Objectives: Targeted neonatal echocardiography is increasingly integrated into neonatal care and plays a crucial role in the evaluation and management of persistent pulmonary hypertension of the newborn. The objective of this study was to assess the utilisation of echocardiography and quality of reporting the findings in a tertiary neonatal ICU, with reference to recent imaging guidelines. Methods: All neonates (N = 49) who required inhaled nitric oxide for persistent pulmonary hypertension at Oulu University Hospital from September 2016 to September 2021 were included in this retrospective study. Altogether, 113 echocardiography evaluations were performed during their treatment. Patient characteristics, treatment outcomes, and details of echocardiography reports were systematically collected and evaluated. Results: Transthoracic echocardiography was performed prior to the start of nitric oxide treatment in all except two critically ill neonates. Echocardiography evaluations were mostly performed by neonatologists (42%), and indications for imaging were diagnostic initial evaluation and treatment follow-up in 49% and 51% of occasions, respectively. The most commonly reported parameters were the patency of arterial duct (88%) and the pattern of ductal shunting (75%), while right ventricular function was reported in only 16% of the reports. Conclusion: Echocardiography was widely used by all specialists involved in the treatment of neonatal pulmonary hypertension but there was a large variation in quality of reports. Allocating resources for structured training and implementing simple, priority-based guidelines, supported by documentation templates and brief, systematic assessment guidance for common clinical scenarios, might improve the quality of reporting.

Objectives/Goals: The goal of this study is to explore the lysogenized bacteriophages of clinical isolates of Pseudomonas aeruginosa (Pa) for their capacity to affect intraspecies competition. This study also aims to explore the capacity of using clinical isolates as a source of new candidates for phage therapy. Methods/Study Population: We compiled a collection of 207 Pa isolates and screened them for the presence of lysogenic phages using polymerase chain reaction (PCR). A subset of 96 phage containing clinical isolates was tested for intra-strain infectivity. Using a representative subset of isolates producing infective and non-infective phage, we evaluated competitive dynamics in liquid co-cultures, bacterial biofilms and in a murine chronic wound model. Results/Anticipated Results: Among all isolates, 74.3% contained detectable phages in their genome, and 63.7% contained detectable phage in their supernatants. Among those tested for intra-strain infectivity, 82.2% of strains demonstrated inhibition of growth on lawns of at least one other strain, while 94.8% of these strains were susceptible to at least one other supernatant. In in vitro co-culture competition experiments, strains producing infective phages outcompeted competitors more effectively than strains producing non-infective phage. Infective phage producing strains were more resistant to biofilm invasion than non-infective counterparts. In vivo competition experiments showed that PAO1 was significantly reduced when co-infecting with an infective phage-producing strain compared to a non-infective one. Discussion/Significance of Impact: Collectively, these data demonstrate that clinical isolates of Pa frequently encode active bacteriophages that can mediate intraspecies competition and confer a competitive advantage during infection. Future work will center on combining these phages as therapeutic cocktails targeting acute Pa infections.

Objectives/Goals: This work identifies ordinary and novel ingredients of a recipe for a learning community created by translational scientists to support their mutual interests in broadly engaged team science. The goal of creating this recipe is to share our findings, enabling the replication of this work at other CTSAs. Methods/Study Population: Inspired by O’Brien et al. (2025), our MICHR CoLab+ learning community (N = 8) is cooking up a “community recipe” for collaborative learning. Our multidisciplinary mix includes members from six MICHR teams. In our first guided session, we blended open dialog and reflection to identify key ingredients and tools, including metaphors for our team’s strengths, values, and goals. Using Teams, Miro, and generative AI, we captured early insights to refine over time. Results/Anticipated Results: By co-creating a community recipe, members of the MICHR CoLab+ deepen their understanding of shared strengths, values, and purpose. The recipe showcases what makes our community unique while fostering unity and belonging. Once complete, it will help us overcome barriers, accelerate discovery, and deliver real-world impact in translational science. Discussion/Significance of Impact: This work extends research helping translational scientists cross boundaries in universities. Building on work on learning communities for learning health systems (Ferguson, et al., 2024; Wenger, 1998), it shows how co-created “recipes” foster collaboration across disciplines, institutions, and cultures to strengthen translational science.

