Johns Hopkins University

NIH Research Projects · FY 2024 · 2023-07

Multi-material decomposition using spectral CT provides quantitative information on tissue composition. This information is beneficial for many clinical applications including CT imaging of the cardiac vasculature and the abdomen. Clinical implementation for spectral CT has taken different paths, such as using dual-source, fast kVp switching, and photon counting or sandwich detectors; each of these solutions has its own strengths and weaknesses. In particular, the limited spectral diversity of existing solutions limits the number of differentiated materials, leaving many clinical questions unanswered. The unmet clinical need for a satisfying spectral CT solution that is capable of multi-material decomposition motivates this proposal. We propose a practical solution to spectral CT using stationary spectral encoding. This technique is simple enough to be implemented at low engineering cost on all energy-integrating CT scanners. The key element in our solution is a ring- shaped, stationary spectral encoder that can be attached to the CT gantry opening. The spectral encoder is made of thin materials of spectrally diverse properties arranged around its perimeter. As the x-ray tube and the detector rotate around the patient, the emitted rays are continuously modulated by the encoder materials, thereby providing essentially endless possibilities in terms of spectral diversity. Multi-material decomposition is accomplished by advanced material decomposition algorithms that reconstructs the material maps directly from the spectral encoder CT data. The goal of this proposal is to develop and optimize the spectral encoder towards future physical construction and clinical evaluation studies. In Aim 1 we will build a computational platform to generate the spectral encoder CT data, and develop material decomposition algorithms. In Aim 2 we will optimize the stationary spectral encoder design parameters for the best possible material decomposition performance. These aims collectively provide a practical pathway for clinical translation: the results from these aims will guide prototype development, which then will be followed by real data acquisition with physical phantoms and patient studies. The proposed spectral encoder can be used for all CT scanners and will make multi-material decomposition widely available.

NIH Research Projects · FY 2025 · 2023-07

The Johns Hopkins University (JHU) Trial Innovation Center (TIC) is a well-established, highly functioning team with a goal of dramatically improving the conduct, efficiency and impact of multisite randomized controlled trials. The TIC includes experienced trial scientists, project managers, statisticians, and trial staff with external collaborators from 5 research intensive CTSA Hubs. BIOS, a JHU trials research group, will operationally convene this group and provide staff to execute version 2.0 of the Trial Innovation Network (TIN) program and its specific tasks as previously and collaboratively determined by the TICs, RICs and NCATS. During TIN 1.0 our joint expertise Developed and Demonstrated new methods for multicenter trials and provided these methods via the TIN platform to individual CTSA Hub PIs wishing to perform multisite randomized trials. This proposal is derived from our established track record of trial execution accomplishments and trial science innovations, which will facilitate dissemination of these methods and specific trial tools towards the NCATS goal to speed translational research. We identified needs not met in TIN 1.0 including: trial training of hub staff, training in operations rather than strategy, preceptorship for Hub CCC/DCC capabilities, and need for up-to-date operational methods/tools. In TIN 2.0 we will further Develop new trial tools and methods for testing their ease of implementation at CTSA hubs, Demonstrate the effectiveness of this approach, and Disseminate broadly to CTSA Hubs, by using case studies and didactics. We propose an integrated, coordinated, multi-stakeholder TIC process to improve the efficiency and quality of multi-site trial initiation and subsequent execution by CTSA sites. Our group of external collaborators will work as a sample of the larger CTSA-TIN consortium to develop Hub implementation and dissemination approaches on both a case- and consortium-wide basis. The JHU TIC will leverage operational activities in CTSA trials implementation to study novel operational innovations that improve participant engagement, intervention adherence and measurement of trial endpoints. We will measure benefits using explicit efficiency- and quality-focused metrics to test these innovations. The scientific purpose of our team’s efforts will be to demonstrate that TIC innovations in trial design, execution, and evaluation can lead to better trial performance, including faster start-up, faster completion, greater protocol compliance and more precise endpoints. We will disseminate results of validated CTSA-TIN innovations produced from consortia trials to CTSA Hub clinical trial teams and research trainees. We will collaborate with NCATS to utilize the platform demonstrated in TIN 1.0 to engage and equip a multisite randomized clinical trial workforce through the CTSA Hubs to perform trials faster and at a higher quality in TIN 2.0.

