Objectives/Goals: We have shown that parathyroid hormone-related protein (PTHrP) is enriched at the LIFR promoter in breast cancer cells and inhibits the expression of dormancy-associated genes including LIFR. The objective of this study is to define where all PTHrP binds DNA and identify pathways that are regulated by PTHrP that promote breast cancer colonization of the bone. Methods/Study Population: In this study, we use human estrogen receptor-positive MCF7 breast cancer cells which we and others have reported lie dormant in the bone. MCF7 cells were engineered to express either PTHrP with an HA-tag (MCF7P), or a vector control (MCF7V). We use Cleavage Under Targets and Release Using Nuclease (CUT&RUN), a method of mapping protein-DNA interactions, to define where PTHrP binds DNA. Here, an HA-specific antibody identifies regions of DNA that are bound to PTHrP in MCF7P cells compared to MCFV cells. Next, we perform DNA sequencing and gene set enrichment analysis (GSEA) on genes identified by CUT&RUN to identify pathways that are regulated by PTHrP. These experiments will determine how PTHrP regulates dormancy and breast cancer colonization in the bone. Results/Anticipated Results: We completed IgG (-control), H3K4me3 (+ control), and HA (PTHrP) CUT&RUN on MCF7V and MCF7P cells, and submitted DNA for sequencing. This study will define where PTHrP binds the genome and identify pathways regulated by PTHrP. Previously, through ChIP-qPCR we showed that PTHrP binds the LIFR promoter to repress LIFR expression. Given this result, we expect that PTHrP binds to the promoters of dormancy-associated genes including LIFR in MCF7P cells compared to MCF7V cells. PTHrP may be involved in regulating other processes besides dormancy to induce expansion of breast cancer cells in the bone, so we will use GSEA to identify pathways that are altered in MCF7P cells when PTHrP is over-expressed compared to MCF7V cells. Together, this will define how PTHrP regulates gene expression of bone metastatic breast cancer cells. Discussion/Significance of Impact: This study will unveil mechanisms of metastatic breast cancer expansion in the bone by defining where PTHrP binds the genome to regulate gene expression. These findings will reveal therapeutic vulnerabilities that will be used to target bone-disseminated tumor cells to prevent lethal recurrence.

Federal and local agencies have identified a need to create building databases to help ensure that critical infrastructure and residential buildings are accounted for in disaster preparedness and to aid the decision-making processes in subsequent recovery efforts. To respond effectively, we need to understand the built environment—where people live, work, and the critical infrastructure they rely on. Yet, a major discrepancy exists in the way data about buildings are collected across the United SStates There is no harmonization in what data are recorded by city, county, or state governments, let alone at the national scale. We demonstrate how existing open-source datasets can be spatially integrated and subsequently used as training for machine learning (ML) models to predict building occupancy type, a major component needed for disaster preparedness and decision -making. Multiple ML algorithms are compared. We address strategies to handle significant class imbalance and introduce Bayesian neural networks to handle prediction uncertainty. The 100-year flood in North Carolina is provided as a practical application in disaster preparedness.

The scientific manuscript review process can often seem daunting and mysterious to authors. Frequently, medical journals do not describe the peer-review process in detail, which can further lead to frustration for authors, peer reviewers, and readers. This editorial describes the updated manuscript review process for Prehospital and Disaster Medicine. It is hoped that this editorial will lead to increased clarity and transparency in the review process.

Foliar-applied postemergence applications of glufosinate are often applied to glufosinate-resistant crops to provide nonselective weed control without significant crop injury. Rainfall, air temperature, solar radiation, and relative humidity near the time of application have been reported to affect glufosinate efficacy. However, previous research may have not captured the full range of weather variability to which glufosinate may be exposed before or following application. Additionally, climate models suggest more extreme weather will become the norm, further expanding the weather range to which glufosinate can be exposed. The objective of this research was to quantify the probability of successful weed control (efficacy ≥85%) with glufosinate applied to some key weed species across a broad range of weather conditions. A database of >10,000 North American herbicide evaluation trials was used in this study. The database was filtered to include treatments with a single postemergence application of glufosinate applied to waterhemp [Amaranthus tuberculatus (Moq.) Sauer], morningglory species (Ipomoea spp.), and/or giant foxtail (Setaria faberi Herrm.) <15 cm in height. These species were chosen because they are well represented in the database and listed as common and troublesome weed species in both corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] (Van Wychen 2020, 2022). Individual random forest models were created. Low rainfall (≤20 mm) over the 5 d before glufosinate application was detrimental to the probability of successful control of A. tuberculatus and S. faberi. Lower relative humidity (≤70%) and solar radiation (≤23 MJ m−1 d−1) on the day of application reduced the probability of successful weed control in most cases. Additionally, the probability of successful control decreased for all species when average air temperature over the first 5 d after application was ≤25 C. As climate continues to change and become more variable, the risk of unacceptable control of several common species with glufosinate is likely to increase.

