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.

The self-interaction spin-2 approach to GR has been extremely influential in the particle physics community. Leaving no doubt regarding its heuristic value, we argue that any view of the metric field of GR as nothing but a stand-in for a self-coupling field in at spacetime runs into a dilemma: either the view is physically incomplete in so far as it requires recourse to GR after all, or it leads to an absurd multiplication of alternative viewpoints on GR rendering any understanding of the metric field as nothing but a spin-2 field in at spacetime unjustified.

Advance consent presents a potential solution to the challenge of obtaining informed consent for participation in acute stroke trials. Clinicians in stroke prevention clinics are uniquely positioned to identify and seek consent from potential stroke trial participants. To assess the acceptability of advance consent to Canadian stroke clinic physicians, we performed an online survey. We obtained 58 respondents (response rate 35%): the vast majority (82%) expressed comfort with obtaining advance consent and 92% felt that doing so would not be a significant disruption to clinic workflow. These results support further study of advance consent for acute stroke trials.

Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are “black boxes.” The initial response in the literature was a demand for “explainable AI.” However, recently, several authors have suggested that making AI more explainable or “interpretable” is likely to be at the cost of the accuracy of these systems and that prioritizing interpretability in medical AI may constitute a “lethal prejudice.” In this paper, we defend the value of interpretability in the context of the use of AI in medicine. Clinicians may prefer interpretable systems over more accurate black boxes, which in turn is sufficient to give designers of AI reason to prefer more interpretable systems in order to ensure that AI is adopted and its benefits realized. Moreover, clinicians may be justified in this preference. Achieving the downstream benefits from AI is critically dependent on how the outputs of these systems are interpreted by physicians and patients. A preference for the use of highly accurate black box AI systems, over less accurate but more interpretable systems, may itself constitute a form of lethal prejudice that may diminish the benefits of AI to—and perhaps even harm—patients.

Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are “black boxes.” The initial response in the literature was a demand for “explainable AI.” However, recently, several authors have suggested that making AI more explainable or “interpretable” is likely to be at the cost of the accuracy of these systems and that prioritizing interpretability in medical AI may constitute a “lethal prejudice.” In this article, we defend the value of interpretability in the context of the use of AI in medicine. Clinicians may prefer interpretable systems over more accurate black boxes, which in turn is sufficient to give designers of AI reason to prefer more interpretable systems in order to ensure that AI is adopted and its benefits realized. Moreover, clinicians may be justified in this preference. Achieving the downstream benefits from AI is critically dependent on how the outputs of these systems are interpreted by physicians and patients. A preference for the use of highly accurate black box AI systems, over less accurate but more interpretable systems, may itself constitute a form of lethal prejudice that may diminish the benefits of AI to—and perhaps even harm—patients.

Invasive aquatic plants constantly threaten freshwaters and associated environs globally. Water resource managers frequently seek new control tactics to combat invasive macrophytes, especially when the availability of herbicides registered for submersed plant control is limited. The synthetic auxin herbicide, florpyrauxifen-benzyl, recently registered (2018) for aquatic site applications in the United States, has shown success in controlling several invasive aquatic weeds. Studies were conducted to evaluate responses of native and invasive submersed plants to florpyrauxifen-benzyl under growth chamber conditions to provide insight on the selectivity of varying herbicide concentrations in New Zealand. Florpyrauxifen-benzyl concentrations evaluated ranged from 0.01 to 107.86 µg ai L−1, encompassing the maximum use concentration (48 µg L−1) for submersed plant applications. Dose–response metrics indicated the New Zealand native species watermilfoil [Myriophyllum triphyllum Orchard] was highly sensitive to florpyrauxifen-benzyl following a 21-d static exposure, having a dry weight 50% effective concentration (EC50) value of 1.2 µg L−1. The invasive species oxygen-weed [Lagarosiphon major (Ridley) Moss] and Canadian waterweed (Elodea canadensis Michx.) were less sensitive, with dry weight EC50 values of 35.4 and >107.86 µg L−1, respectively. Brazilian waterweed (Egeria densa Planch.) was most tolerant to the tested concentrations, as EC50 values were not achieved. Overall, results indicate florpyrauxifen-benzyl demonstrates potential for controlling L. major, with further large-scale screening required to confirm control among field site applications. As the native species (M. triphyllum) was most sensitive to florpyrauxifen-benzyl compared with the invasive plant evaluated (I/N ratio indicated >31.3 times more sensitive), any targeted concentration used for invasive plant control for field applications would likely injure the native M. triphyllum plants. Future studies should investigate additional native and invasive species for management guidance and consider how exposure times influence plant response using similar florpyrauxifen-benzyl concentrations tested in the present study.

Late Holocene relative sea-level reconstructions are commonly generated using proxies preserved in salt-marsh and mangrove sediment. These depositional environments provide abundant material for radiocarbon dating in the form of identifiable macrofossils (salt marshes) and bulk organic sediment (mangroves). We explore if single-step graphitization of these samples in preparation for radiocarbon dating can increase the number and temporal resolution of relative sea-level reconstructions without a corresponding increase in cost. Dating of salt-marsh macrofossils from the northeastern United States and bulk mangrove sediment from the Federated States of Micronesia indicates that single-step graphitization generates radiocarbon ages that are indistinguishable from replicates prepared using traditional graphitization, but with a modest increase in error (mean/maximum of 6.25/15 additional 14C yr for salt-marsh macrofossils). Low 12C currents measured on bulk mangrove sediment following single-step graphitization likely render them unreliable despite their apparent accuracy. Simulated chronologies for six salt-marsh cores indicate that having twice as many radiocarbon dates (since single-step graphitization costs ∼50% of traditional graphitization) results in narrower confidence intervals for sample age estimated by age-depth models when the additional error from the single-step method is less than ∼50 14C yr (∼30 14C yr if the chronology also utilizes historical age markers). Since these thresholds are greater than our empirical estimates of the additional error, we conclude that adopting single-step graphitization for radiocarbon measurements on plant macrofossils is likely to increase precision of age-depth models by more than 20/10% (without/with historical age markers). This improvement can be implemented without additional cost.