Johns Hopkins University

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY: This is a submission for a National Institutes of Health R01 award called The BLAAST Project, which aims to conduct a randomized, double-blinded, placebo, non-inferiority trial of pediatric care enhanced by a novel automated digital stethoscope, compared to standard care, in Bangladesh (Aim 1) with an integrated implementation assessment (Aim 2) and economic evaluation (Aim 3) over three years among young, low-risk children with non-severe clinical pneumonia. Antibiotics are a mainstay of the treatment of acute lower respiratory infections in young children in low- and middle-income countries (LMICs) like Bangladesh even though most episodes are caused by self-limiting viruses. Innovative child friendly tools that improve the diagnosis of respiratory illnesses, safely reduce the unnecessary use of antibiotics, and are suitable for implementation in LMICs are urgently required to safely improve antibiotic stewardship and stem the rising rates of antibiotic resistance globally. In this project (Bangladesh Lung Auscultation Artificial Intelligence for Antibiotic Stewardship or BLAAST) we aim to utilize a novel FDA-approved digital stethoscope with automated lung sound analytics developed and validated over a period of ten years from evidence across seven LMICs. In Aim 1, we will determine whether treatment failure frequency among children in rural Bangladesh managed by clinical guidelines enhanced by a novel automated digital stethoscope is non-inferior to guidelines alone. We hypothesize treatment failure frequency among `enhanced IMCI' participants will be no worse than standard care by a +/-2% margin, safely reducing antibiotic use by 50-60%. In Aim 2 we will assess digital auscultation implementation and antibiotic use during pediatric respiratory care in rural Bangladesh to inform strategies of antibiotic stewardship. Lastly, in Aim 3 we will evaluate if a diagnostic strategy enhanced by an automated digital stethoscope is a sustainable alternative to standard care for children in rural Bangladesh. We hypothesize that care augmented by a digital stethoscope will have additional benefits via reduced antibiotic use that will outweigh digital auscultation costs resulting in cost-effectiveness compared to current practice. BLAAST affords a unique opportunity to evaluate the efficacy of clinical guidelines enhanced by an automated digital stethoscope on child pneumonia outcomes in Bangladesh, if digital auscultation may be instrumental in the wider antibiotic stewardship strategy, and whether a digital stethoscope diagnostic tool is cost-effective in the care of children with respiratory illnesses.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT All our sensations, decisions, and actions are mediated by signals flowing through networks of neurons, the fundamental information-processing units of the brain. Each neuron receives thousands of inputs from other neurons at synapses and converts particular patterns of inputs into output (action potentials). Understanding the operations that neurons can perform will help reveal the algorithms that the brain utilizes to produce behavior. A rich body of theoretical work has put forward several models of neural computation of varying complexity. Some propose that spatially clustered inputs are more effective at driving output whereas other models suggest that diffuse input is better. It is still unclear which models, if any, accurately describe single neuron computation in vivo and during behavior. The study of single neuron computation requires the simultaneous measurement of many inputs to, and the output from, a neuron in vivo, which has not yet been possible. In my research, I will leverage novel imaging technologies to overcome current limitations and measure the input and output signals of individual cortical neurons. I hypothesize that action potential generation in vivo is more likely after a neuron receives clustered synaptic input. I will address this hypothesis through the following Specific Aims: Aim 1: Characterize the spatiotemporal relationships between synaptic input patterns and action potentials. Aim 2: Investigate how inputs change when the brain drives activity in a specific neuron. Aim 3: Determine whether hierarchical nonlinearities are needed to model a neuron’s computation. This project will result in new models of the neuron that better represent the range of computations performed in vivo. Given that neuropsychiatric diseases, such as schizophrenia, autism spectrum disorder, and bipolar disorder, have been hypothesized to affect proteins that dictate a neuron’s computational properties, a comprehensive understanding of neural computation would allow for mechanistic explanations of how such diseases affect patients’ cognitive capabilities.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY A major component of the tumor microenvironment, tumor-associated macrophages (TAMs) play a critical role in the orchestration of immunosuppression, cancer cell proliferation, angiogenesis, and metastasis, as well as in resistance to cancer therapies. As the bulk of TAMs in established tumors arise from circulating monocytes, targeting this differentiation process represents an attractive therapeutic strategy. Notably, the cytokines macrophage colony-stimulating factor (M-CSF) and granulocyte-macrophage colony-stimulating factor (GM- CSF) are both associated with TAM differentiation. Nonetheless, M-CSF and GM-CSF can also have distinct functional effects as they stimulate different receptors and downstream signaling pathways. In recent years, studies in the emerging field of immunometabolism have demonstrated that changes in intracellular metabolism downstream of cytokine activation can actively regulate immune cell differentiation and function. Despite all this, the differences in TAM-associated functions induced by M-CSF and GM-CSF in differentiated cells and whether early differential metabolic changes in monocytes contribute to these functional differences remain poorly understood. My preliminary data shows that GM-CSF derived macrophages have significantly higher expression of the TAM markers CD206 and PD-L1 than M-CSF derived macrophages, and that these differences and others are already conspicuous in monocytes after only 7 hours of cytokine stimulation. Interestingly, my preliminary data also shows that GM-CSF, but not M-CSF, results in a transient 7-hour period of prominent glycolytic oscillations in monocytes. Together, these results indicate that M-CSF and GM-CSF can produce unique effects on monocyte metabolism and TAM marker expression in differentiated cells. Considering previous studies and my preliminary findings, the central hypothesis of this proposal is that M-CSF and GM-CSF derived macrophages exhibit significant differences in TAM-associated functional characteristics due to early differential metabolic changes in monocytes. I propose to test this hypothesis through the following specific aims: Aim 1: Characterize differences in TAM-associated functional attributes and their regulation between M-CSF and GM-CSF at early and end points of differentiation of monocytes into TAM-like cells; Aim 2: Investigate whether differences in early metabolic changes induced by M-CSF and GM-CSF in monocytes contribute to differences in TAM marker expression in differentiated cells. These aims will be achieved through a combination of immunology, cancer biology, genome-wide profiling, and cell metabolism techniques with human monocytes isolated from healthy donor peripheral blood and differentiated in in vitro cultures to TAM-like cells. Collectively, the results of this work will advance our understanding of important functional differences between M-CSF and GM-CSF induced TAM- like cells and potentially reveal novel metabolic mechanisms that control TAM-associated functions, which may ultimately improve TAM-targeting cancer therapeutics.

