Objectives/Goals: Youth with IBD have preventive, psychosocial, and acute care needs beyond those of peers, yet receipt of services does not match those needs. Our objectives are to assess the feasibility of (1) an individualized care plan intervention to improve perceived and measured care quality and (2) a pragmatic trial design embedded in pediatric IBD practice. Methods/Study Population: This is a pilot rollout-design randomized trial (n = 60) at a regional academic medical center. Eligible patients are 13–19 years old with IBD for at least 3 months and scheduled for a follow-up visit during the trial. Research staff recruits from one cluster at a time until goal enrollment (14–16). Enrollees are randomized 1:1 to intervention (MyIBD now) or control (MyIBD after the trial). MyIBD combines a tabular summary of individualized acute, chronic, and preventive care needs with nurse facilitator support for patients to use the information. Surveys at baseline, 6 and 12 months measure care quality (Patient Assessment of Chronic Illness Care scale, vaccines, health services) and patient self-management skills (Partners in Health scale). Implementation outcomes are collected via chart review. Results/Anticipated Results: To date, 44 subjects have been randomized. Among subjects, the mean age is 16 years; 73% have Crohn’s disease, 77% have commercial insurance, 75% receive anti-TNF therapy, and 14% live in a rural area. Mean baseline perceived care quality (PACIC scale) is 76.9 (sd 16.3; out of 100); mean baseline perceived self-management skill (PIH scale) is 78.1 (sd 13.4; out of 96). On objective care quality measures, 59% have completed the HPV vaccine series, 32% have received an additional pneumonia vaccine; in the past year 68% have had a screening for mood disorders, 20% an emergency department visit for IBD, and 18% an IBD hospitalization. To date, the IBD clinical team has achieved 100% completion (intervention subjects receive MyIBD plus nurse facilitation) and 0% contamination (control subjects inappropriately receive MyIBD). Discussion/Significance of Impact: Study results to date support the feasibility of the pragmatic, embedded trial design and indicate opportunities for improvement in care quality as perceived by patients and as measured by common preventive and acute care quality indicators. An individualized care plan supported with nurse facilitation may improve pediatric IBD care quality.

Objectives/Goals: Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease with a mean survival of only 11 months even with the most advanced treatment to date. The desmoplastic microenvironment of PDA is thought to play a critical role in therapy resistance. One pathway that might be responsible for resistance to immunotherapy is the CXCR4-CXCL12 axis. Methods/Study Population: In this study, we propose to evaluate the effect of CXCR4-CXCL12 inhibition on dual checkpoint inhibition in KPC mouse model of PDAC and patient-derived explants. PDAC mouse models are made with pancreatic cancer cells driven by loss of TP53 and activation of KRAS. These models are treated with PD1 inhibitor Balstilimab and an FC-modified CTLA4 Botensilimab with or without CXCR4 inhibitor BL8040. In addition, we make explants of patient tumors along with their tumors and autologous peripheral blood mononuclear cells and this model is similarly challenged with BOT/BAL and BL8040. Using immunofluorescence and flow cytometry, we quantify and evaluate the spatial relationships between different cell populations. Most notably, we evaluate the relative abundance of CD8+ T cells in control and treated conditions. Results/Anticipated Results: We expect the inhibition of CXCR4-CXCL12 axis, along with two new potent checkpoint blockers, will lead to infiltration of CD8+ T cells in both the mouse and human PDAC models. We also expect this to translate into more tumor cell killing as demonstrated by Caspase activities and tumor shrinkage. Discussion/Significance of Impact: If our hypothesis is proven in both mouse and human PDAC models, this study will serve as a basis for a phase I/II clinical trial testing this combination of drug.

