Assessing extinction risk is important for protecting species, as it is the starting point for conservation efforts. However, in Antarctica, none of the c. 116 species of bryophytes (the main terrestrial plant group) have been assessed. The global Aichi Biodiversity Targets stipulate that countries should have knowledge of the extinction risk of their entire flora. However, the Convention on Biological Diversity does not apply to the area of Antarctic Treaty governance, as Antarctica is not subject to national sovereignty. Recognizing the importance of understanding threats in this remote and ecologically sensitive region, we assessed the extinction risk of the moss Roaldia revoluta (Pylaisiaceae) in Antarctica. As far as we are aware, this is the first extinction risk assessment of a native plant on the Antarctic continent. Additionally, we provide a tool for estimating the number of bryophyte individuals. Our findings indicate R. revoluta should be categorized as Endangered. The species has not been documented in any Antarctic Specially Protected Area, suggesting both weakness in survey effort and a potential gap in conservation action. This study underscores the need for specific measures to mitigate the extinction risk faced by R. revoluta as an exemplar of threats facing Antarctic mosses, and emphasizes the importance of devoting resources to conserving Antarctic flora. This study will encourage further initiatives to investigate the risks facing Antarctic botanical diversity and strengthen support for safeguarding the continent’s biodiversity.

Despite substantial investment in clinical and translational research, only a small proportion of evidence-based interventions are adopted and sustained in routine practice, contributing to persistent delays between discovery and population benefit. Dissemination and implementation (D&I) science is a critical discipline for addressing this gap, and the NIH Clinical and Translational Science Award (CTSA) program (established 2006) has been strategically positioned as a national infrastructure to advance D&I capacity. We conducted a national environmental scan of publicly available websites and documents from all 66 CTSA hubs (May–July 2025), using a structured extraction tool to capture D&I-specific activities across seven domains: institution and community partnerships, formal D&I organizational structures within the CTSA, consultation services, collaborative programming, training opportunities, educational offerings, and pilot funding mechanisms. Findings reveal substantial heterogeneity in D&I science activities across CTSA hubs; 45% had a formal D&I unit, 54% offered D&I consultation services, and 37% provided collaborative programming. Structured workforce development was limited: 12% offered D&I-focused training grants, 15% offered structured educational programs, and 15% provided D&I-specific pilot funding. Consultation models varied widely in scope, access, and evaluation practices. These findings demonstrate uneven development of D&I science infrastructure across CTSAs and highlight opportunities to strengthen capacity nationally.

Objectives/Goals: To develop an information-theoretic alternative to ALE that integrates uneven datasets using log-likelihood ratios (LLRs) under noise versus signal world models. This approach aims to improve reproducibility, signal-to-noise ratio, and computational scalability in neuroimaging meta-analysis. Methods/Study Population: We used both real and simulated coordinate-based datasets to build an information-theoretic meta-analysis framework. The method models each study’s activations under noise versus signal expectations and computes voxelwise LLRs to combine information asymmetrically across uneven datasets. Implemented in Python with NumPy and custom modules, it integrates watershed segmentation for cluster detection and simulation-based calibration. Validation compares results to ALE, testing robustness to injected noise and recovery from highly imbalanced datasets. Results/Anticipated Results: Studies are ongoing. We anticipate improved SNR and recovery robustness compared to ALE, as our approach avoids pre-thresholding before combining information across datasets. Simulation evidence suggests far greater computational efficiency (e.g., reducing 45-min–20-hour ALE runs to under two minutes locally). Conceptually, the framework parallels modern AI training strategies – modeling signal and noise distributions to calibrate evidence rather than relying on fixed significance thresholds. These innovations leverage information theory, watershed algorithms, and simulation calibration to yield interpretable, high-resolution evidence maps. Discussion/Significance of Impact: This framework advances coordinate-based meta-analysis by modeling evidence directly rather than inferring it through p-values. It improves reproducibility, interpretability, and cross-disorder comparability, supporting more robust and scalable neurocircuit mapping for researchers and clinicians.

The Deep South has the highest rates of obesity, diabetes, and hypertension in the nation, with marked disparities by race, socioeconomic status, and rurality. The mission of the Forge AHEAD Center is to improve health outcomes and reduce the burden of cardiometabolic diseases across the Deep South, with a particular focus on the prevention and treatment of these chronic diseases. Forge AHEAD is unified thematically by its application of a precision public health approach across the care continuum, defined as delivering the right intervention to the right population at the right time. This approach acknowledges the importance of context and individual beliefs and preferences, as well as the need for multi-level and multi-domain interventions to achieve health improvements. The Center brings together an interdisciplinary team of investigators from 4 institutions in 3 contiguous states in the region, as well as non-academic partners to extend cardiometabolic research into real-world community and clinical settings. Given the high prevalence of cardiometabolic diseases in the Deep South and the strong research base of the partnering institutions, the Forge AHEAD Center is ideally situated to inform research, clinical care, and policy to improve health outcomes in a region of substantial need.

Partner engagement is critical for embedded pragmatic research, yet few structured methods guide early collaboration to strengthen feasibility and mutual understanding. In this case study, Brown University researchers and leaders from a US-based medical practice, Bluestone Physician Services, used the readiness assessment for pragmatic trials (RAPT) model to guide structured discussion and qualitative readiness assessment of a partner-identified intervention concept aimed at improving the timing of palliative care services. Collaborative completion of RAPT created a shared process for assessing feasibility, contextual fit, and alignment with Bluestone priorities. The exercise identified domains needing refinement and guided planning to strengthen data, workflows, and measurement, demonstrating that RAPT can serve as a practical framework for early-stage co-design in pragmatic research.

Biodiversity monitoring is essential to inform the state of wildlife populations, and the impacts of environmental change, conservation intervention, and sustainable development policies and actions. We review the current state of bird monitoring across Africa using public questionnaires and semi-structured interviews. We received 87 questionnaire responses from 46 (of 54) countries and, additionally, 24 in-depth interviews were carried out. Multiple data collection methods were reported with total counts of individuals being most frequent, but all-species surveys, essential for quantifying ecosystem health, were restricted to bird atlases and Common Bird Monitoring (CBM) projects in Kenya, Uganda, and Botswana. Data collection relied largely on volunteers, but their motivation, recruitment, training, and retention is a continuing challenge. The most sustainable programmes were driven by clear policy objectives (e.g. waterbird monitoring under the Ramsar Convention or the Convention on the Conservation of Migratory Species), monitoring of individual groups (e.g. raptors, vultures, bustards), specific threatened species, and where clear national priorities had been set within government agencies. Use of monitoring data by governments in country biodiversity reports or National Biodiversity Species Action Plans (NBSAPs) varied widely and, for many countries, simply did not exist. A lack of skilled analysts and a comprehensive approach to data curation and ownership were identified as major limitations. A more strategic approach to funding and monitoring is needed, whereby smaller funders collaborate to reduce costs associated with applying for small amounts of money, and bird (and biodiversity) monitoring is explicitly integrated with sustainable development goals to exploit broader funding streams.