Objectives/Goals: To design a flexible, comprehensive framework for Data Science Units to cultivate sustainable, long-term relationships with Clinical and Translational Science Research Units. Best practices for managing Data Science collaborations are presented to improve the quality and efficiency of research conducted throughout academic health centers. Methods/Study Population: Leaders of Data Science Units across six institutions formed a workgroup to develop guidance and best practices for Data Science Units to establish long-term, sustainable collaborations with Clinical and Translational Science Research Units. This guidance is based on tools and protocols developed and employed by the participating units, which range from larger groups with over 20 partnerships to a unit with three partnerships that is actively working to expand. Importantly, partnerships are highly variable, with some partnerships at one institution representing engagement with over 500 faculty, whereas some partnerships at another institution involve the lab of a single investigator. Results/Anticipated Results: We offer guidance in three domains: (1) Identifying the needs for a new partnership, including assessing required effort and data science expertise, setting partnership priorities, developing formal agreements, and identifying goals and metrics; (2) managing data science teams by implementing regular meetings, creating project intake and prioritization processes, and effort monitoring; and (3) evaluating the successes and failures/gaps of the collaboration by measuring the metrics mapped to the goals. For each domain, we provide specific suggestions on which parties should be involved and how frequently the processes should occur. This guidance is applicable both to larger collaborative partnerships and to smaller, single faculty or staff partnerships, whether they are new or well-established. Discussion/Significance of Impact: Effective collaboration between data scientists and clinical and translational investigators is key to advancing data-driven research. The guidance and resources are presented to support Data Science Units in successfully managing long-term collaborations through goal-development, evaluation, and adapting to evolving research needs.

The objective of this study was to investigate the impact of common mental disorder (CMD; depression/anxiety) symptoms and risky substance use in people with epilepsy in Ethiopia (four districts) on quality of life (QoL) and functioning over 6 months. A prospective cohort study was carried out. Multivariable linear regression followed by structural equation modelling (SEM) was employed. In the multivariable regression model, neither CMD symptoms (β coef. = −0.37, 95% confidence interval [CI] −1.30, +0.55) nor moderate to high risk of alcohol use (β coef. = −0.70, 95% CI −9.20, +7.81) were significantly associated with a change in QoL. In SEM, the summative effect of CMD on QoL was significant (B = −0.27, 95% CI −0.48, −0.056). Change in functional disability was not significantly associated with common mental disorder (CMD) symptoms (β coef. = −0.03, 95% CI −0.48, +0.54) or with moderate to high risk of alcohol use (β coef. = −1.31, 95% CI −5.89, 3.26). In the SEM model, functional disability was predicted by both CMD symptoms (B = 0.24, 95% CI 0.06, 0.41) and seizure frequency (B = 0.67, 95% CI 0.46, 0.87). In this rural Ethiopian setting, co-morbid CMD symptoms and seizure frequency independently predicted functional disability in people with epilepsy.

Given any toric subvariety Y of a smooth toric variety X of codimension k, we construct a length k resolution of ${\mathcal O}_Y$ by line bundles on X. Furthermore, these line bundles can all be chosen to be direct summands of the pushforward of ${\mathcal O}_X$ under the map of toric Frobenius. The resolutions are built from a stratification of a real torus that was introduced by Bondal and plays a role in homological mirror symmetry.

As a corollary, we obtain a virtual analogue of Hilbert’s syzygy theorem for smooth projective toric varieties conjectured by Berkesch, Erman and Smith. Additionally, we prove that the Rouquier dimension of the bounded derived category of coherent sheaves on a toric variety is equal to the dimension of the variety, settling a conjecture of Orlov for these examples. We also prove Bondal’s claim that the pushforward of the structure sheaf under toric Frobenius generates the derived category of a smooth toric variety and formulate a refinement of Uehara’s conjecture that this remains true for arbitrary line bundles.

