Johns Hopkins University

NIH Research Projects · FY 2024 · 2024-12

Project Summary Biological sex has profound effects on the effectiveness of vaccines that protect against pathogens of pandemic potential, including influenza A viruses. Following influenza vaccination, females of reproductive ages (18-49 years) produce greater antiviral antibody responses than age-matched males, which correlates with greater estradiol (E2) concentrations in females. How estrogens drive greater B cell activation and antibody production after vaccination is not known. Estrogen receptor signaling in B cells might alter metabolic signaling to cause sex differences in vaccine-induced immunity. Activation of mTOR, in particular, and a switch towards β-oxidation as a primary energy source has been identified as indispensable for B cell proliferation, differentiation, and antibody production. Prior studies have demonstrated that females show greater preference for the use β- oxidation for energy production when under high energy demand. Thus, I hypothesized that differential activation of mTOR and downstream utilization of lipids for β-oxidation may be a potential mediator of sex differences in vaccine-induced immunity. My preliminary data show that after H1N1 vaccination in mice, adult females have greater activation of mTOR and mTOR-related proteins in splenic B cells than age-matched males. I hypothesize that greater mTOR activation in B cells from females is partially regulated by E2 through an ERα-mTOR feedback loop. My central hypothesis is that sex steroid signaling causes distinct metabolic signatures in B cells and that differential regulation of mTOR is the central mechanism governing sex-specific differences in vaccine-mediated humoral immunity. In Aim 1, I will test whether manipulation of mTOR and selected downstream proteins using small molecule agonist and antagonist can reverse sex differences in immune responses using a mouse model of influenza vaccination. I will use immunofluorescence assays and seahorse analysis of mitochondrial respiration to dissect sex differences in metabolic activation in B cells following vaccination, which will be correlated with measures of protective immunity. In Aim 2, I will examine the effects of sex chromosome complement and sex steroid signaling on both mTOR activation and metabolic activation of B cells. Through these experiments, I seek to define the cellular mechanisms mediating sex differences in vaccine-induced immunity. These results have significant translational application. As a fellow, the research that I have outlined is crucial to extend my training in animal models, viral immunology, sex-based biology, and biomedical research to refine my expertise in using metabolomics-based approaches to gain mechanistic insight into biological phenomena.

NIH Research Projects · FY 2026 · 2024-12

Abstract: Radiopharmaceutical therapy (RPT) is a highly effective cancer treatment, especially for metastatic cancers. There is significant interest in developing novel radiopharmaceuticals labeled with β-emitters (βRPT) or α-emitters (αRPT) for various cancer types. Due to the limited range of α-particles and the low energy of β-particles, it is crucial to measure the distribution of these radiopharmaceuticals at a microscale level within the organs and tumor anatomy of small animals, commonly used for studying RPT toxicity and efficacy. For example, while the full liver and kidneys may serve as sources and targets in the regular dosimetry schema for intermediate-to-high energy βRPT, more relevant sources for αRPT and low-energy βRPT might be the blood sinuses in the liver lobules or individual glomeruli in the kidney nephrons. Associated targets could include the central Kupffer cells or the convoluted proximal tubules, respectively. Conversely, tumor morphology is intricate, involving cells at different stages of the cell cycle, each potentially associated with distinct target densities and distributions for radiopharmaceuticals. Current imaging technology lacks the capability to convey high-resolution information on in vivo radioactivity distribution, necessitating the acquisition of data through ex vivo methods. Importantly, these methods also lack the ability to provide real-time mapping of the distribution of RPTs and their kinetics in living animals. In this project, we propose to develop a hyperspectral single-photon emission microscope system, named Alpha-Scope, for in vivo 3D autoradiography of radiopharmaceuticals and the radioactive daughter radionuclide in small animals. The Alpha-Scope system utilizes a novel CZT imaging spectrometer, offering excellent intrinsic detector resolution and unprecedented energy resolution over a wide energy range of 30-600 keV. This allows for effective separation of the γ-ray and x-ray peaks from therapeutic radionuclides and most of their radioactive daughters. The advanced detector hardware will be combined with a novel synthetic compound eye gamma camera design to provide ultrahigh sensitivity while allowing simultaneous imaging of multiple radionuclides at an excellent imaging resolution of 100 μm. Furthermore, we will develop a novel approach that leverages predicted posterior estimates and incorporates data fidelity corrections to handle high-noise data. The new imaging system will be validated through phantom experiments and small animal studies using αRPT currently under investigation at JHU. The outcome of this project will yield an unprecedented imaging tool crucial for the development and comprehension of novel RPTs. As specified in the STRIPE FOA, this tool will be particularly valuable for examining target efficacy, studying microdosimetry, and understanding radiobiological effects on both normal tissues and tumors, facilitating treatment optimization.

NIH Research Projects · FY 2025 · 2024-12

PROJECT SUMMARY: Cognitive flexibility is disrupted in many neuropsychiatric diseases, but how the brain generates flexible behavior is not fully understood. Learning from recent actions requires neural mechanisms that maintain information about relevant decision variables to influence future decisions. Persistent activity in cortical areas required for cognitive flexibility, such as prefrontal cortex (PFC), connect an animal's choices and recent outcomes. Neural mechanisms for generating and maintaining this persistent activity involve excitatory loops between the neocortex and subcortical structures. Recent studies suggest that the claustrum, a poorly understood subcortical nucleus that forms reciprocal connections with the neocortex, is particularly highly interconnected with cortical areas strongly implicated in behavioral flexibility. We propose to test whether the claustrum contributes to generating flexible behaviors using two tasks, dynamic foraging and reversal learning. These tasks require medial prefrontal cortex (mPFC) and lateral orbitofrontal cortex (lOFC) function respectively, two areas likely influenced by claustrum activity based on recent studies of claustro-cortical- claustral loops. First, we will test the hypothesis that the activity of claustrum neurons encodes decision variables in these two tasks. Second, we will determine whether claustrocortical neurons are required for dynamic decision making and reversal learning, respectively. In addition, we will test whether claustrocortical projections contribute to generating persistent cortical activity and influence the encoding of decision variables by cortical neurons. We will further test whether claustrocortical neurons with projections biased to two different cortical areas, Cla→mPFC and Cla→lOFC neurons, form distinct functional modules within the claustrum and whether the claustrocortical projections to mPFC and lOFC influence cortical activity using similar cellular mechanisms. Third, we will test whether claustrocortical projections are required for learning at different timescales, both during and after the acquisition of a reversal learning task. We predict that claustrocortical loops contribute to generating and maintaining persistent activity in the cortex required for task performance and learning at multiple timescales. Together, these data will represent the first studies of claustrum neurons in well established, carefully controlled, decision-making tasks combined with quantitative models using normative theory. Furthermore, these experiments will directly test effects of claustrocortical inputs on an animal's responses and on cortical activity during flexible behavior, enabling the integration of the claustrocortical system into models of flexible decision making and cognitive control in health and disease.

