Dartmouth College

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Pseudomonas aeruginosa (Pa) frequently co-infects with other bacterial and fungal species. For example, 50% of adults with cystic fibrosis (CF) are chronically infected with Pa and Candida albicans (Ca) commonly co- infects. Antagonistic interactions between Pa and Ca can enhance the growth and virulence of both species, resulting in worse clinical outcomes. We found that the sensor kinase CbrA, which is known to regulate carbon catabolite repression and Pa metabolism, is necessary for Pa antagonism of Ca. This is in part through its control of the transcription factor PhoB which we have shown regulates the production of toxins with antifungal activity. Both CbrA and PhoB have been independently implicated in Pa fitness and virulence, but this work is the first that connects these two important regulators. We have also shown that a subset of clinical isolates that are associated with worse clinical outcomes and increased antagonism toward Ca have elevated CbrA activity and CbrA-mediated activation of PhoB. Understanding the mechanism of CbrA activation and its role in Ca antagonism will shed light on Pa polymicrobial interactions as well as in virulent clinical isolates. We propose that CbrA activity is mediated via the conserved Per-Arnt-Sim (PAS) domain via a redox-active small molecule ligand and the candidate will use genetic and biochemical approaches to test this model in Aim 1. As CbrA is conserved across other bacterial species, this will provide insight into similar regulatory pathways. In Aim 2, the candidate will investigate the role of CbrA and phosphate availability in PhoB-mediated Pa antagonism of Ca. Because PhoB activity is also controlled by extracellular phosphate concentrations, the candidate will examine the CbrA-PhoB relationship at physiological phosphate concentrations as well as the high phosphate concentrations present in many laboratory media. This candidate plans to pursue a career in academia in the area of microbial interactions in microbial communities. This work will be supported by several collaborations with biochemists and metabolomics experts, provide the candidate experience working with both a bacterium (Pa) and a fungus (Ca), and establish collaborations in critical areas including metabolite analyses and mentor relationships with researchers in the field. This project will provide opportunities for the candidate to develop their scientific and professional skills and advance their career in research.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Updates: I am moving to a new position at Dartmouth College as an independent, tenure-track Assistant Professor in the Department of Psychological and Brain Sciences. Here I will conduct the R00 phase experiments and develop my own independent research program. The overall aims of the R00 phase have not changed from the K99 proposal. Identifying the neural circuit mechanisms underlying both homeostatic and uncontrolled motivation are crucial for developing more targeted and effective therapeutic treatments for neuropsychiatric disorders like major depression or bipolar disorder. Within mesolimbic brain reward circuitry, the ventral tegmental area (VTA) is a major regulator of both reward and aversion. While generally reduced to its dopamine projection neurons, the VTA also contains neurons that co-release inhibitory GABA and excitatory glutamate and, similar to dopamine projections, can modulate motivation. However, the functional role of this GABA/glutamate co-release is still not well understood, and major questions regarding their role in positive vs. negative reinforcement remain. In particular, why would neurons simultaneously send an inhibitory and excitatory signal? During the R00 phase, I will unify my prior expertise with newly acquired skills to determine the physiological and behavioral role of a newly-described VTA GABA/glutamate projection to amygdala. Using in vivo calcium imaging, I will first monitor activity of VTA GABA/glutamate terminals in amygdala during an effort-based instrumental sucrose task (Aim 1), and will then identify the net effect of optogenetically stimulating VTA GABA/glutamate terminals on cell-defined amygdala populations (Aim 2). These results will significantly expand our understanding of the role of VTA co-release in complex motivated behavior relevant to models of bipolar disorder and depression, and will crucially pave the way for more targeted approaches that form the basis my independent research program.

NSF Awards · FY 2024 · 2024-09

Ni-based superalloys were developed in the 1940s and have been continuously improved ever since, culminating in the current single-crystal jet turbine blades made by directional solidification. However, the cost of such turbine blades exceeds $15,000 and replacement costs when a jet engine is overhauled can be hundreds of thousands to millions of dollars. Thus, a cost-effective method of producing Ni-based superalloy turbine blades is imperative. This award supports research into methods to produce columnar-grained structures or single crystals of nickel alloys by directional recrystallization (DR), a solid-state process, of additively manufactured (AM) material, in which the complex structures are built layer-by-layer by powder fusion. The goal is to investigate if production of a single crystal Ni-based superalloy turbine blade is feasible via the integrated route of AM and DR, and to understand the physics underlying such a processing route. The technology, although focused on Ni alloys, is nonspecific and could be used for other materials, and easily scaled up. The project will train undergraduates and Ph.D. students. In addition, undergraduates from Smith College and from the University of Massachusetts will undertake an annual workshop on AM technology. To gain a fundamental understanding of DR processing of AM materials, the project will use several printing strategies to make different AM microstructures using laser powder bed fusion and laser directed energy deposition of Ni-Al alloys, and the microstructures before and after DR processing will be characterized. The project will build a new DR system specifically for this purpose. Several scientific questions will be addressed: (1) Are carbides or similar insoluble particles necessary to prevent equiaxed grain growth and thus enable columnar-grained structures to grow? (2) Are the columnar structures produced by primary recrystallization or secondary recrystallization? (3) Can this technology grow columnar grains or single crystals at high hot-zone velocities? Previous work has indicated that the upper hot zone velocity to propagate columnar grains is substantially higher than that required to nucleate them. (4) Can this technology use a spiral growth selector built into an AM sample to provide grain selection during DR to produce single crystals? (5) Can single crystals or columnar-grained structures with complex geometries, such as hollow components used for air-cooled Ni-based superalloy turbine blades, be produced by the integrated approach of AM and DR? If successful, this project can generate new understanding in the manufacturing of high-performance alloys, which will advance aerospace industries and alloy manufacturing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Estimates of the magnitude of sea-level rise largely come from computer models that predict ice-sheet behavior. For these models to accurately predict sea-level rise, physical ice-sheet processes must be properly represented. Accurate predictions of ice-sheet behavior and the magnitude of sea-level rise are critical for decision makers. This project will simulate the complete disappearance of the Laurentide Ice Sheet that once covered much of North America. The retreat of the Laurentide Ice Sheet that began about 20,000 years ago presents a natural test case to better understand 1) the physical driving mechanisms that result in the complete disappearance of an ice sheet, and 2) the rate at which an ice sheet disappears. Lessons learned from this research will provide key insights into how large-scale ice-sheet retreat occurs which has clear relevance for predicting the future evolution of Earth’s vulnerable extant ice masses, such as the Greenland and West Antarctic ice sheets. A key question in ice-sheet science is determining how the influence of dynamic mass loss changes through time for a retreating ice sheet and what might control this variability. Lessons from prior episodes of ice-sheet retreat in the geologic record can elucidate how the role of dynamic mass loss changes with time in a fluctuating climate and improve ice-sheet model performance. The researchers will use the next-generation state-of-the-art Ice Sheet System and Sea-level Model (ISSM) to explore the disappearance of the Laurentide Ice Sheet over the last 20,000+ years. In a first-of-its-kind application, ISSM will be used at a spatial resolution capable of capturing large-scale ice-streaming and ice discharge through narrow fjords, along with implementation of coupled solid-Earth-sea-level feedbacks to investigate the role of dynamic ice discharge in driving the disappearance of the Laurentide Ice Sheet. To test model performance, the researchers will compare simulations of Laurentide Ice Sheet retreat against both existing and new geologic benchmarks generated over the course of this project. This project will provide the first quantitative estimates of how the percentage of dynamic mass loss versus surface mass balance evolved over the course of a full deglacial sequence and how this evolution influenced the fate of the Laurentide Ice Sheet. The project will develop a new collaboration with California State University, Long Beach, which is a designated minority serving institution, to recruit students from the Los Angeles area for internships at NASA’s Jet Propulsion Laboratory by leveraging an existing program. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

