OBJECTIVES/GOALS: We designed the Biocascade Exhaled Breath Sampler (BEBS) to characterize viral aerosol shedding among individuals with influenza and other respiratory virus infections. We first aimed to test the BEBS on volunteer COVID-19 cases and report the aerodynamic size distribution of exhaled breath aerosol particles carrying SARS-CoV-2 RNA. METHODS/STUDY POPULATION: From June 15 through December 15, 2022, we recruited 27 PCR-confirmed COVID-19 cases from a college campus and the surrounding community to provide 30-minute breath samples into a well-validated Gesundheit-II (G-II) exhaled breath aerosol sampler. Among these individuals, 17 provided an additional exhaled breath sample into the newly designed BEBS. We quantified samples for viral RNA using reverse transcription digital polymerase chain reaction (RT-dPCR) and determined the viral RNA copies collected within two aerosol size fractions (≤5 µm and >5 µm in diameter) from the G-II, and four aerosol size fractions (<1.15 µm, 1.15–3.2 µm, 3.3–8.2 µm, and >8.2 µm) from the BEBS. RESULTS/ANTICIPATED RESULTS: Individuals with a SARS-CoV-2 Omicron BA.4 or BA.5 infection shed virus in aerosols at an average rate of 7.5x103 RNA copies per 30-minute G-II sample, with 78% of the total RNA in aerosols ≤5 µm in diameter. Among the BEBS samples, 10% of the total viral RNA was detected in aerosols <1.15 µm, 43% in 1.15–3.2 µm, 37% in 3.3–8.2 µm, and 10% in the >8.2 µm size fraction. Based on viral RNA loads, our results indicate that exhaled aerosols ≤3.2 µm contribute the majority of SARS-CoV-2 inhalation exposure. DISCUSSION/SIGNIFICANCE: Our data provide additional evidence that respirable aerosols contribute to the spread of SARS-CoV-2. Thus, our data suggest that mitigation measures designed to reduce infectious aerosol inhalation, such as ventilation and the use of air cleaners and respirators, are needed to control the spread.

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph–based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly “Question-of-the-Month (QotM) Challenge” series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

With the aim of producing a 3D representation of tumors, imaging and molecular annotation of xenografts and tumors (IMAXT) uses a large variety of modalities in order to acquire tumor samples and produce a map of every cell in the tumor and its host environment. With the large volume and variety of data produced in the project, we developed automatic data workflows and analysis pipelines. We introduce a research methodology where scientists connect to a cloud environment to perform analysis close to where data are located, instead of bringing data to their local computers. Here, we present the data and analysis infrastructure, discuss the unique computational challenges and describe the analysis chains developed and deployed to generate molecularly annotated tumor models. Registration is achieved by use of a novel technique involving spherical fiducial marks that are visible in all imaging modalities used within IMAXT. The automatic pipelines are highly optimized and allow to obtain processed datasets several times quicker than current solutions narrowing the gap between data acquisition and scientific exploitation.

We consider the time evolution in two spatial dimensions of a double vorticity layer consisting of two contiguous, infinite material fluid strips, each with uniform but generally differing vorticity, embedded in an otherwise infinite, irrotational, inviscid incompressible fluid. The potential application is to the wake dynamics formed by two boundary layers separating from a splitter plate. A thin-layer approximation is constructed where each layer thickness, measured normal to the common centre curve, is small in comparison with the local radius of curvature of the centre curve. The three-curve equations of contour dynamics that fully describe the double-layer dynamics are expanded in the small thickness parameter. At leading order, closed nonlinear initial-value evolution equations are obtained that describe the motion of the centre curve together with the time and spatial variation of each layer thickness. In the special case where the layer vorticities are equal, these equations reduce to the single-layer equation of Moore (Stud. Appl. Math., vol. 58, 1978, pp. 119–140). Analysis of the linear stability of the first-order equations to small-amplitude perturbations shows Kelvin–Helmholtz instability when the far-field fluid velocities on either side of the double layer are unequal. Equal velocities define a circulation-free double vorticity layer, for which solution of the initial-value problem using the Laplace transform reveals a double pole in transform space leading to linear algebraic growth in general, but there is a class of interesting initial conditions with no linear growth. This is shown to agree with the long-wavelength limit of the full linearized, three-curve stability equations.