NIH Research Projects · FY 2026 · 2024-12

Summary Radiofluorination is one of the most important processes in molecular imaging, and to date, metal- centered fluorination by either substitution or exchange mechanisms have been infrequently designed and implemented for short-lived fluorine-18 since its inception in the early 1970s. The broad aims of the project are to develop new methods of fluorine-18 incorporation into complex molecules by using irreversible metal-fluorine bond formation. This will both complement and contrast the currently existing fluorination methods for radiochemistry, including that of aluminium fluoride (AlF), which has proven successful but with some apparent limitations. Each metal center will be evaluated for its pharmacological properties, as well as indirect effects such as the capacity to act as a multi-modality core or ability to pair with a therapeutic isotope in the same chelator to create a theranostic pair, and upon testing the suitable functionality that the methods are resistant to, we will demonstrate the best routes (as defined by the properties measured previously) in a head-to-head against currently existing AlF radiolabeling for a well-known biological target, prostate-specific membrane antigen (PSMA) and carbonic anhydrase IX (CAIX), that we have extensive experience in handling and imaging in-house. At the same time, application of successful methods within the GMP set-up will enable swift future translation and progress of a method, rather than being abandoned as unsuitable for human-use.

NIH Research Projects · FY 2026 · 2024-12

Project Summary Influenza A virus (IAV) impacts pregnant women and their offspring to a greater extent than the general population during pandemics and seasonal epidemics. Pregnancy is a risk factor for severe outcomes from IAV infection, including increased risk of hospital admission and death, and is also associated with adverse perinatal and fetal outcomes. While IAV does not replicate in the placenta, IAV infection induces placental damage and inflammation, which can be mitigated using steroids and result in reversed perinatal outcomes in a mouse model. The maternal gut microbiome is crucial in maintaining physiological homeostasis during pregnancy, but how virus-induced dysbiosis contributes to adverse fetal outcomes is unknown. I hypothesize that adverse fetal outcomes, including intrauterine growth restriction, may be enhanced by IAV-induced changes in the diversity and composition of the maternal gut microbiome. The goal of this project is to investigate the mechanisms by which the maternal gut microbiome contributes to adverse fetal and perinatal outcomes using an outbred pregnant mouse model of IAV infection. My preliminary data show that IAV infection reduces maternal fecal microbial diversity and bacteria associated with short-chain fatty acid (SCFA) production, which is associated with intrauterine growth restriction and developmental delays in offspring. The central hypothesis of this proposal is that placental damage, inflammation, and intrauterine growth restriction during IAV infection of pregnant dams are caused by changes in the maternal gut microbiome, which increases intestinal barrier permeability, reduces the production of microbial metabolites (SCFA), and enhances intestinal inflammatory immune cell populations. Utilizing my previous experience in clinical bacteriology and recently developed expertise with mouse models of pregnancy, Aim 1 will focus on characterizing changes in intestinal morphology, microbial metabolites, and intestinal immune cell populations after IAV infection. Aim 2 will investigate the direct effect of IAV-induced maternal gut dysbiosis on adverse perinatal outcomes using fecal-microbial transplantation. If changes in the maternal gut microbiome contribute to adverse fetal outcomes after IAV infection, then probiotic supplementation will reduce placental damage, inflammation, and intrauterine growth restriction. The research aims outlined in the proposal will assist in continuing my training in animal models, viral immunology, and microbiome-based experimental manipulations, further enhancing my expertise in the relationships between viral pathogens and native host bacteria.

NIH Research Projects · FY 2026 · 2024-12

PROJECT SUMMARY Heart failure (HF) is a significant cause of cardiovascular-related death in the United States, with its incidence increasing by over 40% when accompanied by obesity. The obese-HF phenotype is particularly common in HF with a preserved ejection fraction, a major unmet medical need. The adverse interaction between obesity and HF appears due, in part, to compromised myocardial metabolic fuel availability and flexibility. The heart's high energy demand relies on ATP, mostly derived from FFA oxidation in mitochondria. Long chain fatty acids (LCFA), which have over 12 carbons, are transported into mitochondria for beta oxidation through the acyl-carnitine cycle. Our recent study found marked reductions in myocardial medium and long chain acyl-carnitines in human HF as compared to controls, yet corresponding plasma levels were normal or elevated. This raises the question of whether extracellular acylcarnitines (ex-ACs) can be taken up from plasma by the heart to be used for fuel, and if in HF this process is diminished. In new preliminary data, I now show there is lower expression of the plasma membrane LCFA transporters (CD36, FATP3) and the protein needed to add carnitine to the FA (carnitine palmitoyltransferase 1b, CPT1b). Whether this plays a key role in impeding ex-AC uptake by the myocytes or the heart, and the fate of any ex-AC that is internalized is unknown. This project tests the hypothesis that ex-ACs are taken up and undergo beta- oxidation by myocytes in vitro to contribute to ATP synthesis, O2 consumption, and CO2 generation. The studies explore the fate of ex-ACs in cardiomyocytes and their utilization in both normal and stressed cells and hearts. In Aim 1, I test the hypothesis that ex-ACs are taken up by cardiomyocytes via the critical membrane transporter CD36, or if not, by another currently unknown transporter, and once taken up they undergo beta oxidation. These studies utilize radiolabeled (14C) and heavy labeled (13C) palmitoyl-carnitine and oleoyl-carnitine, each contrasted to their FFA form (palmitic acid and oleic acid) to determine cellular uptake and beta oxidation. The role of critical transporters, carnitine modulators/recyclers are tested using pharmacological or genetic based loss of function studies. In Aim 2, I explore the fate of ex-AC in vivo, comparing normal mice to those under acute and chronic pressure overload via transverse aortic constriction (TAC). I will further examine the addition of a metabolic stress induced by chronic high fat diet. To understand the uptake and processing in vivo, I will inject 13C labeled acyl-carnitines into the bloodstream and measure organ specific uptake and downstream catabolic incorporation of the labeled carbon (e.g into Krebs cycle intermediates). My goal is to understand the mechanisms and metabolic consequences of ex-AC pertinent to cardiomyocyte metabolism, with the ultimate hope of enhancing their use as fuel in heart failure. This research may provide insights to address the major unmet medical needs in HF, particularly in the context of obesity and HFpEF.

