Imagery-based survey is capable of producing archaeological datasets that complement those collected through field-based survey methods, widening the scope of analysis beyond regions. The Geospatial Platform for Andean Culture, History and Archaeology (GeoPACHA) enables systematic registry of imagery survey data through a ‘federated’ approach. Using GeoPACHA, teams pursue problem-specific research questions through a common data schema and interface that allows for inter-project comparisons, analyses and syntheses. The authors present an overview of the platform's rationale and functionality, as well as a summary of results from the first survey campaign, which was carried out by six projects distributed across the central Andes, five of which are represented here.

OBJECTIVES/GOALS: During the COVID-19 pandemic, translational scientists sought to provide scientific and data expertise to school districts serving diverse and disadvantaged students to enable equitable access to in-person learning. METHODS/STUDY POPULATION: We showcase two CTSA examples. One is a partnership with the second largest U.S. school district; the second is a national network of scientists and urban and rural school districts. In each example, CTSAs assembled expert science teams to support data-driven decision-making. The teams provided honest brokering of COVID-19 science, scientific interpretation that is sensitive to local context, and responses to community-driven questions. The teams collaborated with school district partners to design actionable data displays on key metrics including primary COVID-19 cases, school-acquired cases, quarantines, and missed school. The national ABC Science Collaborative) provided a platform for shared learning and reproducibility and credibility of science using district data. RESULTS/ANTICIPATED RESULTS: The CTSAs developed easily interpretable and actionable data displays. Partnered school districts observed data in real time to identify signals of change. Districts in the national network were able to learn in real time from variation across districts based on policies and procedures that they adopted, such as quarantine, masking, and physical distancing. DISCUSSION/SIGNIFICANCE: This scientific collaboration is a model of rapid CTSA response, informing science and real-time action. The data displays enable school districts to explain decisions regarding student and staff health and safety. These partnerships and data designs are infrastructure that can be quickly mobilized for emergent and for ongoing information needs.

OBJECTIVES/GOALS: To describe how the UCLA Clinical and Translational Science Institute (CTSI) assembled and deployed a science team in support of a local jurisdictions effort to manage and control COVID-19 outbreaks in one of the nations largest metropolitan regions, Los Angeles County (LAC). METHODS/STUDY POPULATION: During the COVID-19 pandemic (2020-21), building an efficient data infrastructure to support outbreak management became a priority for the local health department. In response, the UCLA CTSI assembled a science team with expertise across the translational continuum: epidemiology, laboratory and microbiology, machine learning, health policy, medicine and clinical care, and community engagement. The team partnered with a new LAC Data Science Team to foster a collaborative learning environment for scientists and public health personnel, employing improvement and implementation science to help mitigate COVID-19 outbreaks in sectors including healthcare, skilled nursing facilities, and K-12 education. The goal was a public health workforce that is prepared to problem-solve complex, evolving outbreaks. RESULTS/ANTICIPATED RESULTS: The science team created a learning environment with data modeling and visualization, problem-based learning, and active knowledge and skills acquisition. First, control charts and time series methods were used to visualize COVID-19 data and find signals for action. Second, a series of 16 Grand Rounds offered interactive sessions on problem-solving of outbreak challenges in different sectors. Third, a biweekly Public Health Digest provided fieldworkers with the latest scientific studies on COVID-19. All three elements guided and empowered the workforce to implement timelier, efficient outbreak mitigation strategies in the field. The partnered team also identified barriers to adoption of selected new data and management techniques, revealing areas for further skill-building and data-driven leadership. DISCUSSION/SIGNIFICANCE: The UCLA CTSI science team offered a backbone science infrastructure for helping public health and other sector agencies manage COVID-19 outbreaks and mitigation. It showed promise in bringing and translating science into public health practice. It revealed future priorities for CTSI innovation and scientific support of public agencies.

OBJECTIVES/GOALS: A UCLA Clinical and Translational Science Institute (CTSI) science team partnered with the second largest US school district, with over 500,000 K-12 students, to design and implement a statistical process control dashboard to guide COVID-19 response, including mitigation and vaccination outreach. METHODS/STUDY POPULATION: District data for students, teachers, and staff are updated daily and include COVID-19 test results, counts of quarantine after positive tests, and COVID-19 vaccination rates. Displays used a new hybrid Shewhart control chart to detect changes in test positivity rates and distinguish meaningful signals from noise (random day-to-day variation). The dashboard uses the Shiny and plotly packages in R to display interactive graphs of each data stream (cases, tests, and vaccinations) charted at multiple levels (districtwide, subdistricts, schools). Displays of variation over time show policy impacts and inequities. Selected displays use municipal COVID-19 data to complement district data. RESULTS/ANTICIPATED RESULTS: The district has used the displays to assess the impact of their COVID-19 response and to identify variation in close to real-time to suggest areas with need for additional resources for mitigation or vaccination. The CTSI team has continued to edit and add displays in response to the district’s changing operational needs and questions. DISCUSSION/SIGNIFICANCE: The UCLA CTSI team developed and implemented a robust data visualization dashboard to monitor COVID-19 case rates and plan vaccination outreach efforts. Control charts enabled the district to distinguish noise from signal, thereby rapidly identifying when specific parts of the district needed targeted support to achieve equity goals.