NSF Awards · FY 2024 · 2024-09

This project aims to challenge established narratives about women's political behavior after suffrage by investigating the roles of electoral institutions and political geography in shaping gender gaps in voter turnout and preferences. The theoretical contribution lies in developing a new framework that explains how electoral systems and political geography drive variations in women's political participation across different regions and geographic space. Specifically, it posits that proportional representation and compulsory voting systems both diminish gender gaps in turnout, but that preference gaps at the national level depend on how local political geography combine with the demography of turnout. Empirically, the project tests these propositions in cross-national and within-country investigations, focusing on places that enfranchised women from 1906-1945 and under-studied areas. These cases provide unique institutional variation vis-à-vis more highly studied cases. By integrating new political domains, the study can better test the theory that electoral competition and political geography significantly affect gender gaps after suffrage. The methods involve collecting and digitizing historical electoral returns and census data, cross-nationally and then with a sub-national focus on polling-station-level data and state-level data. Advanced AI-assisted transcription techniques will be employed to process handwritten records. This approach will enable a comprehensive analysis of the gender turnout gap and preference gap across different electoral systems. By leveraging these unique datasets, the project will provide new insights into the effects of electoral institutions on women's political behavior, contributing to a broader understanding of political participation. The findings will have significant implications for political development theories and will support the education and training of underrepresented students in quantitative research methods. 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

PROJECT SUMMARY This is a proposal for a two-year career transition award to study atypical B cells as a novel immunologic and metabolic target to improve vaccine responses in immunosuppressed individuals. The candidate is currently a postdoctoral research fellow at the Johns Hopkins University School of Medicine. The proposal builds on the candidate's extensive experience in vaccine immunology and immunometabolism to understand how metabolic reprogramming of B cells contributes to successful vaccine responses. The COVID-19 pandemic has highlighted the need to develop and rapidly deploy highly immunogenic vaccines. However, insufficient immune responses in immunocompromised individuals have emphasized that novel vaccine formulations may be required for specific populations to overcome immunosuppression. To date, the basic immunology behind successful vaccine responses during immunosuppression has not been well characterized. By dissecting the immunologic and metabolic landscape following vaccination in immunosuppressed individuals, we hope to generate building blocks to reverse engineer vaccines for specific patient populations. Preliminary data from the principal investigator indicates that solid organ transplant recipients, who respond poorly to vaccination due to a variety of immunosuppressive drugs, manage to successfully respond to COVID-19 vaccination by expanding atypical B cells that are reliant on fatty acid oxidation. To further these findings, the principal investigator has proposed a research plan consisting of 3 specific aims. Aim 1 will define populations of immunosuppressed individuals who utilize atypical CD11c+ B cells as a salvage pathway to successful vaccine responses. Aim 2 will assess atypical CD11c+ B cell and T cell interaction to determine specific immunological contexts that drive CD11c+ B cell expansion. Aim 3 will target fatty acid oxidation using vaccine adjuvants to enhance atypical CD11c+ B cell development. Together, these studies will answer how atypical B cells develop in the presence of immunosuppression, what agents we can use to metabolically target them, and who will benefit from vaccine strategies targeting atypical B cells. The principal investigator will also learn new techniques necessary to accomplish the proposed research under the advisory team (Drs. Cox, Bailey, Durbin, Ji, and Pearce), all of whom have pioneering expertise in vaccinology, immunology, immunometabolism, and biostatistics. Importantly, her advisory committee collectively has a very strong track record of training both clinical and postdoctoral fellows who have successfully transitioned into independent investigators at top tier research institutions. She will also engage in and present at national seminars, take coursework on metabolic modeling, clinical vaccinology, Jr. Faculty leadership program, grant-writing seminars, and training on running a laboratory. The outlined career development and research plan will provide the candidate with unique cross-disciplinary skills that will enable her transition to independence and identify promising strategies to improve vaccine responses in immunocompromised individuals.

NIH Research Projects · FY 2026 · 2024-09

The adverse effects of poor treatment in healthcare settings on cognitive impairment are poorly understood, particularly among aging Americans. My F99 research established an association between these experiences and adverse cardiovascular events. Cardiovascular events are themselves known risk factors for cognitive decline. Building on this foundation, my K00 research will investigate the longitudinal impact of poor treatment in the healthcare settings on cognitive impairment and incident Alzheimer’s disease and related dementias (AD/ADRD). The research will leverage longitudinal data from the Health and Retirement Study (HRS) to test my central hypothesis that poor treatment in healthcare settings increases AD/ADRD risk and risk of cognitive impairment among aging adults. To evaluate this, the K00 research phase will use rigorous statistical methods, including survival analysis to estimate the impact of patient-provider interactions on incident AD/ADRD and longitudinal models to examine how trajectories of cognitive impairment are associated with these experiences over time. To achieve these research goals and facilitate my transition to independence, I will undertake a structured, mentored training program at Johns Hopkins University under the guidance of my primary mentor, Dr. Roland J. Thorpe, Jr.. This plan is designed to help me acquire foundational knowledge in the determinants of cognitive impairment, develop expertise in advanced longitudinal data analysis, and cultivate the leadership capabilities essential for an interdisciplinary research career. The findings from this K00 project will provide preliminary data for a subsequent career development award application, such as a K99/R00 or K01, which I plan to develop during the award period. This research and training trajectory is crucial for my overarching career objective to become a leading researcher focused on barriers to care that impact the cognitive health of aging Americans and aligns directly with the NIA's mission to understand and improve healthcare quality while aging.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Many important cellular processes are regulated through the formation and dissolution of the biomolecular condensates via liquid-liquid phase separation (LLPS). LLPS enriches specific factors in the biomolecular con- densates while excluding others, thereby creating a unique environment that either promotes or restricts certain biochemical reactions. To investigate how the dynamic process of LLPS and the reverse process that results in the dissolution of biomolecular condensates, biosensors capable of survey the biophysical properties of conden- sates as they form and dissolve within cells are highly desirable. The stability of a biomolecular condensate depends on electrostatic forces as well as hydrophobic interactions between the molecules residing in the con- densate. Currently there are no known biosensors for real-time monitoring of environmental hydrophobicity in living cells, limiting our understanding of how hydrophobicity changes over the lifetime of biomolecular conden- sates. Here we propose to develop a genetically encoded hydrophobicity biosensor, consisting of a pair of fluo- rescent proteins that can undergo Förster Resonance Energy Transfer (FRET). This hydrophobicity sensor will report FRET efficiency as the readout of hydrophobicity value. As proof of concept, we will create a recombinant protein in which the fluorescent profiting pair is fused with paxillin, an important protein in neurite growth, migra- tion of neuron and microglial cell, as well as endocytosis in cells of the neural system. We plan to first establish a calibration curve by which hydrophobicity can be quantified. Then we plan to demonstrate that this hydropho- bicity sensor can be used intracellularly to monitor the hydrophobicity changes in biomolecular condensates to which paxillin partitions. If successful, our design principle can be readily applied to measure hydrophobicity of condensates containing other molecules.

