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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Soil Origin and Plant Genotype Modulate Switchgrass Aboveground Productivity and Root Microbiome Assembly

Switchgrass (Panicum virgatum) is a model perennial grass for bioenergy production that can be productive in agricultural lands that are not suitable for food production. There is growing interest in whether its associated microbiome may be adaptive in low- or no-input cultivation systems. However, the relative impact of plant genotype and soil factors on plant microbiome and biomass are a challenge to decouple. To address this, a common garden greenhouse experiment was carried out using six common switchgrass genotypes, which were each grown in four different marginal soils collected from long-term bioenergy research sites in Michigan and Wisconsin. We characterized the fungal and bacterial root communities with high-throughput amplicon sequencing of the ITS and 16S rDNA markers, and collected phenological plant traits during plant growth, as well as soil chemical traits. At harvest, we measured the total plant aerial dry biomass. Significant differences in richness and Shannon diversity across soils but not between plant genotypes were found. Generalized linear models showed an interaction between soil and genotype for fungal richness but not for bacterial richness. Community structure was also strongly shaped by soil origin and soil origin × plant genotype interactions. Overall, plant genotype effects were significant but low. Random Forest models indicate that important factors impacting switchgrass biomass included NO 3 – , Ca 2+ , PO 4 3– , and microbial biodiversity. We identified 54 fungal and 52 bacterial predictors of plant aerial biomass, which included several operational taxonomic units belonging to Glomeraceae and Rhizobiaceae, fungal and bacterial lineages that are involved in provisioning nutrients to plants.

plant biomass↗
DOE OSTI2016

Predicting plant attractiveness to pollinators with passive crowdsourcing

Global concern regarding pollinator decline has intensified interest in enhancing pollinator resources in managed landscapes. These efforts frequently emphasize restoration or planting of flowering plants to provide pollen and nectar resources that are highly attractive to the desired pollinators. However, determining exactly which plant species should be used to enhance a landscape is difficult. Empirical screening of plants for such purposes is logistically daunting, but could be streamlined by crowdsourcing data to create lists of plants most probable to attract the desired pollinator taxa. People frequently photograph plants in bloom and the Internet has become a vast repository of such images. A proportion of these images also capture floral visitation by arthropods. Here, we test the hypothesis that the abundance of floral images containing identifiable pollinator and other beneficial insects is positively associated with the observed attractiveness of the same species in controlled field trials from previously published studies. We used Google Image searches to determine the correlation of pollinator visitation captured by photographs on the Internet relative to the attractiveness of the same species in common-garden field trials for 43 plant species. From the first 30 photographs, which successfully identified the plant, we recorded the number of Apis (managed honeybees), non-Apis (exclusively wild bees) and the number of bee-mimicking syrphid flies. We used these observations from search hits as well as bloom period (BP) as predictor variables in Generalized Linear Models (GLMs) for field-observed abundances of each of these groups. We found that non-Apis bees observed in controlled field trials were positively associated with observations of these taxa in Google Image searches (pseudo-R 2 of 0.668). Syrphid fly observations in the field were also associated with the frequency they were observed in images, but this relationship was weak. Apis bee observations were not associated with Internet images, but were slightly associated with BP. Our results suggest that passively crowdsourced image data can potentially be a useful screening tool to identify candidate plants for pollinator habitat restoration efforts directed at wild bee conservation. Increasing our understanding of the attractiveness of a greater diversity of plants increases the potential for more rapid and efficient research in creating pollinator-supportive landscapes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Association Mapping of Cell Wall Synthesis Regulatory Genes and Cell Wall Quality in Switchgrass