NIH Research Projects · FY 2024 · 2024-12

Craniofacial injuries require complex treatments to facilitate bone healing, however, current treatment methods for critical-sized bone loss fail to adequately promote complete healing. This is in part due to our limited understanding of how cell types in bone communicate via secreted factors to reconstruct native bone tissue. Specifically, peripheral nerves innervate bone to control bone formation during development and healing. In bone healing, nerves infiltrate into defects immediately after injury and retract as healing ensues. When nerves are inhibited prior to injury, bone formation is reduced. In non-healing defects, nerves fail to retract to baseline, suggesting that nerve retraction may be required for healing. Understanding the signaling interactions that control these phenomena could result in the identification of targets to facilitate improved bone formation. Our objective is to investigate the role of nerve infiltration and retraction on bone healing through identification of signaling interactions between nerves and osteoprogenitors in healing and non-healing defects. Nerves in the skull are challenging to visualize and require advanced 3D imaging. Further, it is difficult to identify secreted factors and signaling interactions that are specific to the distally located nerve cell bodies. Thus, I will combine advanced imaging and single cell transcriptomic techniques to reveal nerve 3D spatial associations and signaling interactions with osteoprogenitors in calvarial defect injuries. First, I will create sub critical- (1-mm) and critical- sized (4-mm) defects in the parietal bones of Baf53b-tdTomato mice, which constitutively express tdTomato in all peripheral nerves. I will use quantitative light sheet imaging (QLSM) to visualize tdTomato+ nerves and Osx+ osteoprogenitors at early and late timepoints following injury to reveal the spatial associations with and proliferation of EdU+ osteoprogenitors that occurs as nerves infiltrate into both defects and only fully retract in sub critical-sized defects. I will co-register QLSM images with μCT scans to investigate how neuroskeletal spatial associations correlate with regions of bone formation. To explore signaling interactions between nerves and osteoprogenitors, I will inject a tdTomato+ AAV retrograde tracer into the parietal bone to label nerve cell bodies in the trigeminal ganglia that innervate the defect region. I will harvest the trigeminal ganglia and defect region for single cell RNA-sequencing. Using differential gene expression and ligand-receptor analysis, I will uncover the signaling interactions between nerves and osteoprogenitors that mediate the osteoprogenitor proliferation, differentiation, and, ultimately, bone formation. I will next induce nerve retraction at early and late timepoints using Baf53b-tdTomato/TrkAF592A mice to establish the role of nerve retraction on osteoprogenitor proliferation and bone formation. Lastly, I will evaluate neural signaling factors identified through scRNA-seq analysis through in vitro studies with neural conditioned media cultured with osteoprogenitors. Taken together, these data will elucidate potential therapeutic targets to regenerate bone in non-healing bone injuries.

NSF Awards · FY 2024 · 2024-12

This project seeks to answer the question how much fresh (low salinity) water is carried from the Arctic Ocean along the East Greenland Coast into the North Atlantic Ocean and how much this transport may vary as more of the Greenland and Arctic ice sheets melt. For this purpose, an array of six moorings is to be deployed on the Northeast Greenland Shelf to make continuous measurements of temperature, salinity, and current velocities. An exciting new feature of this array includes a variable ballast buoy at the top of one of the moorings, the one closest to the coast, that allows measurements to be made all the way to the ocean surface when the region is ice free, but that prohibits collision of the instruments with sea-ice or icebergs in winter by keeping the mooring line below the ice then. The mooring observations are to be complemented by a modeling study that estimates how the East Greenland Coastal Current evolves over longer time scales. A collaboration with European partners who have a similar mooring array in deeper waters further offshore allows to examine the spatial extent of the current system. Together these efforts will fill a critical gap in our understanding of Arctic-Subarctic exchange, and results will be applicable to a range of scientific fields beyond physical oceanography including climate science, marine biogeochemistry, and fisheries management, among others. The oceanic circulation of the high-latitude North Atlantic is a critical component of our climate system and is potentially sensitive to the release of fresh, surface waters from the Greenland Ice Sheet and the Arctic Ocean. A large gap exists in our monitoring of this freshwater input on the Northeast Greenland Shelf (NEGS). This gap will be filled by measuring the southward-flowing East Greenland Coastal Current (EGCC) on the NEGS for the first time with continuous, direct measurements over an entire year. Based on existing data from summer shipboard sections and satellites, it is hypothesized that the freshwater transport in the EGCC is as strong as the freshwater transport of the better known East Greenland Current (EGC) further offshore at the shelf break. If true, the EGCC would be a major contributor to the total freshwater budget of the Arctic and a key player in Arctic-Subarctic exchange. In addition to the mooring array, it will be analyzed how these data fit into the larger scale NEGS circulation using model simulations, reanalysis products, and satellite data. The new ice-avoiding buoy technology that is to be developed as part of this project has the potential to be widely applicable to a range of environments and is significantly more cost-effective than other similar products. Results from this project will: (1) quantify the volume, heat, and freshwater transports of the EGCC on the NEGS, (2) compare these transports to those of the EGC measured by European partners, (3) identify the physical drivers of transport variability in the EGCC, and (4) assess the long-term variability of the EGCC and its role in the Arctic freshwater budget. 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 2026 · 2024-12

Community health workers (CHWs) are lay health workers who are part of or closely affiliated with the communities that they serve. A large body of evidence demonstrates that CHW-delivered interventions improve health outcomes and reduce disparities across a range of conditions. CHWs work in various settings, including community organizations, educational institutions, health facilities, and health departments. In the United States, CHWs are increasingly integrated into clinical settings. Their integration into clinical settings may be beneficial because they can help patients navigate care, improve cultural competency among the team, and provide health education to complement messaging from healthcare providers. However, CHWs are not always integrated effectively into clinical care teams. This may increase CHWs’ stress and burnout, reduce their potential to support patients, and exacerbate disparities within the workforce. The proposed study will use an exploratory sequential mixed-methods design to: 1) Explore how CHWs are integrated into clinics, 2) Identify patterns of perceived stress and professional quality of life among CHWs in different work settings, 3) Generate a model of implementation best practices to foster CHW professional quality of life and integration into clinical settings. This application will leverage support from the Mid-Atlantic Center for Cardiometabolic Health (MACCH), a P50 grant from NIMHD that includes efforts to integrate CHWs into care teams to improve cardiometabolic health in Maryland. Ms. Shannon Fuller is a PhD candidate in social and behavioral sciences at the Johns Hopkins Bloomberg School of Public Health. She seeks this fellowship to receive training in rigorous community-engaged and participatory research to complete the proposed research study with support from her mentorship team. Her training plan includes didactic and experiential training in community-engaged research, ethnographic methods, organizational behavior and theory, survey collection and analysis, advanced quantitative and mixed methods, grant writing, and dissemination. With the support of a robust mentorship team (Sponsor: Dr. Lisa A. Cooper), the proposed research and training activities will help Ms. Fuller develop into an independent researcher dedicated to advancing the dissemination of evidence-based interventions that reduce population-level disparities and support the health workforce. The proposed application aligns with NIMHD’s interest in understanding and addressing health disparities that occur within the context of health care settings and to improve the quality of care.