River floods in hilly and mountainous areas have caused billions of dollars in damage to homes, businesses, roads and bridges over recent decades. Local communities and planners rely on flood hazard maps to identify areas at risk of being submerged in river floods. However, floodwater scouring of the land beneath roads, bridges and buildings causes the most damage during floods in steep river valleys, and current flood hazard maps need to be updated to account for this risk. Furthermore, communities affected by recent floods have enacted various measures to reduce the damage from future floods, but it is unclear which of these measures are most effective in hilly and mountainous regions. Developing effective solutions to these problems requires close partnerships between scientists, communities most impacted by river floods, and professionals engaged in flood hazard planning. In this two-year project, three workshops are convened to build and strengthen partnerships, collect information about recent floods, and identify the most pressing research questions related to river flooding. The research team includes undergraduate and postdoctoral researchers. Data products and analysis are provided to communities to aid in decision-making and planning. This project has four goals: (1) strengthen partnerships and develop relationships with community organizations relevant to river flood hazards; (2) co-develop with community partners a suite of critical research questions in the broad areas of flood erosion hazards, flood adaptation solutions, and implementation challenges; (3) develop a database of flood erosion impacts and flood adaptation measures for local communities; and (4) identify effective strategies for sharing climate and flood data with communities. This project uses a Community-Based Participatory Research (CBPR) approach to build equitable community partnerships, and involves the participation from community members, organizations representing those most vulnerable to flooding, and actors engaged in flood hazard planning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Heart disease is difficult to study. Animal models are not always effective; neither are most cell culture studies. This leads to many failed drug developments. Scientists are now using human stem cells to make more faithful human cardiac models for research. One problem is that these cells are still immature, making it uncertain how well they can model disease. To develop a more effective representation of a heart, an attempt will be made to create a “heart on a chip”. The current standard methods of cardiovascular research are based on static two-dimensional cell cultures and animal models. They both have significant limitations. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have shown to be promising as an alternative for these in vitro studies. However, a key bottleneck in the current applications of hiPSC-CMs lies in their structural and functional immaturity, leading to less predictive results in disease modeling and drug toxicity tests. By employing biochip design, machine learning, developmental biology, and tissue engineering, this project will build the foundation for overcoming this obstacle and develop methodologies for an efficient and rational manufacturing pipeline of mature hiPSC-CMs. To achieve this goal, the team will develop models to understand cardiac cell-cell and cell-matrix interaction dynamics needed in enhancing the maturity of hiPSC-CMs using microchip engineering with artificial intelligence-driven feedback. The ability to manufacture mature hiPSC-CMs at scale and speed could accelerate drug and cardiac disease model development. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

To fully decode brain functions/dysfunctions and unlock brain-computer-interface potential, neural recording needs to be performed with high spatiotemporal resolution across three dimensions. This project will investigate a set of foundational flexible-electronic design and systems research problems to, for the first time, establish a new neural probe paradigm, a monolithic 3D neuroelectronic system. This program will not only produce a powerful tool for neuroscience research and investigating/diagnosing nervous system disorders but also create unique opportunities for novel prostheses and brain-computer interfaces. The team will maximize the broader impacts of our research by intersecting with (1) systems-based bioelectronic education, (2) K-12 outreach and undergraduate research, and (3) semiconductor workforce development. Cognition and behavior both rely on coordinated activity from neural circuits distributed in 3D. However, to date, the mainstay neural devices are constrained to 2D interfacing with the brain, largely due to the predominant planar semiconductor fabrication process that produces these devices. The investigator hypothesizes that a simple back-end-of-line (BEOL) rolling process can transform appropriately designed, post-fabricated flexible electronics into a 3D neuroelectronic probe with monolithicity and highly controlled electrode and shank distribution. This project will holistically test this hypothesis through novel rolling process development and corresponding design rule establishing, innovative neuroelectronic design and fabrication, chronic bench characterization, and in vivo system validation. The unprecedented monolithic 3D neuroelectronics will yield profound impacts not only for studying and connecting with the brain but also for a wide range of electroactive tissues, including peripheral nervous systems, cerebral organoids, and engineered nerve scaffolds. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

