Seed Grant Awards Description FY 2027

Daily biological clocks coordinate physiology and behavior with predictable environmental cycles, but how these clocks respond to rapid changes in temperature remains poorly understood. This question is increasingly important as changing temperatures alter seasonal cues that govern behaviors such as dormancy and migration, with potential consequences for conservation, pest management, and organismal responses to climate change.

Our preliminary studies in the fruit fly Drosophila melanogaster reveal a rapid response to cooling in vrille, a core gene of the circadian clock. Remarkably, this response is conserved among fly species separated by more than 40 million years of evolution. We propose to determine whether this response reflects rapid temperature sensitivity of the circadian clock itself or an independent role of vrille in thermal stress. Using sensitive gene expression assays, we will measure coordinated responses among five core clock genes in the central nervous system and in the peripheral clock following rapid cooling. Either outcome will resolve a critical mechanistic question and provide the preliminary evidence needed to motivate a larger research program.

The primary outcome will be a proposal to the National Science Foundation’s Integrative Ecological Physiology (IEP) program (NSF 26-517), which is particularly well aligned with our goal of connecting molecular mechanisms of temperature sensing to organismal physiology, behavior, and environmental responses. The project will also generate a publishable dataset, provide research training for a postdoctoral scholar and undergraduate, and potentially support a complementary NIH proposal. This focused investment will position promising preliminary findings for competitive external funding within one year.

Manufactured homes, (a.k.a. mobile homes or “trailers”) provide a major source of affordable housing and a primary route to low-income homeownership in the U.S. About 40% of manufactured homes are located in manufactured home communities (MHCs). MHCs have distinct water and sanitation issues due to a history of exclusionary housing ordinances and a divided housing tenure where landlords own the property where households rent lots to place their homes. As with other renters, MHC homeowners depend on property owners’ investment in and governance of critical infrastructure. A growing body of research has documented severe issues with water quality in MHCs. This project will provide the first systematic analysis of MHC residents’ experiences of drinking water quality, trust, and institutional engagement by combining a novel dataset of laboratory water test results with qualitative data collected through in-depth interviewing and ethnographic observations. I will use these data to develop external grants to analyze MHC water quality and resident activism in four select states with different regulatory regimes, variations in state oversight, and distinct modes of resident organizing and civic engagement. An RDO seed grant would cover two foundational project components to strengthen external proposals: 1) pilot data in Colorado where a first-in-the-nation law requires the Department of Public Health and Environment (CDPHE) to test drinking water in every MHC in the state and 2) funding for field visits in Colorado, Michigan, Vermont and West Virginia to document ongoing issues with contamination in MHCs and engage with local resident-activists organizing for improvements, which will setting the stage for a larger community-engaged comparative study.

Dark matter is one of the major unanswered questions in physics. Experiments searching for it must recognize extremely faint detector signals amid electrical noise. Atrigger is the rapid decision that determines which signals are saved for study; improving that decision could help scientists make better use of sensitive detectors. We request $20,000 to develop an artificial intelligence and machine learning (AI/ML) trigger prototype using data currently being collected by the Super Cryogenic Dark Matter Search (SuperCDMS). Two CU Denver undergraduates will work with our interdisciplinary advising team: one will prepare and analyze the data, and the other will build a neural network, a computer model that learns patterns from examples. Together, we will test whether the model preserves more weak signals or rejects more noise than a conventional method. The project will deliver a tested software prototype, clear performance comparisons, and an initial assessment of the electronics needed for future implementation. These results will strengthen a subsequent U.S. Department of Energy (DOE) application. If our September 2026 DOE proposal is not funded, the pilot will provide evidence for a stronger revised proposal. If it is funded, the pilot will support an extension to SuperCDMS data and a future application. The Seed investment therefore combines a practical path toward external funding with paid undergraduate experience in experimental physics, data analysis, and AI.

Access to reproductive healthcare in the U.S. has changed dramatically over the past two decades, expanding in some areas and contracting in others. Research on changes in access to reproductive healthcare often relies on state- or national-level data, yet a primary way that policy changes affect access is through the opening or closing of facilities at the local level. Despite their interconnections, types of reproductive healthcare tend to be researched in isolation from one another. This approach limits our understanding of whether and how places that lack access to care (“Reproductive Healthcare Deserts”) overlap across time and space, and the implications for maternal and infant health. Under a 2-year R21 developmental grant, the Reproductive Healthcare Desert (RHD) team developed a public dashboard (rhdproject.org) and database that map geographic access to contraceptive, abortion, maternity, and infertility care between 2010-2024. We seek seed funding for critical work that will substantially improve our changes of securing external funding to expand and extend the database and to maximize its utility for improving reproductive healthcare across the country. To be competitive for an NIH large research grant (R01), we need to test the link between RHD exposure and maternal and infant health, improve the spatial sophistication of our analytic approaches, and strengthen the case for the project’s implications for healthcare, an NIH priority. We seek seed funding to accomplish all these goals.