NIH Research Projects · FY 2025 · 2024-09

Overall Project Summary/Abstract Prostate cancer has become the most frequently diagnosed cancer in men in the United States (US) and a major cause of cancer morbidity and mortality, with 33,000 American men (~90 every day) dying annually from the disease. Considerable progress over the last decade resulted in the approval of multiple new hormonal and cytotoxic therapies, each producing modest improvement in survival. Yet, despite a broad palette of therapeutic options and the emerging promise of immunotherapy, the cure of metastatic prostate cancer has remained elusive. However, over the past two decades, dedicated prostate cancer research, accomplished by Johns Hopkins Prostate Cancer Program investigators and other researchers, led to a remarkable accumulation of knowledge about the molecular mechanisms by which human prostate cancers arise and progress. These studies identified adaptive autoregulation of androgen receptor activity, mutations and alterations in DNA-repair pathways and an immunosuppressive microenvironment as fundamental characteristics of prostate cancer producing resistance to hormonal, DNA-targeted and immune based therapies and allowing for progression that eventually threatens life. To make significant advancement in the treatment of prostate cancer, the goal of this new Prostate SPORE application is to translate new insights about the role played by adaptive changes in the hormonal axis, DNA-repair and the immune system in the pathobiology of prostate cancer into new hypotheses tested in clinical trials. The transcendent overall objective of the Johns Hopkins Prostate Cancer SPORE is to reduce prostate cancer mortality via the focused pursuit of translational research in prostate cancer.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Pulmonary endothelial cells (ECs) are in direct contact with laminar blood flow, resulting in exposure to shear stress. Normal blood flow provides a physiologic degree of shear stress at which ECs achieve quiescence. Pathologic changes in shear stress can occur in several conditions ranging from pulmonary embolism, where shear stress acutely decreases due to vessel occlusion, to pulmonary hypertension (PH), where shear stress in the distal arteries increases due to luminal narrowing. These disease entities carry considerable morbidity and mortality despite available therapeutics. The biochemical derangements that occur when shear stress is altered are not well-characterized, and elucidating these pathways may provide novel insight into potential therapeutic targets to prevent long-term dysfunction of ECs. In vitro culture of ECs is often performed under static conditions, leading to underappreciation of the effects of physiologic shear stress on normal cellular function as well as the biochemical and functional impact of shear perturbations. Aquaporin 1 (AQP1), a ubiquitous protein that forms water channels, is known to be expressed in vivo in the pulmonary endothelium, but we noted that AQP1 expression is not observed in human lung microvascular endothelial cells (hLMVECs) grown in static cell culture. My preliminary data show restored AQP1 expression in cultured hLMVECs with exposure to physiologic shear stress, suggesting a critical role of shear stress in dynamically regulating AQP1 expression. Increased AQP1 has recently been linked to important cellular functions, including angiogenesis and proliferation in certain malignancies, as well as contributing to vascular remodeling through apoptosis resistance and hyperproliferation in the ECs from rat models of PH. Regulation of AQP1 is not well-described in hLMVECs but is calcium- dependent in pulmonary vascular smooth muscle cells. Aim 1 of this proposal is designed to elucidate the biochemical signaling that occurs in response to changes in shear stress. In preliminary data, I show intracellular calcium levels increase in response to increased shear stress. I seek to define this signaling pathway focusing on the role of activation of the membrane ion channel, TRPV4, which can increase calcium influx in ECs in response to mechanical stimuli, in regulating AQP1 levels. Aim 2 will explore the functional outcome of changes in AQP1 expression in response to varying degrees of shear stress, focusing on apoptosis and proliferation. Techniques utilized will include but are not limited to cell culture under shear stress, ratiometric calcium measurement, protein and mRNA measurement, immunofluorescence microscopy, and measures of apoptosis and proliferation. Completion of this project will provide novel insight into the impact of shear stress on EC function, and how derangements in shear stress may alter cell signaling and cell growth and survival. The skills acquired in the design and execution of this study and the experimental results obtained will provide the necessary foundation for a K award and an excellent platform on which to start a career as an independently funded clinician-scientist focused on diseases of endothelial dysfunction.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract The visual accessibility of a space refers to the effectiveness with which vision can be used to travel safely and pursue intended activities in the space. Visual accessibility of a space reduces significantly for impaired vision, leading to higher risks of encountering hazardous situations, falling, and being disoriented in navigation. It is possible to improve the environmental accessibility by enhancing the visibility of informative or hazardous features through cost-effective modifications of contrast, illumination, and materials. However, it is difficult for people with normal vision, even those with rehab expertise, to judge whether specific objects or features would be visible for individuals with different levels of vision impairment, or to examine the efficacy of modifications. This research aims to develop an objective tool for evaluating the accessibility of indoor spaces to complement the current observational practice in visual environmental evaluation. This tool will be implemented as a smartphone app for easy use by rehab specialists and the general public. Using computer vision algorithms, RGB camera and LiDAR sensing technology, the tool will 1) visualize an environment for a specified level of vision impairment, 2) flag hazardous features, such as edges of stairs and chairs that are not visible for this level of vision, and 3) generate visibility metrics that quantify the visibility for a given object to the level of vision. The development and validation of this tool will be conducted in environments with different levels of realism including high-dynamic range images on digital displays, controlled lab spaces simulating real environments, and real clinical and home environments. The engineering approaches will be established through rigorous sensor testing in real environments. The computational algorithms will be developed using a large database of visibility ratings by low vision participants. The app will be first validated in controlled laboratory environments and then implemented in complex real environments including eye clinics and homes. This research strives to support the highest level of independence for people with vision impairment before they need to rely on assistive technology or human assistance. This endeavor is supported by a team with expertise in low vision research and rehabilitation, computer vision and modeling, architecture lighting and design, and assistive technology development. The proposed tool will facilitate the services provided by rehab specialists, caregivers, and facility managers in environmental evaluation and modification which will in turn enhance safety and independence in people with vision impairment. It will also facilitate telehealth by allowing easy sharing of home evaluation results. A tool that provides quantitative measures will contribute to the consciousness-raising of visual accessibility among the public. The engineering and computational approaches, once established, can be extended to platforms other than the smartphone models in the current development phase and can generalize to broader environmental contexts.