NIH Research Projects · FY 2025 · 2024-12

PROJECT SUMMARY Retinal ganglion cells (RGCs) are solely responsible for transmitting signals from the eye to the brain. They do so via their axons, which make up the optic nerve (ON). As such, loss of RGCs results in diseases like glaucoma, a leading cause of irreversible blindness worldwide. Loss of RGCs is considered irreversible, as the human eye normally fails to regenerate lost RGCs or degenerated RGC axons. Nevertheless, restoring vision to patients via regrowth of the ON represents a major therapeutic goal for the field. Endogenous ON regeneration and RGC transplantation are the two main areas of research being pursued to reach this therapeutic goal. Advances in neuroprotection, stem cell biology, and regenerative medicine are bringing these goals closer to reality. One promising approach for replacing lost RGCs is to inject human stem cell derived RGCs into the eye. Progress has been made in replacing other lost retinal cell types, such as retinal pigment epithelium, with stem cell derived cells. Despite recent studies identifying factors that promote RC survival and neurite outgrowth, promoting transplanted RGC axons to regenerate an ON all the way to the brain to restore visual function remains a major therapeutic challenge. The capacity of human RGCs to achieve this essential goal is unknown. Specifically, it is unclear if modulating intrinsic RGC-expressed factors can promote human RGC axonal regeneration, regrowth of the ON, and restoration of visual function. Preliminary data suggest that even in a highly permissive environment, hRGC neurite outgrowth is limited. This and other recent studies in mice suggest that intrinsic, i.e. RGC expressed, factors are a key barrier to ON regeneration and functional recovery in the clinic. This has yet to be systematically investigated in a regenerative species. Accordingly, I hypothesize that intrinsic factors regulating RGC survival, neurite outgrowth and targeting, and functional recovery can be revealed through a systematic interrogation of gene function in the context of a naturally regenerative environment, the zebrafish. To test my hypothesis, I will explore 1) how intrinsic factors regulate ON regeneration in zebrafish; and 2) test how modulation of intrinsic factors can stimulate ON formation in human RGCs transplanted into zebrafish. I will take advantage of zebrafish amenability to large-scale screening to test ~100 genes for the ability to promote endogenous RGC survival, axonal and dendritic outgrowth, and functional recovery in zebrafish. I will further examine the ability of gene modulation to enhance transplanted human RGC survival, ON growth, and functional recovery in zebrafish. These studies will increase our understanding of the genetic networks governing ON regenerative potential. Characterizing zebrafish and human RGC and ON regenerative potential will bring us closer to understanding how to develop regenerative therapies and successful transplantation strategies for patients.

NIH Research Projects · FY 2026 · 2024-11

Summary/Abstract Transgender women are at elevated risk for acquisition of HIV, but there is little population-specific data to address whether there are specific features of HIV immunopathogenesis or reservoir maintenance among these individuals. Multiple lines of data indicate significant differences between cisgender women and men with lower levels of setpoint viral load, lower levels of residual viral activity and different patterns of immune activation in response to HIV in cisgender women. Data also indicate that sex steroid hormone exposure contributes to these differences, including a direct suppressive effect of estradiol on HIV latency reversal. These data suggest that gender affirming hormone therapy may impact HIV reservoir features and immune responses in transgender women, but this question has not been directly studied. In this proposal, we address this knowledge gap, leveraging two unique cohorts of transgender women to explore the impact of hormone therapy on measures of the HIV reservoir and immune/inflammatory features. Our first cohort is an existing cross-sectional cohort of TW (n=120) who are evenly divided by HIV serostatus and current hormone exposure; this cohort specifically addresses the impact of sex steroid hormone exposure and gender identity with and without concurrent HIV. Our second cohort is derived from a ACTG 5403, a clinical trial currently enrolling TW living with HIV (TWLH) on suppressive antiretroviral therapy who have been off hormonal therapy. Participants (N=90) initiate a standardized protocol for titration of estrogen therapy with outcomes focused on pharmacokinetic interactions with ART and participant satisfaction. Blood samples (viable cells and plasma) are collected and stored for the virologic, and immune assays described in this proposal. With these two cohorts we will explore three specific aims: 1. Explore the impact of estradiol therapy on measures of the HIV reservoir size, activity, intactness, integration site and clonality. 2. Characterize the impact of HIV and hormone therapy on immune cell profiles by flow cytometry, single cell transcriptomic profiling and plasma inflammatory proteome. 3. Investigate the impact of hormone therapy on metabolic features in the plasma proteome and by cellular energy dependence assays. These three complementary aims with large and well-characterized cohorts will allow us to define the impact of hormone therapy on HIV reservoir and immune cell dynamics and to explore the potential mechanistic role of immune metabolism in some of these effects.

NSF Awards · FY 2024 · 2024-11

NON-TECHNICAL DESCRIPTION: Materials with higher and higher strengths are often the target of materials scientists for structural engineering applications – stronger materials enable safer structures as well as lightweighting for more energy-efficient transportation. Several pathways are available for enhancing strength through control over defects in the material. However, efforts to-date have failed to bring material strengths anywhere near the holy grail of strengthening, referred to as the ideal strength. This failure has not come from a lack of materials engineering, nor would innovations in materials design or processing immediately solve the problem. Instead, prior approaches have been too limited in scope from the viewpoint of the material’s deformation physics, which is addressed in this research by considering novel design pathways for controlling material structure and, in turn, the defects that govern strength. The findings of this project are applicable to advanced materials with increased chemical complexity, which are desired for modern engineering applications. An interactive online learning module transcending traditional institutional barriers – denoted the Mechanics Interactive Teaming (MINT) initiative in engineering education – is being developed to engage students cooperatively at the partnering universities with new virtual learning modules focused on cutting-edge topics in materials science. The initial focus on graduate curricula is being broadened to reach undergraduates through the Women in Science and Engineering Program at Stony Brook University and further expanded for working professionals using relevant design problems through collaboration with the Advanced Casting Research Center at UC Irvine. TECHNICAL DESCRIPTION: This research enables materials with near-ideal strength by developing a fundamental understanding of dislocation nucleation and propagation as rate-limiting deformation mechanisms in nanostructured alloys where defect confinement and interaction with grain boundary and lattice solutes act as local barriers to plasticity. Specific research questions to be answered include: (i) what are the important transition states and associated energy barriers for dislocation nucleation at solute-decorated interfaces and for propagation within a nanoscale alloy crystal, (ii) how does interfacial structure and energy variation upon doping alter dislocation nucleation/propagation, and (iii) how do solute atoms inside the grain, which can potentially act as local pinning points but also alter the properties of the lattice, influence dislocation propagation? A practical hypothesis of this research is that the strength of nanocrystalline alloys can be maximized by synergistic doping to stabilize the grain boundaries against local plasticity and delay defect nucleation while simultaneously inhibiting dislocation propagation through the nanograin interiors. Using a combination of atomistic modeling, multi-modal structural characterization, and unique micromechanical testing, this hypothesis is being tested in nanostructured aluminum and copper alloys, where their intrinsically different stacking fault energies will provide access to different confined slip events. In a broad sense, this research will define new strengthening paradigms in nanoengineered metallic materials and establish the mechanistic underpinnings of solute-biased interfacial energy landscapes for understanding fundamental dislocation physics in confined slip environments. 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 2026 · 2024-11

