Author: slquinlan

The University of Georgia Laboratory of Archaeology will use funds to rehouse and digitize its paleoenvironmental archives from Georgia’s coastal zone. The collections include artifacts and documentary archives about Native American history, represented by excavations on Georgia’s barrier islands and adjacent mainland areas and pertaining to Native American sites from 4500 years ago to the 17th century. For the project, staff will work with two graduate students, five undergraduate students, and a database consultant to inventory, rehouse, and digitize collections. Additionally, staff will consult with members of descendent communities related to the material histories of the artifacts, such as members of the Geechee (Sapelo Island and Pinpoint Community) and the people of the Muscogee Nation.

• Funder: Institute of Museum and Library Services
• Amount: $385K
• PI: Victor Thompson (Franklin College)

Systemic and structural racism is a public health crisis. However, little is known about the impact of structural racism and discrimination (SRD) on the health and emotional well-being of individuals across the life course. While prior studies have shown associations between discrimination and negative health outcomes in adults (e.g., cardiometabolic disease, depression), these studies have been cross-sectional and primarily examined individual-level sources of racism and discrimination. Much more research is needed to fill gaps in our understanding about the relationship between SRD and health disparities before interventions can be developed. To significantly advance the field regarding SRD and health equity, studies need to include: (1) multi-level measures of SRD including individual (both intrapersonal and interpersonal), neighborhood, institutional, and societal/policy levels; (2) rigorous mixed-methods designs (e.g., ecological momentary assessment (EMA), biological measures, geographic information system (GIS) data, surveys); (3) multi-site samples with urban and rural participants; (4) a life course approach; (5) whole-person outcome measures (i.e., mental, physical, behavioral health); and (6) longitudinal study designs. Including these study elements will allow for comprehensively examining the relationships between SRD and health and emotional well-being to identify mechanisms to target in interventions to mitigate SRD. The main objective of the proposed study is to examine multiple levels (i.e., individual, neighborhood, institutional, societal/policy) of SRD and associations with mental, physical, and behavioral health outcomes across the life course to identify intervention targets to promote health equity. The proposed study is built on a prospective longitudinal cohort study of 627 racially/ethnically diverse families (i.e., African American, Hispanic, Native American, Immigrant/Refugee, White) across the life course (childhood, adolescence, adulthood/parenthood) from urban settings (i.e., Minneapolis, St. Paul). The parent R01 already has three time-points of mixed-methods data (i.e., EMA, GIS, survey) that includes discrimination and neighborhood segregation measures and physical and behavioral health outcomes carried out using a community-based participatory approach. For the proposed study, a sample of 300 racially/ethnically diverse families from rural Georgia (i.e., Athens) will be added to compare SRD experiences in urban versus rural settings. In addition, cardiometabolic and stress biomarker data (i.e., heart rate, blood pressure, waist circumference, lipids, HbA1C, cytokines) and multi-level measures of structural racism (i.e., individual, neighborhood, institutional, societal/policy) will be added at two time points, 18 months apart. The proposed study will be one of the first to prospectively measure multiple levels of SRD using mixed-methods across two sites and associations with mental, physical, and behavioral health disparities across the life course in diverse families. Results of the study will inform the development of an intervention targeting multi-level SRDs to promote health equity.

• Funder: NIH (via University of Minnesota)
• Amount: $1.4 million
• PI: Allan Tate (Public Health)

Modern metabolomics have revolutionized biology and biomedical research. It is now possible to identify specific metabolic biomarkers associated with disease or response to treatment, which can translate into improved diagnostics. However, key gaps in knowledge remain that limit the impact of metabolomics. First, advances in analytical instrumentation that fueled the growth of metabolomics are limited to biofluids or extracts of tissues or cells. Metabolism is a highly dynamic process that can change rapidly with environmental conditions, but most metabolomics techniques are not able to monitor the dynamic process directly in vivo. Rather, when they are measured at all, dynamics are measured by discrete sampling, which leads to multiple samples and added variance. A second limitation in metabolomics is our ability to identify unknown metabolites with high confidence. Many of the “features” measured by LC-MS or NMR in metabolomics studies remain unknown, limiting the biological impact.  Our laboratory has recently developed methods to address these gaps in knowledge. Through NIGMS funding, we have developed improved NMR probes that allow for greater sensitivity in NMR measurements. This is important because NMR is the best method for unknow metabolite identification. Our current probe will be commissioned in February 2022 and is optimized for 13C detection at 21.1 T (900 MHz 1H); we expect that it will provide the highest possible 13C NMR sensitivity available. This technology allows for data that will substantially improve our ability to identify unknown metabolites. We have also developed metabolite “fraction libraries”, which start with chemical separation of a specific sample followed by measurement of each fraction by 1D and 2D NMR and LC-MS/MS. The data from a fraction library will allow unknowns to be identified by efficiently linking the NMR and LC-MS data. In this MIRA we will make a fraction library knowledgebase by developing tools to connect the different datasets. We have also developed an approach called continuous in vivo metabolism by NMR (CIVMNMR). We have applied CIVM-NMR to growing Neurospora crassa, a filamentous fungus that has been used to link genetics to metabolism. We can monitor the growth of N. crassa in real-time with about 1 minute resolution for over 1 week. This allows us to measure quantitative metabolic details of all the metabolites and lipids with concentrations greater than 25 µM. We have made computational tools to extract over 300 growth curves from a single CIVM-NMR dataset, allowing us to functionally characterize the metabolic changes over time as a function of carbon source, temperature, or oxygen availability. In this MIRA project, we will expand CIMV-NMR by measuring metabolic mutants under different environments and build a web server that connects all the data. 

• Funder: NIH
• Amount: $3.5 million
• PI: Art Edison (Complex Carbohydrate Research Center)