ABSTRACT A number of anti-HIV-1 broadly neutralizing antibodies (bNAbs) targeting highly conserved and vulnerable epitope regions of the envelope glycoprotein (Env) are being investigated for a range of clinical applications based on their ability to robustly prevent infection in a variety of animal models. Successful monoclonal antibody (mAb) prophylaxis aims to offer an alternative to vaccine development efforts, and the relatively long half-lives and tolerability profiles of bNAbs promise to offer a complement to the small-molecule inhibitors comprising current pre-exposure prophylaxis (PrEP) options. While bNAbs represent a promising approach to provide protection from infection, suppress plasma and tissue viremia, and reduce viral reservoirs, results from the first major bNAb prevention efficacy trial were mixed. Protection against infection with neutralization susceptible strains was observed, but fewer strains were sufficiently susceptible than anticipated, and overall efficacy criteria were not met. Our objective is to define and refine the means by which bNAbs can be used to restrict HIV replication in vivo using a more stringent model in which their ability to delay or prevent systemic viremia in the context of seeded HIV infection is monitored. We hypothesize that the antiviral activity afforded by a single bNAb can be enhanced by one or more of two distinct strategies that will be rigorously tested for in vivo antiviral activity by benchmarking their ability to delay detectable plasma viremia in the context of spreading infection. Guided by strong preliminary data, the project goals will be achieved though completion of two Specific Aims: 1) Define the ability of Fc engineering to improve bNAb antiviral activity across diverse envelope epitopes, 2) Define the ability of bNAb combinations, with and without Fc engineering to improve bNAb antiviral activity. Each strategy will be evaluated for effects on neutralization and effector function in vitro and in vivo for the ability to delay or prevent systemic viremia. Collectively, these studies will generate unprecedented insights into the means whereby bNAbs, if introduced in early infection after mucosal exposure, delay or restrict viral spread thereby lowering the viral burden and improving outcomes. This work will inform on both next-generation rational vaccine design and the ongoing deployment of bNAb prophylaxis and therapy—driving innovation relevant to combatting HIV acquisition and transmission across diverse intervention strategies and populations.

NSF Awards · FY 2024 · 2024-08

For a quantum system that evolves in isolation, conservation of the total energy demands that the generator of the dynamics, the Hamiltonian, obeys the mathematical constraint of “Hermiticity” – which ensures that observable quantities evolve reversibly in time. Still, non-Hermitian dynamics emerge naturally in open quantum systems whenever the interaction with the environment cannot be ignored, and dissipative, irreversible evolution ensues. For quantum systems comprising many indistinguishable, “bosonic” degrees of freedom (such as photons, phonons, or even more exotic particles like “magnons”), non-Hermitian effects can arise in the dynamics as a sole consequence of quantum statistics, despite the physical Hamiltonian being Hermitian at the many-body level. The exploration of non-Hermitian dynamics has witnessed an impressive acceleration recently, due to both the merger with fundamental aspects from topological physics and the identification of novel dynamical phenomena. Exciting applications have been uncovered, ranging from enhanced parameter sensing to new modalities for quantum-limited amplification and routing of quantum information. The broad aim of this project is to advance the knowledge frontiers of non-Hermitian physics, by both using concepts and tools from quantum information science (notably, “entanglement”) to characterize aspects of non-Hermitian dynamics in bosonic systems, and by fully embracing an open-system paradigm where non-Hermitian attributes and dissipation are integral to the operation and control of quantum devices. In parallel, this program will incorporate a strong educational and training component at the graduate and postdoctoral level, on subjects at the boundary between open quantum systems and quantum statistical mechanics, dynamical system theory, and quantum information processing. This project will synergistically incorporate theory and experiment throughout its duration. It builds on a body of theoretical results that the principal investigator has established for bosonic systems described by quadratic (“Lindblad”) master equations and on the joint experimental realization of a tunable non-Hermitian nonlinear microwave-cavity dimer, while pushing the investigation in several new directions. Specific research objectives include: (i) to obtain a complete theoretical understanding of non-Hermitian dynamics in quadratic bosonic systems, by seeking a characterization of dynamical stability phase transitions through the lenses of entanglement theory, and by allowing for explicit time-dependence, with a focus on Floquet non-Hermitian dynamics; (ii) to experimentally demonstrate a quantum analog of the tunable nonlinear dimer we have currently realized at room temperature, and leverage it towards achieving enhanced quantum state transfer in quantum networks; (iii) to make headway toward implementing and exploring many-body non-Hermitian nonlinear dynamics in a six-site bosonic system. Besides being responsive to a timely motivation, we expect the proposed program to contribute fundamental insight into the interplay between non-Hermiticity and many-body quantum physics. From a practical standpoint, these investigations may point to enhanced protocols for dissipative quantum information processing directly applicable in circuit quantum-electrodynamic settings. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-08

Project Summary Housing is a critical social determinant of health and key contributor to racial/ethnic health disparities in the US. In the context of rising housing costs, a recent recession, and the COVID-19 pandemic, experiences with housing instability such as foreclosure, eviction, and homelessness are a serious and growing public health concern. Black and Latino households are at an elevated risk of encountering these adverse housing transitions compared with their White counterparts. Moreover, the subsequent exposures to heightened psychosocial stress and financial strain have been shown to be particularly detrimental to Black and Latino physical and mental health. Despite policy efforts to increase homeownership among Black and Latino households, homeownership gaps remain large and have been widening. And given that homeowners are more advantaged than renters, including having access to own household wealth and wealthier kin networks, owners may be better equipped to sustain spells of housing instability over time and should be integral to understanding how health disparities manifest later in life. Yet, we know little about the long-term health consequences of housing instability, and how these stressful experiences contribute to racial/ethnic disparities in late-life health. In addition, much of what is known about wealth and late-life health rests upon research limited to Black-White comparisons, as well as work that has not considered the roles of extended kin financial resources and adverse housing transitions. To remedy these issues, this project will leverage nationally representative longitudinal data from the Panel Study of Income Dynamics (PSID) to evaluate a theoretical model of housing instability and late-life health among Black, Latino, and White households. The unique features of the PSID allow us to: (1) estimate the effects of housing instability on late-life health, and whether the effects vary by racial/ethnic group and housing tenure; (2) determine whether racial/ethnic disparities in exposure to housing instability mediate racial/ethnic health disparities later in life; and (3) determine whether extended-family wealth moderates the effects of housing instability on late-life health, and whether the health effects vary by racial/ethnic group and housing tenure. This project will complete these three aims using a counterfactual framework that produces robust causal estimates of housing instability over time on late-life health outcomes, including cognitive functioning, psychological distress, self-rated health, and functional limitations. Estimates will come from marginal structural models with inverse-probability-treatment weights, which will allow for time-varying confounders that overcome challenges facing conventional regression techniques (e.g., selection bias, reverse causality)—a key innovation of this project.