Social contact refers to the facilitation of connection and interactions between people with and without mental health conditions. It can be achieved, for example, through people sharing their lived experience of mental health conditions, which is an effective strategy for stigma reduction. Meaningful involvement of people with lived experience (PWLE) in leading and co-leading anti-stigma interventions can/may promote autonomy and resilience. Our paper aimed to explore how PWLE have been involved in research and anti-stigma interventions to improve effective means of involving PWLE in stigma reduction activities in LMICs. A qualitative collective case study design was adopted. Case studies from four LMICs (China, Ethiopia, India and Nepal) are summarized, briefly reflecting on the background of the work, alongside anticipated and experienced challenges, strategies to overcome these, and recommendations for future work. We found that the involvement of PWLEs in stigma reduction is commonly a new concept in LMIC. Experienced and anticipated challenges were similar, such as identifying suitable persons to engage in the work and sustaining their involvement. Such an approach can be difficult because PWLE might be apprehensive about the negative consequences of disclosure. In many case studies, we found that long-standing professional connectedness, continued encouragement, information sharing, debriefing and support helped the participants’ involvement. We recommend that confidentiality of the individual, cultural norms and family concerns be prioritized and respected during the implementation. Taking into account socio-cultural contextual factors, it is possible to directly involve PWLEs in social contact-based anti-stigma interventions.

Medical researchers are increasingly prioritizing the inclusion of underserved communities in clinical studies. However, mere inclusion is not enough. People from underserved communities frequently experience chronic stress that may lead to accelerated biological aging and early morbidity and mortality. It is our hope and intent that the medical community come together to engineer improved health outcomes for vulnerable populations. Here, we introduce Health Equity Engineering (HEE), a comprehensive scientific framework to guide research on the development of tools to identify individuals at risk of poor health outcomes due to chronic stress, the integration of these tools within existing healthcare system infrastructures, and a robust assessment of their effectiveness and sustainability. HEE is anchored in the premise that strategic intervention at the individual level, tailored to the needs of the most at-risk people, can pave the way for achieving equitable health standards at a broader population level. HEE provides a scientific framework guiding health equity research to equip the medical community with a robust set of tools to enhance health equity for current and future generations.

OBJECTIVES/GOALS: Despite a steady rise of graduate degrees in biostatistics earned in the US, the percent from minorities remains low. This poster will describe the Collaborative Undergraduate Biostatistics Experience (CUBE), an 8-week program aimed to diversify and bring awareness to the field of collaborative biostatistics, from recruitment through evaluation. METHODS/STUDY POPULATION: The CUBE program is funded jointly by the NIH’s NIDA/NIAAA (award number: 1R25DA058482-01) and is designed to give underrepresented minority (URM) undergraduate students in STEM the opportunity to engage in a collaborative biostatistics and health data science experience, along with related professional development activities. The program is built on four pillars: 1) training in introductory biostatistics, 2) training in R programming, 3) professional development, and 4) a collaborative research project addressing research questions in various disciplines. The CUBE program was delivered in the summer of 2022 as a pilot to four URM students at Virginia Tech (VT) and the University of Virginia (UVA), with two at each site. In summer 2023, the program was offered to 5 students (3 VT, 2 UVA). RESULTS/ANTICIPATED RESULTS: This poster will provide strategies learned over two summers with respect to recruitment and enrollment, along with details on the program content, timeline, and short- and long-term program evaluation metrics (both quantitative and qualitative). The CUBE program was well-received by students participating in summers 2022 and 2023, where improved attitudes towards statistics were demonstrated, and 7 of the total 9 participants (78%) over the past two summers expressed interest in pursuing a graduate degree in biostatistics or a career in quantitative research. Of these 7 students, 1 is currently enrolled in a biostatistics graduate program in the United States. DISCUSSION/SIGNIFICANCE: Results can be used to offer recommendations to leaders in the field on how to establish similar programs seeking to provide a pipeline for equity and diversity in the practice of collaborative biostatistics and health data science.

