We recently reported on the radio-frequency attenuation length of cold polar ice at Summit Station, Greenland, based on bi-static radar measurements of radio-frequency bedrock echo strengths taken during the summer of 2021. Those data also allow studies of (a) the relative contributions of coherent (such as discrete internal conducting layers with sub-centimeter transverse scale) vs incoherent (e.g. bulk volumetric) scattering, (b) the magnitude of internal layer reflection coefficients, (c) limits on signal propagation velocity asymmetries (‘birefringence’) and (d) limits on signal dispersion in-ice over a bandwidth of ~100 MHz. We find that (1) attenuation lengths approach 1 km in our band, (2) after averaging 10 000 echo triggers, reflected signals observable over the thermal floor (to depths of ~1500 m) are consistent with being entirely coherent, (3) internal layer reflectivities are ≈–60$\to$–70 dB, (4) birefringent effects for vertically propagating signals are smaller by an order of magnitude relative to South Pole and (5) within our experimental limits, glacial ice is non-dispersive over the frequency band relevant for neutrino detection experiments.

Background: Previously, our hospital manually built a static antibiogram from a surveillance system (VigiLanz) culture report. In 2019, a collaboration between the antimicrobial stewardship team (AST) and the infection control (IC) team set out to leverage data automation to create a dynamic antibiogram. The goal for the antibiogram was the ability to easily distribute and update for hospital staff, with the added ability to perform advanced tracking and surveillance of organism and drug susceptibilities for AST and IC. By having a readily available, accurate, and Clinical and Laboratory Standards Institute (CLSI)–compliant antibiogram, clinicians have the best available data on which to base their empiric antibiotic decisions. Methods: First, assessment of required access to hospital databases and selection of a visualization software (MS Power BI) was performed. Connecting SQL database feeds to Power BI enabled creation of a data model using DAX and M code to comply with the CLSI, generating the first isolate per patient per year. Once a visual antibiogram was created, it was validated against compiled antibiograms using data from the microbiology laboratory middleware (bioMerieux, Observa Integrated Data Management Software). This validation process uncovered some discrepancies between the 2 reference reports due to cascade reporting of susceptibilities. The Observa-derived data were used as the source of truth. The antibiogram prototype was presented to AST/IC members, microbiology laboratory leadership, and other stakeholders to assess functionality. Results: Following feedback and revisions by stakeholders, the new antibiogram was published on a hospital-wide digital platform (Fig. 1). Clinicians may view the antibiogram at any time on desktops from a firewall (or password)–protected intranet. The antibiogram view defaults to the current calendar year and users may interact with the antibiogram rows and columns without disrupting the integrity of the background databases or codes. Each year, simple refreshing of the Power BI antibiogram and changing of the calendar year allows us to easily and accurately update the antibiogram on the hospital-wide digital platform. Conclusions: This interdisciplinary collaboration resulted in a new dynamic, CLSI-compliant antibiogram with improved usability, increased visibility, and straightforward updating. In the future, a mobile version of the antibiogram may further enhance accessibility, bring more useful information to providers, and optimize AST/IC guidelines and education.

Disclosures: None

Background: The off-target effects linezolid have the potential to cause serotonin syndrome when given in conjunction with serotonergic agents. Despite package insert labeling as a contraindication, several postmarketing studies have demonstrated a low incidence of serotonin syndrome with the concomitant use of linezolid and other serotonergic agents. Linezolid provides a convenient oral option for gram-positive infections. However, due to concerns for serotonin syndrome, the use of linezolid is sometimes avoided. Methods: We performed a single-center, retrospective, medical record review of all adult inpatients from September 2021 to September 2022. Patients included had 1 administration of linezolid and 1 inpatient administration of a selective serotonin reuptake inhibitor (SSRI) or serotonin and norepinephrine reuptake inhibitor (SNRI) within 14 days. The primary outcome was the incidence of serotonin syndrome as defined by the Hunter serotonin toxicity criteria, which were retrospectively applied to each patient based on medical-record documentation. We compared patients receiving 1 versus multiple serotonergic agents. Secondary outcomes included duration of hospitalization and adverse outcomes based on concerns for serotonin syndrome such as need for rescue, ICU admission, or change in medication. Results: Of the 50 included patients from a convenience sample, 27 (54%) were on linezolid and >1 serotonergic agent. Patients had similar baseline characteristics (Table 1). The most common concomitant agent used was an SSRI. Other agents that predispose patients to serotonin syndrome included opioid analgesics and other classes of antidepressants (Fig. 1). Serotonin syndrome occurred within 48 hours in 1 patient on an SNRI and a continuous fentanyl drip. There was no need for rescue or ICU admission due to serotonin syndrome. No patients were readmitted due to serotonin syndrome, and no differences were observed in hospital lengths of stay. Conclusions: Exposure to a single serotonergic agent combined with receipt of linezolid was not associated with any cases of serotonin syndrome. Exposure to multiple serotonergic agents was not associated with a high incidence of serotonin syndrome. This small series supports previous reports demonstrating relative safety of linezolid given with serotonergic agents and encourages review of interruptive drug–drug interaction alerts for linezolid within the electronic ordering system.