NIH Research Projects · FY 2025 · 2023-07

Metastatic castration-resistant prostate cancer (mCRPC) tumors are characterized by an abundant, tumor- promoting immune infiltrate that is composed of immune suppressive tumor-associated macrophages (TAMs). These cells promote angiogenesis, suppress T cell recruitment and/or activation and promote metastasis in mCRPC. T cells exclusion by TAMs in mCRPC leads to resistance of immune checkpoint therapy. Annually, nearly 270,000 men will be diagnosed with prostate cancer (PCa) in the U.S. in 2021 and more than 33,000 men will die from this disease. Therefore, mCRPC is an unmet medical need and there is an urgent need to develop innovative therapeutics that would target immune suppressive TAMs that will enhance responses to therapies and benefit mCRPC patients. We sought to re-establish an anti-tumor immune response by targeting surface receptors on TAMs that help drive PCa progression. Using human PCa tumor microarrays, we published that the macrophage mannose receptor (CD206) increased during PCa progression to mCRPC. Our team then selectively targeted of CD206 using RP-182, a 10-mer amphipathic analog of host defense peptide that selectively induces a conformational switch of CD206 expressed on TAMs. RP-182-mediated induction of CD206 in human and murine TAMs elicits a program of endocytosis, phagosomelysosome formation, cancer cell phagocytosis, and reprograms immune-suppressive TAMs to an anti-tumor inflammatory phenotype. In syngeneic and autochthonous murine cancer models, RP-182 suppressed tumor growth, extended survival, and was an effective combination partner with chemo- or immune checkpoint therapy. In the proposed studies, we will evaluate the premise that CD206+ TAMs play an essential role in PCa tumor progression and therapeutic resistance. We hypothesize that the immune-suppressive CD206+ TAMs drive PCa resistance to immunotherapies and therapeutic inhibition of CD206+ TAMs will re-educate TAMs to the pro-inflammatory phenotype, enhance anti-tumor immune responses and will synergize with chemo- or immune checkpoint therapy. The specific aims of this proposal are: 1) Establish the contribution of CD206+ TAM function in PCa tumorigenesis and immune evasion; 2) Elucidate how inhibition of CD206+ TAMs may synergize wirh anti-PD- L1 to enhance anti-tumor immunity 3) Correlate CD206+ TAM infiltrate with Nivolumab response, PCa bone metastasis and patient outcomes. Utilizing a humanized mice and a novel syngeneic mCRPC mouse model in which tumors are heavily infiltrated with CD206+ TAMs and refractory to immune checkpoint therapy, we will characterize the changes in adaptive and immune responses after CD206 is inhibited both in vitro and in vivo. In the third aim, we will measure CD206+ TAM expression in human PCa from mCRPC bone and single-cell RNA sequenced PCa tumors from a Nivolumab clinical trial. Targeting CD206+ TAMs in syngeneic murine tumor models and patient-derived xenotransplantation models in humanized mice has great potential to alter the tumor microenvironment and enhance anti-tumor immune responses that may lead to novel therapeutics for mCRPC.

NIH Research Projects · FY 2026 · 2023-07

Project summary High-throughput molecular technologies are increasingly being used in biomedical and basic science. New tech- nologies and assays are being developed at a rapid pace, and have the potential to interrogate cellular processes at an unprecedented resolution and throughput. As a result of the developments in measurement technologies, more investigators in molecular biology are in need of statistical methods to analyze complex data. We have a track record of developing such methods and the R35 mechanism will provide us with the flexibility to pivot our effort as new molecular approaches are being developed. We will focus on methods for (1) measuring the shared molecular component between experiments, (2) differ- entiation and cell cycle measurements using single-cell RNA-seq, (3) detecting selection acting on molecular features such as DNA methylation, histone modifications and transcription factor binding, and (4) epigenomics assays including nanopore sequencing.