NSF Awards · FY 2024 · 2024-09

Electronic devices, from cell phones to entertainment consoles to medical devices and laptops, have become a mainstay of our society. All of these devices rely on the availability of electricity and tiny chips that constitute the “brain” of the device. Critical to this technology is the availability of a trained workforce with the multidisciplinary skill set who are able to produce these tiny and complex machines as well as innovate new technologies. The microelectronics industries where chips are manufactured constantly update their products to take advantage of new materials with better properties and improved ways of fabricating them from raw feedstocks. There is a strong need to commercialize these products efficiently, sustainably and cheaply. Increasingly, this means incorporating machine learning (ML) and artificial intelligence (AI) into the design and fabrication process. This National Science Foundation Research Traineeship (NRT) award to Johns Hopkins and Morgan State Universities will prepare students fluent in both the science underpinning electronic device fabrication and AI, and thereby prepare them for the tens of thousands of new jobs that the microelectronics industry will need to fill over the next decade. Trainees will also become skilled in basic business principles to acquaint them with the skills they will need to understand supply chain concerns, make strong business cases for new designs, and learn to become entrepreneurs. Our program will also educate trainees to understand career options in this broad business sector and provide them with the skills to be able to communicate with and manage individuals, teams and investors. They will learn about the cutting edge of chip design and manufacturing, from next-generation materials capable of handling different environments and applications to quantum computers. Our efforts will be targeted towards creating opportunities for those who traditionally do not have access to such high-tech career options and help create mentoring relationships that last a lifetime. As we near the limit of advances in microchip capacity and scaling, there is an imperative to become more creative with the use of new materials, new processing approaches, and new device designs to meet the insatiable need for continued performance growth. Recent Chips and Science Act legislation also stimulated new approaches to associated challenges in materials discovery and in the incorporation of new processes and device architectures. This training program will educate STEM graduate students to create the next generation of materials and devices driven by AI/ML integration. This innovative experiential educational program puts the student at the center of an individualized course of learning and career preparation. Trainees will be prepared to explore career options by acquiring customized skills needed for a specific career-focused track and will obtain path-distinguishing skills that will make them attractive hires. Their experiences include hands-on work in both physical and computational/AI labs; student training in funding oversight to teach leadership skills and ingenuity; presentation of a business plan to potential investors; participation in an internship at a venue relevant to their chosen track; intensive networking with domain experts; and exposure to career opportunities at annual interaction events. Four research thrusts explore advances in AI-Driven Development of: low-dimensional and quantum materials; materials for advanced semiconductor manufacturing; advanced computing hardware; and next-generation electronics for new environments and applications. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs. 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 · 2024-09

Dr. Peter Abadir is an active Geriatrician and associate professor of Medicine, Electrical, and Computer Engineering at Johns Hopkins University (JHU). He has put forth this K24 Mid-Career Development proposal dedicated to mentorship in patient-centric translational research. Dr. Abadir’s research connects molecular changes associated with aging to physical and cognitive declines observed in older adults. He's been instrumental in bridging the fields of aging research and engineering at JHU, leading to the creation of both the Hopkins GeroTech Program and Artificial Intelligence and Technology Collaboratory (AITC) for Aging Research. Candidate: Dr. Abadir is committed to further training to broaden his research program and mentor emerging scholars from both biology and engineering. Recognized as an accomplished clinician-scientist, he boasts significant achievements in translational research, particularly concerning frailty and Alzheimer's disease. His escalating leadership roles span both institutional and national platforms centered on patient-oriented research and aging-focused mentorship. As the co-PI of the Johns Hopkins AITC and the co-director of its Clinical Translation and Validation Core, Dr. Abadir actively contributes to the innovation of technologies tailored for older adults. Furthermore, he directs the molecular measurement core at the Older American Independence Center (OAIC) and is the associate director of the Translational Aging Research Training Program (T32). Mentoring Plan/Environment: Dr. Abadir's K24 proposal taps into the wealth of training assets at Johns Hopkins including resources from the JHU AITC, OAIC, the Institute for Clinical and Translational Research, and various T32 training grants. Special attention is given to mentoring investigators focused on populations at highest risk for aging-related conditions. Ideal mentees exhibit interest at the intersection of aging, technology, and Geroscience. The structured mentoring approach categorizes mentees based on experience, allocating specific effort percentages to ensure quality interactions. Regular individual meetings, hands-on research training, data interpretation, and presentation skills enhancement form core of mentoring strategy. Multi-tiered evaluations ensure consistent mentorship quality. This strategy aims to cultivate future leaders in translational aging research from both biological and engineering fields. Research Plan: The pioneering research funded by this K24 award aims to harness Artificial Intelligence (AI) tools and analytics for assessing physical and cognitive digital biosignals in frail older individuals including those with Alzheimer’s disease and associating these with molecular markers. The study will evaluate the accuracy and reliability of a new method that uses AI to analyze non-invasive multimodal biometric signals like speech, voice, eye movements, handwriting, and gait. This methodology will enhance our understanding of the varied characteristics of frailty in older individuals and pinpoint early cognitive shifts, including signs of Alzheimer’s. Building upon the existing efforts at Johns Hopkins AITC and OAIC, this research seeks to uncover new insights and broaden avenues for upcoming researchers.

