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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Current measurements in the intermittent-contact mode of atomic force microscopy using the Fourier method: a feasibility analysis

Atomic force microscopy (AFM) is an important tool for measuring a variety of nanoscale surface properties, such as topography, viscoelasticity, electrical potential and conductivity. Some of these properties are measured using contact methods (static contact or intermittent contact), while others are measured using noncontact methods. Some properties can be measured using different approaches. Conductivity, in particular, is mapped using the contact-mode method. However, this modality can be destructive to delicate samples, since it involves continuously dragging the cantilever tip on the surface during the raster scan, while a constant tip–sample force is applied. In this paper we discuss a possible approach to develop an intermittent-contact conductive AFM mode based on Fourier analysis, whereby the measured current response consists of higher harmonics of the cantilever oscillation frequency. Such an approach may enable the characterization of soft samples with less damage than contact-mode imaging. To explore its feasibility, we derive the analytical form of the tip–sample current that would be obtained for attractive (noncontact) and repulsive (intermittent-contact) dynamic AFM characterization, and compare it with results obtained from numerical simulations. Although significant instrumentation challenges are anticipated, the modelling results are promising and suggest that Fourier-based higher-harmonics current measurement may enable the development of a reliable intermittent-contact conductive AFM method.

14 SOLAR ENERGY↗
DOE OSTI2025

Single-nuclei transcriptome analysis of IgM+ cells isolated from channel catfish (Ictalurus punctatus) spleen

Catfish production is the primary aquaculture sector in the United States, and the key cultured species is channel catfish (Ictalurus punctatus). The major causes of production losses are pathogenic diseases, and the spleen, an important site of adaptive immunity, is implicated in these diseases. To examine the channel catfish immune system, single-nuclei transcriptomes of sorted and captured IgM + cells were produced from adult channel catfish. Three channel catfish (~1 kg) were euthanized, the spleen dissected, and the tissue dissociated. The lymphocytes were isolated using a Ficoll gradient and IgM + cells were then sorted with flow cytometry. The IgM + cells were lysed and single-nuclei libraries generated using a Chromium Next GEM Single Cell 3’ GEM Kit and the Chromium X Instrument (10x Genomics) and sequenced with the Illumina NovaSeq X Plus sequencer. The reads were aligned to theI. punctatusreference assembly (Coco_2.0) using Cell Ranger, and normalization, cluster analysis, and differential gene expression analysis were carried out with Seurat. Across the three samples, approximately 753.5 million reads were generated for 18,686 cells. After filtering, 10,637 cells remained for the cluster analysis. The cluster analysis identified 16 clusters which were classified as B cells (10,276), natural killer-like (NK-like) cells (178), T cells or natural killer cells (45), hematopoietic stem and progenitor cells (HSPC)/megakaryocytes (MK) (66), myeloid/epithelial cells (40), and plasma cells (32). The B cell clusters were further defined as different populations of mature B cells, cycling B cells, and plasma cells. The plasma cells highly expressedighmand we demonstrated that the secreted form of the transcript was largely being expressed by these cells. This atlas provides insight into the gene expression of IgM + immune cells in channel catfish. The atlas is publicly available and could be used garner more important information regarding the gene expression of splenic immune cells.

Immunology↗
DOE OSTI2023

A multiscale landscape approach for prioritizing river and stream protection and restoration actions

River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Regional climate change projections from NA-CORDEX and their relation to climate sensitivity

Abstract The climate sensitivity of global climate models (GCMs) strongly influences projected climate change due to increased atmospheric carbon dioxide. Reasonably, the climate sensitivity of a GCM may be expected to affect dynamically downscaled projections. However, there has been little examination of the effect of the climate sensitivity of GCMs on regional climate model (RCM) ensembles. Therefore, we present projections of temperature and precipitation from the ensemble of projections produced as a part of the North American branch of the international Coordinated Regional Downscaling Experiment (NA-CORDEX) in the context of their relationship to the climate sensitivity of their parent GCMs. NA-CORDEX simulations were produced at 50-km and 25-km resolutions with multiple RCMs which downscaled multiple GCMs that spanned nearly the full range of climate sensitivity available in the CMIP5 archive. We show that climate sensitivity is a very important source of spread in the NA-CORDEX ensemble, particularly for temperature. Temperature projections correlate with driving GCM climate sensitivity annually and seasonally across North America not only at a continental scale but also at a local-to-regional scale. Importantly, the spread in temperature projections would be reduced if only low, mid, or high climate sensitivity simulations were considered, or if only the ensemble mean were considered. Precipitation projections correlate with climate sensitivity, but only at a continental scale during the cold season, due to the increasing influence of other processes at finer scales. Additionally, it is shown that the RCMs do alter the projection space sampled by their driving GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Risk Assessment of Hydrogen Fuel Cell Electric Vehicles in Tunnels