NIH Research Projects · FY 2024 · 2023-07

PROJECT SUMMARY The goal of this project is to provide the building blocks for an independent research program focused on the neural basis of reward-based memory across distributed brain networks. Humans and other animals experience events in the moments they occur while the brain has evolved powerful neural processes to re-activate the neurons encoding these events in the ‘time in-between’. Reactivation of task-relevant neuronal ensembles occur during both wake and sleep states, and enable the binding and compression of neuronal representations in a temporal window compatible with neuronal plasticity. The role of awake and sleep reactivations in supporting episodic, hippocampus-dependent memories is well established. However, reactivation have been reported to also occur beyond the hippocampus, in both cortical and subcortical structures, and in both hippocampal- dependent and -independent tasks. This leads to the exciting possibility that reactivations may be a fundamental mechanism underlying memory formation and consolidation, and that they occur brain-wide, distributed among regions encoding different modalities and variables. However, their role in cue-driven, goal-directed sensorimotor tasks remain largely unexplored and evidence of multiregional reactivations is weak, in part because of technical difficulty to investigate neuronal population activity across multiple simultaneously recorded brain circuits. This proposal aims at testing the role of multi-region neuronal reactivations during wake and sleep in forming and consolidating associative networks to support reward-based learning. In the K99 phase, Dr. Drieu will focus on the role of multi-regional reactivation in cue-guided, goal-directed learning. She will test the hypothesis that the simultaneous reactivation of stimulus-, action-, and reward-selective neurons across brain regions during the waking state forms associative networks (Aim 1) subsequently reactivated during sleep for consolidation (Aim 2). In the R00 phase, Dr. Drieu will address whether transient synchronous activity spanning multiple brain areas in different brain states participate in the transition from cue-driven, allocentric memories to egocentric memories (Aim 3). To achieve these goals, Dr. Drieu will perform high-density, multi-site neuronal recordings using Neuropixels 2.0 combined with advanced closed-loop optogenetic methods in freely moving rats. The technical and scientific skills that Dr. Drieu will develop during the training period of this project will not only be crucial for the accomplishment of her immediate scientific goals, they will also become the pillars for the research she will develop in her own independent laboratory in the field of reward-based learning and memory. This training will be complemented by intense career developmental activities and mentorship that will prepare her for the practical aspects of laboratory management, teaching and fund raising. Overall, Dr. Drieu’s future research will provide new insights into the neural mechanisms involved in memory formation. This will lay the groundwork to better understand whether and how these mechanisms go awry in pathologies associated with reward-related disorders such as addiction, and with memory deficits such as Alzheimer’s disease.

NIH Research Projects · FY 2025 · 2023-07

The application of modern machine learning algorithms in radiology continues to grow, as these tools represent potential huge improvements in efficiency, accessibility and accuracy of diagnostic and screening tools. At the same time, these increasingly complex machine learning models can result in predictions of different accuracies in different settings, such as those resulting from different imaging acquisition protocols, different imaging equipment, or different phenotypic tissue characteristic. Such lack of robustness of predictive models are particularly important in public health applications that focus on large scale population-based screening, as in cancer screening for breast and lung cancer. Thus, it is paramount to understand these sources of variability in machine learning screening algorithms, as well as developing methods to mitigate them. This proposal will develop tools to quantify, correct, and analyze the sources of prediction errors in algorithms in relation to different sources of variability in data acquisition in real world settings. In particular, we will develop analysis and algorithms to quantify the difference in predictive performance by a machine learning model in situations where information about the sources of variability itself (such as acquisition location, tissue characteristics, and acquisition protocols) are not directly observable, and we will provide algorithms that correct for their worst-case difference in predictive power. We will analyze our tools under distribution shifts, whereby differences across medical centers exist, as is common in large scale cancer screening programs. This project will also perform inference on the training samples and features most highly associated with difference in predictive power, thereby providing guidance on the development of solutions to prevent these limitations in the future. Our tools will be validated on a variety of large real-world radiology datasets spanning multiple imaging modalities, including general chest X-ray datasets that include lung cancer diagnoses (CheXpert and MIMIC-CXR), as well as the Emory Breast Cancer Imaging Dataset (EMBED) and the National Lung Cancer Screening Trial, evaluating and correcting disparities for predictive algorithms with different acquisition protocols, technical equipment, and data quality. The results of this project will establish critical knowledge about the propensity of machine learning models for medical imaging diagnosis to be sensitive to imaging settings, as well as foundational tools to quantify and mitigate these limitations in potentially game-changing technologies.