NSF Awards · FY 2024 · 2024-09

This award funds the research activities of Professors Marc Kamionkowski, David E. Kaplan. Surjeet Rajendran, and Ibrahima Bah at Johns Hopkins University. The quest to understand the fundamental laws of physics is at an important nexus. While we await the discovery of new physics at accelerator experiments and ongoing dark-matter searches, existing null results have forced theorists to discard long-held theoretical preferences and think deeply about entirely new ideas for fundamental physics and novel experimental techniques to test these new ideas. This effort is also advanced by the development of new mathematical tools to help understand the structure of the theories from which our models of fundamental physics are constructed. The effort is now also advanced by exciting new discoveries in cosmology and astrophysics. The JHU particle-theory group tackles central problems at the juncture of theory and experiment in particle physics and cosmology and in the formal mathematical tools that are the foundation of physical theories. This group will advance new ideas for cosmological observations and fundamental-physics searches and propose new mechanisms and models that may ultimately help in the grand synthesis of nature's laws. The research will proceed in parallel with the training of students and postdocs who will evolve to become scientific leaders, and the group will remain vigorous in its quest to communicate the excitement of particle physics and cosmology to the general public. Theoretial research along these lines advances the national interest by optimizing our investment in major experimental facilities in their quest to understand new physical laws. More specifically, Profs. Kaplan and Rajendran will develop new non-accelerator directions for exploring the fundamental laws of nature while pushing to pursue a deeper understanding of the phenomena we see. Rajendran will do related work on new ideas for the fundamental laws of quantum mechanics. Kamionkowski proposes to develop a suite of new early-Universe probes with forthcoming observations, and to study novel models to account for the Hubble tension. Bah proposes work in geometric engineering of QFTs and in the study of a new class of “topological stars” and their possible phenomenological consequences. There is much overlap between the boundaries of the research interests of the group members, and novel ideas will emerge from collaborations that emerge from these intersections. 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/Abstract Tuberculosis (TB) remains a global public health problem. Globally, 10 million people develop active TB each year, but one-third of them are not diagnosed or started on treatment. Systematic screening of high-risk populations, known as “active case finding,” can facilitate early diagnosis and reduce the global TB burden. While chest X-ray (CXR) is a sensitive tool for TB screening, high-burden countries often do not have enough qualified readers needed to scale up CXR-based screening. Advances in artificial intelligence (AI) offer a promising alternative through computer-aided detection (CAD). CAD systems analyze a CXR for signs of TB and generate a numeric score that can be used to select people for further testing. Recently endorsed by the WHO for TB screening, commercial CAD systems have begun their deployment for active case finding. However, for CAD to realize its full potential and have a meaningful impact on TB epidemiology, it is essential to tailor its implementation to the local population and screening context. This proposal aims to optimize the implementation of digital X-ray technology with CAD for community-based TB screening in sub-Saharan Africa. This will be accomplished by evaluating two novel screening strategies against the current standard approach, which is to offer sputum testing to individuals with an X-ray abnormality score above a set threshold. The first strategy is to individually adjust this threshold according to client characteristics such as age, sex, HIV status, and symptoms (Aim 1). The second strategy is to develop and utilize an independent CAD model, trained on chest radiographs from the local screening population, as opposed to relying on a commercial CAD product trained on a larger, but less representative dataset (Aim 2). In addition to evaluating the diagnostic accuracy of these approaches, the feasibility and cost-effectiveness of each strategy will be evaluated against the conventional method within the Ugandan context (Aim 3). This mentored patient-oriented research will not only inform future implementation of CAD for TB screening but also provide a robust training platform for the award recipient. Through both research and career development training, the recipient will acquire essential skills in advanced statistics, AI analytics, implementation science, and health economics, as well as hands-on experience in field data collection. This will lay the foundation for an independent career as a clinical investigator focused on the implementation of AI-driven health innovations in resource-limited settings.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY/ABSTRACT Immune thrombotic thrombocytopenic purpura (iTTP) is a rare, life-threatening disorder characterized by acute episodes of systemic microvascular thrombosis caused by deficiency of ADAMTS13, a von Willebrand factor cleaving protease. iTTP survivors remain at risk for multiple adverse neurologic outcomes including cognitive impairment and a five-fold increased risk of stroke. During the K99 award, Dr. Chaturvedi conducted a single- center prospective study and established that 50% of iTTP survivors have silent cerebral infarction (SCI), defined as magnetic resonance imaging evidence of brain ischemia in the absence of overt neurologic deficits, which is a much higher rate than reported in population-based cohorts. SCI is also independently associated with cognitive impairment in iTTP survivors. Critical unanswered questions that are addressed in this R00 proposal are: 1) do SCI occur during iTTP remission or are they only sequelae of acute iTTP, or both? 2) are SCI a risk factor for future stroke, and 3) how can we prevent SCI and their devastating neurologic sequelae (cognitive impairment and stroke)? The applicant will build upon the K99 study to conduct a multi-center observational study at three clinical sites with established prospective iTTP cohorts and a track record of research in iTTP (Johns Hopkins University, Ohio State University, and University of Minnesota). Aim 1 will elucidate the natural history of SCI and establish the incidence and risk factors for new SCI and stroke occurring during clinical remission of iTTP, with a focus on remission ADAMTS13 activity and other modifiable risk factors such as hypertension. Aim 2 will evaluate the impact of the novel anti-VWF therapy (caplacizumab), used in the treatment acute iTTP, on the prevalence of SCI and cognitive impairment by comparing with matched patients treated without caplacizumab, and adjusting for other acute iTTP specific variables such as neurologic involvement at presentation, and time to clinical response and ADAMTS13 activity recovery. Dr. Chaturvedi and her research team have established the infrastructure, expertise, protocols and have a record of accomplishment of successful clinical research in rare diseases. This R00 proposal will provide critical data that will directly impact clinical care in iTTP. Identifying whether early anti- VWF therapy or maintaining higher remission ADAMTS13 protect against SCI and cognitive impairment will change current paradigms of treatment where anti-VWF is not considered universally cost-effective, and only ADAMTS13 levels <20% are targeted to prevent relapse. if we establish that SCI are strongly associated with stroke, then SCI is an attractive shorter-term endpoint for an intervention to reduce the burden of cerebrovascular disease, potentially reducing the duration and expense of clinical trials. In addition to building infrastructure for and informing the design of a subsequent clinical trial of an intervention to alleviate the long- term neurologic morbidity of iTTP, this R00 proposal will also build a data and sample biorepository to investigate biomarkers and mechanisms of SCI in iTTP for a subsequent R01 application.

NIH Research Projects · FY 2024 · 2024-08

PROJECT SUMMARY Individuals with Subjective Cognitive Decline (SCD) and mild cognitive impairment (MCI) are significantly more likely to have increased AD biomarkers (e.g. amyloid β) and higher risks of developing Alzheimer’s Disease and Related Dementias (ADRD). Sleep disturbances have been associated with increased risks preclinical AD, ADRD, and all-cause dementia. However, most of these studies focus on sleep’s association with the incidence of SCD, MCI, or dementia individually, rather than the progression of cognitive impairment from SCD to MCI to dementia. The latter is of key clinical importance when attempting to halt or treat AD progression. In addition to sleep, recent studies have shown that physical frailty is also closely interrelated with cognitive impairment, with evidence that they predict one another, share common risk factors, and have similar potential mechanisms. The co-existence of both physical frailty and cognitive impairment (MCI/SCD), also known as cognitive frailty, is supposed to be a predictor of severe health consequences with the synergic negative effects of both. However, this synergic effect on future cognitive decline and progression to dementia is still underexamined in the literature. Moreover, given the interrelationship between physical frailty and cognitive impairment, it is possible that physical frailty moderates the associations between sleep disturbances and progression from SCD/MCI to dementia. Therefore, the overall goal of this project is to investigate the roles of sleep disturbances and physical frailty in SCD/MCI’s cognitive progression and explore whether physical frailty is a moderator of sleep’s association with the cognitive progression. In the F99 phase, the PI will use six waves of longitudinal Health and Retirement Study data from the 2010 to 2020 to examine the associations of baseline self-reported insomnia symptoms and physical frailty with 10-year cognitive trajectories and subsequent incidence of MCI/dementia in SCD. In the K00 phase, the PI will shift the population to MCI, a more advanced AD stage, with a focus on actigraphy-measured sleep and neuroimaging cognition measures. The PI will use the UK Biobank data to examine the associations of sleep (both actigraphy-derived and self- reported) and physical frailty with brain structure (magnetic resonance imaging data), subsequent cognitive function, and incident ADRD among older adults with MCI. In both phases, physical frailty will be examined as a moderator in the associations between sleep and cognitive outcomes. This research will help to pinpoint at- risk populations for ADRD, advance understanding of the roles of sleep and physical frailty in ADRD progression in SCD and MCI, and suggest strategies for delaying AD/dementia progression through the lens of sleep and physical frailty. Further, the training objectives nested in the F99 and K00 phases of this award will allow the PI to gain necessary knowledges and skills to develop into an independent investigator in aging research, with a focus on the sleep and cognitive health in older adults.

