Objectives/Goals: Given the challenges that early career research scientists face, especially preparing for promotion and tenure, the decision on whether to join a research team can be fraught. We developed a novel training to support informed decision-making regarding new scientific teaming opportunities. Methods/Study Population: A team science workshop entitled “Should I join this research team” was designed for early career investigators from varied disciplinary backgrounds. Learning objectives for attendees included 1) describing the role of team science in translational research, 2) determining if teaming opportunities are a good fit, and 3) crafting thoughtful responses to requests. The training was initially delivered to 38 attendees (11 K scholars) during a virtual national meeting. We adapted this training for in-person delivery to K and T scholars at our CTSA regional partners. Instructional methods shared across virtual and in-person modalities included self-reflection, think and share activities, and scenario application. In-person delivery also included short video clips and small group discussions. Results/Anticipated Results: Multiple Likert-scale items were completed by workshop participants before and after completing the workshop to evaluate attendees’ confidence in their perceived abilities to explain strengths and limitations of team science, identify characteristics of effective science teams, evaluate a team invitation, assess costs and benefits, negotiate collaborative team invitations, etc. Preliminary data from the virtual workshop suggests that 54.6% of scholars were either not at all or only slightly confident in evaluating a teaming invitation. After the workshop, 45.5% reported being very confident, and 9.1% reported extreme confidence in evaluating a team invitation. Evaluation of the in-person training, along with a comparison of virtual and in-person learning outcomes will also be presented. Discussion/Significance of Impact: Our multimodal training is designed to equip early career investigators with the tools needed to evaluate and respond effectively to research team invitations. We believe this novel training will result in informed teaming decisions for early career research scientists.

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.

Background: Medicare claims are frequently used to study Clostridioides difficile infection (CDI) epidemiology. Categorizing CDI based on location of onset and potential exposure is critical in understanding transmission patterns and prevention strategies. While claims data are well-suited for identifying prior healthcare utilization exposures, they lack specimen collection and diagnosis dates to assign likely location of onset. Algorithms to classify CDI onset and healthcare association using claims data have been published, but the degree of misclassification is unknown. Methods: We linked patients with laboratory-confirmed CDI reported to four Emerging Infections Program (EIP) sites from 2016-2020 to Medicare beneficiaries using residence, birth date, sex, and hospitalization and/or healthcare exposure dates. Uniquely linked patients with fee-for-service Medicare A/B coverage and complete EIP case report forms were included. Patients with a claims CDI diagnosis code within ±28 days of a positive CDI test reported to EIP were categorized as hospital-onset (HO), long-term care facility onset (LTCFO), or community-onset (CO, either healthcare facility-associated [COHCFA] or community-associated [CA]) using a previously published algorithm based on claim type, ICD-10-CM code position, and duration of hospitalization (if applicable). EIP classifies CDI into these categories using positive specimen collection date and other information from chart review (e.g. admit/discharge dates). We assessed concordance of EIP and claims case classifications using Cohen’s kappa. Results: Of 10,002 eligible EIP-identified CDI cases, 7,064 were linked to a unique beneficiary; 3,451 met Medicare A/B fee-for-service coverage inclusion criteria. Of these, 650 (19%) did not have a claims diagnosis code ±28 days of the EIP specimen collection date (Table); 48% (313/650) of those without a claims diagnosis code were categorized by EIP as CA CDI. Among those with a CDI diagnosis code, concurrence of claims-based and EIP CDI classification was 68% (κ=0.56). Concurrence was highest for HO and lowest for COHCFA CDI. A substantial number of EIP-classified CO CDIs (30%, Figure) were misclassified as HO using the claims-based algorithm; half of these had a primary ICD-10 diagnosis code of sepsis (226/454; 50%). Conclusions: Evidence of CDI in claims data was found for 81% of EIP-reported CDI cases. Medicare classification algorithms concurred with the EIP classification in 68% of cases. Discordance was most common for community-onset CDI patients, many of whom were hospitalized with a primary diagnosis of sepsis. Misclassification of CO-CDI as HO may bias findings of claims-based CDI studies.

Background: Extrapulmonary nontuberculous mycobacteria (ENTM) infections are difficult to treat and often require prolonged therapy or surgery. Few population-based studies describe ENTM epidemiology, though well-known healthcare-associated outbreaks have occurred. Using the first year of multi-site ENTM surveillance, we characterized rates and how frequently ENTM infections may be related to healthcare. Methods: CDC’s Emerging Infections Program conducted active, laboratory- and population-based surveillance for ENTM cases in 4 sites (Colorado [5 counties], Minnesota [statewide], New York [1 county], and Oregon [statewide]) in 2021. An incident ENTM case was NTM isolation from a non-pulmonary specimen, excluding stool or rectal swabs, in a resident of the surveillance area without either medical record documentation of prior ENTM infection or isolation of ENTM in the prior 12 months. Demographic, clinical, information on selected healthcare and community exposures, and laboratory data were collected via medical record review. We calculated incidence per 100,000 population using U.S. Census population estimates and performed descriptive analyses. Results: A total of 180 incident ENTM cases were reported in 2021. The crude annual incidence rate was 1.3 per 100,000 persons. Incidence increased with age (from 0.95 per 100,000 among 0–17 year-olds to 2.65 per 100,000 among persons ≥65), ranged from 0.8 among non-Hispanic Asian persons to 1.6 per 100,000 in non-Hispanic Black persons, and was similar among males (1.3 per 100,000) and females (1.4 per 100,000; Figure 1). Mycobacterium avium complex (64 [35.6%]) was the most frequently isolated species group, followed by Mycobacterium chelonae complex (31 [17.2%]). Skin and soft tissue infections were the most frequent infection type (37 [20.6%]); 27 cases (15.0%) were associated with disseminated and/or only bloodstream infection, and 56 cases (31.1%) had no infection type documented. Among 93 cases with localized ENTM infections (i.e., infections that were not disseminated and/or only bloodstream infections), 38.7% had only healthcare-related exposures, 14% had only community-related exposures and 6.5% had both exposure types at the site of infection (Figure 2). Healthcare-related exposures at the infection site included surgery (23.7%), injection/infusion (21.5%), and medical devices (18.3%). The most frequent community-related exposure at the infection site was trauma (17.2%). Only one case was part of a known outbreak, which was healthcare-associated. Conclusions: ENTM infections are relatively rare, but nearly half of patients with localized ENTM infections had prior healthcare-related exposures. This indicates that the burden of ENTM infections related to healthcare may be much larger than what has been suggested from reported outbreaks.