Objectives/Goals: We describe the prevalence of individuals with household exposure to SARS-CoV-2, who subsequently report symptoms consistent with COVID-19, while having PCR results persistently negative for SARS-CoV-2 (S[+]/P[-]). We assess whether paired serology can assist in identifying the true infection status of such individuals. Methods/Study Population: In a multicenter household transmission study, index patients with SARS-CoV-2 were identified and enrolled together with their household contacts within 1 week of index’s illness onset. For 10 consecutive days, enrolled individuals provided daily symptom diaries and nasal specimens for polymerase chain reaction (PCR). Contacts were categorized into 4 groups based on presence of symptoms (S[+/-]) and PCR positivity (P[+/-]). Acute and convalescent blood specimens from these individuals (30 days apart) were subjected to quantitative serologic analysis for SARS-CoV-2 anti-nucleocapsid, spike, and receptor-binding domain antibodies. The antibody change in S[+]/P[-] individuals was assessed by thresholds derived from receiver operating characteristic (ROC) analysis of S[+]/P[+] (infected) versusS[-]/P[-] (uninfected). Results/Anticipated Results: Among 1,433 contacts, 67% had ≥1 SARS-CoV-2 PCR[+] result, while 33% remained PCR[-]. Among the latter, 55% (n = 263) reported symptoms for at least 1 day, most commonly congestion (63%), fatigue (63%), headache (62%), cough (59%), and sore throat (50%). A history of both previous infection and vaccination was present in 37% of S[+]/P[-] individuals, 38% of S[-]/P[-], and 21% of S[+]/P[+] (P<0.05). Vaccination alone was present in 37%, 41%, and 52%, respectively. ROC analyses of paired serologic testing of S[+]/P[+] (n = 354) vs. S[-]/P[-] (n = 103) individuals found anti-nucleocapsid data had the highest area under the curve (0.87). Based on the 30-day antibody change, 6.9% of S[+]/P[-] individuals demonstrated an increased convalescent antibody signal, although a similar seroresponse in 7.8% of the S[-]/P[-] group was observed. Discussion/Significance of Impact: Reporting respiratory symptoms was common among household contacts with persistent PCR[-] results. Paired serology analyses found similar seroresponses between S[+]/P[-] and S[-]/P[-] individuals. The symptomatic-but-PCR-negative phenomenon, while frequent, is unlikely attributable to true SARS-CoV-2 infections that go missed by PCR.

Objectives/Goals: Cerebral amyloid angiopathy (CAA) characterized by the accumulation of amyloid-beta in the cerebrovasculature, affects blood vessel integrity leading to brain hemorrhages and an accelerated cognitive decline in Alzheimer’s disease patients. In this study, we are conducting a genome-wide association study to identify genetic risk factors for CAA. Methods/Study Population: We genotyped 1253 additional AD cases using and curated existing genome-wide genotype data from 110 AD and 502 non-AD donors from the Mayo Clinic Brain Bank. We performed QC and imputation of all datasets. We conducted GWAS in AD only (N =  1,363), non-AD only, as well as the combined cohort (N = 1,865) by testing imputed variant dosages for association with square root transformed CAA using linear regression, adjusting for relevant covariates. To assess associations in the context of major CAA risk factors, we performed interaction analysis with APOEe4 presence and sex; and pursued stratified analyses. We collected peripheral gene expression measures using RNA isolated from 188 PAXgene tube samples of 95 donors collected across multiple time points. More than 1/3 of these participants have MRI measures collected. Results/Anticipated Results: Variants at the APOE locus were identified as the most significant in our study. In addition, several other variants with suggestive association were found under the main model adjusting for AD neuropathology (Braak and Thal). LINC-PINT splice variant remained associated with lower CAA scores in AD cases without the APOEe4 risk allele. To enhance the robustness of our findings, we are pursuing further expansion of our study cohort. In the periphery, we expect to identify expression changes associated with neuroimaging indicators of CAA and determine if variants and genes discovered via GWAS are implicated in these changes. Discussion/Significance of Impact: We expect this study will provide further insight into the genetic architecture underlying risk for CAA both in the context of significant AD pathology and without. Characterization of genetic variants and functional outcomes in the context of neuropathology may lead to new avenues of research aimed at identifying biomarkers and therapies to treat CAA

Objectives/Goals: This study examines associations between childhood violence exposure, accelerated biological aging, and adolescent depression using DNA methylation-based epigenetic clocks. Findings aim to identify biomarkers for early detection, guide interventions, and address youth mental health disparities. Methods/Study Population:Data from the Future of Families and Child Wellbeing Study (N = 4,898), a diverse urban U.S. cohort, were analyzed. Childhood violence exposure, assessed using the Parent-Child Conflict Tactics Scale, included measures of physical, emotional, and psychological aggression and neglect. Biological aging at age 15 was evaluated using second-generation epigenetic clocks derived from saliva DNA methylation patterns, while depressive symptoms were measured with the CES-D scale. Multiple linear regression models tested associations between early violence exposure, epigenetic aging, and depressive symptoms, adjusting for socioeconomic status, caregiver mental health, and other key covariates. Results/Anticipated Results: Preliminary results suggest that early violence exposure may be linked to accelerated biological aging and depressive symptoms during adolescence, a critical developmental period. Epigenetic clocks offer an objective method for identifying high-risk youth, complementing mental health evaluations. With further validation and participatory action research, these findings could guide the development of biomarkers for longitudinal testing in school-based screenings and community health programs. These tools aim to be accessible, culturally relevant, and tailored to diverse populations, enhancing early detection, informing personalized interventions, and supporting scalable clinical applications. Discussion/Significance of Impact: This study explores links between early adversity, biological aging, and mental health, advancing understanding of adolescent depression. Epigenetic biomarkers could improve risk detection and guide tailored interventions in schools and community settings, enhancing access and reducing disparities.