We evaluated the effectiveness of community-based rehabilitation (CBR) in reducing depressive symptoms, alcohol use disorder, food insecurity and underweight in people with schizophrenia. This cluster-randomised controlled trial was conducted in a rural district of Ethiopia. Fifty-four sub-districts were allocated in a 1:1 ratio to the facility-based care [FBC] plus CBR arm and the FBC alone arm. Lay workers delivered CBR over 12 months. We assessed food insecurity (self-reported hunger), underweight (BMI< 18.5 kg/m2), depressive symptoms (PHQ-9) and alcohol use disorder (AUDIT ≥ 8) at 6 and 12 months. Seventy-nine participants with schizophrenia in 24 sub-districts were assigned to CBR plus FBC and 87 participants in 24 sub-districts were assigned to FBC only. There was no evidence of an intervention effect on food insecurity (aOR 0.52, 95% CI 0.16–1.67; p = 0.27), underweight (aOR 0.44, 95% CI 0.17–1.12; p = 0.08), alcohol use disorder (aOR 0.82, 95% CI 0.24–2.74; p = 0.74) or depressive symptoms (adjusted mean difference − 0.06, 95% CI −1.35, 1.22; p = 0.92). Psychosocial interventions in low-resource settings should support access to treatment amongst people with schizophrenia, and further research should explore how impacts on economic, physical and mental health outcomes can be achieved.

‘Animal Ethics Dilemma’ is a freely available computer-supported learning tool (www.animalethicsdilemma.net or www.aedilemma.net) which has been developed primarily for veterinary undergraduates but is applicable also to students in other fields of animal science. The objectives of the computer program are to promote students' understanding of the ethics related to animal use, to illustrate ethical dilemmas that arise in animal use, to broaden students' moral imagination, and to enable students to differentiate between types of ethical argument. The program comprises five case studies: (1) the blind hens; (2) ANDi the genetically modified monkey; (3) euthanasia of a healthy dog; (4) animal slaughter; and (5) rehabilitation of seals. Special consideration has been given to enhancing the pedagogic value of the program. Students can control their learning by selecting a variety of ways to explore the program; for example, they can navigate the program using the ‘Assist Me’ option, which explains the basis of the ethical arguments. Reality text provides details of real events on which the case is based, and a glossary of terminology is available for the students to explore. Selected access to a case template is also available, enabling students and teachers to create their own case studies. Evaluation of the program has been ongoing during its development.

Expansion of the meat inspection process to incorporate animal-based welfare measurements could contribute towards significant improvements in pig (Sus scrofa domesticus) welfare and farm profitability. This study aimed to determine the prevalence of different welfare-related lesions on the carcase and their relationship with carcase condemnations (CC) and carcase weight (CW). The financial implications of losses associated with CC and CW reductions related to the welfare lesions were also estimated. Data on tail lesions, loin bruising and bursitis, CW and condemnation/trimming outcome (and associated weights) were collected for 3,537 slaughter pigs (mean [± SEM] carcase weight: 79.2 [± 8.82] kg). Overall, 72.5% of pigs had detectable tail lesions, whilst 16.0 and 44.0% were affected by severe loin bruising and hind limb bursitis, respectively. There were 2.5% of study carcases condemned and a further 3.3% were trimmed. The primary cause of CC was abscessation. While tail lesion severity did not increase the risk of abscessation, it was significantly associated with CC. Male pigs had a higher risk of tail lesions and of CC. The financial loss to producers associated with CC and trimmings was estimated at €1.10 per study pig. CW was reduced by up to 12 kg in cases of severe tail lesions. However, even mild lesions were associated with a significant reduction in CW of 1.2 kg. The value of the loss in potential CW associated with tail lesions was €0.59 per study pig. Combined with losses attributable to CC and trimmings this represented a loss of 43% of the profit margin per pig, at the time of the study, attributable to tail biting. These findings illustrate the magnitude of the impact of tail biting on pig welfare and on profitability of the pig industry. They also emphasise the potential contribution that the inclusion of welfare parameters at meat inspection could make to pig producers in informing herd health and welfare management plans.