ABSTRACT Targeting a reductive dehalogenase as a new strategy for controlling mosquito populations The enzyme iodotyrosine deiodinase gained prominence from its role in salvaging iodide from iodotyrosine. This activity is necessary for generating the iodinated hormone thyroxine that is required for all vertebrates. Surprisingly, this enzyme was also found nearly ubiquitous in invertebrates that do not require iodide nor generate thyroxine. Initial studies have suggested that its ability to process a range of halotyrosines (X = I, Br, Cl, not F) remains the same in fruit flies, but its biological role is quite different. The dehalogenase protects flies from the accumulation of endogenous halotyrosine that would otherwise suppress male fertility. Inhibition of the dehalogenase or accumulation of a halotyrosine in vivo significantly decreases fly populations by a mechanism orthogonal to those currently used to mitigate vector-borne disease. Homologs of the dehalogenase are present in most insects and offer a new and potent target for eliminating such vectors if the results from fruit flies extend to other invertebrates. The Anopheles gambiae mosquito was selected as the test organism in our investigations due to its importance as a vector of malaria. Despite a vast amount of research and field work, this disease remains a health priority and its return has recently been reported in the United States. Knowledge gained from fruit flies now guides our experiments on the mosquito. Loss of fertility will be examined after alternative external exposure to halotyrosines and internal suppression of the dehalogenase by chemical and genetic strategies. Analytical chemistry will identify which halotyrosine is generated endogenously and whether halogenation targets tyrosine free in solution or tyrosyl residues within proteins. Initial efforts are also planned to identify the peroxidase responsible for halogenation to build a foundation for broad investigations in the future on the nature and function of an overlooked cycle of halogenation and dehalogenation in insects. The most immediate impact of these studies will derive from a newfound ability to limit mosquito populations and the diseases that they spread.

NSF Awards · FY 2024 · 2024-11

High-frequency (HF, 3–30 MHz) radio waves play a significant role in long-distance communications. They have applications in short-wave international broadcasting and communications by aircraft, military operations, and amateur radio operators and are useful during emergency situations. HF radio wave communication is possible through wave reflection and refraction in the ionosphere, which is part of the upper atmosphere at 100-2000 km altitude. The project aims at investigating the effect of the ionospheric density fluctuations on the propagation of HF radio waves, and the results of this project are expected to improve understanding of ground HF communications. This research will provide opportunities to under-represented communities in STEM areas at a minority serving institution. The effort is being led by a woman scientist and involves several early career scientists. The project integrates research into the Ham Radio Science Citizen Investigation program to investigate the effects of disturbances on HF communication. The results will be widely distributed and of significant interest to various groups, including amateur radio enthusiasts, emergency services, airlines, maritime organizations, and defense users. The research work will investigate the effect of ionospheric density fluctuations on HF wave propagation. Since solar and geomagnetic activities significantly influence the ionosphere, HF radio communications are also sensitive to space weather. The project will address three scientific questions: (a) How are ground HF communications affected by different solar and geomagnetic activities? (b) How do small-scale density irregularities appear in various space weather conditions? (c) How do HF waves propagate through the irregular density profile?; and finally (d) How does space weather affect small-scale density irregularities and ground HF communications?. To achieve these goals, researchers will utilize satellite, HF amateur radio communication data sets, and will perform full-wave simulations using advanced finite element method (FEM) code, Petra-M by adopting a realistic density fluctuation profile. By comparing the predicted wave properties from the Petra-M code with the observed HF communications, it will be possible to evaluate how well the model simulates real-life conditions while providing new insight into how the HF radio waves propagate through ionospheric irregularities. 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 · 2024-11

PROJECT SUMMARY/ABSTRACT Significance: Novel genetic tools are an emerging avenue for understanding causal relationships between biomarkers and diseases, especially through efficient study designs, such as the genetic instrumental variable method Mendelian Randomization (MR). Tools such as polygenic risk scores (PRS) can be used to efficiently sum the genetic liability of traits and estimate causality in MR. However, both PRS and MR have historically performed poorly in diverse ancestry populations due to their reliance on primarily European ancestry data. This is further compounded by the disproportionate disease burden in marginalized populations due to structural and social factors. We will use the observed association between low density lipoprotein cholesterol (LDL) and coronary artery disease (CAD) from observational epidemiological studies to interrogate the use of a PRS for LDL (PRSLDL) as a valid genetic instrument in MR of diverse groups, modeling genetic and non- genetic disease contributors, and minimizing potential shortcomings of the causal approach. Specific Aims: We aim to 1) characterize differences in the predictive ability of a multi-ethnic PRSLDL for LDL between racial/ethnic groups, with and without adjustment for relevant non-genetic risk factors, 2) determine the effects of individual- and group-level environmental exposures on the PRSLDL performance, stratified by racial/ethnic groups, and 3) assess the causal effect of LDL on CAD in diverse populations, using the PRSLDL as an instrumental variable and stratifying by self-identified racial/ethnic groups. We will use the All of Us Research Program and Population Architecture Using Genomics and Epidemiology (PAGE) cohorts. The long- term objective of this work is to extend the application of new genetic tools to diverse groups. Approach: All analyses will be stratified by racial/ethnic groups to be consistent with prior literature of the relationship between LDL and CAD, particularly with respect to environmental influences. Aim 1 will employ linear regressions of PRSLDL on LDL, with and without adjustment for disease-predictive variables to understand if clinical risk factors change the performance of PRSLDL between racial/ethnic groups. Aim 2 will incorporate regression interaction terms of smoking and air quality with the PRSLDL to inform the differential role of environment in PRSLDL performance by racial/ethnic group. Aim 3 will execute MR, conduct MR sensitivity analyses, and note key MR violations when applied to diverse populations. Fellowship Goals: The proposed study, which addresses several of NHGRI’s strategic goals, will serve as the doctoral dissertation for Ms. Jayati Sharma, a PhD student in the Department of Epidemiology at the Johns Hopkins Bloomberg School of Public Health. A comprehensive training program, including mentored research training from experts in genetic epidemiology, statistical genetics, and cardiovascular genetics, will provide the applicant a tailored experience to achieve her goal of becoming a successful academic genetic epidemiologist studying the equitable application of genetic tools to promote public health in diverse ancestry populations.