The need to understand the risks and implications of traffic incidents involving hydrogen fuel cell electric vehicles in tunnels is increasing in importance with higher numbers of these vehicles being deployed. A risk analysis was performed to capture potential scenarios that could occur in the event of a crash and provide a quantitative calculation for the probability of each scenario occurring, with a qualitative categorization of possible consequences. The risk analysis was structured using an event sequence diagram with probability distributions on each event in the tree and random sampling was used to estimate resulting probability distributions for each end-state scenario. Here, the most likely consequence of a crash is no additional hazard from the hydrogen fuel (98.1–99.9% probability) beyond the existing hazards in a vehicle crash, although some factors need additional data and study to validate. These scenarios include minor crashes with no release or ignition of hydrogen. When the hydrogen does ignite, it is most likely a jet flame from the pressure relief device release due to a hydrocarbon fire (0.03–1.8% probability). This work represents a detailed assessment of the state-of-knowledge of the likelihood associated with various vehicle crash scenarios. This is used in an event sequence framework with uncertainty propagation to estimate uncertainty around the probability of each scenario occurring.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

An approach to nearest neighbor analysis of pigment-protein complexes using chemical cross-linking in combination with mass spectrometry

Herein, protein cross-linking is the process of chemically joining two amino acids in a protein or protein complex by a covalent bond. When combined with mass spectrometry, it becomes one of the structural mass spectrometry techniques gaining in importance for deriving valuable three-dimensional structural information on proteins and protein complexes. This platform complements existing structural methods, such as NMR spectroscopy, X-ray crystallography, and cryo-EM. Photosynthetic pigment protein complexes serve as light-energy harvesting systems and perform photochemical conversion as part of the “early events” of photosynthesis. This chapter outlines how to prepare cross-linking pigment protein complex samples for LC-MS/MS analysis, including identification of the cross-linked species, network analysis in a protein complex, and structural modeling and justification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Strong effect of liquid Fe–S on elastic wave velocity of olivine aggregate: Implication for the low velocity anomaly at the base of the lunar mantle

The origin of the seismic low velocity zone (LVZ) observed at the base of the lunar mantle is important for understanding the nature of the lunar mantle. Liquid Fe–S is considered as a possible candidate of the cause of the LVZ. However, effect of liquid Fe–S on elastic wave velocity of mantle rock has been considered to be minor, according to theoretical estimation based on the high dihedral angle of liquid Fe–S in olivine aggregate observed in previous microstructural analysis of polished sample cross sections. Here, in this work, we carry out direct measurements of elastic wave velocities of liquid Fe–S-bearing olivine aggregate and report strong reduction of the elastic wave velocities in the presence of liquid Fe–S. The effects of liquid Fe–S in olivine aggregates are much more pronounced than the theoretical estimation. Three-dimensional X-ray microtomography analysis reveals that the geometry of liquid Fe–S strongly depends on the size, with larger liquid Fe–S blobs having low aspect ratios, which may predominantly affect elastic wave velocity. Since smaller spherical Fe–S blobs are much more abundant than the larger elongated blobs, conventional dihedral angle analyses based on scanning electron microscope images tend to statistically over-sample smaller blobs and under-sample larger blobs. Our results suggest that the LVZ at the base of the lunar mantle can be explained by the presence of 4.3–5.0 vol.% liquid Fe–S. The LVZ may be a hidden reservoir of highly siderophile elements (HSEs), which may explain the low abundance of HSEs in the lunar mantle compared to the Earth.

58 GEOSCIENCES↗
DOE OSTI2021

Confined Ni-In intermetallic alloy nanocatalyst with excellent coking resistance for methane dry reforming