Tversky's contrast model of proximity was initially formulated to account for the observed violations of the metric axioms often found in empirical proximity data. This set-theoretic approach models the similarity/dissimilarity between any two stimuli as a linear (or ratio) combination of measures of the common and distinctive features of the two stimuli. This paper proposes a new spatial multidimensional scaling (MDS) procedure called TSCALE based on Tversky's linear contrast model for the analysis of generally asymmetric three-way, two-mode proximity data. We first review the basic structure of Tversky's conceptual contrast model. A brief discussion of alternative MDS procedures to accommodate asymmetric proximity data is also provided. The technical details of the TSCALE procedure are given, as well as the program options that allow for the estimation of a number of different model specifications. The nonlinear estimation framework is discussed, as are the results of a modest Monte Carlo analysis. Two consumer psychology applications are provided: one involving perceptions of fast-food restaurants and the other regarding perceptions of various competitive brands of cola softdrinks. Finally, other applications and directions for future research are mentioned.

Foliar-applied postemergence herbicides are a critical component of corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] weed management programs in North America. Rainfall and air temperature around the time of application may affect the efficacy of herbicides applied postemergence in corn or soybean production fields. However, previous research utilized a limited number of site-years and may not capture the range of rainfall and air temperatures that these herbicides are exposed to throughout North America. The objective of this research was to model the probability of achieving successful weed control (≥85%) with commonly applied postemergence herbicides across a broad range of environments. A large database of more than 10,000 individual herbicide evaluation field trials conducted throughout North America was used in this study. The database was filtered to include only trials with a single postemergence application of fomesafen, glyphosate, mesotrione, or fomesafen + glyphosate. Waterhemp [Amaranthus tuberculatus (Moq.) Sauer], morningglory species (Ipomoea spp.), and giant foxtail (Setaria faberi Herrm.) were the weeds of focus. Separate random forest models were created for each weed species by herbicide combination. The probability of successful weed control deteriorated when the average air temperature within the first 10 d after application was <19 or >25 C for most of the herbicide by weed species models. Additionally, drier conditions before postemergence herbicide application reduced the probability of successful control for several of the herbicide by weed species models. As air temperatures increase and rainfall becomes more variable, weed control with many of the commonly used postemergence herbicides is likely to become less reliable.

The gut microbiome is impacted by certain types of dietary fibre. However, the type, duration and dose needed to elicit gut microbial changes and whether these changes also influence microbial metabolites remain unclear. This study investigated the effects of supplementing healthy participants with two types of non-digestible carbohydrates (resistant starch (RS) and polydextrose (PD)) on the stool microbiota and microbial metabolite concentrations in plasma, stool and urine, as secondary outcomes in the Dietary Intervention Stem Cells and Colorectal Cancer (DISC) Study. The DISC study was a double-blind, randomised controlled trial that supplemented healthy participants with RS and/or PD or placebo for 50 d in a 2 × 2 factorial design. DNA was extracted from stool samples collected pre- and post-intervention, and V4 16S rRNA gene sequencing was used to profile the gut microbiota. Metabolite concentrations were measured in stool, plasma and urine by high-performance liquid chromatography. A total of fifty-eight participants with paired samples available were included. After 50 d, no effects of RS or PD were detected on composition of the gut microbiota diversity (alpha- and beta-diversity), on genus relative abundance or on metabolite concentrations. However, Drichlet’s multinomial mixture clustering-based approach suggests that some participants changed microbial enterotype post-intervention. The gut microbiota and fecal, plasma and urinary microbial metabolites were stable in response to a 50-d fibre intervention in middle-aged adults. Larger and longer studies, including those which explore the effects of specific fibre sub-types, may be required to determine the relationships between fibre intake, the gut microbiome and host health.