NIH Research Projects · FY 2024 · 2023-07

Early-stage and late-stage retinal progenitor cells (RPCs) selectively generate retinal neurons in discrete temporal windows over the course of retinal development. Müller glia (MG), and late-stage RPCs have similar gene expression profiles and express many shared transcription factors (TFs) that repress proliferative and neurogenic competence. Upon retinal injury, many of these TFs are downregulated in MG, while TFs that drive reactive gliosis are upregulated. This process is necessary to activate neurogenic competence in fish and amphibians. However, MG in mammals lack neurogenic competence, and TFs that maintain quiescence are rapidly re-expressed following injury. We have identified key regulators of proliferative and neurogenic competence in both RPCs and MG through multiomic analyses. I am now exploring the possibility that a single AAV-based reagent can be used to reprogram MG to early-stage RPC-like cells that generate early-born retinal cell types, including cone photoreceptors, in situ. I hypothesize that MG can be reprogrammed to gain proliferative and neurogenic competence in mammals by disrupting the function of TFs that promote late-stage RPC identity and are also expressed in adult MG. Furthermore, I anticipate that overexpression of TFs that promote early-stage RPC identity in MG-derived progenitors may promote generation of early-born retinal cell types (Fig 1B). Finally, by combining these overexpression and loss of function approaches with overexpression of TFs that promote photoreceptor specification, I expect to be able to generate substantial numbers of early-born cone photoreceptors. I propose two aims to address this hypothesis. Aim I: Alter retinal development trajectory and reprogram adult MG using overexpression of full-length and dominant-negative constructs of candidate TFs. Multiplexed single-cell (sc)RNA-seq analysis will be used to identify constructs that promote proliferative and neurogenic competence in electroporated late-stage RPCs and transduced adult MG. Immunohistochemistry will be used to validate findings from the scRNA-seq data. This aim will allow for the functional characterization of TFs that regulate the transition between early and late stages of developmental competence in RPCs, as well as the transition of MG from a quiescent to a neurogenic state. This aim will also identify constructs that promote the production of early-born cell types, including cone photoreceptors, in neonatal retinal explants and mature MG. Aim II: Overexpression of Prdm1 in reprogrammed adult MG to drive cone photoreceptor formation. Prdm1 is selectively and strongly expressed in photoreceptor precursors and stimulates photoreceptor differentiation. Overexpression of Prdm1 may induce reprogrammed MG to produce early-stage RPC-like cells that are neurogenic and specifically generate mature cone photoreceptors. This project has significant potential to contribute to the development of novel gene therapies for photoreceptor dystrophies, including age-related macular degeneration, Stargardt's disease, and retinitis pigmentosa.

NIH Research Projects · FY 2024 · 2023-07

PROJECT SUMMARY Genetic variation affecting gene expression level and splicing accounts for a large proportion of phenotypic variation between humans, including health and disease. The variants that underlie these phenotypic changes are often discovered by associating individuals’ gene expression data with their genotypes. These methods can be confounded by population structure in the sample, which leads to false positive and negative errors. As such, samples are often selected from relatively homogenous populations. However, this limits the applicability of results to populations not included in the study, and limits the resolution at which potentially causal variants can be identified. Previous work has shown that controlling for population structure locally across the genome in association studies of diverse samples serves to reduce error. However, these methods assign individuals to one of a few ancestral populations and do not fully capture the relatedness between included samples. To extend the results of association studies to diverse cohorts, I will develop a method to control for local relatedness between samples in association studies. The Ancestral Recombination Graph (ARG) is a data structure which encodes the genealogical relationships between samples at each locus along the genome. In Aim 1, I will develop a linear mixed model approach for association mapping that utilizes a similarity matrix derived from the ARG to control for local relatedness between samples. One barrier in extending the results of association studies investigating gene expression is that the majority of data currently available is from individuals of European descent. To address this limitation, I recently generated gene expression data for a large, globally diverse human sample. In Aim 2, I will use the method developed in Aim 1 to map expression level- and splicing-associated variation in this sample. I will then investigate enrichment of epigenomic features near associated variants to determine the functional mechanisms by which they may be driving transcription differences, and I will intersect my findings with previously discovered disease associations. Using this globally diverse dataset, I will also explore the diversity and evolution of human gene expression, elucidating the extent to which patterns of gene expression are partitioned within versus between populations and the sources of such stratification. Extending association studies to diverse cohorts requires not only diverse datasets, but also tools that can appropriately control for patterns of population structure within those datasets; the research proposed here addresses both goals. This will allow the discovery of associations in previously underrepresented groups and will also serve to improve confidence in discovering causal variants. Together, this proposed work will characterize the functional mechanisms linking genetic variation and phenotypic differences in a globally diverse human cohort.

