Paleontology provides insights into the history of the planet, from the origins of life billions of years ago to the biotic changes of the Recent. The scope of paleontological research is as vast as it is varied, and the field is constantly evolving. In an effort to identify “Big Questions” in paleontology, experts from around the world came together to build a list of priority questions the field can address in the years ahead. The 89 questions presented herein (grouped within 11 themes) represent contributions from nearly 200 international scientists. These questions touch on common themes including biodiversity drivers and patterns, integrating data types across spatiotemporal scales, applying paleontological data to contemporary biodiversity and climate issues, and effectively utilizing innovative methods and technology for new paleontological insights. In addition to these theoretical questions, discussions touch upon structural concerns within the field, advocating for an increased valuation of specimen-based research, protection of natural heritage sites, and the importance of collections infrastructure, along with a stronger emphasis on human diversity, equity, and inclusion. These questions offer a starting point—an initial nucleus of consensus that paleontologists can expand on—for engaging in discussions, securing funding, advocating for museums, and fostering continued growth in shared research directions.

Background: Admission screening for CRO carriage may prevent transmission, but there is a lack of consensus on the best targeted approach. Using a well-characterized cohort of medical intensive care unit (MICU) patients prospectively screened for CRO carriage at time of admission (MAriMbA cohort), we compared the effectiveness of common targeted strategies (singly and in combination) available to hospitals in Illinois to identify MICU patients at risk for CRO carriage, including: (a) screening patients transferred from external facilities (e.g., short- and long-term acute care hospitals); (b) screening patients with a tracheostomy or pressure ulcer; or (c) querying the Illinois XDRO registry for prior CRO history. Methods: Results of rectal swab samples collected within 48 hours of MICU admission during 1/2017-1/2018 and cultured for CROs (carbapenem-resistant Enterobacterales [CRE], CR Pseudomonas aeruginosa [CRPA], and CR Acinetobacter baumannii [CRAB]) were used as the reference standard. Patients’ status as direct transfer from an external healthcare facility and presence of tracheostomy or pressure ulcer were collected prospectively during the MAriMbA study. History of CRO colonization before MICU admission was queried retrospectively from the Illinois XDRO Registry (xdro.org), with the limitation that most reports available during the study period were restricted to CRE. We evaluated each predictors’ independent association with admission CRO status and combined variables in a planned logistic regression modeling approach. Results: CRO colonization was detected in 37 (2.6%; including 26 CRE, 10 CRPA, and 1 patient co-colonized with CRE and CRAB) of 1,423 unique MICU admissions. For univariate analyses, presence of a tracheostomy (OR 9.32, 95% CI 4.29-20.27), presence of pressure ulcer (OR 3.07, 95% CI 1.42-6.64), transfer from an external healthcare facility (OR 1.97, 95% CI 1.02-3.82), and prior CRO history reported to the Illinois XDRO Registry (OR 72.96, 95% CI 25.83-206.07) were associated with higher odds of CRO colonization. A model combining these variables improved the predictive capability (AUC 0.73) (Table). Prior CRO history reported to the Illinois XDRO Registry identified 27% of CRO cases, with number needed to screen (NNS) of only 2 patients. Adding tracheostomy, pressure ulcer, and external facility transfer together improved detection of admission CRO cases to 68%, with NNS of 20 patients (Figure). Conclusion: In a region with well-established inter-facility communication of CRO history via the Illinois XDRO Registry, the addition of screening patients with a tracheostomy, transfer from an external facility, or pressure ulcer may improve early identification of CRO carriage at time of MICU admission.

