duty single-cylinder compression ignited engine in dual-fuel diesel–natural gas mode. The objective of the present work is to investigate and highlight the correlations between combustion behavior and pollutant emissions, especially unburned hydrocarbons (HC) and oxides of nitrogen (NOx). Based on the analysis of crank-resolved pollutants measurements performed through fast FID and fast NOx systems under different engine operating conditions, two correlations were found demonstrating a good accordance between pollutant production and combustion behavior: Net Cyclic Hydrocarbon emission—cyclic IMEP variations (R 2 = 0.86), and Cyclic NOx—maximum value of the Rate of Heat Released (R 2 = 0.82).

33 ADVANCED PROPULSION SYSTEMS↗