Objectives/Goals: To address the manual, time-consuming processes of validating IRB compliance and ensuring the secure delivery of i2b2 data, this project automates compliance checks, streamlines Protected Health Information (PHI) access, and provides timely, secure data availability while reducing administrative burdens and non-compliance risks. Methods/Study Population: This project enhances the i2b2 application to automate compliance processes and facilitate secure data delivery through integration with REDCap. By linking i2b2 with the IRB system, the application performs automatic compliance checks for project requests, verifying GCP and HIPAA certifications, only allowing the release of IRB-approved PHI variables, safeguarding against unauthorized data access. Manual signatures confirm non-automated compliance processes. Once verified, the application automatically creates a REDCap project, assigns user access, and securely delivers data, ensuring compliance with HIPAA regulations. Results/Anticipated Results: The automated system successfully streamlined IRB compliance checks and data delivery for i2b2 requests. Validation of certifications like GCP and HIPAA, now occurs automatically, significantly reducing the risk of non-compliance. Personnel access to data is limited to IRB-approved PHI, ensuring data security and adherence to institutional standards. The integration with REDCap has reduced manual processes, cutting data request processing time to approximately 30 minutes. Researchers and administrative staff experienced a notable decrease in administrative burden, with faster, more efficient access to approved data while maintaining full compliance with IRB and HIPAA regulations. Discussion/Significance of Impact: The lessons learned can be adapted by institutions to improve compliance efficiency and reduce administrative overhead. Implementing similar automation of certification checks and data delivery, sites can enhance data security, minimize errors, and ensure faster, compliant access to research data.

There has been limited focus placed on exploring food insecurity within the UK-ex-Armed Forces population. The present study aims to build on initial work by investigating the prevalence and associated factors of food insecurity within UK veterans and their families and their current health status. 881 veterans (or a family member) who previously served in the Royal Navy and Royal Marines, Army and the Royal Air Force completed an online survey to explore health status, food insecurity and receipt of benefits. In total, 16.9% of survey respondents were part of food-insecure households, with 12% of these also experiencing some element of hunger. Working age, non-officer rank at the time of service discharge, not being married, living in rented accommodation, having at least one medical condition and in receipt of other benefits were significant risk factors associated with food insecurity. Understanding the specific risk factors associated with food insecurity is vital to develop personalised interventions and policies, such as income support programmes and affordable housing initiatives. However, more work is needed to further explore the factors associated with food insecurity, particularly in the long term.

Boduch-Grabka and Lev-Ari (2021) showed that so-called “native” British-English speakers judged statements produced by Polish-accented English speakers as less likely to be true than statements produced by “native” speakers and that prior exposure to Polish-accented English speech modulates this effect. Given the real-world consequences of this study, as well as our commitment to assessing and mitigating linguistic biases, we conducted a close replication, extending the work by collecting additional information about participants’ explicit biases towards Polish migrants in the UK. We did not reproduce the original pattern of results, observing no effect of speaker accent or exposure on comprehension or veracity. In addition, the measure of explicit bias did not predict differential veracity ratings for Polish- and British-accented speech. Although the current pattern of results differs from that of the original study, our finding that neither comprehension nor veracity were impacted by accent or exposure condition is not inconsistent with the Boduch-Grabka and Lev-Ari (2021) processing difficulty account of the accent-based veracity judgment effect. We explore possible explanations for the lack of replication and future directions for this work.

Archaeologists tend to produce slow data that is contextually rich but often difficult to generalize. An example is the analysis of lithic microdebitage, or knapping debris, that is smaller than 6.3 mm (0.25 in.). So far, scholars have relied on manual approaches that are prone to intra- and interobserver errors. In the following, we present a machine learning–based alternative together with experimental archaeology and dynamic image analysis. We use a dynamic image particle analyzer to measure each particle in experimentally produced lithic microdebitage (N = 5,299) as well as an archaeological soil sample (N = 73,313). We have developed four machine learning models based on Naïve Bayes, glmnet (generalized linear regression), random forest, and XGBoost (“Extreme Gradient Boost[ing]”) algorithms. Hyperparameter tuning optimized each model. A random forest model performed best with a sensitivity of 83.5%. It misclassified only 28 or 0.9% of lithic microdebitage. XGBoost models reached a sensitivity of 67.3%, whereas Naïve Bayes and glmnet models stayed below 50%. Except for glmnet models, transparency proved to be the most critical variable to distinguish microdebitage. Our approach objectifies and standardizes microdebitage analysis. Machine learning allows studying much larger sample sizes. Algorithms differ, though, and a random forest model offers the best performance so far.