The effects of overdispersion and zero inflation (e.g., poor model fits) can result in misinterpretation in studies using count data. These effects have not been evaluated in paleoecological studies of predation and are further complicated by preservational bias and time averaging. We develop a hierarchical Bayesian framework to account for uncertainty from overdispersion and zero inflation in estimates of specimen and predation trace counts. We demonstrate its application using published data on drilling predators and their prey in time-averaged death assemblages from the Great Barrier Reef, Australia.

Our results indicate that estimates of predation frequencies are underestimated when zero inflation is not considered, and this effect is likely compounded by removal of individuals and predation traces via preservational bias. Time averaging likely reduces zero inflation via accumulation of rare taxa and events; however, it increases the uncertainty in comparisons between assemblages by introducing variability in sampling effort. That is, there is an analytical cost with time-averaged count data, manifesting as broader confidence regions. Ecological inferences in paleoecology can be strengthened by accounting for the uncertainty inherent to paleoecological count data and the sampling processes by which they are generated.

ABSTRACT IMPACT: Characterizing the cellular composition of human adipose tissue may contribute to the prevention and/or treatment of obesity-associated metabolic diseases. OBJECTIVES/GOALS: Our aims in this study were to use single-cell techniques 1. to characterize cell types within the stromavascular fraction of human adipose tissue, 2. to identify subsets of cells within each type (sub-clustering), 3. to identify gene sets and pathways that may provide information on the function and significance of each cell cluster. METHODS/STUDY POPULATION: Abdominal subcutaneous adipose tissue samples from n=6 healthy volunteers (1M, 5F, age 28-38 y, BMI 24.5-63.0 kg/m2) were collected by aspiration or during surgery. In 3 subjects, all females, paired femoral samples were also collected. After collagenase digestion approximately n=10,000 cells/sample were used for single-cell RNA sequencing using the 10X Genomics platform. After QC and downstream analysis, data were analyzed in Seurat v.3.1.5. We identified first different cell types and then subclusters in an unbiased fashion. Gene Set Enrichment Analysis (GSEA) was used for pathway analysis. RESULTS/ANTICIPATED RESULTS: Progenitor markers are related to extracellular matrix, eg DCN (logFC progenitors vs other cells types=3.17, expressed in 99.7% (pct.1) of progenitors, 26.1% (pct.2) of others). Endothelial and pericytes shared markers like RBP7 (logFC=1.67, pct.1 0.88, pct.2 0.39); pericytes also showed unique markers, eg RGS5 (logFC=2.29, pct.1 0.89, pct.2 0.17). Progenitors are further divided into 11 sub-clusters, one of which showed enrichment of CD36 (high proliferation potential), FABP4 (differentiation), and of the novel marker PALMD (logFC=7.13, pct.1 0.94, pct.2 0.48). All p<10E-5. GSEA analysis suggests that inflammatory pathways are downregulated in both adipose progenitors and endothelial/pericyte cells in the femoral compared to the abdominal depot. DISCUSSION/SIGNIFICANCE OF FINDINGS: Single cell RNA sequencing provides unique insights into the molecular profile of cell types and the identification of novel subsets of cells within the human adipose tissue. Such cellular heterogeneity may explain differences in adipose function between individuals and eventually in the risk of obesity-associated metabolic diseases.

We performed a prospective study of 501 patients, regardless of symptoms, admitted to the hospital, to estimate the predictive value of a negative nasopharyngeal swab for severe acute respiratory coronavirus virus 2 (SARS-CoV-2). At a positivity rate of 10.2%, the estimated negative predictive value (NPV) was 97.2% and the NPV rose as prevalence decreased during the study.

Optical tracking systems typically trade off between astrometric precision and field of view. In this work, we showcase a networked approach to optical tracking using very wide field-of-view imagers that have relatively low astrometric precision on the scheduled OSIRIS-REx slingshot manoeuvre around Earth on 22 Sep 2017. As part of a trajectory designed to get OSIRIS-REx to NEO 101955 Bennu, this flyby event was viewed from 13 remote sensors spread across Australia and New Zealand to promote triangulatable observations. Each observatory in this portable network was constructed to be as lightweight and portable as possible, with hardware based off the successful design of the Desert Fireball Network. Over a 4-h collection window, we gathered 15 439 images of the night sky in the predicted direction of the OSIRIS-REx spacecraft. Using a specially developed streak detection and orbit determination data pipeline, we detected 2 090 line-of-sight observations. Our fitted orbit was determined to be within about 10 km of orbital telemetry along the observed 109 262 km length of OSIRIS-REx trajectory, and thus demonstrating the impressive capability of a networked approach to Space Surveillance and Tracking.