Background: Clostridioides difficile infection (CDI) disproportionately impacts hematology-oncology patients. In June 2022, our hospital implemented screening of asymptomatic patients admitted to the hematology-oncology unit to reduce CDI rates by early identification and isolation of C. difficile carriers. We evaluated the impact of admission screening on rates of CDI and compared incidence of diarrhea and subsequent symptomatic testing stratified by asymptomatic admission testing result. Method: During the intervention period (July 2022 – July 2024), asymptomatic patients admitted to the hematology-oncology unit were tested for C. difficile (perirectal swab, Cepheid GeneXpert®, Sunnyvale, CA). Guidelines for C. difficile symptomatic testing (unformed stool, Cepheid GeneXpert®) and treatment did not change between the baseline (May 2020 – May 2022) and intervention periods. Monthly CDI rates were calculated using CDC definitions based on clinical symptoms and positive C. difficile testing (community onset [CO] if positive in the first three hospital days, hospital-onset [HO] if day 4 or later). We performed an interrupted time-series analysis adjusted for repeated measures to compare CO-CDI and HO-CDI rates per 10,000 patient-days between baseline and intervention periods. The risk of developing diarrhea through hospital day 14 or being tested for symptomatic CDI during the intervention’s first year (July 2022 – June 2023) was analyzed using a cohort of asymptomatic C. difficile carriers and non-carriers in a 1:2 ratio, matched on hospital length of stay and date of admission. Result: The incidence rate ratio was 0.45 (P=0.10) for HO-CDI (Figure 1) and 0.15 (P=0.049) for CO-CDI (Figure 2) after screening implementation. During the first year of the intervention, 25 individuals were identified as asymptomatic C. difficile carriers by positive admission screen and were matched to a cohort of 50 asymptomatic non-carriers. There were no significant differences in development of diarrhea during hospital days 1-3 or days 4-14 between carriers and non-carriers (Table). None of the carriers received symptomatic C. difficile testing during hospitalization, compared to 20% of matched non-carriers (P=0.03). Conclusion: There was no significant change in HO-CDI rates and a statistically significant reduction in CO-CDI rates after implementation of C. difficile admission screening. Patients identified as carriers at time of admission were less likely to be tested for CDI during hospitalization than non-carriers, despite similar rates of diarrhea. Admission screening for C. difficile may reduce CDI rates through a variety of mechanisms; changes in provider testing behavior for patients previously screened for C. difficile may play a role.

We present the Evolutionary Map of the Universe (EMU) survey conducted with the Australian Square Kilometre Array Pathfinder (ASKAP). EMU aims to deliver the touchstone radio atlas of the southern hemisphere. We introduce EMU and review its science drivers and key science goals, updated and tailored to the current ASKAP five-year survey plan. The development of the survey strategy and planned sky coverage is presented, along with the operational aspects of the survey and associated data analysis, together with a selection of diagnostics demonstrating the imaging quality and data characteristics. We give a general description of the value-added data pipeline and data products before concluding with a discussion of links to other surveys and projects and an outline of EMU’s legacy value.

Objectives/Goals: Identifying and indexing rare disease studies is labor intensive, especially in research centers with a large number of trials. To address this gap, we applied natural language processing (NLP) and visualization techniques to develop an efficient pipeline and user-friendly web interface. Our goal is to offer the rare disease study identification (RDSI) tool for adoption by other sites. Methods/Study Population: The RDSI retrieves study information (short and long titles, study abstract) from the IRB system. These descriptive fields are then processed by the MetaMap Lite NLP program for identifying disease terms and standardizing them to UMLS concepts. By terminology identifier mapping, the diseases intersecting with concepts in rare disease databases (Genetic and Rare Disease program and Orphanet) are further scored to pinpoint studies that focus on a rare disease. The web interface displays a scatter bubble chart as an overview of all the rare diseases, with each bubble size proportional to the number of studies for that disease. In addition to the visual navigation, users can search studies by disease name, PI, or IRB number. Search results contain detailed study information as well as the evidence used by algorithms of the pipeline. Results/Anticipated Results: The RDSI identification results and functions were verified manually and spot-checked by several study investigators. The web interface is a self-contained solution available to our staff for various use cases like reporting or environment scan. We have built in a versioning mechanism that logs the date of each major result in the process. Therefore, even as the rare disease data sources evolve over time, we will be able to preserve any historical context or perform updates as needed. The RDSI outputs are replicated to Mayo Clinic’s enterprise data warehouse daily, allowing tech-savvy users to leverage any useful intermediate results at the backend. We anticipate the performance of the rare disease identification to be further enhanced by employing the advancements in AI technology. Discussion/Significance of Impact: The RDSI represents an informatics solution that offers efficiency in identifying and navigating rare disease clinical studies. It features the use of public databases and open-source tools, manifesting return on investment from the broad translational science ecosystem. These considerations are informative and adoptable by other institutions.