Inefficient conversion of biomass to biofuels is one of the main barriers for biofuel production from such materials. Approximately half of polysaccharides in biomass remain unused by typical biochemical conversion methods. Conversion efficiency is influenced by the composition and structure of cell walls of biomass. Grasses such as wheat, maize, and rice, as well as dedicated perennial bioenergy crops, like switchgrass, make up ~55% of biomass that can be produced in the United States. Grass cell walls have a different composition and patterning compared with dicotyledonous plants, including the well-studied model plant, Arabidopsis. This project identified genetic determinants of cell wall composition in grasses using both naturally occurring genetic variation of switchgrass and gene network reconstruction and functional assays in rice. In addition, the project linked functional data in rice and other species to switchgrass improvement efforts through curation of the most abundant class of regulators in the switchgrass genome. Characterizing natural diversity of switchgrass for variation in cell wall composition and properties, also known as quality, provides an unbiased avenue for identifying biologically viable diversity in switchgrass cell walls. To characterizing natural diversity, this project generated cell wall composition and enzymatic deconstruction data for ~450 genotypes of the Switchgrass Southern Association Collection (SSAC), a diverse collection composed of 36 switchgrass accessions from the southern U.S. distribution of switchgrass. Comparing these data with other measures of cell wall quality for the same samples demonstrated the complementary nature of the diverse characterization platforms now being used for biomass characterization. Association of the composition data with ~3.2K single nucleotide variant markers identified six significant single nucleotide variant markers co-associated with digestibility and another compositional trait. These markers might be used to select switchgrass genotypes with improved composition in breeding programs for biofuel and forage production. Because the SSAC continues to be characterized by collaborators in the bioenergy community, the data generated will be used to identify additional markers in higher resolution genotyping data to approach identifying the genes and alleles that cause natural variation in switchgrass cell wall quality. For example, these markers can be surveyed in the 2100-member Oklahoma Southern and Northern Lowland switchgrass collections that this project also characterized. An orthogonal approach to biodiversity studies, using comparative functional genomics permits systematic querying of how much regulatory information is likely to be transferable from dicots to grasses and use of accumulated functional genomics resources for better-characterized grass species, such as rice, itself a biomass source in global agriculture and in certain regions. The project generated and tested a number of specific hypotheses regarding cell wall transcription factors and enzymes of grasses. To aid identification of cell wall regulators, the project assembled a novel, highdepth and -quality gene association network using a general linearized model scoring system to combine rice gene network data. Using known or putative orthologs of Arabidopsis cell wall biosynthesis genes and regulators, the project pulled from this network a cell wall sub-network that includes 96 transcription factors. Reverse genetics of a co-ortholog of the Arabidopsis MYB61 transcription factor in rice revealed that this regulatory node has evolved the ability to regulate grass-specific cell wall synthesis enzymes. A transcription factor with such activity has not been previously characterized to our knowledge, representing a major conclusion of this work. Changes in gene expression in a protoplast-based assay demonstrated positive or negative roles in cell wall regulation for eleven other transcription factors from the rice gene network. Eight of fifteen (53%) of these have not previously been examined for this function. Some of these may represent novel grass-diverged cell wall regulators, while others are likely to have this function across angiosperms. A parallel effort of this project to expand knowledge of enzymes that have evolved to function in grass cell wall synthesis, revealed that a grass-diverged enzyme in rice, OsAT 5 , ferulates monolignols that are naturally incorporated into grass cell walls. This finding opens potential natural selection avenues for improving biomass composition for downstream processing by weak base pretreatment. Thus, this project has significantly expanded knowledge of cell wall synthesis and regulation in rice, information that can be used in reverse genetics and synthetic biology approaches to re-engineer cell walls for improved production of biofuel and high-value products. To lay the foundation for translating these results directly for switchgrass improvement, the project employed a comparative phylogenetic analysis of the major group of cell wall transcription factors that have been found to function in cell wall regulation, the R 2 R 3 MYBs. This analysis concluded that known cell wall regulators are largely conserved across switchgrass, rice, maize, poplar, and Arabidopsis. This interpretation is also largely consistent with the gene network analysis described above, though both approaches provide evidence that some co-orthologs of Arabidopsis regulators have diminished or increased in importance based on gene expression patterns. Also, several clades containing dicot cell wall regulators have expanded, consistent with the evolution of new cell wall regulators. This latter result is supported by functional analysis of the R 2 R 3 MYB protein SWAM 1 in a collaboration between this project and the DOE-funded group of Dr. S. Hazen at the University of Massachusettes. The curation of the switchgrass genome through this project provides specific targets for future engineering of switchgrass cell wall regulation and may also facilitate identification of regulators that underlie the molecular markers that are genetically linked to differences in cell wall quality. With the goal of spurring further research and technological developments in lignocellulosic biofuel production, this work has been communicated to the bioenergy and cell wall communities though various presentations and publications. To date, three manuscripts have been published, two others are near to publication, three others are in an advanced state, and two to four more are likely to be written based on analyses still in progress. In addition, project participants have presented thirteen posters and talks at regional, national, and international meetings about aspects of this project. In sum, the work supported by this funding has made and communicated significant progress in identifying the genes that grasses use for cell wall synthesis and regulation, information that will be used by project participants and others to improve the efficiency of conversion of lignocellulosic biomass to biofuels.