NIH Research Projects · FY 2026 · 2024-11

PROJECT ABSTRACT To develop functioning gametes, both the germ cells and somatic cells of the gonad must determine their sexual identity. While sex determination and sex-specific gene expression are well characterized in the somatic gonad of Drosophila, little is known about how germ cells determine their sex. The RNA binding protein Sex lethal (Sxl) has been shown to be master regulator of female somatic sex determination. Sxl is also important in the germline, where it is necessary and sufficient for female identity. However, autonomous sex determination downstream of Sxl is not well characterized in the germline. Interestingly, germline sex determination is also regulated non-autonomously via somatic signals. How sex determination in the germline is regulated by a combination of autonomous cues, downstream of Sxl, and non-autonomous cues, based on somatic cell signaling, is unknown and of great interest to the field. I will examine expression of Tdrd5l (Tudor domain-containing protein 5-like), a gene discovered by our lab, which is expressed in a male-specific manner in the undifferentiated germline and is important for male germline sexual identity. Tdrd5l RNA is initially expressed in the embryonic germline of both sexes, but subsequently becomes male-specific at the third larval instar (L3) stage by an unknown mechanism. Preliminary data show that a Tdrd5l-GFP transcriptional reporter is expressed in a male-specific manner during the L3 stage, while sex-specific expression of Tdrd5l RNA in developing germ cells is independent of Sxl. However, we have found that a male soma is sufficient to drive expression of Tdrd5l RNA in female germ cells. Interestingly, Tdrd5l is regulated independently of JAK/STAT signaling, which is the key male-specific signal regulating germline gene expression. Altogether, our study of Tdrd5l regulation indicates that a previously unidentified signal from the somatic gonad to the germline regulates sex-specific germline gene expression. In the adult gonad, expression of Tdrd5l is repressed in undifferentiated female germ cells by the RNA binding protein Sex lethal (Sxl). We have found that deletion of possible Sxl binding sites in the Tdrd5l RNA causes derepression of Tdrd5l protein expression, indicating that part of the sex-specific regulation is post- transcriptional. However, whether Sxl directly binds the Tdrd5l RNA is unknown, as is the mechanism by which Sxl regulates Tdrd5l expression. Thus, I will investigate how Sxl post-transcriptionally regulatesTdrd5l expression, using deletions of each binding site to determine Sxl’s germline role. Together, a study of how Tdrd5l is regulated both transcriptionally and post-transcriptionally in a sex- specific manner will provide insight into the multiple levels by which sex-specific gene expression is regulated in the germline. Understanding sex-specific gene expression in the germline will further our understanding of improper germline development leading to infertility and provide insight into developing new fertility treatments.

NSF Awards · FY 2024 · 2024-11

Sudden cardiac death (SCD) remains a leading cause of mortality worldwide, with an incidence ranging from 50 to 100 per 100,000 people in the general population of Europe and North America. SCD accounts for 15-20% of all deaths. Despite advancements in medical science, accurately assessing the individualized risk of SCD remains a significant unmet clinical need. Digital twins of hearts offer a powerful tool for personalized medical care, enabling data-informed decision-making under uncertainty, that is crucial for early identification and prevention of heart conditions. However, even the most advanced state-of-the-art digital twin models contain systematic errors due to our incomplete understanding of human biology, the limited availability and quality of patient data, and the inherent uncertainties present in the models. The primary goal of this research project is not to build the perfect cardiac digital twin, but rather to make the best currently achievable digital twin of a patient’s heart better by reliably transforming it to the truth (data). Beyond the scientific findings, this research will be incorporated into educational and outreach programs designed to attract underrepresented groups to engineering and enhance undergraduate and graduate education in biomedical engineering and applied mathematics. The project employs novel, scalable, and data-driven mathematical/algorithmic calibration tools, that combine mathematics, scientific computation, and machine learning to account for the biological variability of individual patients. The approach will not involve adding more physics or biology to the cardiac digital twin model, or increasing the resolution of the digital twins’ spatial discretization; what is sought, rather, is identifying and mathematically correcting any deviations (model errors) in the current cardiac digital twin using available data and numerical analysis-inspired machine learning algorithms. These tools will reduce the simulation time required to inform clinical intervention (ablation) in patients with cardiomyopathy, and will hopefully broadly enhance the predictive capabilities and utility of digital twins across various application domains beyond our cardiac-focused effort. The outcomes of this study are expected to fundamentally advance the use of cardiac digital twins in clinical practice and lay a foundation for studying the risk of sudden death for patients with ischemic and nonischemic cardiomyopathy. 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 · 2024-11

Feathered wings are a fascinating part of bird flight, yet they are not well understood. These wings have unique properties, from tiny barbicels that maintain structural integrity to individual feathers that change position, shape, and alignment. Flight feathers are both flexible and strong, and act individually or together depending on the flight situation. The close arrangement of feathers enables complex airflows between them, affecting aerodynamic force generation and feather deformation. However, our knowledge of these dynamics is limited. This project aims to investigate the unique properties of feathers and feathered wings that enhance flight capabilities, including their porosity and deformability, and their ability to change shape during flapping. The research combines experiments on isolated feathers, groups of feathers, computational models, and live bird observations to study this complex problem. The fascination and intrigue evoked by bird flight and the multi-modal research approach adopted here will be leveraged for outreach to undergraduate and K-12 students. The students and trainees involved in this project will become part of a new generation of scientists and engineers capable of applying computational and experimental methods across disciplines to tackle complex problems. The goals of this project are to: (1) investigate the aerodynamics and aero-structural dynamics of individual feathers; (2) study the interactional flow effects in multi-feather configurations; and (3) explore the aerodynamics of flapping flight with feathered wing-inspired models. First-of-their-kind computational models will be developed to incorporate not only the complex vortex dominated flows generated by feathers but also the aero-structural deformations and feather permeability. These computational models will be parameterized by structural testing and wind-tunnel studies of feathers as well as flying birds. The simulations will use innovative modeling approaches and efficient computational algorithms to bridge the very large range of scales that are encountered in this multi-physics problem. Micro-computed tomography imaging, micro-tensile testing, and wind-tunnel recordings of the aeroelasticity of feathers will provide key data for input and comparison with the simulations. The computational models of multi-feathered flapping wings parameterized from feather kinematics extracted from birds in flapping flight will significantly advance understanding of the function of this unique and intriguing flight “device.” The findings could improve designs for drones, making them lighter, quieter, and more efficient. The research could also lead to better understanding of flow over porous surfaces, benefiting various fields like aeronautics, biomedicine, and engineering. Finally, this research will enable exceptional educational and training opportunities for students at the intersection of biology and engineering. 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 · 2024-10