NSF Awards · FY 2024 · 2024-08

Solar flares are the most energetic phenomena in the solar system, during which the flare Above-the-Loop-Top (ALT) regions are the key to understanding energy release in solar flares. This project aims to obtain a more comprehensive picture of the energy release in flare ALT regions by systematically investigating the energy transfer associated with spatially resolved supra arcade downflows (SADs). The improved knowledge of the energy transfer in solar flares is critical to understanding the basic science needed to meet the goals of the National Space Weather Strategy and Action Plan, which aims to develop tools to forecast space weather and mitigate its impacts. The project involves state-of-art MHD models, innovative particle simulations, and an image synthesis approach, to compare with observations in multiple wavelengths and viewing perspectives (including microwave imaging spectroscopy in fans that have been rarely studied in the community). This project, led by several early-career women PIs, will involve undergraduate students and support a graduate student. There are outreach activities and developing open-source codes planned for this project. Over the decades, the developments of 2D standard solar flare models have significantly improved the comprehension of solar eruptions. However, recent observations have indicated the importance of SADs, which are frequently observed from a face-on viewing perspective, to energy transfer in flare ALT regions. The project will thoroughly explore the role of SADs in energy transfer in the ALT regions by combining observations and simulations. The science questions to be addressed are: (1) How do SADs engage in energy transfer in ALT regions? (2) What are the statistical features of plasma conditions around SADs? And (3) What are observational signatures related to energy transfer processes of SADs in ALT regions? First, they will perform a statistical study on the thermal characteristics and the physical relationship between these characteristics and the dynamics of SADs. Second, they will perform 3D magnetohydrodynamics (MHD) simulations to investigate the energy release in flares. They will synthesize the emissions incorporating different viewing perspectives and multi-wavelengths to compare with observations, including radio emissions in fans that are rarely discussed in the literature. Third, they will carry out particle simulations with time-resolved dynamics provided by the MHD framework to explore the impact of SADs on energetic particles. Combining the three steps above, they will comprehensively determine the role of SADs on energy transfer in flares and use the findings to improve the traditional scenario of energy release in flares. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY Knowledge of tissue oxygen levels has enormous clinical significance for accurate prognosis and treatment of several pathologies including cardiovascular diseases, stroke, wound healing, and cancer. Currently, there is an unmet need for devices that can measure oxygen reliably in the clinical settings. Although several methods are promising for clinical oximetry, they lack the ability to make reliable and repeated measurements of absolute values of oxygen, for example pO2, during or post-therapy. Oximetry based on electron paramagnetic resonance (EPR) offers certain unique advantages including accuracy, direct detection and high sensitivity and specificity to molecular oxygen (O2). Unfortunately, the adaptation of EPR oximetry for clinical measurements is faced with certain limitations, most notably due to restrictions that arise from the existing hardware. The conventional EPR systems are large, bulky units with restrictive spacing between the magnet poles (for patient placement) and require the patient to be transported to the EPR facility for measurements. Major changes in the hardware and more importantly out-side-the-box approaches in the overall design are needed to make the EPR technology a viable tool for use by bedside or at treatment site for successful clinical adaptation and implementation. The overall goal of this project is to develop an innovative device for on-site monitoring of pO2 in patients. We propose to construct a unique self-contained ultra-small, needle-shaped EPR probe-head, namely OxyTrack that can be used on-site, in the clinic or procedure room. In contrast to the existing EPR systems that contain a formidably large magnet thereby necessitating the patients transported to the EPR magnet, our innovative approach will use an extremely miniaturized magnet that is tightly integrated with resonator and oxygen-sensing probe, making a single unit (sensor). The integrated unit will be built inside the tip of a 21G syringe needle for minimally invasive insertion into tissues of interest. The EPR spectrometer, an external device connected to the OxyTrack needle, will be built based on state-of-the-art software-defined-radio (SDR) technology. We will assess the efficacy, reliability, and safety of the OxyTrack using tissue models and animals and validate the system performance using existing methods for oximetry. The specific aims of this project include: (i) Design and construction of an OxyTrack needle with built-in magnet, resonator, and oxygen sensor; (ii) Development of a compact spectrometer to work with the OxyTrack sensor; and (iii) Testing and validation of the OxyTrack system performance in vitro and in vivo. The OxyTrack oxygen sensor, when established as intended, will be a very valuable clinical tool for clinical conditions where tissue oxygen is a critical variable for decision making, e.g., cancer patients and patients with diabetic peripheral vascular diseases.

NIH Research Projects · FY 2026 · 2024-08

A substantial amount of research over the past 50 years involving Medicare and other health insurance claims data has focused on evaluating variation in health care use and outcomes across geographic regions. For example, over the last quarter-century, the Dartmouth Atlas Project has focused on variation in Medicare feefor-service health care use for diagnostically defined cohorts of patients, often conditioning on future outcomes (e.g., death) to account for variation in health status. Numerous other claims studies have also used Medicare claims data to estimate comparative effectiveness of different treatments and procedures. Almost all of these types of research studies have used a nationwide measure of health care markets created at Dartmouth known as “Hospital Referral Regions (HRRs).” These regional markets, and the methodology underlying their delineation, have remained largely unchanged for nearly 30 years. In addition, because Medicare primarily covers individuals aged 65 and over, these regional measures—even at the time—are not representative of the whole population, leading to questions regarding the external validity of the published results especially given the tendency to equate such findings with the whole population. Motivated by the recent surge of interest in health and health care, a growing interest in cutting-edge statistical and machine learning methods, availability of newer and more extensive data on younger populations, and advances in network and geospatial analysis, this project proposes to revisit the methodology, definitions, and practical applications of regional and network measures of health care use and outcomes. These new approaches will avoid the potential fallacies of prior geographic measures by better capturing care patterns of populations of interest, and will facilitate geographic variations and comparative-effectiveness research with greater statistical power to detect effects of interest. Secondly, this project will develop new measures that quantify heterogeneity of geographic and other variations in use and spending across population strata, including heterogeneity indices. Thirdly, this project will evaluate the lack of representativeness of Medicare estimates and develop procedures to generalize results to other populations. Results of all analyses, including the algorithms for HRR delineation, will be used to modernize statistical and geographic approaches to characterizing health care access, use and outcomes. These will be widely disseminated to research and stakeholder communities, thus empowering health professionals and researchers to define analysis and administrative units pertaining to their specific health care systems and needs. This project will have a major impact on the research communities engaged in the evaluation of geographic variation in health care delivery and health outcomes.