Objectives/Goals: The goal of this project was to, first, identify potential improvements to administrators’ processes surrounding the maintenance and export of a digital research platform using human-centered design and, second, explore whether this approach could be integrated into a system evaluation of implementation and impact of the platform. Methods/Study Population: In alignment with the A3 template for quality improvement, MICHR staff prepared to conduct a systems evaluation of MICHR’s support and dissemination of Your Health Research (YHR), a digital platform for study participant recruitment by (1) identifying the background of programmatic and scientific opportunities being addressed, (2) assessing the current state of MICHR’s management of YHR, and (3) identifying S.M.A.R.T. goals for improvement, as well (4) the drivers of improvement. The iterative nature of the work that was undertaken aligns with the intent of A3 framework which presents these 4 steps as an iterative process. These iterative efforts included a tabletop exercise, a blueprinting workshop, and a survey of MICHR program staff about potential improvements. Results/Anticipated Results: YHR is designed to facilitate recruitment into clinical and translational research studies; the findings presented here show that it is feasible to evaluate the way MICHR deploys this tool for increasing effect. The use of Systems Evaluation Theory was not only appropriate (Renger, et al, 2025), this work shows how human-centered design approaches can be integrated into systems evaluations to facilitate the identification and continuous improvements to those systems (Melles, et al., 2021; Holman, et al, 2019; Meyer, et al, 2022). This work shows how clinical and translational science organizations like MICHR can contribute to the emergence of learning health systems by evaluating the infrastructure of academic medical centers designed to facilitate participant recruitment into research (Lopez et al., 2025). Discussion/Significance of Impact: This study responds to an enduring need for more research into the ways research institutions like MICHR can increasingly provide investigators with better infrastructure and tools, such as access to population-based data for real-time adjustments to their clinical and translational research studies.

Objectives/Goals: To assess how rigor and reproducibility activities across the Clinical and Translational Science Awards (CTSA) consortium are aligned with NCATS Translational Science Principles (TSPs) and the NIH’s new plan to promote gold standard science. Methods/Study Population: We conducted a retrospective, descriptive review of all CTSA hub Research Performance Progress Reports (RPPRs) submitted for the most recent reporting year, focusing on the Accomplishments section. Reports were systematically searched using predefined rigor and reproducibility-related keywords. Relevant content was abstracted using a structured framework to categorize activities across domains, including education and training, institutional support, and data management and sharing. Results were summarized quantitatively by award mechanism. Results/Anticipated Results: Sixty-two of 66 CTSA institutions reported activities related to scientific rigor and reproducibility in the RPPR Accomplishments section. Among these hubs, rigor and reproducibility activities were most frequently reported under K awards (48 hubs), followed by UL2 or UM1 awards (43 hubs) and T awards (38 hubs). These findings indicate broad engagement across the CTSA consortium, with variation in how rigor and reproducibility activities are reported across award mechanisms. Discussion/Significance of Impact: Most CTSA hubs document multiple rigor and reproducibility activities as their accomplishments, reflecting alignment with NCATS TSPs. Characterizing these efforts across award mechanisms can inform strategies to strengthen translational science research that meets the NIH’s gold standard science.

Objectives/Goals: Maternal diabetes is associated with increased inflammation during pregnancy, which may elevate the risk of motor, cognitive, and language delays in their offspring. Our objective is to characterize the neurodevelopmental outcomes at 12 months of age in children born to diabetic mothers using two validated assessment tools. Methods/Study Population: We assessed 54 children across three groups: type 1 diabetes mellitus (DM) (T1DM n = 6), type 2 DM (T2DM n = 24), and control (n=24). Neurodevelopment was assessed using two standardized tools: the Ages and Stages Questionnaire 3rd edition (ASQ-3), a parent questionnaire, and the Bayley Scales of Infant and Toddler Development, 4th edition (BSID-IV). The ASQ-3 is composed of five domains: Communication, Gross Motor, Fine Motor, Problem Solving, and Personal-Social. The BSID-IV is also composed of five domains: Cognitive, Language (Receptive and Expressive), Motor (Gross and Fine), Social-Emotional, and Adaptive Behavior. For this study, we assessed only the Cognitive and Language domains of the BSID-IV. We used the Cochran–Mantel–Haenszel (CMH) Mean Scores test to compare the mean scores across the three groups. Results/Anticipated Results: The ASQ-3 showed no statistically significant differences between groups across all five domains. However, several children showed delays or were at risk for delays in multiple domains: Communication: (1 [1.85%]; 4 [16%] delayed), Gross Motor: (4 [7.4%] delayed), Fine Motor: (13 [24.1%] at risk; 7 [12.9%] delayed), Problem Solving: (9 [16.7%] at risk; 11 (20.3%) delayed, and Personal-Social: 8 [14.8%] at risk, 10 (20%) delayed). Similarly, the BSID-IV showed no statistically significant group differences in Cognition and Language. However, below-average performance was observed in both domains. For Cognition, 14 children (25.9%) scored below average (T1DM:1 [1.85%], T2DM: 7 [12.9%], Con = 6 [11.11%]). For Language, 12 children (22.22%) (T1DM = 1 [1.85%], T2DM = 4 [7.4%], and Con = 7 [12.9%]). Discussion/Significance of Impact: Children from all groups had delays in fine motor, problem-solving, personal-social, cognitive, and language development. These findings suggest that maternal diabetes may influence neurodevelopment. We suggest that these children have continued neurodevelopmental follow-up with their pediatrician to improve these delays.