This proposal seeks unifying physical principles that define rules of life in bacteria, which are among the most abundant forms of life on earth. The research addresses the essential process of bacterial cell surface formation in these organisms. It will serve as a roadmap for how cell surface formation may occur in evolutionary related systems in higher life forms. The broader impacts include the intellectual power of connecting physical observations to principles of life, and the research activities benefit society at large through novel insights about living systems. The work offers meaningful opportunities for undergraduate research experiences and trains graduate students in multidisciplinary approaches to science. The outcome from these efforts will be the training of diverse and creative investigators that will increase creativity and productivity in the STEM fields in our country. The periplasm of Gram-negative bacteria is devoid of an external energy source to achieve sorting and folding of the membrane proteins that are found in their outer membranes. The research interrogates how this process is achieved solely through thermal energy, thermodynamic binding potentials, kinetic on- and off-rates and local cellular expression levels of the periplasmic chaperones. This research will interrogate the periplasmic protein interaction network using a multi-scale approach that will include structural measurements of key binding events, solution conformation determinations and calculations of unfolded membrane protein reactants, computational modeling of experimental data, and cellular localization and dynamics experiments in vivo. The results of this research will be integrated into a global, systems-wide understanding of the chaperone network in the bacterial periplasm. This project is funded by the Molecular Biophysics Cluster in the Division of Molecular and Cellular Sciences 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 · 2024-10

The objective of this Civic Innovation Challenge (CIVIC) project is to support research on design and implementation of a machine learning (ML)-based system, called WAUTO (Water operations AUTOmation), to optimize wastewater treatment plant operations during extreme weather events. Working with the Little Patuxent Wastewater Reclamation Plant (LPWRP), researchers from the Johns Hopkins University Applied Physics Laboratory (APL) and the Whiting School of Engineering (WSE) aim to enhance LPWRP’s resilience to extreme weather. Climate change is resulting in more frequent floods with higher water levels than what current models predict. In Howard County, MD, two floods, each expected to occur only every 1,000 years, took place within two years. The challenges faced by LPWRP are common nationwide. Smaller facilities, usually serving economically disadvantaged and marginalized communities, are especially vulnerable to flooding events. The WAUTO intends to enable continued system operation essential to public health and prosperity throughout the disaster. A wide range of stakeholders are engaged, including engineers, plant managers, and government officials. Success of this project could pave the way for the deployment of cutting-edge ML-based solutions for protecting critical infrastructures of national importance. In this project, the researchers build a high accuracy model to predict the inflow and plant capacity as well as a model of plant equipment. Using features such as the water table / river levels and weather for the first model, and schematics/documentation and subject matter expertise for the second, the team trains a Reinforcement Learning (RL) agent to optimize plant operations by taking actions such as adjusting water flow rates and equalizing tank levels, based on predictions from the models as well real-time observations. For the Stage 2 Pilot, WAUTO will deployed at LPWRP through a phased approach as confidence in its performance improves. This civic-academic team consists of professionals from LPWRP, the Howard County Department of Public Works (DPW), researchers from APL and WSE, experts in geology and weather, and members from the broader community. This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy. 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 · 2024-10

Multiple systems of the brain are coordinated to produce the intelligence that enables complex behaviors. While data collections tools have been steadily increasing the ability to record activity from across the entire brain, analyses of these data have primarily focused on dividing neurons by anatomical areas and analyzing neural activity within and across brain areas. Recent observations suggest, however, that coordination of brain activity is related to, but not restricted to anatomical boundaries. There is a functional architecture of the brain that represents the work that the brain computes across the the anatomical hardware. This project aims to disentangle the functional architecture by developing new models specialized in exploring the different types of brain computations. As opposed to current models, the emphasis on finding circuitry within the brain that combines in different ways to support flexible computation will uncover how brains can flexibly adapt to produce robust intelligence. Specifically, this project will develop this framework to understand how computation is distributed in two important model behaviors: navigation in whole-brain recordings of zebrafish larvae, and decision making in rodents. Aim 1 will identify systems underlying navigation, using the advanced optical imaging tools available that capture the simultaneous activity of both neurons and glia over the entire zebrafish larval brain. First, a behaviorally-decomposed dynamical system will be developed to explicitly tie the subsystems across the brain to behavioral elements including swim bouts and visual stimuli. Second, the decomposed dynamical systems model will be extended to explicitly capture the asymmetric nature of neural-glial interactions. Aim 2 will identify subsystems underlying visual decision making in multi-electrode recordings of rodents. Despite the ability to record many neurons in multiple brain areas, these neurons still represent only a fraction of the neurons in these areas, let alone the entire brain. To address this limitation this project will develop a multi-scale missing-neuron dynamical system that will treat hidden systems as a hidden set of latent variables that operate in parallel to the observed neurons. These methods will reveal how the functional architecture is structured and how different pathways are activated under different conditions, e.g., error trials. Taken together this project will establish new quantitative models to uncover the functional architecture of the brain and provide new insight into both navigation and decision making. 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 · 2024-10

Developing accurate and interpretable models is crucial for the safety and efficacy of machine learning in an ever-increasing range of applications. To achieve state-of-the-art performance, algorithms rely on expensive and opaque optimization procedures that implicitly learn the most important features of the dataset to build the model. The complex nature of these algorithms impedes our ability to interpret the patterns in the data used to generate the output and obtain mathematical performance guarantees. This project will develop a library of fast and accurate machine-learning algorithms with interpretable mechanisms for learning the most relevant information from a dataset. This project will also create a corresponding mathematical toolkit for analyzing these algorithms to guide optimal implementation and provide statistical guarantees. These interpretable and theoretically justified algorithms will be of particular value for safety-critical applications in engineering and healthcare. This project will be complemented by the mentorship of undergraduate and graduate research projects utilizing data science for the public good. Many modern machine-learning algorithms generate complex models using random partitions of the available data set. The most successful approaches, such as random forests and neural networks with piecewise linear activation functions, rely on optimization procedures that generate a data-adaptive partition, making the algorithm very difficult to analyze. On the other hand, purely random forests and random feature models generate random partitions of the feature space independently of the data. These methods are more amenable to theoretical analysis, but their performance and scalability suffer in the presence of large and high-dimensional datasets. This project will utilize and expand the toolkit of random tessellation processes in stochastic geometry to close the theoretical and computational gap between data-independent and data-adaptive random partitioning methods in machine learning. This mathematical framework consists of expressive models for random partitions with parameters that will be learned from data and an extensive theory from which to develop a comprehensive understanding of the mathematical properties of the learned models. The goals of the project are to develop state-of-the-art random partitioning algorithms for data analysis, provide matching theoretical performance guarantees, and study fundamental statistical and computational trade-offs of data-adaptivity in the partitioning process. 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 · 2024-09