Background: C. difficile is the leading healthcare-associated pathogen. The C. difficile real-time polymerase chain reaction (PCR) stool test, used by >70% of hospitals, is highly sensitive but cannot differentiate colonization from infection. Inappropriate C. difficile testing may result in overdiagnosis and unnecessary treatment. Healthcare costs attributed to C. difficile are substantial, but the economic burden associated with C. difficile false positives in colonized patients is poorly understood. C. difficile PCR cycle threshold (CT) is as an inverse proxy for organism burden; high CT (≥30.9) has a high (>98%) negative predictive value compared to the reference gold standard, thus is a marker of colonization. Conversely, a low CT (≤28.0) suggests high organism burden and high specificity for true infection. Methods: A propensity score matching model for cost per hospitalization was developed to determine the costs of a hospital stay associated with C. difficile and to isolate the financial impacts of both true C. difficile infection and false positives. Relevant predictors of C. difficile positivity used in the model were age, Charlson comorbidity index, white blood cell count, and creatinine. We used CT data to identify and compare 3 inpatient groups: (1) true CDI, (2) C. difficile colonization, and (3) C. difficile negative. Results: A diagnosis of C. difficile adds significantly (>$3,000) to unadjusted hospital cost compared to a negative result. Propensity-adjusted analyses demonstrated that C. difficile colonization was associated with significantly increased (median, $5,000) hospital cost whereas any positive or true diagnoses of C. difficile were not associated with increased cost. Colonized patients also had significantly higher lengths of stay (1 day) and cost per length of stay ($218 per day). Conclusions:This is the first C. difficile cost analysis to utilize PCR CT data to differentiate colonization. Surprisingly, patients with a high CT had disproportionately higher hospital costs compared to matched C. difficile–negative patients, which was not seen among patients with a low CT or with any positive result. We hypothesize that this unexpected finding may be due to misdiagnosis and mistreatment of diarrhea not caused by C. difficile or unadjusted factors associated with high cost and non–C. difficile diarrhea. In addition, the discrepantly high cost attributed to C. difficile diagnosis cited in the literature ($3,000–11,000 per hospitalized case) could be explained by the common use of administrative data to identify C. difficile cases and controls as opposed to our study, which directly linked cost data to C. difficile–positive and –negative test results.

Funding: None

Disclosures: None

Background: UV-C light reduces contamination of high-touch clinical surfaces. Few studies have tested the relative efficacy of UV-C devices in real-world clinical environments. Methods: We assessed the efficacy of the Tru-D (SmartUVC) and Moonbeam-3 UV-C (Diversey) devices at eradicating important clinical pathogens in 2 hyperbaric chambers at a tertiary-care hospital. Formica sheets were inoculated with 106–107 CFU of MRSA (USA300) or 104–105 CFU of C. difficile (NAP1). Sheets were placed in 6 predetermined locations throughout the chambers. Two Moonbeam-3 UV-C devices were positioned in the center of each chamber and were run for 3-minute (per manufacturer’s instructions) and 5-minute cycles. One Tru-D was positioned in the center of the chamber and was run on the vegetative cycle for MRSA and the spore cycle for C. difficile. UV-C dosage was measured for both machines. Quantitative cultures were collected using Rodac plates with DE neutralizing agar and were incubated at 37C for 48 hours. C. difficile was likewise plated onto sheep’s blood agar. Results: We ran each combination of chamber, microbe, and UV-C device in triplicate for In total, 108 samples per species.

