Tetflupyrolimet is a novel herbicide that inhibits dihydroorotate dehydrogenase (DHODH), interfering with de novo pyrimidine biosynthesis in susceptible plants. While tetflupyrolimet efficacy for preemergence grassy weed control in rice (Oryza sativa L.) and managed turfgrass systems has been explored, there is minimal information regarding effects that edaphic factors may have on activity, particularly those pertaining to soil hydraulics. Dose–response experiments revealed 6- to 8-fold differences in tetflupyrolimet activity on annual bluegrass (Poa annua L.) due to soil texture, with higher activity reported following applications to sand compared with clay loam. Higher tetflupyrolimet activity in sand could be related to matric potential, as activity following applications to plants growing in sand exceeded that observed on clay loam across a wide range of volumetric water contents (15% to 60%). Once volumetric water content increased to ≥ 80%, no differences in tetflupyrolimet activity were detected between soils, suggesting that post-application irrigation could mitigate potential reductions in efficacy on finer-textured soils when moisture is limited. These findings underscore that soil texture and, consequently, moisture retention affect tetflupyrolimet activity to the extent that application rates could vary based on soil texture in turfgrass systems. Further research exploring a broader range of soil types and field conditions is warranted to refine tetflupyrolimet rate recommendations based on soil type.

Many experiments investigating different decision theories have relied heavily on pairwise choices between lotteries. These are easy to incentivise, but often yield only limited dichotomous information. This paper considers whether respondents’ judgments about their strength of preference (SoP) for one alternative over another can usefully supplement standard choice data. We report extensive evidence that such judgments show sensitivity to variations in question format and parameter values in the directions we should expect, not only within-subject but also between-sample. We illustrate how such judgments can usefully supplement standard pairwise choice data and enrich our understanding of observed behaviour.

The concept of interaction classes (iClasses) for multi-environment trial data was introduced to address the problem of summarising variety performance across environments in the presence of variety by environment interaction (VEI). The approach involves the fitting of a factor analytic linear mixed model (FALMM), with the resultant estimates of factor loadings being used to form groups of environments (iClasses) that discriminate varieties with different patterns of VEI. It is then meaningful to summarise variety performance across environments within iClasses. The iClass methodology was developed with respect to a FALMM in which the genetic effects for different varieties were assumed independent. This was done for pedagogical reasons but it was pointed out that the accuracy of variety selection is greatly enhanced by considering the genetic relatedness of varieties, either via ancestral or genomic information. The focus of the current paper is therefore to extend the iClass approach for FALMMs which incorporate such information. In addition, a measure of stability of variety performance across iClasses is defined. The utility of the approach for variety selection is illustrated using a multi-environment trial dataset from the lentil breeding programme operated by Agriculture Victoria.

OBJECTIVES/GOALS: To introduce the new Team Science Community Toolkit, co-created by community and academic partners, and showcase its potential to empower Community Organizations (COs) in achieving equity in community-engaged research (CER). METHODS/STUDY POPULATION: In response to the challenges faced by COs in CER collaborations, qualitative interviews were conducted with CO staff from historically marginalized communities. These interviews informed the development of the Team Science Community Toolkit, a collaborative effort involving a Community Advisory Board (CAB) and Team Science experts from Northwestern University. The toolkit, designed using a community-based participatory research approach, incorporates the Science of Team Science and User-Centered Design principles. Integrated into the NIH-sponsored COALESCE website, it includes templates, checklists, and interactive tools, along with a real-world simulation, to support COs in all stages of the research process. RESULTS/ANTICIPATED RESULTS: Focus groups and usability testing involving external community experts validated the toolkit’s content and usability. Participants expressed enthusiasm and a sense of empowerment, indicating that the toolkit allows them to actively shape research processes and infuse their specific voices and needs into their partnerships. The toolkit is designed to support breaking down barriers like jargon and cultural adaptability to improve accessibility and open conversation. The impact of this Team Science focused toolkit is under evaluation. This presentation will showcase the toolkit, detail its collaborative development, and explore potential applications, ultimately offering a path to more equitable and valuable community-based research. DISCUSSION/SIGNIFICANCE: By providing COs with the resources and knowledge to participate as equal partners in research collaborations, it enhances self-advocacy, transparency, and equity. The toolkit has the potential to utilize Team Science to foster productive communication in community-academic research partnerships.

The potential of artificial intelligence (AI) in water management is widely recognised by research and practice communities alike, with an increasing number of applications showed tackling water supply, stormwater and wastewater management challenges. However, there is a critical knowledge gap in understanding the fundamental role of AI in the development of urban water infrastructure (UWI). This review aimed to provide an analysis of how AI could be aligned to support the future development of UWI systems. Four types of AI analytics – descriptive, diagnostic, predictive and prescriptive – are discussed and linked to the improvement in the performance of UWI systems from three categories: reliability, resilience and sustainability. It is envisioned that AI technology will play a pivotal role in UWI transitioning to the future through underpinning the five development pathways: decentralisation, circular economy, greening, decarbonisation and automation. The barriers in improving AI adoption in the real world are also highlighted from four dimensions: cyber-physical infrastructure, institutional governance, social-economic systems and technological development in wider society. Embedding AI in the development pathways and tackling the barriers can ensure that AI-empowered systems are deployed in an equitable and responsible way to improve the resilience and sustainability of future UWI systems.

Birnbaum (2020) reanalyses the data from Butler and Pogrebna (2018) using his ‘true and error’ test of choice patterns. His results generally support the evidence we presented in that paper. Here we reiterate the reasons for our agnosticism as to the direction any cycles might take, even though the paradox that motivated our study takes a ‘probable winner’ direction. We conclude by returning to the potential significance of predictably intransitive preferences for decision theory generally.