Objectives/Goals: The operation of a clinical trials unit involves multifaceted tasks and stakeholders. A competent information system is critical to daily operations while ensuring smooth conduct of clinical research. We share 15 years of experience in the design and implementation of such a system at Mayo Clinic to inform other institutions with similar interests. Methods/Study Population: The Informatics team collaborated closely with nurse leaders and elicited input from additional stakeholders including nurse unit coordinators, lab managers, schedulers, investigators, study coordinators, and regulatory specialists throughout the phases of system design, development and continuous enhancements, and expansion. The stakeholders offered insights on the corresponding requirements throughout the study life cycle, from engaging with the study sponsor, operational review for protocol execution, development of study budgets, human subject protection and risk mitigation, data management and integration, to outcome monitoring, and regulatory reporting. The activities were then translated into functional components and implemented as a seamless and effective solution. Results/Anticipated Results: Patient safety, scientific rigor, operation automation, efficiency, and regulatory requirements were all considered in developing an integrated system, or the clinical research trials unit (CRTU) Tools. Our institution has leveraged the system for essential tasks from the study start-up, visit scheduling and execution, specimen collection and tracking, to individual protocol metrics and billing. We adopted a measure-as-we-go methodology so that data such as visit census, resource usage, and protocol deviation are tracked and collected during routine use of the system. Specifically, an issues/concerns/exceptions (ICE) tool is used for quality control and patient safety. Moreover, data quality greatly benefits from a task dictionary, standardizing the study activities that can be ordered and executed. Discussion/Significance of Impact: The implementation of a well-rounded clinical trials unit information system not only improves the operation efficiency and team productivity but also ensures scientific rigor and contributes to patient safety. We believe the experience can be informative to other institutions. More details will be shared in the poster.

Members of norsethite-type carbonate solid solutions with the compositions Ba(Mg1–xMnx)(CO3)2, (x = 0, 0.25, 0.50 and 0.75) have been synthesised under high-pressure and -temperature conditions (3GPa, 800°C) for the first time. The synthetic transparent crystals gradually changed their appearance from colourless to blue lustre with the increasing Mn2+ content (XMn). The results of the crystal structure analyses reveal that the lattice parameters (a, c, unit-cell volume, Mg/Mn–O bond lengths and Ba–O bond lengths) complied with a linear increase with XMn. In contrast, the C–O bond lengths and O–C–O bond angles decreased, because the CO32– group was squeezed by the expansion of the (Mg/Mn)O6 octahedra. Moreover, the Raman and infrared vibrations, except for the lattice mode T, shift to low frequency with the increasing XMn, and the slight corresponding variations of the atomic positions were also determined. These new results demonstrate the impact of Mg2+–Mn2+ substitution on the crystal chemistry of norsethite-type solid solutions, with further implications for the natural occurrence and environmental of norsethite-type and dolomite/ankerite-type carbonates.

Hypertensive heart disease and hypertrophic cardiomyopathy both lead to left ventricular hypertrophy despite differing in aetiology. Elucidating the correct aetiology of the presenting hypertrophy can be a challenge for clinicians, especially in patients with overlapping risk factors. Furthermore, drugs typically used to combat hypertensive heart disease may be contraindicated for the treatment of hypertrophic cardiomyopathy, making the correct diagnosis imperative. In this review, we discuss characteristics of both hypertensive heart disease and hypertrophic cardiomyopathy that may enable clinicians to discriminate the two as causes of left ventricular hypertrophy. We summarise the current literature, which is primarily focused on adult populations, containing discriminative techniques available via diagnostic modalities such as electrocardiography, echocardiography, and cardiac MRI, noting strategies yet to be applied in paediatric populations. Finally, we review pharmacotherapy strategies for each disease with regard to pathophysiology.