09 BIOMASS FUELS↗
DOE OSTI2018

Bayesian Design of Experiments for Logistic Regression to Evaluate Multiple Forensic Algorithms

When evaluating the performance of several forensic classification algorithms, it is desirable to construct a design that considers a variety of performance levels for each of the algorithms. We describe a strategy to use Bayesian design of experiments with multiple prior estimates to capture anticipated performance. Our goal is to characterize results from the different classification algorithms as a function of multiple explanatory variables and use this to choose a design about which units to test. Bayesian design of experiments has been successful for generalized linear models, including logistic regression models. Here, we develop methodology for the case where there are several potentially nonoverlapping priors for anticipated performance under consideration. The weighted priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other candidate design choices. Additionally, we show how this can be applied in the multivariate input case and provide some useful summary measures. The shared information plot is used to evaluate design point allocation, and the D-value difference plot allows for the comparison of design performance across multiple potential parameter values in higher dimensions. Here, we illustrate the methods with several examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

How to Host An Effective Data Competition: Statistical Advice for Competition Design and Analysis

Data competitions rely on real-time leaderboards to rank competitor entries and stimulate algorithm improvement. While such competitions have become quite popular and prevalent, particularly in supervised learning formats, their implementations by the host are highly variable. Without careful planning, a supervised learning competition is vulnerable to overfitting, where the winning solutions are so closely tuned to the particular set of provided data that they cannot generalize to the underlying problem of interest to the host. This paper outlines some important considerations for strategically designing relevant and informative data sets to maximize the learning outcome from hosting a competition based on our experience. It also describes a postcompetition analysis that enables robust and efficient assessment of the strengths and weaknesses of solutions from different competitors, as well as greater understanding of the regions of the input space that are well-solved. The postcompetition analysis, which complements the leaderboard, uses exploratory data analysis and generalized linear models (GLMs). The GLMs not only expand the range of results we can explore, they also provide more detailed analysis of individual subquestions including similarities and differences between algorithms across different types of scenarios, universally easy or hard regions of the input space, and different learning objectives. When coupled with a strategically planned data generation approach, the methods provide richer and more informative summaries to enhance the interpretation of results beyond just the rankings on the leaderboard. The methods are illustrated with a recently completed competition to evaluate algorithms capable of detecting, identifying, and locating radioactive materials in an urban environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Radiographic stool quantification: an equivalence study of 484 symptomatic and asymptomatic subjects

