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.

Children with congenital heart disease (CHD) can face neurodevelopmental, psychological, and behavioural difficulties beginning in infancy and continuing through adulthood. Despite overall improvements in medical care and a growing focus on neurodevelopmental screening and evaluation in recent years, neurodevelopmental disabilities, delays, and deficits remain a concern. The Cardiac Neurodevelopmental Outcome Collaborative was founded in 2016 with the goal of improving neurodevelopmental outcomes for individuals with CHD and pediatric heart disease. This paper describes the establishment of a centralised clinical data registry to standardize data collection across member institutions of the Cardiac Neurodevelopmental Outcome Collaborative. The goal of this registry is to foster collaboration for large, multi-centre research and quality improvement initiatives that will benefit individuals and families with CHD and improve their quality of life. We describe the components of the registry, initial research projects proposed using data from the registry, and lessons learned in the development of the registry.

We present new data from the debris-rich basal ice layers of the NEEM ice core (NW Greenland). Using mineralogical observations, SEM imagery, geochemical data from silicates (meteoric 10Be, εNd, 87Sr/86Sr) and organic material (C/N, δ13C), we characterize the source material, succession of previous glaciations and deglaciations and the paleoecological conditions during ice-free episodes. Meteoric 10Be data and grain features indicate that the ice sheet interacted with paleosols and eroded fresh bedrock, leading to mixing in these debris-rich ice layers. Our analysis also identifies four successive stages in NW Greenland: (1) initial preglacial conditions, (2) glacial advance 1, (3) glacial retreat and interglacial conditions and (4) glacial advance 2 (current ice-sheet development). C/N and δ13C data suggest that deglacial environments favored the development of tundra and taiga ecosystems. These two successive glacial fluctuations observed at NEEM are consistent with those identified from the Camp Century core basal sediments over the last 3 Ma. Further inland, GRIP and GISP2 summit sites have remained glaciated more continuously than the western margin, with less intense ice-substratum interactions than those observed at NEEM.

Precision Medicine is an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle. Autoimmune diseases are those in which the body’s natural defense system loses discriminating power between its own cells and foreign cells, causing the body to mistakenly attack healthy tissues. These conditions are very heterogeneous in their presentation and therefore difficult to diagnose and treat. Achieving precision medicine in autoimmune diseases has been challenging due to the complex etiologies of these conditions, involving an interplay between genetic, epigenetic, and environmental factors. However, recent technological and computational advances in molecular profiling have helped identify patient subtypes and molecular pathways which can be used to improve diagnostics and therapeutics. This review discusses the current understanding of the disease mechanisms, heterogeneity, and pathogenic autoantigens in autoimmune diseases gained from genomic and transcriptomic studies and highlights how these findings can be applied to better understand disease heterogeneity in the context of disease diagnostics and therapeutics.

OBJECTIVES/GOALS: The effect of immunosuppressive metabolites on anti-tumor immunity in human papillomavirus (HPV)-associated vs carcinogen-driven head and neck cancer is unknown. The objective of this study is to define the extent to which metabolites impair this response and identify novel metabolic targets for enhancing anti-tumor immunity. METHODS/STUDY POPULATION: HPV-associated and carcinogen-driven head and neck squamous cell carcinoma specimens were frozen following surgical excision, and tumor sections were cut onto glass slides. Slides were coated in alpha-cyano-4-hydroxy-cinnamic acid (CHCA) matrix and subjected to mass spectrometry imaging using matrix-assisted laser desorption ionization (MALDI) on a Bruker SolariX XR 12T Hybrid QqFT-ICR mass spectrometer run in positive mode. Slides were then stained for immunohistochemistry (IHC) using markers of CD8 T cells, macrophages (CD163), B cells (CD20), and tumor cells (panCK). Mass spectrometry imaging and IHC spatially resolved data will be co-registered and metabolite intensity in regions of interest (cell types) quantified. RESULTS/ANTICIPATED RESULTS: A total of seven HPV-associated (three metastatic lymph nodes and four primary tumors) and six carcinogen-driven (primary tumors) HNSC specimens were subjected to MALDI and IHC. Metabolites significantly enriched in HPV-associated HNSC relative to carcinogen-driven HNSC include 2,3-diphosphoglyceric acid, xanthine, 2,3,5-Trichloromaleylacetate, and indole-3-carboxyaldehyde. Metabolites significantly enriched in carcinogen-driven HNSC relative to HPV-associated HNSC include hesperetin 3'-O-sulfate, hypoxanthine, phosphorylcholine, and L-homocysteine sulfonic acid. In ongoing analyses, we anticipate identifying a relationship between CD8+ T cell enriched vs depleted regions and immunosuppressive metabolites (e.g., kynurenine, adenosine monophosphate). DISCUSSION/SIGNIFICANCE: Defining the extent to which CD8+ T cells interact with the metabolic milieu of the microenvironment will provide a foundation for metabolic Precision Medicine. Strategically targeting metabolic pathways to enhance the anti-tumor immune response will be leveraged for the design and implementation of immune modulatory metabolic therapy.