NIH Research Projects · FY 2025 · 2024-08

Project Summary Common genetic variation is an important player in human diseases. One central goal of human genetic studies is to identify causal genetic variants in diseases and understand the mechanism. Many genome-wide association studies (GWAS) have been performed to identify associations between genetic variants and a myriad of human diseases. However, moving from GWAS results to identification of causal variants, and a mechanistic understanding of how the variants elicit diseases remains a major challenge in the field. This challenge is what I aim to address in my research program. Recent research efforts have led to the generation of large scale functional genomic datasets, in particular single cell transcriptomic and epigenomic data. Because most common variants are located in noncoding genomic regions and their functional effects are mostly unknown, such functional genomic datasets have the potential to provide important information about the variant’s functional role, for example if a variant has gene regulatory effect, which cell or tissue type it has an effect in, if such an effect is related to diseases, etc. However, the current methods and analyses used by researchers in the field are unable to garner such information from existing data, so critical gaps in connecting variants to diseases exist. The overall goal of the PI’s research program is to develop the new statistical methods and analyses needed to leverage functional genomics data, in conjunction with GWAS data, to understand variants’ functional effects and their roles in diseases. This goal will be achieved by advancing three key areas: (i) Identification of response expression quantitative trait loci (eQTLs), which are genetic variants that are associated with gene expression only under certain conditions. A powerful response QTL mapping pipeline will be established and used to study response QTL properties and relevance to diseases. (ii) Identification of disease critical cell states using single- cell chromatin accessibility profiling data. Single-cell chromatin accessibility profiling data provide a high- resolution view of cellular regulatory landscapes; novel methods will be established to assess the relevance of these different cellular states to diseases. (iii) Identification of effect context for individual causal variants. A variant may affect a disease through one or a few cell/tissue types relevant to the disease, but this is often not known. Work in this third research area will establish a statistical model that leverages multiple types of functional genomics datasets to address this question. The PI’s work in these areas will yield critical insights about the effect of genetic variation and disease etiology. New approaches and open-source tools for studying common genetic variants and disease genetics will be established. These tools are greatly needed by the research community to make full and effective use of the fast-accumulating functional genomics and GWAS datasets.

NSF Awards · FY 2024 · 2024-08

This project takes a new approach to an old question: how do the rich keep getting richer? Wealth inequality has grown to levels not seen since the Gilded Age of the late 19th Century. For over a century, sociologists have known that elite secrecy supported by clandestine networks of financial and social relationships are major contributors to wealth inequality, but lack of data has limited investigation of the precise relationships. With newly available Big Data resources and advanced network analysis techniques this classic theory has become increasingly relevant and is primed for a data-driven revival. In particular, our project examines empirically at an unprecedented scale the highly confidential offshore financial networks that have built the fortunes of a few thousand high-net-worth individuals around the world to historic levels. By conducting a global network analysis of the phenomenon, informed by recent availability of one of the largest public datasets in the world—the Offshore Leaks database, containing almost 7 terabytes of data, including the Panama, Paradise, and Pandora Papers—this study provides greater clarity than previously has been possible on this topic of timely interest to scholars and decision makers. Guided by questions generated by in-depth ethnographic research on offshore finance, network science and machine learning are used in a large data structuring, analysis, and augmentation effort to: 1) build theory and data infrastructure to advance high-quality research on stratification and secrecy, and 2) address unanswered questions about the growth and network structure of global inequality. Additional contributions to social science include a unique and valuable database resource for other social scientists and a new multi-dimensional model of secrecy. This project is jointly funded by the Sociology Program and by the Human Networks and Data Science - Research (HNDS-R) Program. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

Cereals, such as rice, maize, wheat, and barley, are the most important caloric food sources worldwide. In cereal seeds, two diametrically opposed processes occur in close proximity: ethylene-induced programmed cell death in the starchy endosperm and the maintenance of living cells in the adjacent embryo. The gaseous plant hormone ethylene readily diffuses across cells and tissues, and how the embryo is protected against ethylene-induced programmed cell death has not been determined. The goal of this project is to uncover fundamental mechanisms underlying how the seed embryo is protected from programmed cell death during development using rice as an experimental system. In addition to elucidating a critical developmental mechanism, results from the study will provide avenues by which to modify crops to protect them against a changing climate. The proposed research will provide excellent training opportunities for graduate students and postdoctoral fellows. The principal investigator will participate in public forums to raise science awareness and, through a local partnership, implement an art-science program for pre-teens aimed at developing education and science awareness through a hands-on active learning experience. The goal of this project is to elucidate the role of a clade of ethylene receptors that are hypothesized to modulate ethylene sensitivity on the process of programmed cell death during rice seed development. The first objective is to determine the temporal and spatial pattern of receptor expression in the rice seed, and to determine how this correlates with ethylene activity and programmed cell death. The second objective is to functionally characterize receptor roles in the rice seed by employing CRISPR/Cas9-generated loss-of-function mutations. Mutants will be evaluated for physiological and molecular effects in the embryo and endosperm, along with the effects of ethylene, drought stress, and heat stress, which are predicted to increase sensitivity of the mutant seed to programmed cell death. As a complement to the loss-of-function approach, in the third objective the effects of ectopic receptor overexpression will be evaluated as well as the ability of different receptor variants to rescue mutant seed phenotypes. Additionally, to gain an evolutionary perspective on the role of ethylene in seed development, distantly related grasses to the cereals will be evaluated for how their complement of ethylene receptors correlate with sensitivity to programmed cell death. This award was co-funded by the Physiological Mechanisms and Biomechanics and the Plant, Fungal, and Microbial Developmental Mechanisms Programs in BIO-IOS. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