Purpose: To determine if symptomatic patients referred for radiographic stool quantification have equivalent stool burden to asymptomatic patients. Method: This was an IRB-approved HIPAA-compliant retrospective equivalence cohort study. An a priori equivalence power calculation was performed. Consecutive abdominal radiographs performed in adult outpatients with bloating, constipation, diarrhea, or abdominal pain to assess “fecal loading” [n = 242 (fecal cohort)] were compared to those performed in asymptomatic adult outpatients to assess “renal stones” [n = 242 (renal cohort)]. Radiographs were randomized and reviewed by two blinded independent abdominal radiologists. Exclusion criteria, designed to avoid unblinding, included urinary tract calculi ≥ 0.5 cm, multiple urinary tract calculi, and ureteral stent(s). Readers scored all radiographs (n = 484) for stool burden using validated Leech criteria [scale: 0 (none) to 15 (extreme diffuse)]. Mean Leech scores and 95% confidence intervals were calculated. Multivariable generalized linear modeling was performed to adjust for baseline medication use, age, and gender. The adjusted parameter estimate was used to test for equivalence in the mean difference between cohorts using Schuirmann’s method of two one-sided t-tests. Inter-reader agreement was assessed with intraclass correlation coefficients. Results: Overall mean Leech scores for fecal [6.9 (95% CI 6.7, 7.2)] and renal [7.3 (95% CI 7.1, 7.5)] cohorts were equivalent within a margin of 0.75 (adjusted mean difference: − 0.4 [90% CI − 0.7, − 0.04]; p value = 0.02). Inter-reader agreement was good [ICC: 0.62 (95% CI 0.56, 0.68)]. Conclusion: Radiographic stool quantification produces equivalent results in symptomatic and asymptomatic adults and is of uncertain value.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Direct health-care cost of head and neck cancers: a population-based study in north-eastern Italy

Improvements in prognosis of head-and-neck squamous cell carcinoma (HNSCC) have paralleled with an increase in health-care costs, so that an economic evaluation is of growing importance. Presently, most of the evidence is from insurance-based studies in the USA. Between 2007 and 2010, 879 HNSCC patients were identified through the population-based cancer registry of the Friuli Venezia Giulia region, including 266 oral, 187 oropharyngeal, 136 hypopharyngeal, and 290 laryngeal cancers. Health-care costs from diagnosis to treatment initiation and in the following 2 years were retrieved through a record linkage with the regional health data warehouse. This database collected comprehensive health information on all resident citizens. Generalized linear models with a gamma distribution and log-link function were applied to model costs. The average health-care cost from diagnosis up to 2 years after treatment initiation was €20,184 (95% confidence interval: €19,634 − 20,733). Heterogeneity emerged according to cancer site, elective treatment, and retreatment for cancer persistence/recurrence (no: €13,896; yes: €24,599; p < 0.001). An advanced stage was associated with increased costs stage (I: €12,969; II: €18,276; III: €26,229; IV: €25,574; p < 0.001) as the result of treatment complexity and elevated frequency of patients retreatment due to recurrence. These findings further support strategies to diagnose patients at an earlier cancer stage and the accurate definition of diagnostic and treatment pathways, to start treating patients when radical unimodal approach is still feasible. Besides the advantage in prognosis due to timely curative treatments, this would reduce the economic burden of cancer treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Chemical mixture exposure patterns and obesity among U.S. adults in NHANES 2005–2012