NIH Research Projects · FY 2025 · 2023-07

Project Summary Bladder cancer is the sixth most common cancer in the United States, and according to some studies, the most expensive cancer to manage per patient lifetime. But current screening tests have low sensitivity, high cost, or require invasive procedures, presenting a barrier to the early detection this disease. In prior work, I led a team showing that next-generation sequencing of bulk urinary DNA can serve as a sensitive and specific method for the noninvasive detection of bladder cancer. I now seek to build on this work by addressing three major obstacles to the use of urinary tumor DNA as a biomarker in a screening context: 1) Most patients referred for bladder cancer screening present with hematuria, or blood in their urine. This results in the dilution of tumor DNA by leukocyte DNA and decreased sensitivity of sequencing-based assays. 2) Bulk sequencing of urinary DNA may detect mutations in cell types that do not give rise to bladder tumors (e.g. clonal hematopoiesis), thereby decreasing assay specificity. 3) The high cost and complexity of next-generation sequencing methods limits their accessibility. This proposal seeks to overcome all three obstacles, creating a practical, high performance diagnostic workflow for bladder cancer screening. In Aim 1, I will refine a novel method for the enrichment of urothelial cells from voided urine, called Cell Enrichment by Size and Selective Lysis (CESSL). Using urine samples from patients with known bladder tumors, I will then investigate the achievable degree of tumor cell enrichment and generalizability of CESSL using sequencing and microscopy. Depletion of non-urothelial cells from urine will improve the sensitivity and specificity of downstream assays in the population that presents for screening. In Aim 2, I will develop a flow cytometry assay for the detection of bladder tumor cells in urine based on the presence of aneuploidy and/or global hypomethylation, two DNA aberrations that are present in >90% of bladder tumors and highly specific for cancer. I will then determine the analytical and clinical performance characteristics of this assay, as well as the impact of CESSL on its performance. This proposal will be carried out at the Johns Hopkins Hospital under the mentorship of Bert Vogelstein, MD. It will be guided by a scientific advisory board including experts in pathology, urology, medical oncology, biostatistics, and flow cytometry. Through completion of this proposal, I will develop new skills in cell-based diagnostic methods, diagnostic study design, and laboratory management. My goal is to become an independent laboratory-based physician-scientist who develops novel molecular and cell-based diagnostic tools for solid tumor pathology specimens and evaluates their utility in clinical trials. Successful completion of this study will produce novel methods that I can refine and apply to other pathology sample types in my future laboratory, as well as the data necessary to initiate a prospective study of our assay for bladder cancer screening, forming the basis of an R01 application.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY/ABSTRACT – JOHNS HOPKINS ERC OVERALL Situated in the largest, most highly ranked school of public health in the world, the Johns Hopkins Education and Research Center for Occupational Safety and Health has a mission to provide cutting-edge interdisciplinary academic and research training and continuing education in occupational safety and health and to serve the needs of federal region III (Maryland, Washington, D.C., Virginia, West Virginia, Delaware, and Pennsylvania), as it has done for the past 45 years. The overarching goal of the Johns Hopkins ERC is to build critical capacity in (a) trained personnel in key areas of occupational safety and health through multidisciplinary education and training, (b) improved skills and knowledge of practicing occupational safety and health professionals through continuing education programs, and (c) occupational safety and health research, with the ultimate goal of protecting the safety and health of all workers. Interdisciplinary training is offered to masters’ and doctoral students in Occupational and Environmental Hygiene, Occupational Injury Epidemiology and Prevention, Occupational Epidemiology and Biomarkers, and Occupational Health Psychology, as well as to through our Occupational and Enviornmental Medicine Residency. The ERC aims to increase the knowledge, skills, and abilities of practicing occupational safety and public health professionals to function effectively in complex occupational settings, and to meet community needs by developing and supporting continuing education and outreach activities, including short courses, online educational modules, seminars, and conferences. The ERC also aims to enhance the research training capacity within our region by funding novel pilot projects with an emphasis on creative exploratory prevention/intervention and translation projects that are relevant to the National Occupational Research Agenda. Since its establishment in 1977, the Johns Hopkins ERC has evolved in response to changing demands in the field, as well as to scientific and technological advances that impact occupational safety and health practice, research, and education, while retaining steadfastly its commitment to an integrated, interdisciplinary approach to training researchers and practitioners. Each year, our Center’s Outreach and Continuing Education efforts serve hundreds of organizations within our region alone, including private-sector businesses (e.g., pharmaceutical, poultry, healthcare, food), nonprofit and academic organizations, government agencies (local, state, federal), and the military. The outcomes enabled by the JHU ERC include: (1) our highly trained ERC graduates are placed in relevant occupational safety and health positions in industry, academic institutions, government, health care, and professional associations, and our alumni make exceptional and significant contributions to research-to- practice efforts in the field of occupational safety and health; (2) skills enhancement for occupational safety and health professionals who are prepared to address emerging threats to workforce health; and (3) research results disseminated to key stakeholders through publications, presentations, and outreach.