Disclosures: None

Background: Nirmatrelvir-ritonavir received emergency use authorization (EUA) for the prevention of progression of COVID-19 in December 2021. Most data supporting this authorization are limited to the outpatient setting in unvaccinated patients, and high-quality head-to-head comparisons to other antivirals such as remdesivir are lacking. Patients at high risk of disease progression, such as advanced age, smokers, and those with cardiovascular disease, diabetes, obesity, or cancer continue to be admitted to acute-care settings for various indications, and some are incidentally found to have mild COVID-19. The objective of this project was to compare rates of progression of mild-to-moderate COVID-19 for inpatients treated with remdesivir versus nirmatrelvir-ritonavir. Methods: This study was a single-center, retrospective cohort study that included patients aged ≥18 years with PCR-confirmed SARS-CoV-2 infection who were initiated on nirmatrelvir-ritonavir within 5 days or remdesivir within 7 days of symptom onset between June 2022 and August 2022. The primary outcome was the worsening of symptoms via the WHO ordinal clinical severity scale for COVID-19. Secondary outcomes included escalation of care or readmission due to COVID-19, discharge prior to treatment completion, and any adverse drug reactions (ADRs). Within our institutional guidelines, prior approval is needed for COVID-19 treatment through collaboration between the primary team and antimicrobial stewards. Nirmatrelvir-ritonavir is the preferred agent for both in- and outpatients unless the patient had drug interactions or lack of enteral access, in which case remdesivir was considered. Results: In total, 58 patients were screened and 50 patients were included, 25 patients in each arm. Most were non-Hispanic, white males with at least 1 comorbidity. Compared to the remdesivir arm, the nirmatrelvir-ritonavir arm had more patients with at least a primary COVID-19 vaccine (44% vs 34%). Also, 88% of patients in each arm had a baseline ordinal score of 4, and 12% had a score of 5. Ordinal score changes between the start and end of therapy were similar between groups, and neither had an increase in oxygen requirements (Fig. 1). No readmissions were due to COVID-19, and both medications were well tolerated. Refer to Fig. 2 for secondary outcomes. Conclusions: Nirmatrelvir-ritonavir and remdesivir showed similar safety and efficacy in the treatment of hospitalized patients with mild-to-moderate COVID-19. Current evidence-based guidelines and treatment costs favor nirmatrelvir-ritonavir for patients who can receive this drug.

Disclosures: None

No-till planting organic soybean [Glycine max (L.) Merr.] into roller-crimped cereal rye (Secale cereale L.) can have several advantages over traditional tillage-based organic production. However, suboptimal cereal rye growth in fields with large populations of weeds may result in reduced weed suppression, weed–crop competition, and soybean yield loss. Ecological weed management theory suggests that integrating multiple management practices that may be weakly effective on their own can collectively provide high levels of weed suppression. In 2021 and 2022, a field experiment was conducted in central New York to evaluate the performance of three weed management tactics implemented alone and in combination in organic no-till soybean planted into both cereal rye mulch and no mulch: (1) increasing crop seeding rate, (2) interrow mowing, and (3) weed electrocution. A nontreated control treatment that did not receive any weed management and a weed-free control treatment were also included. Cereal rye was absent from two of the five fields where the experiment was repeated; however, the presence of cereal rye did not differentially affect results, and thus data were pooled across fields. All treatments that included interrow mowing reduced weed biomass by at least 60% and increased soybean yield by 14% compared with the nontreated control. The use of a high seeding rate or weed electrocution, alone or in combination, did not improve weed suppression or soybean yield relative to the nontreated control. Soybean yield across all treatments was at least 22% lower than in the weed-free control plot. Future research should explore the effects of the tactics tested on weed population and community dynamics over an extended period. Indirect effects from interrow mowing and weed electrocution should also be studied, such as the potential for improved harvestability, decreased weed seed production and viability, and the impacts on soil organisms and agroecosystem biodiversity.

We present the third data release from the Parkes Pulsar Timing Array (PPTA) project. The release contains observations of 32 pulsars obtained using the 64-m Parkes ‘Murriyang’ radio telescope. The data span is up to 18 yr with a typical cadence of 3 weeks. This data release is formed by combining an updated version of our second data release with $\sim$3 yr of more recent data primarily obtained using an ultra-wide-bandwidth receiver system that operates between 704 and 4032 MHz. We provide calibrated pulse profiles, flux density dynamic spectra, pulse times of arrival, and initial pulsar timing models. We describe methods for processing such wide-bandwidth observations and compare this data release with our previous release.