For MRSA, the Tru-D vegetative cycle, the 5-minute Moonbeam cycle, and the 3-minute Moonbeam cycle resulted in average CFU log10 reductions of 7.02 (95% CI, 7.02–7.02), 6.99 (95% CI, 6.95–7.02), and 6.58 (95% CI, 6.37–6.79), respectively (Fig. 1). The Tru-D vegetative and 5-minute Moonbeam cycles were similarly effective (P > .99), and both were more effective than the 3-minute Moonbeam cycle (P < .001 and P < .001, respectively). MRSA samples receiving direct UV-C exposure had significantly greater log10 reductions (6.95; 95% CI, 6.89–7.01) than did indirect exposure (6.67; 95% CI, 6.46–6.87; P < .05) (Fig. 2). For C. difficile, the Tru-D sporicidal, the 5-, and 3-minute Moonbeam cycles resulted in average CFU log10 reductions of 1.78 (95% CI, 1.43–2.12), 0.57 (95% CI, 0.33–0.81) and 0.64 (95% CI, 0.42–0.86), respectively (Fig. 1). Tru-D was significantly more effective than either the 3- or 5-minute Moonbeam cycles (P < .00). C. difficile samples receiving direct UV-C exposure had higher dosage and significantly greater log10 reductions (1.34; 95% CI, 1.10–1.58) than did indirect exposure (0.58; 95% CI, 0.31–0.86; P < .01) (Fig. 2). Conclusions: Use of the Tru-D vegetative cycle and the Moonbeam 3- and 5-minute cycles resulted in similar reductions in MRSA; both resulted in significantly greater reductions than the manufacturer’s recommended 3-minute Moonbeam cycle. Therefore, healthcare facilities should carefully evaluate manufacturer-recommended run times in their specific clinical setting. For C. difficile, the Tru-D sporicidal cycle was significantly more effective than either of the Moonbeam cycles, likely due to higher irradiation levels. As such, direct UV-C exposure resulted in greater average reductions than indirect exposure.

Funding: None

Disclosures: None

Ultraviolet C (UV-C) light reduces contamination on high-touch clinical surfaces. We assessed the efficacy of 2 UV-C devices at eradicating important clinical pathogens in hyperbaric chambers. Both devices were similarly efficacious against MRSA but differed significantly against C. difficile. Additionally, direct UV-C exposure was more efficacious against both species than indirect exposure.

As the climate changes and ecosystems shift toward novel combinations of species, the methods and metrics of conservation science are becoming less species-centric. To meet this growing need, marine conservation paleobiologists stand to benefit from the addition of new, taxon-free benthic indices to the live–dead analysis tool kit. These indices, which were developed to provide actionable, policy-specific data, can be applied to the readily preservable component of benthic communities (e.g., mollusks) to assess the ecological quality status of the entire community. Because these indices are taxon-free, they remain applicable even as the climate changes and novel communities develop—making them a potentially valuable complement to traditionally applied approaches for live–dead analysis, which tend to focus on maintaining specific combinations of species under relatively stable environmental conditions. Integrating geohistorical data with these established indices has potential to increase the salience of the live–dead approach in the eyes of resource managers and other stakeholders.

The gomphotheres were a diverse and widespread group of proboscideans occupying Eurasia, North America, and South America throughout the Neogene. Their decline was temporally and spatially heterogeneous, and the gomphotheres ultimately became extinct during the late Pleistocene; however, the genus Cuvieronius is rarely represented in late Pleistocene assemblages in North America. Two alternative hypotheses have been invoked to explain this phenomenon: (1) competitive exclusion by sympatric mammoths and mastodons or (2) ecologic displacement due to an environmental transition from closed forests to open grasslands. To test whether competition for resources contributed to the demise of North American Cuvieronius, we present herein a large collection of stable isotope and dental microwear data from populations occupying their Pleistocene refugium in the Atlantic Coastal Plain. Results suggest that Cuvieronius consumed a wide range of resources with variable textural and photosynthetic properties and was not specialized on either grasses or browse. Further, we document evidence for the consumption of similar foods between contemporaneous gomphotheres, mammoths, and mastodons. The generalist feeding strategy of the gomphotheres likely facilitated their high Miocene abundance and diversity. However, this “jack of all trades and master of none” feeding strategy may have proved challenging following the arrival of mammoths and likely contributed to the extirpation of Cuvieronius in North America.

In patients with β-lactam allergies, administration of non–β-lactam surgical prophylaxis is associated with increased risk of infection. Although many patients self-report β-lactam allergies, most are unconfirmed or mislabeled. A quality improvement process, utilizing a structured β-lactam allergy tool, was implemented to improve the utilization of preferred β-lactam surgical prophylaxis.