NIH Research Projects · FY 2025 · 2024-08

Project Summary Chronic alcohol use has long-lasting detrimental effects on human cognition and behavior that result from changes in brain function. Here we examine changes in corticostriatal circuit function after a 4-week chronic alcohol exposure via alcohol vapor using high-density neural recording (Neuropixels) and optogenetics within rodent models of decision making. In Aim 1 we characterize neural activity changes within the anterior cingulate cortex, orbitofrontal cortex, and dorsomedial striatum as rats exposed to chronic alcohol perform a two-choice probabilistic reversal learning task in which we have previously seen alcohol-induced performance deficits. In Aim 2 we use optogenetic manipulations to probe the role of cingulate cortex-to-dorsomedial striatal and orbitofrontal cortex-to-dorsomedial striatal projections in this behavior in rats exposed to chronic alcohol. In Aim 3, we extend our corticostriatal recording approach to alcohol self-administration to determine if neural activity related to this behavior is altered by prior chronic alcohol exposure via alcohol vapor. Together these studies will provide new information on the impact of chronic alcohol on the activity of large populations of neurons within corticostriatal circuitry that is critical for executive function and cognitive control.

NIH Research Projects · FY 2025 · 2024-08

More than 80,000 adolescents and young adults (AYAs, ages 15- 39 years) are diagnosed annually with cancer in the United States, but relatively few enroll on cancer clinical trials (CCTs). Limited AYA participation on CCTs hinders the ability to further improve AYA cancer care and outcomes. Initiatives to increase AYA CCT enrollment is urgently needed. This proposal identifies several areas for improvement that are immediately addressable and shareable within the Sidney Kimmel Comprehensive Cancer Center (SKCCC), other medical centers, and NCI consortium groups. The approach will significantly improve AYA clinical trial participation at SKCCC by further developing and implementing a clinical trial tool we abbreviate AYA: Alert, Young Adult Navigation, Alliance, initially within the hematologic malignancies (HM)/pediatric BMT program and then beyond. These interventions will cross fertilize collaboration at three levels: 1) Patient; 2) Multi-disciplinary Provider and 3) Center/Systems. The solutions proposed will improve AYA access to and enrollment on CCTs, strengthen the clinical research enterprise, and address cancer disparities – all NCI priorities. This proposal will utilize a new multi-faceted alert system that includes an electronic medical record (EMR) alert to identify AYA patients and the potential clinical trials for which they are eligible. Weekly clinical trial research meetings will alert the multi-disciplinary team to the AYA clinical trial priority list. Patient alerts via our EMR directly linked to the patient’s mobile device will highlight CCT enrollment and upcoming appointments. Automating the identification of trial eligible AYA patients, providing timely information to the study team and physicians, and keeping AYA patients engaged through EMR directed mobile phone messaging will optimize enrollment and compliance. A dedicated clinical research nurse young adult navigator will interact early with AYA patients, help with AYA CCT enrollment, and bridge the knowledge and workflow gap between our adult and pediatric consortium trials. A cohort of prior AYA CCT participant survivor navigators will serve as spokespeople on our AYA website and on social media. An AYA psychosocial navigator will round out the partnership to improve AYA support. Lastly, a multi-faceted education campaign will be launched to improve alliances. NCI consortium enrollment issues will be highlighted at joint HM/pediatric BMT clinical research meetings. We will create cross-network enrollment FAQ documents. Using digital communication, we will provide information to AYAs about CCTs to supplement discussions with providers.. Best practices identified from this project will be readily transferrable to the entire SKCCC enterprise and other academic medical centers. As a nationally recognized BMT expert with a strong commitment to NCI-funded clinical trials and extensive knowledge in clinical research operations, Dr. Symons is poised to lead these efforts and successfully enhance AYA accruals.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY Effective communication strategies are urgently needed to convey the relative risks of tobacco products accurately among adults who currently use combustible tobacco while minimizing such appeal among youth populations. There is a significant gap in research on the impacts of communicating the continuum of tobacco products risks to diverse audiences. Current research has primarily been limited to cross-sectional studies of single message exposures among adults. As such, there is insufficient evidence on how messaging about the continuum of risk of tobacco products would influence the message response, receptivity, behavioral precursors, and tobacco use behaviors among the diverse audiences that these messages must reach. The long-term objective of this project is to optimize future public health communication on the continuum of risk for tobacco products to minimize tobacco use harms among adults who use tobacco products and prevent youth initiation and progression of tobacco product use. Our proposed project, in direct response to RFA-OD-23-021, will assess the effects of FDA tobacco product risk continuum messaging on adult users of combustible tobacco products (including those who have not yet been able to quit) and youth/young adults using an integrated study design that captures the full range of relevant outcomes, from immediate message response and receptivity to longer-term behavior. This project is guided by a theoretical framework integrating key constructs in health communication (Message Impact Framework), persuasion (McGuire's persuasion framework), behavioral economics, and behavioral change theories (Reasoned Action). Our specific aims are to: (1) Generate rankings of messages and identify effective message features based on perceived message effectiveness, and message comprehension; (2) Characterize effects of messages and message features on response and receptivity, and precursors to behavior, including behavioral intentions, and (3) Specify immediate and long-term behavioral effects of tobacco product risk continuum messages. Approach: We will deploy a nimble framework to: refine messaging and develop control messages (message rating survey, cognitive interviews); formally test message response, receptivity, and effects on behavioral precursors (online national experiments, eye-tracking and neuroimaging); and assess immediate and long-term effects on behavior (mobile device-based message delivery and laboratory smoking topography studies) among samples of adults who use combustible tobacco, youth/young adults who use non-combustible tobacco, and youth/young adults who do not use tobacco. Impact: The successful completion of this project will provide FDA with clear, rigorous, and comprehensive evidence regarding the effectiveness of the specific messages provided for this study, as well as theory-informed insights regarding broader message strategies to optimize future public health communication on the continuum of risk for tobacco products to diverse audiences.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY As animals interact with their environment, they build and accrue sound associations with behaviorally relevant outcomes. The mammalian auditory system can be modified by experience and by behavioral context and supports the ability to build these associations. The auditory cortex (AC) supports the ability for animals to learn that particular sounds can signal rewards. The neural responses in the primary auditory cortex (A1) can be re-shaped by audiomotor learning, taking the form of changes at the single-neuron and population level. This learning-induced plasticity decreases after animals are trained at expert levels of behavioral performance for several weeks until the cortical map appears to renormalize and neural responses revert to a near pre- learning state. The plasticity that emerges across learning is not preserved in the cortex during the overtraining phase, yet animals are able to retain task performance. The overall objective of this proposal is to if A1 tutors or offloads these combined representations of sound and action to another pathway for long-term use, which supports long term execution of the task and the renormalization of A1. Our central hypothesis is that the A1 tutors subcortical auditory regions—the medial geniculate body (MGB) and the inferior colliculus (IC)— which subsequently store audiomotor associations. I will address this question in two aims. In Aim 1, I will determine the spatiotemporal dynamics of plasticity in the IC, MGB, and AC across learning and overtraining. In Aim 2, I will identify the causal contributions of the MGB and the IC at the expert level. To do this, I will train mice on an auditory go/no-go task where mice learn to lick to a pure tone for a water reward (S+) and withhold licking to another tone (S-) to avoid a timeout. We use large-scale, two-photon mesoscopic imaging to monitor neural activity in IC neurons, MGB axons, and A1 neurons over the entire course of learning and overtraining (28 days). I developed a new surgical preparation which allows the implantation of a single cranial window over the IC and the AC to enable simultaneous calcium imaging of both regions and the feedforward projections from the MGB to the AC. By tracking the same cell bodies and axons across a month of training, we examine the sequence of stimulus-related and non-stimulus related plasticity and the nature of how learning and overtraining impact these processes across the sensory hierarchy. Using a combination of state-of-the-art optical tools, temporally precise optogenetics, large-scale calcium imaging, and custom computational analyses and tools, these experiments will help us understand the nature of cortical-subcortical interactions that support auditory learning and memory consolidation along three processing stations in the central auditory system.