NIH Research Projects · FY 2024 · 2023-07

PROJECT SUMMARY/ABSTRACT Background. Type 2 diabetes (T2D) disproportionately affects American Indian and Alaska Native (AI/AN) communities, with even greater burden on under-resourced urban AI/AN communities. Past research has shown that nutrition is deeply important for prevention of T2D, yet achieving proper nutrition requires a healthy mental relationship with eating, something that may be difficult to achieve for many AI/ANs who experience a disproportionate burden of mental illness. A promising intervention for improving holistic wellbeing is Intuitive Eating (IE), an adaptive eating style that utilizes aspects of positive psychology to promote connection to internal physiological cues to hunger and satiety. IE is a promising intervention for improving psychological relationships with food, eating behaviors, and mental health but to date there have been no efforts to assess IE’s compatibility with AI/AN cultural food values or the acceptability of IE to AI/AN communities. Study Goals and Aims. The candidate will collaborate with two urban AI/AN communities in Minneapolis and Baltimore to conduct an Exploratory Sequential Mixed Methods Community-Based Participatory Research (CBPR) study. Specific aims are to: 1) qualitatively explore AI/AN cultural eating values and perceptions of IE; 2) Culturally adapt the Intuitive Eating Scale 2 (IES-2) for urban AI/AN cultural and social contexts using community engaged participatory methods; and 3) Examine construct validity of the adapted IES-2 through factor analysis and its associations with health outcome data. Approach. Aim 1 of the study will utilize in-depth interviews with 30-40 urban AI/ANs to explore cultural eating values, eating behaviors, and perceptions of IE. This qualitative data will be analyzed using an inductive approach to gain a nuanced understanding of cultural eating values and eating behaviors within urban AI/AN communities. Aim 2 will utilize CBPR methods to engage community research councils (CRCs) in the integration of Aim 1 findings into the IES-2. Aim 3 will involve pilot testing the adapted measure alongside relevant health data with 250 AI/AN adults. Confirmatory Factor Analysis will be used to examine the construct validity of the adapted IES-2. Secondarily, multiple linear and logistic regression will be used to assess relationships between intuitive/cultural eating values and health outcome data (mental health, cultural connectedness, fruit/vegetable intake, physical activity). Fellowship Information. The proposed NRSA research will serve as the doctoral dissertation of Ms. Maudrie, an American Indian PhD student at the Johns Hopkins Bloomberg School of Public Health, her research and training are supported by a mentorship team of AI/AN health experts. This NRSA research builds upon the candidate’s previous CBPR research with urban AI/AN communities and is aligned with the NIDDK’s mission to improve the prevention of T2D & advance health equity for a high priority population (Urban AI/ANs).