The effect of chemical exposure on obesity has raised great concerns. Real-world chemical exposure always imposes mixture impacts, however their exposure patterns and the corresponding associations with obesity have not been fully evaluated. To discover obesity-related mixed chemical exposure patterns in the general U.S. population. Sparse Decompositional Regression (SDR), a model adapted from sparse representation learning technique, was developed to identify exposure patterns of chemical mixtures with exclusion (non-targeted model) and inclusion (targeted model) of health outcomes. We assessed the relationships between the identified chemical mixture patterns and obesity-related indexes. We also conducted a comprehensive evaluation of this SDR model by comparing to the existing models, including generalized linear regression model (GLM), principal component analysis (PCA), and Bayesian kernel machine regression (BKMR). Eight core exposure patterns were identified using the non-targeted SDR model. Patterns of high levels of MEP, high levels of naphthalene metabolites (ΣOH-Nap), and a pattern of high exposure levels of MCOP, MCNP, and MCPP were positively associated with obesity. Patterns of high levels of BP3, and a pattern of higher mixed levels of MPB, PPB, and MEP were found to have negative associations. Associations were strengthened using the targeted SDR model. In the single chemical analysis by GLM, BP3, MBP, PPB, MCOP, and MCNP showed significant associations with obesity or body indexes. The SDR model exceeded the performance of PCA in pattern identification. Both SDR and BKMR identified a positive contribution of ΣOH-Nap and MCOP, as well as a negative contribution of BP3 and PPB to obesity. Our study identified five core exposure patterns of chemical mixtures significantly associated with obesity using the newly developed SDR model. The SDR model could open a new avenue for assessing health effects of environmental mixture contaminants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2010

Hypertension and hematologic parameters in a community near a uranium processing facility

Background: Environmental uranium exposure originating as a byproduct of uranium processing can impact human health. The Fernald Feed Materials Production Center functioned as a uranium processing facility from 1951 to 1989, and potential health effects among residents living near this plant were investigated via the Fernald Medical Monitoring Program (FMMP). Methods: Data from 8216 adult FMMP participants were used to test the hypothesis that elevated uranium exposure was associated with indicators of hypertension or changes in hematologic parameters at entry into the program. A cumulative uranium exposure estimate, developed by FMMP investigators, was used to classify exposure. Systolic and diastolic blood pressure and physician diagnoses were used to assess hypertension; and red blood cells, platelets, and white blood cell differential counts were used to characterize hematology. The relationship between uranium exposure and hypertension or hematologic parameters was evaluated using generalized linear models and quantile regression for continuous outcomes, and logistic regression or ordinal logistic regression for categorical outcomes, after adjustment for potential confounding factors. Results: Of 8216 adult FMMP participants 4187 (51%) had low cumulative uranium exposure, 1273 (15%) had moderate exposure, and 2756 (34%) were in the high (>0.50 Sievert) cumulative lifetime uranium exposure category. Participants with elevated uranium exposure had decreased white blood cell and lymphocyte counts and increased eosinophil counts. Female participants with higher uranium exposures had elevated systolic blood pressure compared to women with lower exposures. However, no exposure-related changes were observed in diastolic blood pressure or hypertension diagnoses among female or male participants. Conclusions: Results from this investigation suggest that residents in the vicinity of the Fernald plant with elevated exposure to uranium primarily via inhalation exhibited decreases in white blood cell counts, and small, though statistically significant, gender-specific alterations in systolic blood pressure at entry into the FMMP.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2020

Results of a fishery-independent longline survey targeting coastal sharks in the eastern Bahamas between 1979 and 2013

Long-term trends in shark abundance offer important insights for fisheries management. Few fisheries-independent, extended time-series data exist for coastal shark species in the northwest Atlantic Ocean or Caribbean outside of the United States. A decades old dataset comprised of standardized longline surveys provided us with the opportunity to characterize diversity and evaluate changes in the relative abundance of sharks in the eastern Bahamas between 1979–1990 and 2011–2013. Caribbean reef sharks Carcharhinus perezi and tiger sharks Galeocerdo cuvier were the two most commonly captured species throughout the survey and were the only two species analyzed in detail. For both species, sex ratios favored females. Using Bayesian generalized linear models, we found that Caribbean reef shark catch-per-unit-effort (CPUE) exhibited a positive relationship with year and temperature, while size exhibited no relationship with year and a negative relationship with temperature. There was no relationship between tiger shark CPUE and year but there was a positive relationship between size and year. These results are presented in the context of Bahamian shark conservation efforts and the results of other surveys in the region.