Objectives/Goals: To evaluate the translational reliability, reproducibility, diagnostic performance, and subgroup equity of multimodal artificial intelligence (AI) models for dermatology triage across multiple model platforms. Methods/Study Population: Limited access to dermatology expertise delays diagnosis and care, motivating development of multimodal AI systems that integrate clinical images with patient data for triage. We assembled 200 biopsy-confirmed PAD-UFES-20 lesions (melanoma, keratinocyte carcinoma, benign) with paired images and metadata, prioritizing demographic balance. Six multimodal AI models (GPT-5, GPT-5-mini; Gemini 2.5 Pro, Gemini 2.5 Flash; Claude Sonnet-4, Claude Opus-4) analyzed these lesions with identical prompts predicting diagnostic probabilities, triage (urgent vs routine), and rationale. Outcomes included sensitivity, specificity, AUROC, F1, and subgroup equity. Model rationales were reviewed for interpretability, and subset re-prompting tested reproducibility for translational robustness. Results/Anticipated Results: Across six models, sensitivity range was 0.89–1.00, specificity 0.21–0.65, AUROC 0.77–0.87, and F1 scores 0.72–0.81. GPT-5 achieved the most balanced performance (0.92 sensitivity, 0.65 specificity, AUROC 0.87, F1 0.81), while Gemini 2.5 Pro and Flash reached perfect sensitivity but low specificity (0.21–0.25). Claude Sonnet-4 showed near-perfect sensitivity (0.99) but over-called benign cases (0.24 specificity), while Opus-4 had the lowest sensitivity (0.89). Urgent triage aligned with dermatologist biopsy patterns (87–97%), and sensitivity was consistent across sex and skin type (p ≥ 0.29). Subset re-prompting produced similar results, supporting reproducibility. Model rationales reflected dermatologic reasoning, supporting interpretability, and translational readiness. Discussion/Significance of Impact: Multimodal AI models showed balanced diagnostic performance for dermatology triage, with platform-specific trade-offs between sensitivity and specificity. Subgroup equity, interpretable rationales, and subset reproducibility define key elements for reliable translation into dermatology workflows and prospective validation.

Objectives/Goals: This project applies a novel approach (goal-activity congruence) to evaluate a project-based CHW certification course in Houston, Texas. Objectives: (1) improve understanding of learner motivation and (2) develop alternative assessment methods for non-degree healthcare training programs. Methods/Study Population: Data were collected using voluntary pre-post-training surveys including self-reported measures of expected and experienced growth toward learner-articulated goals. As part of the post-training survey, learners were shown text from individual goals developed at the beginning of the course and asked to connect these goals with instructor defined activities from the training. Learners also responded to multiple open-ended items focused on the contribution their training experience made to their career journey and their biggest lessons learned. Data were analyzed using descriptive statistics (goal-activity congruence and self-reported growth) and thematic analysis of qualitative responses. Results/Anticipated Results: Response rates were 50% at entry and 43% at exit. Most respondents reported experiencing “lots” of progress toward their goals (65%), and 93% reported that the training was largely or partly responsible for this progress. Learners reported that the most helpful program activities contributing to their goals included: the community health project (69%), motivational interviewing role plays (66%), and the Logic model assignment (66%). Qualitative themes that emerged included: development of knowledge and motivation to help their community, learning to develop skills and gain access to resources that will contribute to career and community, and helped them to better understand how to help others. Discussion/Significance of Impact: This study demonstrates the viability and value of including activity-goal congruence as a part of training program evaluations. While providers should not be solely guided by learner goals when developing training curriculum, considering them will lead to more effective and well-received trainings.