Vascular rings represent a heterogeneous set of aberrant great vessel anatomic configurations which can cause respiratory symptoms or dysphagia due to tracheal or oesophageal compression. These symptoms can be subtle and may present at varied ages. More recently, many have been identified in patients without symptoms, including fetal echocardiogram, resulting in a conundrum for practitioners when attempting to determine who will benefit from surgical correction. Here, we provide a review of vascular rings and a guide to the practitioner on when to consider additional imaging or referral. Additionally, we discuss the changing landscape regarding asymptomatic patients and fetal echocardiogram.

A growing number of studies focus on how governments can manage audience costs when they want to back down from international crises. In line with previous studies, especially Kohama et al. (2024), this paper argues that the Japanese government can use a variety of reasons to justify its decisions to de-escalate while minimizing domestic audience costs. I found that governments can reduce audience costs using several rhetorical devices, reinforcing the current understanding of audience costs. However, my design, which presented a fait accompli scenario by China against Japan, yielded significantly different results regarding audience costs compared to previous studies on the subject. Specifically, the results of this study indicate that the public might not value economic development following a fait accompli as highly as in less severe scenarios. The results also suggest that leaders might have a harder time backing down after a loss of territory compared to other forms of provocation.

Despite public health efforts, uptake of preventive health technologies remains low in many settings. In this paper, we develop a formal model of prevention and test it through a laboratory experiment. In the model, rational agents decide whether to take up health technologies that reduce, but do not eliminate the risk of adverse health events. As long as agents are sufficiently risk averse and priors are diffuse, we show that initial uptake of effective technologies will be limited. Over time, the model predicts that take-up will decline as users with negative experiences revise their effectiveness priors towards zero. In our laboratory experiments, we find initial uptake rates between 65 and 80% for effective technologies with substantial declines over time, consistent with the model’s predictions. We also find evidence of decision-making not consistent with our model: subjects respond most strongly to the most recent health outcomes, and react to negative health outcomes by increasing their willingness to invest in prevention, even when health risks without prevention are known by all subjects. Our findings suggest that high uptake of preventive technologies should only be expected if the risk of adverse health outcomes without prevention is high, or if preventive technologies are so effective that the risk of adverse outcomes is negligible with prevention.

This paper demonstrates how learning the structure of a Bayesian network, often used to predict and represent causal pathways, can be used to inform policy decision-making.

We show that Bayesian networks are a rigorous and interpretable representation of interconnected factors that affect the complex environment in which policy decisions are made. Furthermore, Bayesian structure learning differentiates between proximal or immediate factors and upstream or root causes, offering a comprehensive set of potential causal pathways leading to specific outcomes.

We show how these causal pathways can provide critical insights into the impact of a policy intervention on an outcome. Central to our approach is the integration of causal discovery within a Bayesian framework, which considers the relative likelihood of possible causal pathways rather than only the most probable pathway.

We argue this is an essential part of causal discovery in policy making because the complexity of the decision landscape inevitably means that there are many near equally probable causal pathways. While this methodology is broadly applicable across various policy domains, we demonstrate its value within the context of educational policy in Australia. Here, we identify pathways influencing educational outcomes, such as student attendance, and examine the effects of social disadvantage on these pathways. We demonstrate the methodology’s performance using synthetic data and its usefulness by applying it to real-world data. Our findings in the real example highlight the usefulness of Bayesian networks as a policy decision tool and show how data science techniques can be used for practical policy development.

Robotic manipulation inherently involves contact with objects for task accomplishment. Traditional motion planning techniques, while having shown their success in collision-free scenarios, may not handle manipulation tasks effectively because they typically avoid contact. Although geometric constraints have been introduced into classical motion planners for tasks that involve interactions, they still lack the capability to fully incorporate contact. In addition, these planning methods generally do not operate on objects that cannot be directly controlled. In this work, building on a recently proposed framework for energy-based quasi-static manipulation, we propose an approach to manipulation planning by adapting a numerical continuation algorithm to compute the equilibrium manifold (EM), which is implicitly derived from physical laws. By defining a manipulation potential energy function that captures interaction and natural potentials, the numerical continuation approach is integrated with adaptive ordinary differential equations that converge to the EM. This allows discretizing the implicit manifold as a graph with a finite set of equilibria as nodes interconnected by weighted edges defined via a haptic metric. The proposed framework is evaluated with an inverted pendulum task, where the explored branch of the manifold demonstrates effectiveness.