NSF Awards · FY 2024 · 2024-08

When organisms are exposed to environmental differences, like changes in temperature conditions, they can grow into alternative forms that are more adapted to particular environments. This project investigates how a nematode roundworm makes the decision to become a long-lived and stress-resistant form instead of a proliferative form that is stress-sensitive. Currently there is little understanding how these types of decisions are made at the molecular level. High-throughput measurements, genome sequencing, and genetic methods will be used to examine this mystery and lay the groundwork for future projects examining how animal development changes in responses to divergent environmental cues. Undergraduate and high school student training is an important component of this grant. High school teachers will develop classroom activities for STEM students in cooperation with the principal investigator and high school students will visit the laboratory to carry out hands on experiments with the worms. Phenotypic plasticity, or the expression of different phenotypes by the same genotype, drives evolutionary adaptation to shifting environments. Despite numerous well-known examples, little is known about the genetic underpinnings and molecular mechanisms that generate phenotypic plasticity. The goal of this grant is to discover how microevolution of this plasticity occurs using the tractable metazoan system Caenorhabditis elegans. Depending on environmental conditions, these nematodes enter an alternative developmental fate, called dauer, or continue development to reproductive adults. Early larval-stage animals that sense high temperature, low food availability, and high population density initiate the development of the dauer stage. Once conditions improve, dauers re-enter development to become reproductive adults. Much of what is known about dauer comes from the study of a single laboratory strain. Although natural variation in dauer formation has been observed, the molecular mechanisms that lead to phenotypic differences remain unknown. An unbiased approach is needed to discover the genes that underlie natural variation in dauer formation in order to understand how phenotypic plasticity evolves. Species-wide association mapping will be performed using a novel high-throughput assay in order to identify loci that underlie differences in this developmental trait. These loci will be narrowed to candidate genes using well tested experimental and computational techniques and then variants will be validated using genome editing. These approaches will lead to discovery of the number and the sizes of genetic effects, the signatures of selection that occur at those loci, and then define the parts of the dauer network involved in the microevolution of phenotypic plasticity. 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

Surprisingly, when tissues like the skin or cornea are wounded, our bodies immediately respond by creating a natural electric field pointing toward the wound center. These fields have nothing to do with the brain or nervous system. Instead, cells can actually use the electric field to navigate, leading them to the wound site (“electrotaxis” or “galvanotaxis”). Controlling this electrical signal is thought to be able to improve our own ability to heal. However, developing next-generation ‘electroceutical’ tools requires us to better understand what cells are doing when following this signal – how do they detect an electric field, and what limits their ability to sense it? Understanding this requires a focus on the interaction between biological cell motility and the physical forces applied to molecules on the cell’s surface. Currently, most of the data in this field suggest that cells follow electric fields because charged sensor molecules are redistributed on the cell’s surface. However, these molecules are so small that the electrical signal will be competing with fluctuating thermal forces (Brownian motion). This competition could affect how accurately cell can respond to the electrical signals and understanding it could lead to better ways to deliver electrical signals to improve cell responses. This project will study how these physical factors limit the accuracy of how both individual cells and groups of cells follow fields. The research is a collaboration between the Camley group, who model how groups of cells respond to chemical cues and have recently developed a biophysical model for single-cell galvanotaxis, and the Cohen group, who are experts in engineering and controlling electrotaxis at the tissue scale. This project will support the development of computational models that include the motion of sensor molecules on the cell’s surface in response to electric fields, the crawling of the cell, and the ways in which cells can influence the electric fields around them. The project will then involve testing these models using experiments with single cells, small numbers of cells, and tissues, and use this data to refine the models. The Broader Impacts of this work include a better understanding of these processes essential to wound healing, as well as developing tools to help guide individual cells or cell sheets—all of which brings us closer to new bioelectric technologies for healing. In addition, this project will support training of scientists in broad communication, outreach, and storytelling through an expansion of Cohen’s ‘Lab Tales’ storytelling training workshop where trainees learn science history and storytelling through a week of hands-on instruction. In more detail, this award will aim to answer three broad questions. First: how does a cell’s shape affect its ability to sense a field? Many single eukaryotic cells stretch perpendicular to an applied electric field. Why? Does it benefit them? To answer, the project will study how the ‘front’ and ‘back’ of a cell reorients when exposed to an electric field, and how this depends on cell shape and orientation. The project will control cell shape by using adhesive micropatterns, allowing for quantitative comparison with theory. Second: Do cells interact while galvanotaxing? Cells, by their presence on the substrate, will alter the local electric field. Can pairs of cells interact through the electric field, with one cell causing the other to reorient? Third: Can groups of cells improve their accuracy by aligning? Many cell types develop so-called “nematic” alignment, where cells’ long axes align with each other – this also includes keratinocytes following electrical fields. How does this affect the group’s ability to respond to signals? 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