The greatest challenge to the welfare of dairy cows occurs in the peripartum period. Given the perception that cow welfare is better in more natural environments, it was hypothesised that cows in a PASTURE-based production system (cubicle housing with grass silage pre-partum and rotational grazing with concentrate supplementation post-partum) would have improved peripartal welfare compared to cows in a HOUSED production system (cubicle housing with a total mixed ration [TMR], pre-partum and post-partum). Blood samples were analysed for acute phase proteins (APP), cortisol, white blood cell (WBC) differential and counts and other biochemical metabolites as non-specific indicators of sub-clinical ill-health and nutritional stress. Daily monitoring of rectal temperature (RT) and rumen fill (RF) scores were used to monitor ill-health and nutritional status. Reproductive health and welfare (calving difficulty, retained placenta, puerperal metritis, endometritis and oestrous cyclicity) was also recorded. No differences were found between treatments for APP, cortisol or WBC. Blood metabolite differences indicated that PASTURE cows were under greater nutritional stress than HOUSED cows. HOUSED cows showed an increase in RF score from day 0 to 10 post-partum and had a higher RF score than PASTURE cows. PASTURE cows had an overall lower RT and lower incidence of reproductive disorders. Results primarily reflect nutritional differences between treatments with PASTURE cows showing greater potential nutritional/metabolic stress in early lactation which has attendant implications for welfare. Nevertheless, this did not result in inferior health and, in accordance with our hypothesis, PASTURE cows’ reproductive health and welfare tended to be better than that of HOUSED cows.

A survey of attitudes towards the welfare and rights of animals was conducted in universities in 11 European and Asian countries, to improve understanding of cultural differences that might impact on trade and international relations. Collaborators’ universities were recruited in each country to assist in the design, translation and administration of the survey via the internet in a convenient selection of the country's universities, providing 3,433 student responses from at least 103 universities. Respondents rated the acceptability of 43 major concerns about animals (focused on type of use, animal integrity, killing animals, animal welfare, experimentation on animals, changes in animal genotypes, the environment for animals and societal attitudes towards animals). Students from European countries had more concern for animal welfare than students from Asian countries, which may be partly explained by increased affluence of European students as there was a positive correlation between student expenditure and concern for animal welfare and rights. Southern and central European countries had most concern for animal rights and unnatural practices. Those in communist or former communist countries in Asia and Europe had most concern about killing animals and those in northern European countries the least. Regional similarities between neighbouring countries were evident in responses to animal issues and there were no differences between ethnic groups within a country. Thus, there were national and continental differences in European and Asian students’ attitudes to animals’ welfare and rights, which appear to arise as a result of the socio-political situation in regions rather than religious or other differences.

The social sciences can help provide a deeper understanding of human-farm animal relations. However, social science research exploring problematic human-farm animal interactions can be of a sensitive nature. Studies that carry risks for participants and the researcher are known methodologically as sensitive research. However, there is little discussion in the animal welfare sciences on how best to conduct research of this nature on animal owners, despite recommendations being made for more interdisciplinary collaboration between the animal welfare sciences and social sciences. Drawing on social science research conducted in 2012 on the human element of on-farm animal welfare incidents in the Republic of Ireland, this short communication presents a case study of the sensitivities and challenges involved in carrying out social science research related to farm animal welfare. This communication details the steps involved in recruiting participants, the methodological challenges encountered, and the approaches used to overcome these challenges. Our experience suggests that when conducting socially sensitive research, careful consideration needs to be applied to the recruitment process, and the study design must aim to minimise the potential risks for all involved. Professionals in the field, such as veterinarians, can play an important role in outlining some of the implications involved, and in overcoming research challenges. Understanding the challenges to this form of research will help to maximise research potential.