The transitivity axiom is common to nearly all descriptive and normative utility theories of choice under risk. Contrary to both intuition and common assumption, the little-known ’Steinhaus-Trybula paradox’ shows the relation ’stochastically greater than’ will not always be transitive, in contradiction of Weak Stochastic Transitivity. We bespoke-design pairs of lotteries inspired by the paradox, over which individual preferences might cycle. We run an experiment to look for evidence of cycles, and violations of expansion/contraction consistency between choice sets. Even after considering possible stochastic but transitive explanations, we show that cycles can be the modal preference pattern over these simple lotteries, and we find systematic violations of expansion/contraction consistency.

B-type supergiants show enormous potential as resourceful tools to address a wide range of astrophysical questions concerning stellar atmospheres, stellar and galactic evolution and the cosmic distance scale. For the purposes of a comprehensive analysis of these objects we test a hybrid non-LTE approach – line-blanketed model atmospheres computed under the assumptions of local thermodynamic equilibrium (LTE) in combination with non-LTE line-formation calculations. An observational sample of 14 Galactic B-type supergiants with masses below about 30 Mȯ is investigated on the basis of high-resolution Echelle spectra. The results of this analysis – atmospheric and fundamental stellar parameters, the characterisation of the interstellar sightlines to the objects, as well as derived spectroscopic distances and multi-species abundances – are subjected to multiple tests of consistency.

OBJECTIVES/GOALS: Osteoarthritis (OA) is a cartilage destroying disease. We are investigating abaloparatide (ABL) activation of parathyroid hormone receptor type 1 (PTH1R), which is expressed by articular chondrocytes in OA. We propose ABL treatment is chondroprotective in murine PTOA via stimulation of matrix production and inhibition of chondrocyte maturation. METHODS/STUDY POPULATION: 16-week-old C57BL/6 male mice received destabilization of the medial meniscus (DMM) surgery to induce knee PTOA. Beginning 2 weeks post-DMM, 40 μg/kg of ABL (or saline) was administered daily via subcutaneous injection and tissues were harvested after 6 weeks of daily injections and 8 weeks after DMM surgery. Harvested joint tissues were used for histological and molecular assessment of OA using three 5 μm thick sagittal sections from each joint, 50 μm apart, cut from the medial compartment of injured knees. Safranin O/Fast Green tissue staining and immunohistochemistry-based detection of type 10 collagen (Col10) and lubricin (Prg4) was performed using standard methods. Histomorphometric quantification of tibial cartilage area and larger hypertrophic-like cells was performed using the Osteomeasure system. RESULTS/ANTICIPATED RESULTS: Safranin O/Fast Green stained sections showed a decreased cartilage loss in DMM joints from ABL-treated versus saline-treated mice. Histomorphometric analysis of total tibial cartilage area revealed preservation of cartilage tissue on the tibial surface. Immunohistochemical analyses showed that upregulation of Col10 in DMM joints was mitigated in the cartilage of ABL-treated mice, and chondrocyte expression of Prg4 was increased in uncalcified cartilage areas in ABL-treated group. The Prg4 finding suggests a matrix anabolic effect that may counter OA cartilage loss. Quantification of chondrocytes in uncalcified and calcified tibial cartilage areas revealed a reduction in the number of larger hypertrophic-like cells in ABL treated mice, suggesting deceleration of hypertrophic differentiation. DISCUSSION/SIGNIFICANCE: Cartilage preservation/regeneration therapies would fill a critical unmet need. We demonstrate that an osteoporosis drug targeting PTH1R decelerates PTOA in mice. ABL treatment was associated with preservation of cartilage, decreased Col10, increased Prg4, and decreased number of large hypertrophic-like chondrocytes in the tibial cartilage.

This paper explores the interaction of informal constraints on human behaviour by examining the evolution of English football jerseys. The jersey provides an excellent setting to demonstrate how informal constraints emerge from formal rules and shape human behaviour. Customs, approved norms and habits are all observed in this setting. The commercialisation of football in recent decades has resulted in these informal constraints, in many cases dating back over a century, co-existing with branding, goodwill and identity effects. Combined, these motivate clubs to maintain the status quo. As a result, club colours have remained remarkably resilient within a frequently changing landscape.

The Late Triassic fauna of the Lossiemouth Sandstone Formation (LSF) from the Elgin area, Scotland, has been pivotal in expanding our understanding of Triassic terrestrial tetrapods. Frustratingly, due to their odd preservation, interpretations of the Elgin Triassic specimens have relied on destructive moulding techniques, which only provide incomplete, and potentially distorted, information. Here, we show that micro-computed tomography (μCT) could revitalise the study of this important assemblage. We describe a long-neglected specimen that was originally identified as a pseudosuchian archosaur, Ornithosuchus woodwardi. μCT scans revealed dozens of bones belonging to at least two taxa: a small-bodied pseudosuchian and a specimen of the procolophonid Leptopleuron lacertinum. The pseudosuchian skeleton possesses a combination of characters that are unique to the clade Erpetosuchidae. As a basis for investigating the phylogenetic relationships of this new specimen, we reviewed the anatomy, taxonomy and systematics of other erpetosuchid specimens from the LSF (all previously referred to Erpetosuchus). Unfortunately, due to the differing representation of the skeleton in the available Erpetosuchus specimens, we cannot determine whether the erpetosuchid specimen we describe here belongs to Erpetosuchus granti (to which we show it is closely related) or if it represents a distinct new taxon. Nevertheless, our results shed light on rarely preserved details of erpetosuchid anatomy. Finally, the unanticipated new information extracted from both previously studied and neglected specimens suggests that fossil remains may be much more widely distributed in the Elgin quarries than previously recognised, and that the richness of the LSF might have been underestimated.