NIH Research Projects · FY 2025 · 2023-07

SUMMARY: Despite substantial progress in clinical approaches to squamous cancer of the esophagus (ESCC), which causes most esophageal cancers (EC) in the world, this deadly tumor usually occurs at late disease stages, with very poor survival. Restricted availability of endoscopy (EGD), along with rarity and delays in histology, impairs detection of ESCC in LMICs, adversely impacting our ability to treat this disease effectively. Thus, in LMICs, inexpensive, safe, locally performable strategies for detecting ESCC are necessary to identify high-risk patients and refer them quickly to suitable diagnostic and therapeutic options. Therefore, a diagnostic approach featuring a retrievable swallowed sponge-on-a-string to gather esophageal specimens for molecular testing, combined with a point-of-care (POC) magnetofluidic chip for sample processing and DNA methylation detection, is proposed. The string-sponge is less expensive, more noninvasive, more convenient, and more rapid than EGD with biopsy. The magnetofluidic chip streamlines DNA purification, DNA bisulphite treatment, and PCR detection of methylation markers into a single POC apparatus. This approach does not necessitate EGD, can be performed in remote areas with portable energy supplies and does not require extensive medical training, and is thereby amenable to implementation in LMICs. Our Specific Aims are: 1: Using a sponge-capsule swallowed/tethered collection device, to construct a methylation marker-based strategy to detect ESCC. In 100 ESCC and 100 benign control patients, we propose (1) building a multivariate model containing biomarker candidates; (2) carrying out feedback-feasibility meetings with health care and endoscopy personnel at Makerere University Hospitals to fine-tune eventual POC usage; 2: In order to achieve a sample-to-answer assay, to implement DNA extraction, bisulfite treatment, and methylation-specific PCR into a magnetofluidic chip with dried reagents. We’ll use magnetofluidic techniques to streamline cell lysis, DNA extraction, bisulphite treatment, and methylation-specific PCR into a compact chip built from cheap thermoplastic materials. In addition, we’ll lyophilize reagents and use heat- deployed wax sealant plugs to permit storage at room temperature. In this fashion, we will fashion a sample-to- answer assay that is easy to use, inexpensive, and free of cold-chain steps; 3: In order to achieve fully automatic high-speed biomarker assaying, to design a small, light apparatus. We’ll engineer an instrument containing programmable magnetic actuation, temperature control, and detection of fluorescence to execute the test in a chip with very little user input. We’ll also design the apparatus to be small, light, easy to operate, portable electricity-powered, and mobile phone-controlled to ease integration with LMIC-based clinical tasking; and 4: Using our POC approach to carry out a diagnostic pilot study of ESCC in Uganda. While applying the magnetofluidic chip and apparatus used in Aim 2 and Aim 3, we’ll carry out a trial to measure specificity and sensitivity in 120 EGD-confirmed cases of ESCC and 360 benign disease control patients in Kampala, Uganda.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY The exposed epithelial surfaces of the body, including the skin, gut, female reproductive tract, and airways, are colonized by microorganisms that contribute to homeostasis and disease. While the resident microbiota has been extensively characterized in many of these sites, the ocular surface microbiome is relatively understudied. The use of metagenomic sequencing approaches has facilitated moving beyond targeted culturing approaches to more fully characterize the breadth of organisms present in a specimen. However, the relative microbial biomass at the ocular surface is much lower than other mucosal surfaces, such as the gut. Metagenomic characterization of low microbial biomass specimens presents numerous challenges, as sources of contamination not only arise during the sampling procedure and from the environment itself, but even from laboratory processing methods. As a result, the lack of protocol standardization and omission of key controls for sources of contamination limits the interpretation and potential for comparison across studies. To address these challenges, we have assembled a large multidisciplinary team of experts in topics including (i) development of standardized protocols and clinical validation of diagnostic tests utilizing metagenomic sequencing for low biomass biospecimens, (ii) development of open source metagenome analysis tools, (iii) clinical assessment of ocular surface and external eye findings among a large, diverse patient population, and (iv) wet lab characterization of microbes under strict cleanliness guidelines. We previously described the use of metagenomic sequencing to detect the presence of pathogens in biopsies from the brain, paraffin embedded ocular tissue specimens, and cerebral spinal fluid (CSF). By comparing a range of specimen pre-treatment and processing approaches and sophisticated software tools, we were able to optimize the methods to maximize organism detection and minimize or remove contamination. We validated our metagenomic sequencing and analytical approaches to the rigor required for use as a diagnostic test. Here, we hypothesize that following similar approaches with low microbial biomass ocular specimens will facilitate the characterization of the healthy ocular surface microbiome. In Aim 1, we will compare specimen processing approaches and validate our analytical methods. In Aim 2, we will compare specimen collection approaches, including collection materials and procedures. We will then use our optimized specimen collection and processing approaches to collect ocular specimens longitudinally for characterization of organism persistence. In Aim 3, we will identify a subset of participants with persistent and/or unique organisms to collect additional specimens for validation of composition and characterization of viability. Upon study completion, we will have contributed to the characterization and understanding of the healthy ocular surface microbiome, and developed protocols, analytical tools, and datasets that will be made publicly available.

NIH Research Projects · FY 2025 · 2023-07

Enter the text here that is the new abstract information for your application. This section must be no longer than 30 lines of text. Project Summary Training at the chemistry biology interface at Johns Hopkins University will be made possible by an independent Ph.D.-granting program that will nucleate a vibrant community of 31 faculty spanning 4 schools and 9 departments. Together, these faculty share a common approach of applying chemical principles and methods to problems of profound importance to biology and medicine. The program offers opportunities to develop research skills applicable over a wide range of dimensions, from single molecules to complex macromolecular assemblies to whole cells. Laboratories are well-funded and focus on mentoring graduate students in rigorous, ethical and independent design and interpretation of experiments in preparation for leadership roles in biomedical research. The highly collaborative nature of Johns Hopkins provides students with access to many faculty and a robust infrastructure of instrumentation and expertise. Prospective students will be actively recruited from across the country to generate a highly qualified pool of applicants that draw from small colleges to large universities. A target of seven students will matriculate annually with support from the training grant. A matching number of positions will be provided by the university to support students in their second year before obtaining fellowships and assistantships for the remainder of the program. Annual cohorts will share a common core curriculum created to reinforce a strong foundation in chemistry while building an aptitude for the biological sciences through a rich selection of electives. A series of three laboratory rotations across different departments will ensure a breadth of experience in research prior to selection of a thesis advisor. Students will join together monthly for meetings on research and professional topics and yearly for student-hosted seminars and a retreat. Training progress of each student will be monitored carefully by a thesis committee to assure a growing proficiency in independent and reproducible experimental design, keen observation, precise data analysis and critical interpretation. Professional development will be enriched by a new course in literature evaluation, proposal writing and public presentation and another course on career planning. The goals of this train program foster original research contributions of high impact while preparing young scientists for sustained success in their chosen career related to research.