This study aimed to determine whether higher intakes of Na, added sugars and saturated fat are prospectively associated with all-cause mortality and CVD incidence and mortality in a diverse population. The nationally representative Canadian Community Health Survey-Nutrition 2004 was linked with the Canadian Vital Statistics – Death Database and the Discharge Abstract Database (2004–2011). Outcomes were all-cause mortality and CVD incidence and mortality. There were 1722 mortality cases within 115 566 person-years of follow-up (median (interquartile range) of 7·48 (7·22–7·70) years). There was no statistically significant association between Na density or energy from saturated fat and all-cause mortality or CVD events for all models investigated. The association of usual percentage of energy from added sugars and all-cause mortality was significant in the base model with participants consuming 11·47 % of energy from added sugars having 1·34 (95 % CI 1·01, 1·77) times higher risk of all-cause mortality compared with those consuming 4·17 % of energy from added sugars. Overall, our results did not find statistically significant associations between the three nutrients and risk of all-cause mortality or CVD events at the population level in Canada. Large-scale linked national nutrition datasets may not have the discrimination to identify prospective impacts of nutrients on health measures.

ABSTRACT IMPACT: The mobilization of a CTSA-sponsored team with multi-disciplinary translational science expertise enabled the university to provide a range of T1-T4 expertise to a large, complex school district that resulted in permanent learning and data science infrastructure. OBJECTIVES/GOALS: The Clinical Translational Science Institute (CTSI) formed a multidisciplinary science team to provide expertise in support of the re-opening of in-person learning in the second-largest U.S. school district during the COVID-19 pandemic. METHODS/STUDY POPULATION: The assembled interdisciplinary science team provided expertise in epidemiology, machine learning, causal inference and agent-based modeling, data and improvement science, biostatistics, clinical and laboratory medicine, health education, community engagement, and experience in outbreak investigation and management. The team included TL1 pre and postdoctoral fellows and mobilized scientists from multiple professional schools and T1-T4 stages of translational research. RESULTS/ANTICIPATED RESULTS: Tangible outcomes achieved using this team approach included the development of practical metrics for use in the school community, a learning process, the integration of preventive design elements into a testing and tracing program, and targeted and data-driven health education. The team, for example, generated new data displays for community engagement and collaborated with the school district in their use to visualize, learn from, and act on variation across a 700 square mile region. DISCUSSION/SIGNIFICANCE OF FINDINGS: Novel translational methods can be used to establish a learning environment and data science infrastructure that complements efforts of public health agencies to aid schools in the COVID-19 pandemic. These new capabilities apply to COVID-19 testing and vaccines and can be mobilized for future population health challenges faced by school districts.

ABSTRACT IMPACT: This study provides public health and K-12 school districts with a pragmatic, flexible, adaptable model showing COVID-19 transmission dynamics, using local data and program elements that are modifiable and with an online model for easy use, to enable safe and equitable re-opening and maintenance of in-person learning. OBJECTIVES/GOALS: School closures resulting from the COVID-19 pandemic disrupt student education and health and exacerbate inequities. Public health agencies and school districts currently lack pragmatic models to assess the effects of potential strategies for resuming and maintaining in-person learning on outcomes such as transmission and attendance. METHODS/STUDY POPULATION: This study explored how various combinations of transmission-mitigating interventions affect health and learning outcomes in a range of underlying epidemiological conditions. The CTSA science team developed a conceptual framework and an agent-based simulation model with parameters including prevalence, transmission, testing, preventive and responsive actions, infection control, population behavior and awareness, and the potential impact of vaccine adoption and exemption policies. The team partnered with a large school district to ensure relevance of the program components to decision-making. RESULTS/ANTICIPATED RESULTS: The model shows that no single program element or condition ensures safety. Combining interventions can result in synergy in the mitigation efforts. Even without testing, an efficient health screening process with forthcoming risk reporting, combined with on-campus infection control, can reduce on-campus transmission. The resulting model is accessible online to enable exploration of likely scenarios. It is adaptable as COVID-19 science evolves, including for testing and vaccines. DISCUSSION/SIGNIFICANCE OF FINDINGS: This research provides public health agencies and school districts with a model that couples local conditions with programmatic elements to help inform the local COVID-19 response, recognizing that decisions about the school community are often complex politically, technically, and operationally when it comes to addressing a health crisis.