The cornerstone of obesity treatment is behavioural weight management, resulting in significant improvements in cardio-metabolic and psychosocial health. However, there is ongoing concern that dietary interventions used for weight management may precipitate the development of eating disorders. Systematic reviews demonstrate that, while for most participants medically supervised obesity treatment improves risk scores related to eating disorders, a subset of people who undergo obesity treatment may have poor outcomes for eating disorders. This review summarises the background and rationale for the formation of the Eating Disorders In weight-related Therapy (EDIT) Collaboration. The EDIT Collaboration will explore the complex risk factor interactions that precede changes to eating disorder risk following weight management. In this review, we also outline the programme of work and design of studies for the EDIT Collaboration, including expected knowledge gains. The EDIT studies explore risk factors and the interactions between them using individual-level data from international weight management trials. Combining all available data on eating disorder risk from weight management trials will allow sufficient sample size to interrogate our hypothesis: that individuals undertaking weight management interventions will vary in their eating disorder risk profile, on the basis of personal characteristics and intervention strategies available to them. The collaboration includes the integration of health consumers in project development and translation. An important knowledge gain from this project is a comprehensive understanding of the impact of weight management interventions on eating disorder risk.

The U.S. has the tools to end the HIV epidemic, but progress has stagnated. A major gap in U.S. efforts to address HIV is the under-utilization of medications that can virtually eliminate acquisition of the virus, known as pre-exposure prophylaxis (PrEP). This document proposes a financing and delivery system to unlock broad access to PrEP for those most vulnerable to HIV acquisition and bring an end to the HIV epidemic.

This special edition of JLME centers on a novel proposal for a national PrEP access program with the potential to break through a failed status quo.

Background: Carbapenem resistance in gram-negative organisms is an important public health problem. The CDC conducted Sentinel surveillance in 2018–2019 to characterize these organisms from 9 facilities in 9 different states. Methods: Carbapenem-resistant Enterobacterales (CRE), Pseudomonas aeruginosa (CRPA), and Acinetobacter spp (CRA) obtained from clinical samples of patients in acute-care or long-term care facilities were submitted to the CDC. Identification was confirmed using matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF), and antimicrobial susceptibility testing (AST) was performed via broth microdilution for 27 antibiotics. All confirmed CRE and CRPA were tested for carbapenemase production (CP) using the modified carbapenem inactivation method (mCIM). The isolates that were mCIM-positive were assessed by real-time PCR for presence of blaKPC, blaNDM, blaVIM, and blaIMP. CP-CRE were also assessed for blaOXA-48-like. All confirmed CRA were tested for the same genes as CRPA and blaOXA-23–like, blaOXA-24/40-like, blaOXA-58–like, and blaOXA-235–like genes. Difficult-to-treat resistance (DTR) was defined as resistance to all β-lactams (excluding newer β-lactam combination agents) and quinolones tested. Results: The CDC confirmed 208 CRE, 161 CRPA, and 94 CRA. Table 1 summarizes AST results for a selection of drugs. We identified 112 (53.8%) mCIM-positive CRE and 6 (3.7%) mCIM-positive CRPA. The PCR results are summarized in Table 2. One mCIM-positive and PCR-negative isolate was positive in a metallo-β-lactamase screen. Conclusions: Resistance among CRE and CRPA to newer β-lactam combination agents was detected. Options for treating CRA are limited. Of 112 CP-CRE, 85.7% harbored blaKPC; CP-CRPA were rare (3.7%); and most CRA harbored blaOXA-23-like (55.3%) or blaOXA-24/40-like (30.9%). Whole-genome sequencing is planned to better understand gene variants, sequence types, and additional resistance markers present among the isolates.