This award provides support to the Ice Drilling Program (IDP) to provide community leadership and to operate and maintain a facility to support ice drilling engineering, field support, and education and outreach. The intellectual merit of this project is embodied in the four closely linked leadership goals of this project which include: 1) producing and maintaining long-term and short-term integrated science and drilling technology plans in collaboration with the U.S. and international ice coring and drilling research communities, 2) providing field support with drilling equipment and expertise to support NSF-funded science, 3) identifying new technology needs and seeking funding for technology development and acquisition, and 4) enhancing communication and information exchange related to ice coring and drilling science and technology within the US and international ice science community. These goals relate to the importance of evidence from the polar ice sheets from ice cores, subglacial bedrock cores, and boreholes to access the subglacial aqueous environment, which has led to many important discoveries that have revolutionized climate science. These discoveries have also had important impacts on policy and thus also have societal relevance. Continued U.S. scientific leadership in this area depends critically not only on the support of scientists doing this research but also on the continued support of a dedicated facility to provide the field drilling support and accomplish engineering and technology development activities. This program and its education and public outreach activities will help to launch graduate students into promising careers and the resulting scientific discoveries will benefit all citizens. Achieving the goals of this project will enable the U.S. ice science research community to realize implementation of their national and internationally-coordinated scientific goals, lead the world in ice science discoveries, nurture the education and development of the next generation of scientists and engineers, and help to communicate the importance of the discoveries to all. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-07

Applicant: Andrea Bucknam Project Summary/Abstract Natural product synthesis contributes significantly to the identification and development of potential therapeutics. Retrosynthetic analysis of a natural product target demands innovation at all levels of study, giving rise to the design of novel reaction technology and creative application of established reactivity to provide access to structures with pharmaceutical potential. Tetracyclic triterpenoid natural products present a challenging landscape for synthetic organic chemists to explore novel chemical transformations. More than one hundred FDA-approved drugs are tetracyclic triterpenoids. Cardenolides are a class of tetracyclic triterpenoid natural products with many members having demonstrated medically-relevant biological activity, but further investigation of their pharmaceutical potential is hindered by limited access to natural sources and a lack of reported approaches to synthesis of the cardenolide carbon framework. The research project proposed herein would report a solution to key challenges to cardenolide synthesis—C10 and C13 quaternary centers, C14 tertiary alcohol, and C17 substitution (steroid numbering)—thus establishing an asymmetric de novo synthesis of a cardenolide natural product, sarmentogenin. A novel oxidative dearomatization/Wagner-Meerwein rearrangement, in which a 1,2-methyl shift from C9 to C10 would establish the quaternary center at C10 and oxidation in the C-ring. This synthesis would be an application of a recently reported methodology from the Micalizio group to install C17 substitution, a historically significant challenge to completing the total synthesis of cardenolide natural products. The long-term success of the project proposed herein would be a report of a cardenolide total synthesis, paving the way for future investigations of pharmaceutically-relevant cardenolide bioactivity. The fellowship award would support continued graduate research and training in the Micalizio laboratory at Dartmouth College. The Micalizio group has a well-established program for developing novel reaction technology to concisely synthesize complex natural product targets. The research supported by the award would take place in an established organic synthesis laboratory with all necessary equipment for the preparation, purification, and characterization of organic compounds.

NSF Awards · FY 2024 · 2024-07

This award will fund about 15 U.S.-based graduate students for attending the 2024 IEEE Secure Development (SecDev) conference from October 7-10, 2024 in Pittsburgh, PA. Research on software security usually focuses on detecting vulnerabilities in software and attacks on resources. However, there is little attention to how programmers can develop secure software from the ground up. The SecDev conference aims to continue its mission of providing a forum where researchers, practitioners, and decision makers can meet to discuss ideas that focus on building security into deployed systems, on topics including development libraries, tools, or processes to produce systems resilient to certain attacks; formal foundations that underpin a language, tool, or testing strategy that improves security; techniques that improve the scalability of security solutions for practical deployment; and experience, designs, or applications showing how to apply cryptographic techniques effectively to secure systems. This award will fund high-quality students who would otherwise not be able to participate in this event. Student participation in SecDev has a number of benefits, allowing them to meet with researchers and leaders in the community to advance both their on-going research and their career development. Student participation also serves larger goals of widening the talent pool of professionals and researchers focused on addressing challenges of developing critical secure systems and services. To this end, the conference will widely advertise the availability of support for students who need funding to attend, to increase the diversity of personal and institutional backgrounds of potential attendees. Students will be selected based on the quality and fit of their research to the goals of the conference, their financial need, and the benefit they are likely to gain from attending; the selection committee will also ensure that students from a wide range of institutions can participate in the conference. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-07