The authors seek to design a lower limb exoskeleton to augment human finned swimming; however, data associated with human finned swimming previously did not exist, particularly data that characterizes the active joint torque requirements for human-scale finned swimming motion and the corresponding thrust generation. Since these data are not directly measurable nor easily computed in human subject experiments, the authors instead employed a human-scale robotic platform to characterize the relationship between joint torque, speed, power, and thrust production during flutter kick swimming, specifically at the hip joints. Among the useful insights from this study: (1) the underwater environment can be accurately modeled as a simple viscous load as seen by the hip joints, where viscous coefficient depends on the type of fin; (2) accordingly, for a given fin, movement at any amplitude and frequency is invariant when motion is normalized by amplitude; velocity and torque by the product of amplitude and frequency; and power and thrust by the square of the product of amplitude and frequency; (3) the power-specific thrust is invariant, regardless of fin type, amplitude of motion, and frequency of motion; and 4) the phasing between right and left legs does not have a significant effect on thrust generation (i.e., kicking in-phase and kicking in opposition behave similarly). The authors hope this data will be useful to other researchers interested in developing lower limb exoskeletons to augment underwater human finned swimming.

Declining labor force participation of older men throughout the 20th century and recent increases in participation have generated substantial interest in understanding the effect of public pensions on retirement. The National Bureau of Economic Research's International Social Security (ISS) Project, a long-term collaboration among researchers in a dozen developed countries, has explored this and related questions. The project employs a harmonized approach to conduct within-country analyses that are combined for meaningful cross-country comparisons. The key lesson is that the choices of policy makers affect the incentive to work at older ages and these incentives have important effects on retirement behavior.

As the proportion of the elderly population in the USA expands, so will the demand for rehabilitation and social care, which play an important role in maintaining function and mediating motor and cognitive decline in older adults. The use of social robotics and telemedicine are each potential solutions but each have limitations. To address challenges with classical telemedicine for rehabilitation, we propose to use a social robot-augmented telepresence (SRAT), Flo, which was deployed for long-term use in a community-based rehabilitation facility catering to older adults. Our goals were to explore how clinicians and patients would use and respond to the robot during rehab interactions. In this pilot study, three clinicians were recruited and asked to rate usability after receiving training for operating the robot and two of them conducted multiple rehab interactions with their patients using the robot (eleven patients with cognitive impairment and/or motor impairment and 23 rehab sessions delivered via SRAT in total). We report on the experience of both therapists and patients after the interactions.

Acid-base titrations and attenuated total reflectance-infrared (ATR-IR) spectroscopy of solutions containing Zn(NO3)2 and the herbicide 3-amino-1,2,4-triazole suggested that soluble complexes ZnL2+ and Zn(OH)L+ form, where L represents aminotriazole. Sorption experiments and modeling in systems containing K-saturated Wyoming (SWy-K) montmorillonite suggest that at low concentrations the aminotriazole sorbs primarily in cationic form via an ion-exchange mechanism. Sorption isotherms for aminotriazole are ‘s’-shaped, indicating a co-operative sorption mechanism as the concentration of the molecule increases. At higher concentrations, ATR-IR spectroscopy indicated the presence of cationic and neutral triazole molecules on the surface, while X-ray diffraction data suggest interaction with interlayer regions of the clay. When the concentration of the herbicide was high, initial sorption of aminotriazole cations modified the clay to make the partitioning of neutral molecules to the surface more favorable. Experiments conducted in the presence of Zn(II) indicated that below pH 7, Zn(II) and aminotriazole compete for sorption sites, while above pH 7 the presence of Zn(II) enhances the uptake of aminotriazole. The enhancement was attributed to the formation of an inner-sphere ternary surface complex at hydroxyl sites (SOH) on crystal edges, having the form [(SOZn(OH)L)]0.

Simple extended constant capacitance surface complexation models have been developed to represent the adsorption of polyaromatic dyes (9-aminoacridine, 3,6-diaminoacridine, azure A and safranin O) to kaolinite, and the competitive adsorption of the dyes with Cd. The formulation of the models was based on data from recent publications, including quantitative adsorption measurements over a range of conditions (varying pH and concentration), acid-base titrations and attenuated total reflectance-Fourier transform infrared spectroscopic data. In the models the dye molecules adsorb as aggregates of three or four, forming outer-sphere complexes with sites on the silica face of kaolinite. Both electrostatic and hydrophobic interactions are implicated in the adsorption processes. Despite their simplicity, the models fit a wide range of experimental data, thereby supporting the underlying hypothesis that the flat, hydrophobic, but slightly charged silica faces of kaolinite facilitate the aggregation and adsorption of the flat, aromatic, cationic dye molecules.

Three-dimensional (3D) food printing is a rapidly emerging technology offering unprecedented potential for customised food design and personalised nutrition. Here, we evaluate the technological advances in extrusion-based 3D food printing and its possibilities to promote healthy and sustainable eating. We consider the challenges in implementing the technology in real-world applications. We propose viable applications for 3D food printing in health care, health promotion and food waste upcycling. Finally, we outline future work on 3D food printing in food safety, acceptability and economics, ethics and regulations.