Although post-error slowing and the “hot hand” (streaks of good performance) are both types of sequential dependencies arising from the differential influence of success and failure, they have not previously been studied together. We bring together these two streams of research in a task where difficulty can be controlled by participants delaying their decisions, and where responses required a degree deliberation, and so are relatively slow. We compared performance of unpaid participants against paid participants who were rewarded differentially, with higher reward for better performance. In contrast to most previous results, we found no post-error slowing for paid or unpaid participants. For the unpaid group, we found post-error speeding and a hot hand, even though the hot hand is typically considered a fallacy. Our results suggest that the effect of success and failure on subsequent performance may differ substantially with task characteristics and demands. We also found payment affected post-error performance; financially rewarding successful performance led to a more cautious approach following errors, whereas unrewarded performance led to recklessness following errors.

Scholarship on “stealth democracy” finds that many citizens want to avoid the debate and conflict that often come with democratic governance. This scholarship has argued that citizens adopt this posture because they are uncomfortable with disagreement and desire a more expedient political process that enables leaders to make decisions without discussion or compromise. We revisit this argument in light of recent political developments that suggest another reason why citizens may desire a more expedient political process. We examine the possibility that some citizens are not merely uncomfortable with disagreement but also want leaders who will aggressively protect them and champion their interests. Using a nationally representative survey, we ask citizens about their preferences for stealth democracy. We also ask questions that tap into their willingness to support leaders who would “bend the rules for supporters” and take aggressive action against political opponents. We find that a substantial component of the electorate continues to prefer a stealth version of democracy. However, we also find that many “stealth democrats” are willing to support leadership practices that would threaten or even undermine democratic norms. We argue that this evidence indicates that, in recent years, many citizens who appear to desire “stealth democracy” pose a threat to democracy itself.

Using 14 proxy human population time series from around the North Pacific (Alaska, Hokkaido and the Kuril Islands), we evaluate the possibility that the North Pacific climate and marine ecosystem includes a millennial-scale regime shift cycle affecting subsistence and migration. We develop both visual and statistical methods for addressing questions about relative population growth and movement in the past. We introduce and explore the use of a Time Iterative Moran I (TIMI) spatial autocorrelation method to compare time series trends quantitatively – a method that could prove useful in other paleoecological analyses. Results reveal considerable population dynamism around the North Pacific in the last 5000 years and strengthen a previously reported inverse correlation between Northeast and Northwest Pacific proxy population indices. Visual and TIMI analyses suggest multiple, overlapping explanations for the variability, including the potential that oscillating ecological regime shifts affect the North Pacific basin. These results provide an opening for coordinated research to unpack the interrelated social, cultural and environmental dynamics around the subarctic and arctic North Pacific at different spatial and temporal scales by international teams of archaeologists, historians, paleoecologists, paleoceanographers, paleoclimatologists, modelers and data management specialists.