Prediction of Residual Cancer Burden (RCB) early in treatment can enhance long-term survival outcomes for breast cancer patients undergoing neoadjuvant chemotherapy (NAC) and their long-term survival.1-3 Near-infra- red spectral (NIRS) tomography (NIRST) provides operational advantages over other imaging technologies (e.g., mammography, ultrasound, Magnetic Resonance Imaging (MRI), CT, Positron Emission Tomography) in the NAC setting because it is noninvasive, portable, low cost, and does not use ionizing radiation or exogenous contrast agents. Crucially, NIRS captures biophysical changes in tissue occurring in the vascular, intra- and extra-cellular matrix compartments. These subtle changes signal a tumor's early response to NAC, even before visible tumor size modifications occur.4-7 Compared to other optical imaging modalities that use reflectance light, which limits tissue imaging depth8, 9, or require high-power lasers posing safety risks10, NIRST captures diffused tomographic signals, allowing for deeper breast tumor sensing. In our previous studies, we have pioneered a NIRST system that quantifies vascular changes in the breast during NAC, highlighting tumor response within about two minutes as the patient sits in a semi-reclined position.11,12 This system correlates tumor NIRST changes with clinical outcomes based on residual cancer burden (RCB) classification.13 Our clinical NIRST data from 35 women on NAC persuades us of NIRST's potential to revolutionize the clinical approach to these patients. This belief stems from recently published results which showcase the normalized percentage change of total hemoglobin in a tumor (ΔHbT%) by the end of the first cycle as a compelling biomarker that discerns either RCB-0 or RCB-II from all cases in other classes (p £ 0.001).13 A thorough multi-class Receiver Operating Curve analysis offers an Area Under the Curve of 0.80, emphasizing the precision of ΔHbT% in distinguishing between RCB classes. We envisage elevating our system's efficiency by integrating flexible circuit strips through a sleek, wearable 64-channel breast interface and applying 3D image reconstruction that reflects full tumor response (instead of partial tumor volume) – the focal point of our proposed Aim 3. Our previous data further indicate that NIRST's diagnostic performance remains undiminished when relying solely on continuous-wave signals and patient-specific scattering estimates derived from mammograms or MRI defined breast density.14 These insights have shaped the hardware platform proposed in Aim 1. However, the current iteration of our NIRST system faces challenges from its dependency on large-core fiber bundles for receiving light from the patient's breast. By phas- ing out these cumbersome fiber bundles, we open avenues for novel 3D image reconstruction methods en- hanced with deep learning—as set out in Aim 2. In essence, this project focusses on technological innovations aimed at creating a comprehensive NIRST breast imaging platform, designed to forecast RCB in early stages of NAC. Accordingly, we are transitioning this platform from academic exploration to a clinically practical solution, while concurrently seeking additional funding to facilitate expansive clinical studies in the foreseeable future.

NSF Awards · FY 2024 · 2024-07

Microbial populations are highly heterogeneous, with different phenotypes emerging even among cells that are genetically identical. This coexistence of cells with different attributes is an important aspect of microbial ecology, conferring resilience and adaptability to microbial populations. Remarkably, the emergence of heterogeneity does not necessarily depend on complex cellular mechanisms, but can instead be achieved through fundamental physical and biological processes that are common to all microbes. Yet, despite our broad understanding of microbial physiology, we still lack a framework to connect the molecular processes happening at the cellular scale to the complex behaviors we observe in microbial communities. The goal of this award is to understand the role of two general features of microbial populations in generating phenotypic diversity: noise in gene expression and spatial variations across microbial colonies. Using antibiotic responses in bacteria as a model system, this project will investigate how these features affect responses in single cells, providing a mechanism for the emergence of complex collective behaviors such as increased antibiotic resistance and “memory” from past events. These studies advance basic research by laying a foundation for future investigations into how complex environments mediate microbial evolution, as well as developing state-of-the-art experimental and computational methods, ultimately leading to a framework to predict the behavior of microbial populations that will guide the development of synthetic systems for biotechnology applications. With support from the National Science Foundation, this research project aims to investigate the hypothesis that the interplay between drug action, gene regulation and cell metabolism determines phenotypic diversity and collective behavior in microbial populations during antibiotic responses. To overcome difficulties in studying cell responses across multiple scales, this approach combines microfluidic experiments to image single bacterial cells and biofilm-like colonies with liquid-culture experiments to measure growth in large planktonic populations. These experiments will be leveraged to develop physical models of the dynamics of antibiotic responses. The research plan will answer two questions: 1) How do stochastic fluctuations generate phenotypic diversity? Here, the investigators will develop a theory to understand how metabolism-mediated feedback mechanisms amplify stochastic variations to generate phenotypic variability in a predictable manner. These results will describe the nature and stability of these different phenotypes and connect single-cell heterogeneity to population-level growth. 2) How are collective responses coordinated among different phenotypes in spatially structured microbial colonies? Here, the investigators will develop a theory to understand the contribution of spatial structure to the collective mechanisms of resistance provided by organization into biofilms. Together, these aims will elucidate how heterogeneity emerges in microbial populations and how it gives rise to complex behaviors at the population level. This project is jointly funded by the Physics of Living Systems and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY In our daily lives, we frequently encounter ambiguous information. Navigating this ambiguity—generating interpretations, adapting them in response to new information, and encoding them in memory—plays a pivotal role in shaping our thoughts and behaviors. Biases in interpretation and memory are both risk factors and symptoms for major depressive and anxiety disorders, with clinical strategies like cognitive reappraisal— deliberate, targeted changes in how someone interprets a situation—aiming to mitigate these biases. However, past work has either focused on isolated parts of this process (e.g., how someone forms an interpretation without examining their likelihood of shifting it) or used simple perceptual stimuli (e.g., visual illusions) where individuals alternate between a small number of definitive percepts. Real-world scenarios, particularly social ones, are inherently more subjective and thus, are more likely to reveal biases associated with conditions like depression or anxiety. Despite their importance, social scenarios have received limited attention in this research context, possibly because of the difficulty in balancing experimental control with ecological realism. This proposal aims to address these gaps by combining functional magnetic resonance imaging (fMRI) with a novel behavioral task paradigm that mimics real-life social ambiguities. Leveraging advancements in natural language processing (NLP), my task involves presenting participants with ambiguous social scenarios, collecting their subjective interpretations, and then exposing them to alternative views from other participants. NLP enables the objective comparison of a virtually unlimited number of interpretations in order to generate alternatives in real time that are tailored to how the participant just interpreted an image. Past work has demonstrated that multivariate neural patterns reflect differences in percepts and interpretations across subjects as well as changes in percepts within subjects, even when sensory input is held constant. My study will investigate where and how shifts in neural patterns to the same sensory information (namely, ambiguous social photographs) predict changes in interpretations (Aim 1) and the encoding of these interpretations into memory (Aim 2). I anticipate that I will find distinct, yet complementary, neural substrates supporting these behaviors. Ultimately, this research will yield a mechanistic model explaining where, how, and why the same sensory information can lead to different subjective interpretations and how these interpretations are encoded into memory. This model will contribute to our fundamental understanding of these cognitive processes and will also generate testable hypotheses for therapeutic interventions aimed at normalizing interpretational and memory biases related to subjective information.