Because individuals develop dementia as a manifestation of neurodegenerative or neurovascular disorder, there is a need to develop reliable approaches to their identification. We are undertaking an observational study (Ontario Neurodegenerative Disease Research Initiative [ONDRI]) that includes genomics, neuroimaging, and assessments of cognition as well as language, speech, gait, retinal imaging, and eye tracking. Disorders studied include Alzheimer’s disease, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson’s disease, and vascular cognitive impairment. Data from ONDRI will be collected into the Brain-CODE database to facilitate correlative analysis. ONDRI will provide a repertoire of endophenotyped individuals that will be a unique, publicly available resource.

Temperature is an environmental factor that influences the development of fish, and when changed abruptly can lead to high mortality. Some species of fish are influenced by this factor, exhibiting a longer time for embryonic development and time to first feeding. This study aims to evaluate the effect of water temperature on embryonic and larval development up to first feeding, to describe the time in hours post fertilization (hpf) of the emergence of different structures and to determine the best hatching rate and survival of animals under different treatments. Five different egg incubation temperatures were used (24, 26, 28, 30 or 32°C, respectively). The eggs were observed at regular intervals of 30 min up to 24 h, every 2 h until 48 h and every 4 h until the display of first feeding in all treatments. Embryonic development was longer for eggs incubated at 24°C and the best results for hatching rate and survival of spawning efficiency were at 28°C. We recommend that incubation of Trichogaster leeri eggs is carried out at 28°C up to the first feeding of larvae.

The present study aimed to provide data on the time required for Melanotaenia boesemani to complete embryonic development, and to investigate the influence that incubation at different temperatures caused in this species. The effects of temperature on the time and hatching rate are presented, as well as information related to embryonic development stages. After fertilization, the eggs were kept in incubators at 23, 26, 29 or 32°C and observed at predetermined times until the moment of hatching. Stages of development were identified and classified according to morphological and physiological characteristics. Oil droplets were visualized inside the eggs as well as filament adhesion present at the chorion. Embryonic development was similar to that observed in other species of the genus Melanotaenia with hatching and faster development in higher temperatures.

The aim of this study was to describe the embryonic and larval development of discus fish (Symphysodon aequifasciatus), and to determine the time required, hours post fertilization (hpf), for the emergence of various structures. To describe embryonic and larval stages, observations were made at regular periods under an optical microscope and images were taken with a digital camera attached to a microscope. The average temperature reached in the experimental tank was 27.9°C. Important facts in embryonic and larval development are described, such as the closure of the blastopore, which occurred at 31.5 hpf; a period of eruption, which occurred at 58.5 hpf; and a mouth opening, which occurred at 90.5 hpf; and larvae that exhibited oriented swimming and eating exogenous food at 136.5 hpf.

Dwarf rainbowfish (Melanotaenia praecox) are an ornamental fish with a high added value and considerable commercial interest. However, little information is known about the organism's reproductive biology, especially the early stages of embryonic development (initial ontogeny). Melanotaenia praecox embryos were examined throughout development to describe the dwarf rainbowfish initial ontogeny. Eggs were incubated at 28°C, and observations were recorded at pre-determined times. Development stages were identified and classified according to morphophysiological characteristics. The initial size of the eggs ranged between 0.99 and 1.04 mm. Oil droplets were observed in the eggs, and fixing filaments for adhesion were observed in the corium. Embryonic development was similar to that of other species in the genus Melanotaenia, in which hatching begins 119.50 h post-fertilisation or 3405.75 degree-h post-fertilisation. The main features of the newly hatched larvae were excellent swimming activity, a reduced yolk sac, mouth movement and an apparently functional digestive system.

The relationships between soil properties, topography and tree species distribution were analysed in a tropical riverine forest at the margins of the Rio Grande, in Bom Sucesso, state of Minas Gerais, south-eastern Brazil. The forest was sampled by three 0.18 ha plots, with each plot made up of eight contiguous 15 m X 15 m quadrats, four of which were placed at the river margin and the remaining four in the forest interior. A canonical correspondence analysis indicated that the species' density distribution was significantly correlated with some soil chemical characteristics and topographical features. The soils of the three sample plots showed statistically significant differences for the levels of Ca, Mg, K and pH, with the fertility (expressed by the cation exchange capacity) increasing from Plot I to Plot III. These variations were mainly explained by the first canonical axis while the second was strongly correlated with topographical variables, separating the quadrats into two groups: those of the higher and steeper sites from those of the lower sites. The only soil property that was significantly different in lower and upper sites was the concentration of phosphorus. No significant difference in tree species distribution was found between river margin and interior quadrats, certainly because this forest sector lies on the outer side of a curve of the river where erosion is currently building high and steep river banks and forcing the forest to retreat. A tentative ecological classification of the 30 most abundant species according to their habitat preference in terms of soil fertility and topographical sites, and to their growth strategy in the forest dynamics, is presented. It is suggested that these factors play an important role in promoting the coexistence of tree species in this type of forest.