Carbon dioxide and methane are two main greenhouse gases which are contributed to serious global warming. Fortunately, dry reforming of methane (DRM), a very important reaction developed decades ago, can convert these two major greenhouse gases into value-added syngas or hydrogen. The main problem retarding its industrialization is the seriously coking formation upon the nickel-based catalysts. Herein, a series of confined indium-nickel (In-Ni) intermetallic alloy nanocatalysts (In x Ni@SiO 2 ) have been prepared and displayed superior coking resistance for DRM reaction. The sample containing 0.5 wt.% of In loading (In 0.5 Ni@SiO 2 ) shows the best balance of carbon deposition resistance and DRM reactivity even after 430 h long term stability test. The boosted carbon resistance can be ascribed to the confinement of core–shell structure and to the transfer of electrons from Indium to Nickel in In-Ni intermetallic alloys due to the smaller electronegativity of In. Additionally, both the silica shell and the increase of electron cloud density on metallic Ni can weaken the ability of Ni to activate C–H bond and decrease the deep cracking process of methane. The reaction over the confined InNi intermetallic alloy nanocatalyst was conformed to the Langmuir-Hinshelwood (L-H) mechanism revealed by in situ diffuse reflectance infrared Fourier transform spectroscopy (in-situ DRIFTS). This work provides a guidance to design high performance coking resistance catalysts for methane dry reforming to efficiently utilize these two main greenhouse gases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

On the product phases and the reaction kinetics of carbothermic reduction of UO 2 +C at relatively low temperatures

The synthesis of UC using carbothermic reduction of UO 2 and C mixtures has been well studied at high temperatures. However, the product phase behavior of carbothermic reduction at low temperatures (≤1773 K) is not well studied. Such a study is important as low temperatures permit single phase UC synthesis without forming secondary higher carbides, and it further supports the knowledge base of the process that needs to be used for transuranic elements such as plutonium that have high vapor pressures at elevated temperatures. Therefore, a low temperature carbothermic reduction of two different C/UO 2 molar ratios under inert and reducing environments have been studied here. Two different sample holding crucibles, alumina (Al 2 O 3 ) and graphite, were also used here to differentiate the hypostoichiometric (UC 1-a ) and oxygen dissolved (UC 1-x O x ) uranium monocarbide phases adding more details on the two systems. Also, the reaction kinetics involved in the formation of UC via the carbothermic reduction of UO 2 +C using product phases instead of evolved gases such as carbon monoxide is reported here. Under inert atmospheres but with significant oxygen partial pressures, the low temperature carbothermic reduction of UO 2 +C produced up to 90 wt.% UC 1-x O x type oxycarbides as was confirmed by Xray powder diffraction. Reducing Ar-4%H 2 environments at these temperatures were not successful in synthesizing UC as it reduces the amount of C required for the carbothermic reduction, leaving UC phase at a non-equilibrium state. Inert atmospheres with low or negligible oxygen partial pressures on the other hand produced near stoichiometric UC at high phase purity, especially at 1673 – 1773 K temperature range. An activation energy of 377±75 kJmol -1 was also calculated using product phase concentrations of the carbothermic reduction of UO 2 +C under these inert Ar (g) atmospheres.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A variance deconvolution estimator for efficient uncertainty quantification in Monte Carlo radiation transport applications

Monte Carlo simulations are at the heart of many high-fidelity simulations and analyses for radiation transport systems. As is the case with any complex computational model, it is important to propagate sources of input uncertainty and characterize how they affect model output. Unfortunately, uncertainty quantification (UQ) is made difficult by the stochastic variability that Monte Carlo transport solvers introduce. The standard method to avoid corrupting the UQ statistics with the transport solver noise is to increase the number of particle histories, resulting in very high computational costs. In this contribution, we propose and analyze a sampling estimator based on the law of total variance to compute UQ variance even in the presence of residual noise from Monte Carlo transport calculations. Here, we rigorously derive the statistical properties of the new variance estimator, compare its performance to that of the standard method, and demonstrate its use on neutral particle transport model problems involving both attenuation and scattering physics. We illustrate, both analytically and numerically, the estimator’s statistical performance as a function of available computational budget and the distribution of that budget between UQ samples and particle histories. We show analytically and corroborate numerically that the new estimator is unbiased, unlike the standard approach, and is more accurate and precise than the standard estimator for the same computational budget.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Spatial variability of aerosol iron mineralogy and oxidation states over the Arctic Ocean