Fisheries-independent survey, Caribbean reef shark↗
DOE OSTI2011

Development of Late Toxicity and International Prostate Symptom Score Resolution After External-Beam Radiotherapy Combined With Pulsed Dose Rate Brachytherapy for Prostate Cancer

Purpose: To investigate the development of gastrointestinal (GI) toxicity, genitourinary (GU) toxicity, erectile dysfunction, and International Prostate Symptom Score (IPSS) resolution in a cohort of patients treated with external-beam radiotherapy (EBRT) followed by a brachytherapy pulsed dose rate (PDR) boost. Methods and Materials: Between 2002 and 2008, 110 patients were treated with 46-Gy EBRT followed by PDR brachytherapy (24.96-28.80 Gy). The investigated outcome variables, GI toxicity, GU toxicity, erectile dysfunction, and IPSS were prospectively scored at several time points during follow-up. Association between time (as continuous and categorical variable) and the outcome variables was assessed using generalized linear models. Results: No statistically significant association was found between time (continuous) and GI toxicity (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.89-1.06), GU toxicity (OR, 0.97; 95% CI, 0.91-1.03), erectile dysfunction (OR, 1.06; 95% CI, 0.99-1.11), and IPSS (-0.11; 95% CI, -0.41-0.20). Also, no statistically significant association was found between these variables and time as a categorical variable. GU toxicity was associated with IPSS resolution (OR, 1.16; 95% CI, 1.09-1.24). Posttreatment IPSS was associated with pretreatment IPSS (0.52; 95% CI, 0.25-0.79). Conclusions: No accumulation of high-grade toxicity over time could be established for a group of patients treated with EBRT and PDR brachytherapy for prostate cancer, probably because high-grade late toxicity resolves with time. Also, differences in IPSS values among patients are smaller after treatment than before treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Correlation Between Radiation Dose to {sup 18}F-FDG-PET Defined Active Bone Marrow Subregions and Acute Hematologic Toxicity in Cervical Cancer Patients Treated With Chemoradiotherapy

Purpose: To test the hypothesis that radiation dose to {sup 18}F-fluorodeoxyglucose positron emission tomography ({sup 18}F-FDG-PET)-defined active bone marrow (BM{sub ACT}) subregions is correlated with hematologic toxicity in cervical cancer patients treated with chemoradiotherapy. Methods and Materials: The conditions of 26 women with cervical cancer who underwent {sup 18}F-FDG-PET before treatment with concurrent cisplatin and intensity-modulated radiation therapy were analyzed. BM{sub ACT} was defined as the subregion of total bone marrow (BM{sub TOT}) with a standardized uptake value (SUV) equal to or above the mean for that individual. Inactive bone marrow (BM{sub INACT}) was defined as BM{sub TOT} - BM{sub ACT}. Generalized linear modeling was used to test the correlation between BM{sub ACT} and BM{sub INACT} dose-volume metrics and hematologic nadirs, particularly white blood cell count (WBC) and absolute neutrophil count (ANC). Results: Increased BM{sub ACT} mean dose was significantly associated with decreased log(WBC) nadir ({beta} = -0.04; 95% CI, -0.07to -0.01; p = 0.009), decreased log(ANC) nadir ({beta} = -0.05; 95% CI, -0.08 to -0.02; p = 0.006), decreased hemoglobin nadir ({beta} = -0.16; 95% CI, -0.27 to -0.05; p = 0.010), and decreased platelet nadir ({beta} = -6.16; 95% CI, -9.37 to -2.96; p < 0.001). By contrast, there was no association between BM{sub INACT} mean dose and log(WBC) nadir ({beta} = -0.01; 95% CI, -0.06 to 0.05; p = 0.84), log(ANC) nadir ({beta} = -0.03; 95% CI, -0.10 to 0.04; p = 0.40), hemoglobin nadir ({beta} = -0.09; 95% CI, -0.31 to 0.14; p = 0.452), or platelet nadir ({beta} = -3.47; 95% CI, -10.44 to 3.50; p = 0.339). Conclusions: Irradiation of BM subregions with higher {sup 18}F-FDG-PET activity was associated with hematologic toxicity, supporting the hypothesis that reducing dose to BM{sub ACT} subregions could mitigate hematologic toxicity. Future investigation should seek to confirm these findings and to identify optimal SUV thresholds to define BM{sub ACT}.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Corticosteroid therapy and airflow obstruction influence the bronchial microbiome, which is distinct from that of bronchoalveolar lavage in asthmatic airways