OBJECTIVES/GOALS: Physical therapy (PT) is key for treating functional decline that inpatients experience but is a constrained resource in hospital settings. The Activity Measure Post-Acute Care (AM-PAC) score is a mobility measurement tool that has been used to define misallocation of PT. We aim to optimize PT referrals using AM-PAC-based clinical decision support . METHODS/STUDY POPULATION: We conducted a prospective study of patients admitted to University of Chicago Medical Center. AM-PAC scores were assessed by nursing staff every 12 hours. Clinical decision support was designed using validated AM-PAC cutoffs (> 18, a predictor of discharge to home). The tool was embedded in hospital medicine note templates, requiring providers to indicate PT referral status based on current AM-PAC scores. The primary outcome, unskilled consult , was defined as PT referral for patients with AM-PAC > 18. Data were collected for one year prior to implementation and one year after implementation for intervention (hospital medicine) and control (general internal medicine) services. Difference in differences analysis was used to assess the association between the intervention and unskilled consults. RESULTS/ANTICIPATED RESULTS: Between October 2018 and March 2021, 18,241 admissions were eligible for the study. Compared to preintervention, there was a lower rate of referral to PT for patients with high AM-PAC mobility scores in the post-intervention period [18.5% vs 16.6%; X2(1) = 7.02; p < 0.01]. In the postintervention time period, the control group experienced a 2.6% increase in unskilled consults while the intervention group experienced a 2.3% decrease, a difference in differences of 4.9% (95% CI -0.07–-0.03 for difference in differences) controlling for age sex, race, LOS, and change in mobility. Compared to preintervention, there was no statistically significant difference in mean change in mobility score post-intervention for either group. DISCUSSION/SIGNIFICANCE: Our results suggest that clinical decision support can decrease unskilled PT consults. Many functionally independent patients can mobilize with nursing or other mobilization staff. Hospitals should consider mobility score-based decision support to prioritize PT for impaired and at-risk patients.

The uptake of electric vehicles (EVs) and renewable energy technologies is changing the magnitude, variability, and direction of power flows in electricity networks. To ensure a successful transition to a net zero energy system, it will be necessary for a wide range of stakeholders to understand the impacts of these changing flows on networks. However, there is a gap between those with the data and capabilities to understand electricity networks, such as network operators, and those working on adjacent parts of the energy transition jigsaw, such as electricity suppliers and EV charging infrastructure operators. This paper describes the electric vehicle network analysis tool (EVENT), developed to help make network analysis accessible to a wider range of stakeholders in the energy ecosystem who might not have the bandwidth to curate and integrate disparate datasets and carry out electricity network simulations. EVENT analyses the potential impacts of low-carbon technologies on congestion in electricity networks, helping to inform the design of products and services. To demonstrate EVENT’s potential, we use an extensive smart meter dataset provided by an energy supplier to assess the impacts of electricity smart tariffs on networks. Results suggest both network operators and energy suppliers will have to work much more closely together to ensure that the flexibility of customers to support the energy system can be maximized, while respecting safety and security constraints within networks. EVENT’s modular and open-source approach enables integration of new methods and data, future-proofing the tool for long-term impact.

The legal brief is a primary vehicle by which lawyers seek to persuade appellate judges. Despite wide acceptance that briefs are important, empirical scholarship has yet to establish their influence on the Supreme Court or fully explore justices’ preferences regarding them. We argue that emotional language conveys a lack of credibility to justices and thereby diminishes the party’s likelihood of garnering justices’ votes. The data concur. Using an automated textual analysis program, we find that parties who employ less emotional language in their briefs are more likely to win a justice’s vote, a result that holds even after controlling for other features correlated with success, such as case quality. These findings suggest that advocates seeking to influence judges can enhance their credibility and attract justices’ votes by employing measured, objective language.

We provide evidence of a network of information flow between activists and other investors prior to 13D filings. We match EDGAR search activity to investor IP addresses, identifying specific investors who persistently download information on an individual activist’s campaign targets in the days prior to that activist’s 13D disclosures. This outside investor’s knowledge of pending activist campaign plans seems to benefit both parties: the informed investor, unnamed in the 13D, increases its holdings in the targeted stock prior to the price surge upon 13D disclosure, while the activist earns voting support that increases their likelihood of pursuing and winning a proxy fight.

Our understanding of homogeneous vapour bubble growth is currently restricted to asymptotic descriptions of their limiting behaviour. While attempts have been made to incorporate both the inertial and thermal limits into bubble growth models, the early stages of bubble growth have not been captured. By accounting for both the changing inertial driving force and the thermal restriction to growth, we present an inertio-thermal model of homogeneous vapour bubble growth, capable of accurately capturing the evolution of a bubble from the nano- to the macro-scale. We compare our model predictions with: (a) published experimental and numerical data, and (b) our own molecular simulations, showing significant improvement over previous models. This has potential application in improving the performance of engineering devices, such as ultrasonic cleaning and microprocessor cooling, as well as in understanding of natural phenomena involving vapour bubble growth.