This study conducts experimental investigations into wake-induced vibration (WIV) of a circular cylinder placed downstream of an oscillating cylinder. Surprisingly, it is observed that the previously identified WIV phenomenon, characterized by a sustained increase in amplitude at higher reduced velocities, does not occur when the upstream cylinder oscillates at large amplitudes. Instead, a different phenomenon, which we refer to as the ‘wake-captured vibration’, becomes dominant. The experiments reveal a negative correlation between the vortex-induced vibration amplitude response of the upstream cylinder and the WIV amplitude response of the downstream cylinder. Through a quasi-steady and linear instability analysis, the study demonstrates that the previously proposed wake-displacement mechanism may not be applicable for predicting the cylinder WIV response in the wake of an oscillating body. This is because the lift force gradients across the wake, measured through stationary cylinder experiments, decrease significantly when the upstream cylinder vibrates at higher amplitudes. Consequently, actively controlled vibration experiments are conducted to systematically map the hydrodynamic properties of the downstream cylinder vibrating in the wake of an oscillating cylinder. The findings align with observations from free-vibration experiments, and help to explain the amplitude and frequency response of WIV. Additionally, wake visualization through particle image velocimetry is conducted to provide further insights into the complex wake and vortex–body interactions.

Background: Early identification of patients colonized with MDROs can help healthcare facilities improve infection control and treatment. We evaluated whether a model previously validated to predict carbapenem-resistant Enterobacterales (CRE) carriage on hospital admission (area under the curve [AUC]=0.86, Lin et al. OFID 2019) would generalize to predict a patient’s likelihood of CRE and non-CRE MDRO colonization at the time of medical intensive care unit (MICU) admission. Methods: We analyzed data collected previously in a retrospective observational cohort study of patients admitted to Rush University Medical Center’s MICU from 1/2017-1/2018 and screened within the first two days for rectal MDRO colonization. Organisms of interest included CRE, carbapenem-resistant Pseudomonas aeruginosa (CRPA), vancomycin-resistant enterococci (VRE), and third-generation cephalosporin-resistant Enterobacterales (3GCR-E). Methicillin-resistant Staphylococcus aureus (MRSA) nasal colonization at admission was determined by routine clinical screening. Each patient’s first MICU admission during the study period was linked to Illinois’ hospital discharge database and assigned a CRE colonization risk probability using the existing model. Model covariates were age, and during the prior 365 days, number of short-term acute care hospitalizations (STACH) and mean STACH length of stay, number of long-term acute care hospitalizations (LTACH) and mean LTACH length of stay, prior hospital admission with an ICD-10 diagnosis code indicating bacterial infection, and current admission to LTACH. Predictive value of the model was evaluated by receiver operating characteristic (ROC) curves. Results: We analyzed 1237 MICU admissions. MDRO admission prevalence is shown in the Table. The model performed well to predict carriage of healthcare-associated MDROs, including CRE, CRPA, composite CR-MDROs (CRE & CRPA), and VRE. However, the model performed poorly for MDROs with known community reservoirs, including 3GCR-E and MRSA (Table). In general, MDRO admission prevalence increased in parallel with predicted CRE colonization risk (Figure). The number needed to screen (NNS) to detect one healthcare-associated MDRO carrier was inversely related to the CRE colonization risk score. For example, NNS in the total cohort compared to those with CRE risk score of >0.5% was: CRE 111 vs 32 patients, CRPA 333 vs 42 patients, composite CR-MDRO 83 vs 18 patients, and VRE 12 vs 4 patients. However, higher CRE risk score cutoff was inversely related to screening sensitivity. Conclusion: A prediction model using prior healthcare exposure information successfully discriminated patients likely to harbor healthcare-associated MDROs upon MICU admission. Prediction scores generated by a public-health accessible database could be used to target screening/isolation or enact protective measures for high-risk patients.