The lung has a diverse microbiome that is modest in biomass. This microbiome differs in asthmatic patients compared with control subjects, but the effects of clinical characteristics on the microbial community composition and structure are not clear. OBJECTIVES: We examined whether the composition and structure of the lower airway microbiome correlated with clinical characteristics of chronic persistent asthma, including airflow obstruction, use of corticosteroid medications, and presence of airway eosinophilia. METHODS: DNA was extracted from endobronchial brushings and bronchoalveolar lavage fluid collected from 39 asthmatic patients and 19 control subjects, along with negative control samples. 16S rRNA V4 amplicon sequencing was used to compare the relative abundance of bacterial genera with clinical characteristics. RESULTS: Differential feature selection analysis revealed significant differences in microbial diversity between brush and lavage samples from asthmatic patients and control subjects. Lactobacillus, Pseudomonas, and Rickettsia species were significantly enriched in samples from asthmatic patients, whereas Prevotella, Streptococcus, and Veillonella species were enriched in brush samples from control subjects. Generalized linear models on brush samples demonstrated oral corticosteroid use as an important factor affecting the relative abundance of the taxa that were significantly enriched in asthmatic patients. In addition, bacterial α-diversity in brush samples from asthmatic patients was correlated with FEV1 and the proportion of lavage eosinophils. CONCLUSION: The diversity and composition of the bronchial airway microbiome of asthmatic patients is distinct from that of nonasthmatic control subjects and influenced by worsening airflow obstruction and corticosteroid use. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

16S ribosomal RNA↗
DOE OSTI2018

A stochastic downscaling approach for generating high-frequency solar irradiance scenarios

Solar power is increasingly cost viable with solar photovoltaic (PV) installations becoming commonplace. PV planning and operational studies, however, require high-frequency solar irradiance scenarios to understand potential electric grid impacts due to the variability and uncertainty of the underlying solar resource. Existing remote sensing solar data products are often available over large spatial domains, but are limited in temporal resolution. For example, the global horizontal irradiance (GHI) component contained within the National Solar Radiation Database (NSRDB) is available at time resolution of 30 min on an approximately four-kilometer grid. In contrast, substantial solar variability is present at finer time scales and this article describes an algorithm to stochastically generate one-minute GHI from widely available sub-hourly NSRDB. A generalized linear modeling (GLM) framework is proposed, which includes non-Gaussian mixtures, and extends the literature involving the synthesis of GHI data. The model is trained on a set of sample locations around Oregon, USA, and validated across the USA using both the Surface Radiation Budget Network (SURFRAD) dataset and Solar Radiation Monitoring Laboratory (SRML) network. Simulated ensembles show good coverage properties and temporal correlation structure. The resulting downscaled ensembles allow for understanding the unpredictable variability inherent in GHI at locations without direct measurements. Here, future work can leverage the algorithm as part of a stochastic optimization of electric grid operations with high-penetration PV systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Compound Drought and Heatwaves at a Global Scale: The Role of Natural Climate Variability-Associated Synoptic Patterns and Land-Surface Energy Budget Anomalies