NSF Awards · FY 2024 · 2024-06

Algebraic geometry is the study of geometric objects, called varieties, which are defined by the solution sets of systems of polynomial equations. It is a far-reaching branch of mathematics, making connections with many other research areas such as commutative algebra, number theory, differential and complex geometry, representation theory, and mathematical physics. In this project the PI will study certain families of varieties that play an important role in the classification of all varieties, namely hyperkaehler varieties and rational varieties. This project focuses on arithmetic questions about these two families. The project includes research training opportunities for undergraduate and graduate students, as well as outreach activities to strengthen the community of individuals in algebraic geometry from underrepresented backgrounds. This project is jointly funded by the Algebra and Number Theory Program and the Established Program to Stimulate Competitive Research. This research program is centered around three projects. In the first, birational transformations of hyperkaehler varieties will be used to study Brauer classes on K3 surfaces in order to identify which Brauer classes can arise as exceptional loci in hyperkaehler contractions. This makes connections to questions about the rationality of families of cubic fourfolds. The second is to study the behavior of rationality of fourfolds in arithmetic families, giving an analogue to previous results in families over the complex numbers. The third project is centered around the intermediate Jacobian torsor obstruction to rationality for geometrically rational threefolds, with the goal of characterizing rationality for a certain family of conic bundle threefolds. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-05

PROJECT SUMMARY/ABSTRACT CANDIDATE: I am a Postdoctoral Research Associate at Memorial Sloan Kettering Cancer Center (MSKCC). During my Ph.D. studies, I dedicated myself to developing biology-based mathematical models of bacterial metabolism. My current research extends my interest from single organisms to microbial communities, with a particular focus on the human intestinal microbiome. Since joining MSKCC, I have compiled a large longitudinal microbiome dataset from hospitalized patients who have undergone allogeneic hematopoietic cell transplantation (allo-HCT). I have also acquired bioinformatic skills and data-driven modeling techniques to profile microbiome compositions and quantify their associations with clinical outcomes. Built upon this dataset, my proposed research aligns well with my long-term career goal of establishing an independent laboratory to elucidate mechanistic links between the intestinal microbiota and infectious diseases. To prepare for my transition to independence and developing a competitive computational research program, I have developed a focused career plan to enhance my computational skills in metagenomic/metabolomic data analyses, community metabolic modeling, and development of neural network models. In parallel, I will improve my soft skills, including presentation, networking, grantsmanship, mentorship, leadership, and teaching. RESEARCH: Immunocompromised patients undergoing intensive antimicrobial therapy are at high risk for developing invasive fungal bloodstream infections (BSIs). Between 2016 and 2020, C. parapsilosis was responsible for the most breakthrough BSI cases among allo-HCT recipients at MSKCC. Typically, C. parapsilosis BSI occurs subsequent to its intestinal expansion. This proposal will leverage my mathematical modeling expertise and the vast microbiome dataset of our allo-HCT cohort to elucidate the ecological mechanisms underlying intestinal expansion of C. parapsilosis. My central hypothesis is that altered intestinal metabolic environment enables C. parapsilosis expansion. Specific Aim 1 will identify bacterial secreted metabolites that inhibit C. parasilosis. In Specific Aim 2, I will investigate the impacts of genomic variations across different C. parapsilosis isolates on their ability to utilize nutrients and grow in the human intestine. The Specific Aim 3 will involve building a machine-learning-powered computational framework for the risk assessment of C. parapsilosis expansion and the rational design of antifungal therapy to reduce the risk. ENVIRONMENT: I will complete the K99 phase of this grant in the Computational & Systems Biology Program at MSKCC, a state-of-the-art cancer research institute. My primary mentor, Dr. Joao Xavier, has a proven track record in mathematical modeling of bacterial microbiomes, while my co-mentor, Dr. Tobias Hohl, is an expert in fungal mycobiomes and infectious disease. The two labs will jointly provide a rich and complementary training and research environment that integrates computational, experimental, and clinical resources.

NIH Research Projects · FY 2026 · 2024-05

PROJECT SUMMARY The preschool years (2-5 years of age) is a critical timeframe to shape the lifetime risk of obesity. While the causes of obesity are complex, appetitive traits related to overeating, such as high food approach and low food avoidance, are robustly associated with a greater BMI among children. Some children are genetically pre- disposed to expressing obesogenic appetitive traits, and those traits may mediate a genetic risk for obesity. Separately, parental feeding practices are emerging as an important, yet modifiable, influence on children’s obesity risk. Coercive control feeding practices, such as strictly limiting a child’s intake of highly palatable foods (restriction) and using food to control children’s negative emotions (emotional feeding), are believed to be detrimental for young children because they impede self-regulatory skills around eating and may increase the saliency of highly palatable foods. Our goal for this project is to disentangle the inter-relationships between coercive control feeding practices, children’s obesogenic appetitive traits, and children’s dietary intake across the preschool years to understand how coercive control feeding practices ultimately impact children’s adiposity gain over time. Importantly, we aim to understand how those effects differ based on children’s underlying genetic risk for obesity. We hypothesize that parents will respond to children’s obesogenic appetitive traits by exhibiting more coercive control feeding practices (restriction, emotional feeding), which in turn, will promote future increase in obesogenic appetitive traits and overconsumption, leading to excess adiposity gain among children. Importantly, we hypothesize children with a high genetic risk for obesity will be most susceptible to the negative effects of coercive control feeding practices because food is highly salient for them. We will test our hypotheses among a cohort of children aged 2.5 years old using a longitudinal study design with repeated assessments every 6 months until children are 5 years old. We include validated assessments of parental feeding practices, child appetitive traits and usual dietary intake. We will assess children’s genetic risk for obesity via candidate single-nucleotide polymorphisms (SNPs) and a polygenic risk score. Importantly, our novel approach expands upon previous research by including our lab’s proven, objective paradigm to measure children’s food approach and overconsumption. Specifically, we will use eye-tracking to measure children’s attentional bias to food, an objective metric of food approach. We also include an eating in the absence of hunger paradigm to objectively measure children’s overconsumption. Study findings can be leveraged to develop tailored strategies to help parents support healthy eating behaviors among their young children that consider the heterogeneity in obesogenic appetitive traits among young children due to genetic risk factors.