The mineralogy and oxidation state of aerosol iron (Fe) play important roles in controlling aerosol Fe solubility and consequent bioavailability in seawater. In this study, the spatial variability of Fe mineralogy and oxidation states in aerosols collected during the US GEOTRACES Western Arctic cruise (GN01) were determined using synchrotronbased X-ray absorption near edge structure (XANES) spectroscopy. Both Fe(II) minerals (biotite, ilmenite) and Fe (III) minerals (ferrihydrite, hematite, Fe(III) phosphate) were found in these samples. However, aerosol Fe mineralogy and solubility observed during this cruise varied spatially and can be grouped into three clusters based on the air masses that affected aerosols collected in different regions: (1) biotite-enriched particles (87 % biotite, 13 % hematite) with the air masses passing over Alaska, showing relatively low Fe solubility (4.0 +/- 1.7 %); (2) ferrihydrite-enriched particles (82 % ferrihydrite, 18 % ilmenite) collected in the remote Arctic air, showing relatively high Fe solubility (9.6 +/- 3.3 %); (3) the fresh dust derived from North America and Siberia, primarily dominated by hematite (41 % hematite, 25 % Fe(III) phosphate, 20 % biotite, 13 % ferrihydrite), showing relatively low Fe solubility (5.1 +/- 3.5). A significant positive correlation was found between Fe oxidation state and Fe fractional solubility, suggesting that long-range transport could modify iron (hydr) oxide such as ferrihydrite through atmospheric processing, influencing aerosol Fe solubility and consequently Fe bioavailability in the remote Arctic Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Molecular Characterization of Organophosphorus Compounds in Wildfire Smoke Using 21-T Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry

Here, we present a detailed molecular characterization of organophosphorus compounds in ambient organic aerosol influenced by wildfire smoke. Biomass burning organic aerosol (BBOA) is an important source of phosphorus (P) to surface waters, where even a small imbalance in the P flux can lead to substantial effects on water quality, such as eutrophication, algal blooms, and oxygen depletion. We aimed to exploit the ultrahigh resolving power, mass accuracy, and sensitivity of Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR MS) to explore the molecular composition of an ambient BBOA sample collected downwind of Pacific Northwest wildfires. The 21-T FT-ICR MS yielded 10533 distinct formulae, which included molecular species comprising C, H, O, and P with or without N, i.e., organophosphorus compounds that have long been quantified in wildfire smoke but have not yet been characterized at the molecular level. The lack of detailed molecular characterization of organophosphorus compounds in BBOA is primarily due to their inherently low concentrations in aerosols and poor ionization efficiency in complex mixtures. We demonstrate that the exceptional sensitivity of the 21-T FT-ICR MS allows qualitative analysis of a previously uncharacterized fraction of BBOA without its selective concentration from the organic matrix, exemplifying the need for ultrahigh-resolution tools for a more detailed and accurate molecular depiction of such complex mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A global soil plasmidome resource unveils functional and ecological roles of plasmids in soil microbiomes

Plasmids play significant roles in microbial adaptation to ecosystems, yet their dynamics remain poorly understood due to identification challenges. We present the Global Soil Plasmidome Resource (GSPR), a comprehensive dataset of 98,728 plasmid sequences amassed from 6860 terrestrial microbial communities and isolates. We explore this resource through various computational approaches, including phylogenetic diversity analysis, host prediction, and extensive functional annotation, to understand the contribution of plasmids to the genetic and functional diversity in soil, correlating these findings with sample type, as well as the soil habitat they were retrieved from. Our analysis reveals insights into plasmid-encoded functions such as effector modules, quorum sensing, and stress resistance, which may contribute to their persistence and microbial adaptation in soil. Furthermore, CRISPR analysis suggests a prevalent role of these elements related to intra-plasmid competition. By contrasting plasmids from cultivated and uncultivated organisms, we identify important functions that expand existing knowledge of plasmid roles in these habitats. This study represents a notable step forward in elucidating plasmid diversity and function within soil microbiomes and establishes a foundational framework for exploring their roles in natural environments.

Fiamenghi, Mateus B↗
DOE OSTI2023

BeyondPlanck: XII. Cosmological parameter constraints with end-to-end error propagation

We present cosmological parameter constraints estimated using the Bayesian BEYONDPLANCK analysis framework. This method supports seamless end-to-end error propagation from raw time-ordered data onto final cosmological parameters. As a first demonstration of the method, we analyzed time-ordered Planck LFI observations, combined with selected external data (WMAP 33–61 GHz, Planck HFI DR4 353 and 857 GHz, and Haslam 408 MHz) in the form of pixelized maps that are used to break critical astrophysical degeneracies. Overall, all the results are generally in good agreement with previously reported values from Planck 2018 and WMAP, with the largest relative difference for any parameter amounting about 1σ when considering only temperature multipoles between 30 ≤ ℓ ≤ 600. In cases where there are differences, we note that the BEYONDPLANCK results are generally slightly closer to the high-ℓ HFI-dominated Planck 2018 results than previous analyses, suggesting slightly less tension between low and high multipoles. Using low-ℓ polarization information from LFI and WMAP, we find a best-fit value of τ = 0.066 ± 0.013, which is higher than the low value of τ = 0.052 ± 0.008 derived from Planck 2018 and slightly lower than the value of 0.069 ± 0.011 derived from the joint analysis of official LFI and WMAP products. Most importantly, however, we find that the uncertainty derived in the BEYONDPLANCK processing is about 30 % greater than when analyzing the official products, after taking into account the different sky coverage. We argue that this uncertainty is due to a marginalization over a more complete model of instrumental and astrophysical parameters, which results in more reliable and more rigorously defined uncertainties. We find that about 2000 Monte Carlo samples are required to achieve a robust convergence for a low-resolution cosmic microwave background (CMB) covariance matrix with 225 independent modes, and producing these samples takes about eight weeks on a modest computing cluster with 256 cores.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Phosphorus chemistry in plant charcoal: interplay between biomass composition and thermal condition