Compound drought and heatwave (CDHW) events have garnered much attention in recent studies. However, thus far, the identification of such events is oversimplified, and their association with natural climate variability is not fully explored. Here, we derive anomalies in the weekly self-calibrated Palmer Drought Severity Index (sc_PDSI) and daily maximum temperatures to identify CDHW events from 1982 to 2016 over 26 climate regions across the globe. Using a Poisson Generalized Linear Model (GLM), we analyze yearly occurrences of seasonal CDHW events and their association with the warm and cold phases of El Nino Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO). ENSO exhibits robust association with CDHW events over the Southern Hemisphere during the austral summer and fall, while PDO influences their occurrences over the Western North America in the Northern Hemisphere during the boreal summer, which is supported by the composites of anomalies in the atmospheric circulations and surface energy budget. However, NAO association with CDHW events is relatively weak. The CDHW occurrence over other regions is driven by a combination of these large-scale natural forcing. Our analyses also highlight that the cooccurrence of weekly to submonthly scale anomalies in the observed temperature and precipitation may not be always aligned between the observations and the reanalysis. Therefore, caution must be exercised while explaining such observed anomalies on the basis of reanalysis-based circulations and surface energy budget. Lastly, our analyses provide a new insight towards concurrent extremes and should help foster research efforts in this area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Linking Hydrology and Dissolved Organic Matter Characteristics in a Subtropical Wetland: A Long-Term Study of the Florida Everglades

Dissolved organic matter (DOM) acts as an important biogeochemical component of aquatic ecosystems that controls nutrient cycling, influences water quality, and links terrestrial and oceanic carbon pools, yet long-term studies of how changing environmental drivers alter its abundance and composition are rare. Using a ten-year, spatially explicit dataset from Everglades National Park (ENP), a globally significant wetland, we investigated the relationships between DOM quality/quantity and hydrologic/climatic drivers along two contrasting marsh-estuarine transects based on generalized linear modeling and a cumulative sums analysis. Analyses revealed distinct spatial, seasonal, and interannual patterns in variability of DOC and optical properties. Landscape-scale seasonal patterns showed an enrichment in microbial-like and protein-like DOM during the dry season relative to the wet season. We found that, while some compositional constituents varied with the solar calendar, responsive to temperature and photoperiod, others varied with the hydrologic calendar. Independent water level and discharge effects indicated strong hydrologic control on DOM quality that differed between the two transects, evidencing differences in their connectivity to areas of high agricultural activity. Across all sites, a significant long-term increasing trend in the fluorescence index was observed, associated with a positive correlation with precipitation and also potential changes in agricultural inputs, with other features associated with drought and hurricanes. Lastly, the cumulative sums analysis revealed differences between the two transects in the sensitivity of DOM composition to decreased water levels associated with 30-year climate scenarios, with the less hydrologically dynamic transect exhibiting greater potential sensitivity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Lactobacillus rhamnosus GG-supplemented formula expands butyrate-producing bacterial strains in food allergic infants

Dietary intervention with extensively hydrolyzed casein formula supplemented with Lactobacillus rhamnosus GG (EHCF+LGG) accelerates tolerance acquisition in infants with cow’s milk allergy (CMA). We examined whether this effect is attributable, at least in part, to an influence on the gut microbiota. Fecal samples from healthy controls ( n =20) and from CMA infants ( n =19) before and after treatment with EHCF with ( n =12) and without ( n =7) supplementation with LGG were compared by 16S rRNA-based operational taxonomic unit clustering and oligotyping. Differential feature selection and generalized linear model fitting revealed that the CMA infants have a diverse gut microbial community structure dominated by Lachnospiraceae (20.5±9.7%) and Ruminococcaceae (16.2±9.1%). Blautia, Roseburia and Coprococcus were significantly enriched following treatment with EHCF and LGG, but only one genus, Oscillospira , was significantly different between infants that became tolerant and those that remained allergic. However, most tolerant infants showed a significant increase in fecal butyrate levels, and those taxa that were significantly enriched in these samples, Blautia and Roseburia , exhibited specific strain-level demarcations between tolerant and allergic infants. As a result, our data suggest that EHCF+LGG promotes tolerance in infants with CMA, in part, by influencing the strain-level bacterial community structure of the infant gut.

59 BASIC BIOLOGICAL SCIENCES↗