Summary Generating synapse-resolution maps or connectomes of the brain are crucial to understanding the neural basis of behavior, and can provide key insights into the onset, progression, and treatment of neurological disease and injury. Towards this goal, major advances in electron microscopy imaging and automated image segmentation have enabled researchers to produce millimeter-scale connectomic datasets, and forge a path towards an even larger whole mouse brain volume. Despite the high quality of automated segmentation at this scale, the enormous extent of axon and dendrite “wiring” in the brain unavoidably leads to errors in neuronal connectivity that require correction with post-hoc proofreading. Although a variety of approaches have been developed to enable faster manual proofreading, the number of human hours needed to correct errors are prohibitive, and prevent us from realizing the full potential of valuable datasets such as the cubic millimeter MICrONS (mouse cortex) and H01 (human cortex) volumes. To enable even larger connectomes, we must develop cost-effective and time-saving automated methods to replace labor-intensive human proofreading where possible and allow human resources to focus on other connectomic tasks that include generating training data and validating automated correction. The goal of this proposal is to build capabilities for scalable automated proofreading, leveraging and extending software tools built during our previous IARPA MICrONS activities: NEURD (short for NEURal Decomposition), an automated error detection and correction framework built by Baylor College of Medicine, and NeuVue, a scalable manual proofreading platform built by the Johns Hopkins University Applied Physics Laboratory. Both tools are deeply integrated and complementary to the existing ecosystem of open- source connectomics tools and resources from the community such as Neuroglancer, PyChunkedGraph (PCG), and Connectomics Annotation Versioning Engine (CAVE). Building on the foundation of these tools and our existing collaboration, we will add capabilities for machine learning enabled error detection of a wider range of error types including both merge and split errors. We will implement an active learning approach that focuses valuable human validation effort on the most informative error examples, with the goal of statistically validating entire classes of edits that can be applied in automated batches to the segmentation. Finally, we will develop a workflow for applying these automated edits to the segmentation in an optimized way that also does not conflict with existing manual proofreading and retains a confidence metric for each edit that can be used for downstream analysis. The successful completion of this project, “Connects-Proof: A Scalable Automated Proofreading Framework for Connectomics” will yield a mature workflow that is validated across multiple data sets and that can support existing and future work in the BRAIN-CONNECTS program.

NSF Awards · FY 2024 · 2024-08

Nontechnical Organic semiconductors and metal halide perovskites are intensively studied materials for a range of clean energy and consumer applications such as solar cells, flexible electronics, and sensors. Although organic semiconductors have great promise, they exhibit significantly different electrical and optical properties depending on the crystal structure created when assembled into solid films. This impacts their potential for use in optoelectronic devices. Although there is a well-recognized need to precisely control crystal structure to manipulate or optimize material behaviors, there is a very limited experimental toolkit for doing so. In this project, the researchers aim to use perovskites as a templating layer that can control the crystal properties of organic films deposited on top. X-ray scattering and ultrafast spectroscopy are used to evaluate the structural properties of organic thin films, and their effect on the optical and electronic properties. This approach allows investigators to finely tune the underlayer periodicity and chemistry simultaneously and thereby optimize the efficiency of energy and charge transport. This paradigm can be used to design better solar cells, light-emitting diodes, and other optoelectronic devices. Students are engaged in the research through training and guidance by the principal investigators and participate in regular meetings between the groups. In addition, the project team is committed to promoting diversity by encouraging recruitment and retention of underrepresented groups to the project, and leading outreach efforts in the community targeted towards middle and high school students. Technical The goal of this project is to develop two-dimensional metal halide perovskites (2D MHPs) as a crystallization templating tool for organic semiconductor (OSC) thin films, to reduce the disorder in crystalline packing, and to control packing geometries for tuning optoelectronic behaviors, including singlet fission and exciton transport. These controlled heterostructures can then be utilized for photovoltaic devices. Numerous research thrusts have focused on how changing the OSC chemistry can impact exciton transport and energy transfer, which generally result in large crystal structure changes, but there is relatively less information on how to finely control the solid-state structure of the OSC to control optoelectronic behavior, and by extension, device performance. This understanding is necessary for controlling processes such as singlet fission and exciton transport, as sub-Angstrom changes in molecular packing can cause significant changes in these behaviors. This project aims to address three objectives: 1) Understanding how 2D MHP thin films can control various OSC thin-film crystalline properties (order, polymorphism, orientation) through lattice registry, 2) Controlling exciton transfer (including singlet fission) and transport in 2D MHP templated OSCs by utilizing these sub-Angstrom changes, and 3) Controlling the heterostructure transport between the 2D MHP layer and the OSC. The research focuses on the prototypical OSC molecule perylenediimide, but the knowledge gained is relevant for other OSCs as well. The success of this project can result in a novel method of controlling the order, packing, and orientation of OSCs and understanding and manipulating structure-property relationships between templated OSCs and optoelectronic properties. There is a scarcity of fundamental knowledge relating to sub-Angstrom changes in OSC solid-state packing and their resulting optoelectronic behavior. The work addresses this gap and advances the knowledge of crystal structure and optoelectronics. The use of a 2D MHP template to reduce defects as well as change the crystal packing while still creating stable structures would be a significant departure from the current understanding of creating ordered OSC thin films, and the optoelectronic control afforded by these structures can open new doors for device applications. 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 · 2024-08

Mitochondria play an essential role in cellular function and impact human health through varied mechanisms, including energy metabolism, cell signaling, and apoptosis. We have previously demonstrated that mitochondrial DNA copy number (mtDNA-CN), which reflects some aspects of mitochondrial function, can readily be measured from DNA extracted from buffy coat, and is associated with various aging-related diseases and phenotypes. The recent availability of whole-genome sequence (WGS) data in large biobanks, along with plasma metabolomics and proteomics, vastly expands the ability to assess mitochondrial function in large sample sizes. Specifically, we hypothesize that a comprehensive assessment of mtDNA variation, including mtDNA-CN, homoplasmy (inherited variation), and heteroplasmy (somatic variation) in 680,000 subjects, combined with metabolomics/proteomics, will identify novel causal associations between mitochondrial function and all-cause mortality, CVD, and frailty. To test this hypothesis we will first identify plasma metabolites/proteins associated with mitochondrial function. We focus on identifying metabolites/proteins associated with mtDNA sequence variation, leveraging the concept of Mendelian randomization (MR) to avoid confounding. We will study omics measured in up to 300,000 UK Biobank (UKB) participants, with validation in TOPMed samples (n~25,000), and compare associations with mtDNA sequence variation to those for mtDNA-CN. Biomarkers associated with mtDNA genetic variation and not mtDNA-CN will be considered orthogonal biomarkers. Second, we will stablish phenotypic associations between biomarkers of mitochondrial function and aging-related diseases. We will determine the association of mitochondrial function biomarker with all-cause mortality, CVD, CVD risk factors, and frailty in UKB samples, with validation in TOPMed samples. We will also explore multivariable models looking for potential interactions between the various measures of mitochondrial function. Finally, we will discriminate causal from non-causal associations of mitochondrial function biomarkers and aging-related disease. We will identify instrument variables for MR by conducting GWAS of nuclear variants with mtDNA-CN, heteroplasmy, and mtDNA-associated metabolites/proteins. We will use MR to determine causality and causal mediation analysis to determine mediated proportions. We will then use systems biology approaches to identify the relevant gene(s) at each locus and map putative functional variants for experimental validation. We will characterize the identified genes by assessing mitochondrial function (e.g., cellular respiration, glycolytic flux) and quantity (nucleoid density, mass). In sum, this proposal will leverage the combination of genetic variation, both inherited and somatic, in conjunction with mtDNA-CN, metabolomics, and proteomics, is a highly innovative approach that will identify readily measurable biomarkers of mitochondrial function. By combining MR with functional validation, we will identify causal genes, identifying therapeutic targets for aging-related diseases exacerbated by mitochondrial deficiency, and serve as potential readouts for testing molecular therapies.