Funding: None

Disclosures: None

Background: Hepatitis C virus (HCV) transmission at outpatient hemodialysis clinics is well documented, but little is known about HCV transmission risks in long-term care facilities (LTCFs) providing hemodialysis services. LTCFs can provide onsite hemodialysis for residents by contracting with a licensed hemodialysis clinic to either provide its staff to the LTCF or to train LTCF staff as caregivers. In August 2019, the Georgia Department of Public Health (DPH) was notified about an HCV seroconversion in patient A at a LTCF providing onsite hemodialysis. Methods: Three residents (including patient A) were receiving hemodialysis at the LTCF in August 2019; patients B and C had chronic HCV infection upon admission. Records were reviewed for medical history, behavioral risk factors, and healthcare exposures. We conducted onsite infection control assessments and interviewed staff. Serum specimens were collected for all 3 patients in August 2019 and HCV tested for genetic similarity using Global Hepatitis Outbreak Surveillance Technology (GHOST). Results: The facility reported initiating onsite hemodialysis in November 2018; facility staff were trained by a dialysis provider. Patient A, admitted in September 2018, was anti-HCV negative in June 2019 and both anti-HCV and HCV RNA positive in July 2019. Patient B was admitted in December 2018, discharged for 1 month in May 2019, and then readmitted. Patients A and B reported previous injection drug use, and they were not observed by staff to use during their stay and had limited mobility. Patient A was wheelchair confined and B was bed confined. Patient C was admitted in May 2019. HCV samples from patients A and B both had HCV genotype 1b and demonstrated 100% genetic relatedness, indicating that patient B was the likely source. Patient C had HCV genotype 1a. Hemodialysis was provided to residents simultaneously in a converted resident room with 4 hemodialysis stations, and the LTCF operated 2 shifts, 3 times per week. We observed multiple infection control gaps, such as preparation of IV medications and inadequate disinfection in the shared dialysis treatment area. Recommendations addressing gaps were issued, and a follow-up site visit was conducted to validate implementation. With the exception of May 2019, patients A and B received hemodialysis on the same shift and days from December 2018 to September 2019. Conclusions: Phylogenetic and epidemiological results indicate HCV transmission likely occurred during hemodialysis services provided by the LTCF. As the provision of dialysis expands to nontraditional settings such as LTCFs, it is essential that proper infection control procedures and oversight are in place.

Funding: None

Disclosures: None

Animal disease events can lead to international trade restrictions which can vary in duration, products included, and geographical extent. Accounting for multilateral resistance between trading partners, a general gravity model of trade is estimated with a Hausman-Taylor and a Hausman-Taylor seemingly unrelated estimator to evaluate the trade quantity impact by commodity resulting from highly pathogenic poultry disease events in 24 exporting markets. Commodity specific results show that quantity traded and products demanded during a disease event differ by commodities. Understanding these impacts can better prepare exporters for potential changes in trade quantity given a disease event.

We examined the feasibility of linear programming (LP) to develop diets that were economical, included traditional (cultural, non-market) foods and met the dietary reference intakes (DRI) in a Canadian Indigenous population. Diet optimisation using LP is a mathematical technique that can develop food-based dietary guidelines for healthy eating in Indigenous populations where food insecurity, availability and cost are important considerations. It is a means of developing nutritionally optimal food combinations that are based on economical and culture-specific foods. Observed food consumption data were derived using 24-h food recalls from the First Nations Food, Nutrition and Environment Study. The LP models were constructed to develop diets meeting DRI, cost and food constraints. Achieving the recommended food intake was not feasible in a model meeting all nutrient requirements. Models that met most nutrient requirements at reduced cost were designed for men and women, separately. In women, it was necessary to increase energy intake to meet most nutrient requirements. Nutrient requirements could not be met for fibre, linoleic and linolenic acids, vitamin D, Ca and K in both sexes, P in women, and Mg and vitamin A in men. Using LP to develop optimal diets for First Nations people, we found simultaneous achievement of all DRI was difficult, suggesting that supplementation might be necessary which goes against recommendations for individuals to meet their nutrient needs through healthy eating patterns. Additionally, to make diets feasible, programmes to reduce market food costs and to support First Nations people in traditional food harvesting are recommended.

Based on radio and X-ray observations, it has been suggested that a black hole of mass ∼106 Mʘ resides in the dwarf starburst galaxy Henize 2-10. This unusual finding has important implications for the formation of massive black holes in the early universe since Henize 2-10 can be viewed as a low redshift analog to the first high-z galaxies. We present long-slit HST STIS spectra that include the central radio/X-ray source. While recent VLT-MUSE spectroscopic observations with 0″.7 seeing show no change in ionization near the central source, our higher spatial resolution STIS observations identify a distinct compact region at the location of the radio/X-ray source. Initial analysis reveals broader (FWHM ∼ 380 km s-1) blue-shifted lines of low ionization. Our analysis focuses on testing two scenarios: a LINER-like AGN and a young (few decades) SNR.