Background: Indiscriminate urine culturing of patients with indwelling urinary catheters may lead to overdiagnosis of urinary tract infections, resulting in unnecessary antibiotic treatment and inaccurate reporting of catheter-associated urinary tract infections (CAUTIs) as a hospital quality metric. We evaluated the impact of a computerized diagnostic stewardship intervention to improve urine culture testing among patients with indwelling urinary catheters. Methods: We performed a single-center retrospective observational study at Rush University Medical Center from April 2018 – July 2023. In February 2021, we implemented a computerized clinical decision support tool to promote adherence to our internal urine culture guidelines for patients with indwelling urinary catheters. Providers were required to select one guideline criteria: 1) neutropenia, 2) kidney transplant, 3) recent urologic procedure, 4) urinary tract obstruction; or if none of the criteria were met, then an infectious diseases consultation was required for approval. We compared facility-wide CAUTI rate per 10,000 catheter days and standardized infection ratio (SIR) during baseline and intervention periods using ecologic models, controlling for time and for monthly Covid-19 hospitalizations. In the intervention period, we evaluated how providers responded to the intervention. Potential harm was defined as collection of a urine culture within 7 days of the intervention that resulted in a change in clinical management. Results: In unadjusted models, CAUTI rate decreased from 12.5 to 7.6 per 10,000 catheter days (p=0.04) and SIR decreased from 0.77 to 0.49 (p=0.09) during baseline vs intervention periods. In adjusted models, the CAUTI rate decreased from 6.9 to 5.5 per 10,000 catheter days (p=0.60) (Figure 1) and SIR decreased from 0.41 to 0.35 (p=0.65) during baseline vs intervention periods. Urine catheter standard utilization ratio (SUR) did not change (p=0.36). There were 598 patient encounters with ≥1 intervention. Selecting the first intervention for each encounter, 284 (47.5%) urine cultures met our guidelines for testing and 314 (52.5%) were averted (Figure 2). Of these, only 3 ( < 1 %) had a urine culture collected in the subsequent 7 days that resulted in change in clinical management. Conclusion: We observed a trend of decreased CAUTIs over time, but effect of our diagnostic stewardship intervention was difficult to assess due to healthcare disruption caused by Covid-19. Adverse outcomes were rare among patients who had a urine culture averted. A computerized clinical decision support tool may be safe and effective as part of a multimodal program to reduce unnecessary urine cultures in patients with indwelling urinary catheters.

The reading the mind in the eyes test (RMET) – which assesses the theory of mind component of social cognition – is often used to compare social cognition between patients with schizophrenia and healthy controls. There is, however, no systematic review integrating the results of these studies. We identified 198 studies published before July 2020 that administered RMET to patients with schizophrenia or healthy controls from three English-language and two Chinese-language databases. These studies included 41 separate samples of patients with schizophrenia (total n = 1836) and 197 separate samples of healthy controls (total n = 23 675). The pooled RMET score was 19.76 (95% CI 18.91–20.60) in patients and 25.53 (95% CI 25.19–25.87) in controls (z = 12.41, p < 0.001). After excluding small-sample outlier studies, this difference in RMET performance was greater in studies using non-English v. English versions of RMET (Chi [Q] = 8.54, p < 0.001). Meta-regression analyses found a negative association of age with RMET score and a positive association of years of schooling with RMET score in both patients and controls. A secondary meta-analysis using a spline construction of 180 healthy control samples identified a non-monotonic relationship between age and RMET score – RMET scores increased with age before 31 and decreased with age after 31. These results indicate that patients with schizophrenia have substantial deficits in theory of mind compared with healthy controls, supporting the construct validity of RMET as a measure of social cognition. The different results for English versus non-English versions of RMET and the non-monotonic relationship between age and RMET score highlight the importance of the language of administration of RMET and the possibility that the relationship of aging with theory of mind is different from the relationship of aging with other types of cognitive functioning.