Crop foraging by African savannah elephants Loxodonta africana negatively affects farmer livelihoods and support for conservation, yet affordable, sustainable and practical solutions remain elusive. To inform conservation priorities, our goal was to assess the hitherto little explored relationships between farmers’ views on agricultural damage and the socio-economic factors limiting their use of elephant deterrents. We tested our hypotheses associated with the demographic categories of age, education level, years spent farming, gender, exposure to information on deterrent methods, farm size, village and relevant combinations of these factors by surveying 206 respondents across six villages in rural Kenya and analysing the resulting data using an information theoretic approach. Respondents were almost four times more likely to use deterrents if exposed to the relevant information, and almost five times more likely to do so if they had secondary education as opposed to none. Farmers with a higher level of education were five times more likely to have received information on deterrents compared to those with no formal education. Participants who had not received information on deterrents were almost three times more likely to believe that they could implement deterrent methods. Respondents who stated that they could not implement deterrents overwhelmingly cited a lack of financial resources as the reason. Overall, we found that crucial information on reducing elephant crop foraging is not reaching the relevant stakeholders, and socio-economic factors such as education and exposure to information appear to limit uptake of protective measures. These insights are important for developing mitigation strategies and supporting the livelihoods of people affected by negative human–elephant interactions, and thus for effective elephant conservation. Our findings also have broader applications for practitioners seeking to understand barriers stakeholders face in their efforts to mitigate negative interactions with wildlife.

OBJECTIVES/GOALS: In this study, we aim to report the role of porins and blaCTX-M β-lactamases among Escherichia coli and Klebsiella pneumoniae, focusing on emerging carbapenem resistant Enterobacterales (CRE) subtypes, including non-carbapenemase producing Enterobacterales (NCPE) and ertapenem-resistant but meropenem-susceptible (ErMs) strains. METHODS/STUDY POPULATION: Whole genome sequencing was conducted on 76 carbapenem-resistant isolates across 5 hospitals in San Antonio, U.S. Among these, NCP isolates accounted for the majority of CRE (41/76). Identification and antimicrobial susceptibility testing (AST) results were collected from the clinical charts. Repeat speciation was determined through whole genome sequencing (WGS) analysis and repeat AST, performed with microdilution or ETEST®. Minimum inhibitory concentrations (MIC) were consistent with Clinical and Laboratory Standards Institute (CLSI M100, ED33). WGS and qPCR were used to characterize the resistome of all clinical CRE subtypes, while western blotting and liquid chromatography with tandem mass spectrometry (LC-MS-MS) were used to determine porin expression and carbapenem hydrolysis, respectively. RESULTS/ANTICIPATED RESULTS: blaCTX-Mwas found to be most prevalent among NCP isolates (p = 0.02). LC-MS/MS analysis of carbapenem hydrolysis revealed that blaCTX-M-mediated carbapenem hydrolysis, indicating the need to reappraise the term, “non-carbapenemase (NCP)®” for quantitatively uncharacterized CRE strains harboring blaCTX-M. Susceptibility results showed that 56% of all NCPE isolates had an ErMs phenotype (NCPE vs. CPE, p < 0.001), with E. coli driving the phenotype (E. coli vs. K. pneumoniae, p < 0.001). ErMs strains carrying blaCTX-M, had 4-fold more copies of blaCTX-M than ceftriaxone-resistant but ertapenem-susceptible isolates (3.7 v. 0.9, p < 0.001). Immunoblot analysis demonstrated the absence of OmpC expression in NCP-ErMs E. coli, with 92% of strains lacking full contig coverage ofompC. DISCUSSION/SIGNIFICANCE: Overall, this work provides evidence of a collaborative effort between blaCTX-M and OmpC in NCP strains that confer resistance to ertapenem but not meropenem. Clinically, CRE subtypes are not readily appreciated, potentially leading to mismanagement of CRE infected patients. A greater focus on optimal treatments for CRE subtypes is needed.

The National COVID Cohort Collaborative (N3C) is a public–private–government partnership established during the Coronavirus pandemic to create a centralized data resource called the “N3C data enclave.” This resource contains individual-level health data from participating healthcare sites nationwide to support rapid collaborative analytics. N3C has enabled analytics within a cloud-based enclave of data from electronic health records from over 17 million people (with and without COVID-19) in the USA. To achieve this goal of a shared data resource, N3C implemented a shared governance strategy involving stakeholders in decision-making. The approach leveraged best practices in data stewardship and team science to rapidly enable COVID-19-related research at scale while respecting the privacy of data subjects and participating institutions. N3C balanced equitable access to data, team-based scientific productivity, and individual professional recognition – a key incentive for academic researchers. This governance approach makes N3C research sustainable and effective beyond the initial days of the pandemic. N3C demonstrated that shared governance can overcome traditional barriers to data sharing without compromising data security and trust. The governance innovations described herein are a helpful framework for other privacy-preserving data infrastructure programs and provide a working model for effective team science beyond COVID-19.

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.