Objectives/Goals: To implement and evaluate a Smartsheet-based system that centralizes management, tracking, and credentialing for the NJ ACTS Clinical Research Coordinator digital badging program, improving efficiency, data integration, and measurable workforce development outcomes. Methods/Study Population: The NJ ACTS CRC digital badging program was integrated into a Smartsheet platform designed to unify data across JotForm, Qualtrics, REDCap, Canvas LMS, and Accredible. Automated workflows track learner enrollment, module completion, and credential issuance in real time. Participants include CRCs and trainees across academic and clinical settings. The platform’s dashboards and automated reports support continuous monitoring, feedback collection, and competency validation. Data from initial cohorts were analyzed to assess usability, process efficiency, and accuracy of training metrics across systems. Results/Anticipated Results: Integration of Smartsheet has improved onboarding efficiency, reduced administrative burden, and enhanced visibility into learner progress. Automated credentialing through Accredible provides timely recognition of competencies. Early results demonstrate increased completion rates and more consistent tracking across partner sites. The unified system enables data-driven decision-making and facilitates the scalable expansion of CRC training efforts within and beyond NJ ACTS institutions. Discussion/Significance of Impact: Smartsheet integration enhances the infrastructure for digital badging and workforce tracking, providing a replicable and scalable model to standardize CRC training nationally and advance competency-based education in translational science.

Objectives/Goals: To culturally adapt and validate the Spanish version of the UCLA Loneliness Scale-10 for the Puerto Rican population and to determine the prevalence and characteristics of loneliness among individuals aged 60 and older across various regions of the island. Methods/Study Population: A quantitative, descriptive, cross-sectional study was conducted including cultural adaptation and psychometric validation of the Spanish UCLA Loneliness Scale-10. A pilot with 47 older adults from northeastern Puerto Rico preceded a stratified random sample of 400 adults aged 60+ from public housing in 24 municipalities, covering Puerto Rico’s eight regions. Sample size was calculated with 99% confidence and 5% error margin. Recruitment occurred Dec 2024–Mar 2025. Inclusion: age ≥60, Spanish-speaking, residing in Puerto Rico. Cognitive function was screened using MMSE. Results/Anticipated Results: Most participants were female (78.3%) and aged 60-70 (59.5%). Over half lived alone (54.3%), and 82% earned under $10,000 annually. The UCLA Loneliness Scale showed high validity (CVI=0.99) and reliability (α=0.88). Loneliness prevalence was 39.8%, mostly moderate, with 4.25% severe. No significant differences in loneliness by gender, marital status, or family composition were found. However, low income, limited family accessibility, poor neighborhood relations, and mobility issues were significantly linked to higher loneliness. Social activity showed a trend toward reducing loneliness but was not statistically significant. Discussion/Significance of Impact: This study with 400 Puerto Rican older adults confirms the culturally adapted UCLA-10 scale’s reliability (α=0.88), crucial for accurately measuring loneliness in this population. Findings reveal 39.8% loneliness prevalence, influenced by socioeconomic and social factors, underscoring the need for culturally sensitive interventions.

Objectives/Goals: Increase enrollment of populations reluctant to participate in precision health and Alzheimer’s disease research by leveraging trusted partnerships, responsive engagement, and a registry-enabled referral pathway. Methods/Study Population: Using a four-way partnership (Institute of Clinical and Translational Sciences Precision Health, research lab partners, Balls-Berry Lab, and community organizations), we implemented a community tailored engagements for adults aged ≥65 at risk for Alzheimer’s disease. Activities included Alzheimer’s education sessions, a sleep-health dinner forum, and direct referrals to active studies. Participants were identified via the local research registry and community networks. Trusted messengers led discussions, facilitated warm hand-offs to coordinators, and supported structured follow-up to sustain engagement and retention. Results/Anticipated Results: In 2025, community events reached >170 participants; >95% identified as Black/African American, and >65% were aged ≥65 years. Across events, about a fourth completed research inquiry cards, with on-site warm hand-offs increasing direct enrollment in active studies. Engagements strengthened trust, improved research literacy, and established a replicable, scalable model. Anticipated 2026 outcomes include expansion to additional precision-health domains, enhanced longitudinal tracking of referrals and enrollments, and broader implementation with urban and suburban partners. Discussion/Significance of Impact: Culturally grounded, community engaged strategies coupled with registry-enabled referrals can measurably improve recruitment, retention, and trust in precision health research, addressing persistent disparities in Alzheimer’s disease studies and accelerating equitable translation.