Background Vegetation fire may change Phosphorus (P) cycling in terrestrial ecosystems through converting biomass into fire residues. Aim The aim of this study was to understand the chemistry and mobility of P in fire residues to help reveal P thermochemistry during biomass burning and post-fire P cycling. Methods A combination of sequential extraction, liquid 31P NMR and P K-edge XANES was used to obtain quantitative P speciation and explain P solubilisation behaviours of charcoal. Key results Despite varying diverse P species existing in raw biomass, only two P structural moieties – orthophosphate and pyrophosphate – were identified in charcoal. However, relative abundance of pyrophosphate differs greatly among charcoal samples from different biomass types, ranging between 0 and 40% of total extractable P. Although P K-edge XANES data indicates abundant soluble phosphate minerals, most P (70–90%) is likely occluded physically in the charcoal. The bicarbonate-extractable P (the Olsen-P) varies significantly and cannot be explained by surface P concentration or elemental stoichiometry alone. Conclusion and implications The results suggest the importance of starting biomass P speciation (i.e. molecular structure and complexation environment) and thermal conditions in controlling P speciation and availability in charcoal. The different P chemistry between charcoal and ash suggests the importance of fire types and severity in disturbing the P cycle.

Forestry↗
DOE OSTI2020

The Adaptive Potential of the Middle Domain of Yeast Hsp90

Abstract The distribution of fitness effects (DFEs) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the distribution of fitness effects of the same ≈2,300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase–chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client-binding interfaces, or residues that are involved in ATPase–chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information.

Cote-Hammarlof, Pamela A.↗
DOE OSTI2024

RhizoMAP: a comprehensive, nondestructive, and sensitive platform for metabolic imaging of the rhizosphere

Elucidating the intricate structural organization and spatial gradients of biomolecular composition within the rhizosphere is critical to understanding important biogeochemical processes, which include the mechanisms of root-microbe interactions for maintaining sustainable plant ecosystem services. While various analytical methods have been developed to assess the spatial heterogeneity within the rhizosphere, a comprehensive view of the fine distribution of metabolites within the root-soil interface has remained a significant challenge. This is primarily due to the difficulty of maintaining the original spatial organization during sample preparation without compromising its molecular content.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study

Internet data can be used to improve infectious disease models. However, the representativeness and individual-level validity of internet-derived measures are largely unexplored as this requires ground truth data for study. This study sought to identify relationships between Web-based behaviors and/or conversation topics and health status using a ground truth, survey-based dataset. This study leveraged a unique dataset of self-reported surveys, microbiological laboratory tests, and social media data from the same individuals toward understanding the validity of individual-level constructs pertaining to influenza-like illness in social media data. Logistic regression models were used to identify illness in Twitter posts using user posting behaviors and topic model features extracted from users’ tweets. Of 396 original study participants, only 81 met the inclusion criteria for this study. Of these participants’ tweets, we identified only two instances that were related to health and occurred within 2 weeks (before or after) of a survey indicating symptoms. It was not possible to predict when participants reported symptoms using features derived from topic models (area under the curve [AUC]=0.51; P=.38), though it was possible using behavior features, albeit with a very small effect size (AUC=0.53; P≤.001). Individual symptoms were also generally not predictable either. The study sample and a random sample from Twitter are predictably different on held-out data (AUC=0.67; P≤.001), meaning that the content posted by people who participated in this study was predictably different from that posted by random Twitter users. Individuals in the random sample and the GoViral sample used Twitter with similar frequencies (similar @ mentions, number of tweets, and number of retweets; AUC=0.50; P=.19). To our knowledge, this is the first instance of an attempt to use a ground truth dataset to validate infectious disease observations in social media data. The lack of signal, the lack of predictability among behaviors or topics, and the demonstrated volunteer bias in the study population are important findings for the large and growing body of disease surveillance using internet-sourced data.

59 BASIC BIOLOGICAL SCIENCES↗