Understanding the unique vulnerability of certain cell populations in the brain to Alzheimer's disease (AD) - a debilitating, chronic disease affecting 6.2M Americans - has proven an elusive goal. Amyloid beta (Aβ) plaques and neurofibrillary tau tangle (NFT) pathology are hallmarks of AD that first become apparent in particularly vulnerable regions of the brain such as the entorhinal cortex (ERC) decades before symptom onset. Understanding how AD pathology affects specific brain regions, including a more complete understanding of the pathologic and molecular changes in selectively vulnerable areas is critical for the development and timing of potential AD treatments. The selective vulnerability of the medial temporal lobe (MTL) is well established, however, a more global picture of how tau pathology affects the mesial temporal lobe, its precise relationship to regional atrophy, and how this pathology is related to molecular changes associated with AD dementia remains unclear. To achieve this goal, we propose to integrate high-field post- mortem imaging, histological and spatial transcriptomic sections from the same individuals in a common coordinate system and learn how gene expression differences in the ERC are associated with early regional susceptibility to AD pathology. The central goal of the proposal is to link the spatial and temporal disease progression of MR markers at mm scale to the molecular substrates of tau pathology and spatial transcriptomics in layer 2 ERC. Uncovering the correlation of neuronal transcriptional changes to NFT pathology and to macroscopic shape change is necessary to understanding the biological link between these different scales and measures of AD pathology. This linkage has so far remained elusive because of the gaps in spatial scale between clinical MRI markers with histological and cellular assessments. We propose to close these gaps by introducing 100 μm high-field postmortem dense MRI reconstructions of the MTL allowing us to combine clinically-derived ERC population disease progression markers with histopathological and molecular profiling in these coordinates. In Aim 1 of this proposal, we will establish a protocol for postmortem high-field MRI and histological analyses of ERC to integrate microscale digital tau-pathology with Mai-Paxinos coordinates and population-based atlas mapping. We draw on ongoing comprehensive and longitudinal studies of aging including BIOCARD and ADRC studies which include cognitive measures, in vivo MRI scans, and postmortem protocols. In Aim 2, we will identify spatial gene expression signatures in layer 2 ERC neurons by anatomic location in Mai-Paxinos coordinates and quantify spatial transcriptional changes associated with regional AD pathology registered to MR measures and clinical outcomes. Integration of regional shape changes by MRI with pathologic and transcriptional information will shed light on the interaction of AD pathology with vulnerable ERC regions and underlying cell type and transcriptional signatures, and will provide the basis for the potential development of new MRI-based biomarkers of AD tau pathology which would be tested in future studies using in vivo clinical MRI.

NIH Research Projects · FY 2025 · 2024-09

Prenatal drug use has increased nearly five-fold over the past two decades and is associated with elevated risk of drug overdose, maternal morbidity and mortality, adverse birth outcomes, and family separation through foster care. States have enacted several types of laws in response to the rising rates of prenatal drug use: 1) child maltreatment laws deeming prenatal drug use child maltreatment; 2) mandatory reporting laws requiring providers to report prenatal drug use to child protective services; 3) testing laws mandating that providers drug test pregnant patients or newborns, and/or giving providers legal protection to drug test pregnant patients without consent; 4) criminalization laws criminalizing prenatal drug use; and 5) priority access laws giving pregnant people priority access to drug treatment. Evidence on these laws’ effects on overdose, treatment engagement and health care use among pregnant and postpartum people and their infants is limited. Critically, evidence on whether and how the effects of these laws differ by race or ethnicity are also lacking. Meanwhile, in 2018, Congress passed the Family First Prevention Services Act (FFPSA), dramatically overhauling state child welfare system financing. FFPSA newly allows the use of federal funds to provide services to parents at risk of losing custody of their children, including paying for SUD treatment services. All five types of prenatal drug laws involve the child welfare system, but no research to date has examined how implementation of FFPSA-driven changes to the child welfare system may vary across states with different prenatal drug law contexts. We fill these critical research gaps through the proposed mixed-method, concurrent-embedded study using an innovative adaptation of difference-in-differences methods. We will examine the effects of state prenatal drug use laws on drug screening and substance use disorder diagnosis (Aim 1) and health care use and nonfatal overdose (Aim 2). We will examine 16 state policy changes during the study period and estimate racial disparities in policy impact using 50-state administrative Medicaid claims for 2015-2022. We will integrate findings from Aims 1 and 2 with a qualitative analysis characterizing how states have implemented FFPSA across heterogeneous prenatal drug law contexts (Aim 3). The proposed study is the first to use 50 state Medicaid data and robust causal inference methods to evaluate state laws’ effects on substance use-related outcomes (Aims 1 & 2) and to conduct a novel exploration of a new federal law, FFPSA, which has far- reaching implications for state child welfare systems’ interaction with parents with substance use. Findings will inform other researchers, health system leaders, and policymakers dedicated to improving the health and well- being of families affected by substance use.

NIH Research Projects · FY 2025 · 2024-09

The “virtual front door”–websites and digital information–is often the first interaction point that patients have with healthcare systems. However, people who are blind or have low vision face barriers in accessing healthcare information and the appointment-making processes when website information is inaccessible. The American Health Information Management Association (AHIMA) Foundation reported that in 2022, only 5% of hospitals were compliant with Website Content Accessibility Guidelines (WCAG 2.1) and other legal requirements. Principles of universal design could help people who are blind, have low vision, or other disabilities readily establish care. Universal design improves program uptake and effectiveness but is rare in healthcare. We have developed the RAMP (Removing Barriers to the Management of Patient care) score to evaluate the universal design of healthcare system websites and processes for allowing people to establish necessary specialty care. This project will improve the “virtual front door” to specialty care for people who are blind or have low vision. Aim 1, we will refine our RAMP score to more robustly capture the experience of people who have low vision and or are blind in making healthcare appointments. In Aim 2, we will scale RAMP scoring and develop a publicly available data dashboard to allow comparisons of these scores across academic medical centers. And in Aim 3, we will use implementation science approaches to develop a toolbox of tailorable interventions that outline specific actions which academic medical centers can take to improve RAMP scores. By advancing the science of digital medicine, and we will build tools with which academic medical centers can better provide care to people have low vision or are blind, as well as Americans with other disabilities.