NIH Research Projects · FY 2025 · 2023-07

The Johns Hopkins Predoctoral Training Program in Human Genetics (HG) has long been a nationally preeminent training environment for human genetic research. It has grown steadily since its inception (1980) in parallel to the explosive growth of genetics and genomics, and their application to medicine. Although supported by preceptor faculty across 20 departments, the HG has its administrative and philosophical home in the McKusick-Nathans Department of Genetic Medicine (DGM). Eighty faculty mentors engage in training our current cohort of sixty-one students. The preceptors’ research includes human and model organism genetics and genomics, study of genes and variants underlying human monogenic disorders and complex traits, quantitative genetics, gene therapy, oncogenetics, stem cells, technology development, big data and machine learning. An average of 12 students graduate each year and obtain their PhD in 5.3 years (average). The objectives of the HG program are: (1) to provide a biomedical curriculum with breadth and depth; (2) to ensure an understanding of the fundamental roles of genetic variation in human biology, and disease; (3) to provide robust training in rigorous, reproducible, responsible, and ethical research; (4) to equip our trainees with relevant professional skills and the opportunity to explore career options; and (5) to foster a supportive training environment. In the first year, we introduce students to the evolving concepts of the gene, molecular biology, genomics, cell structure and dynamics, pathways and regulation, extending deeper with advanced topics in human genetics. We introduce a new computational bootcamp to provide fundamental computational and statistical skills, a theme that is iterated throughout their courses. In their second year we have developed two highly innovative courses: Systems, Genes and Mechanisms in Disease and Genomic Technologies Applications and Considerations. The courses integrate didactic presentation with student-led seminars, team-based problem solving and discussion, placing their genetic training in a human biological and pathological context and equipping them for the design and implementation of contemporary genomic experimental strategies. We provide training in rigorous and ethical experimental design and implementation, and career planning and professional development through workshops, internship opportunities and required courses. Our preceptors receive mentoring training; are appropriately mentored; and they are accountable. The overall goal of our HG program is to educate the next generation of leaders in human genetics. We seek to train independent scientists who are passionately curious about the role that genetic variation plays in the human condition. This education prepares our students to answer important basic science questions and to translate this information into bio-medical advances. The success of our graduates, in pursuing academic careers, roles in government, private sector research, or using genetics in law and public policy supports this. We request 14 training grant slots to support training grant eligible students during their first year in the program.

NIH Research Projects · FY 2024 · 2023-07

Proposal Summary Protective factors across the life course can have profound effects on individual health. It has been well established that adverse childhood experiences and lifetime exposure to discrimination and victimization have negative mental and physical health effects. For women who are Black and transgender, adversity can be compounded by the intersectional impact of racism and gender-based discrimination. A constellation of interpersonal protective factors throughout the lifespan, including positive childhood experiences, family acceptance, and social support, may help to improve mental health outcomes among individuals as they experience adversity throughout the life course. Additionally, mental health symptom self-management may moderate the relationship between Black transgender women's experiences with protective factors and current psychological distress symptoms. Self-management, defined as drawing upon one's own ability to promote health or manage disease, may be instrumental in improving mental health outcomes and could be vital for this population due to significant known barriers to healthcare engagement. However, there is limited exploration of protective factors and self-management on mental health outcomes among Black transgender women. To address this gap, a convergent mixed-methods study is proposed to increase our understanding of how protective factors are associated with mental health self-management and psychological distress among Black transgender women. This training grant, nested within a larger parent study, takes a strengths-based approach to examine complex relationships between the variables of interest. The specific aims are: Aim 1. Determine the associations among interpersonal protective factors (i.e., positive childhood experiences, perceived family acceptance, and current social support) and current symptoms of psychological distress for Black transgender women (N=150). Aim 2. Determine the role of mental health self-management in moderating the associations between interpersonal protective factors, symptoms of depression, and symptoms of PTSD. Aim 3. Use thematic content analysis of in-depth interviews with 30 Black transgender women from Aim 1 to analyze how interpersonal protective factors influenced Black transgender women's abilities to self-manage psychological distress symptoms. Findings will inform future recommendations for interventions aimed at decreasing the harmful effects of adversity and discrimination for racially diverse transgender youth and adults.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY/ABSTRACT It is unknown why some patients regain their pre-morbid health following appropriate treatment for Lyme disease while others progress to develop post-treatment Lyme disease (PTLD). Significant prior published and preliminary data suggest that variability in clinical, immunologic, and metabolic factors at the onset of infection with B. burgdorferi contribute to the development of divergent post-treatment outcomes, including PTLD. In this study, we will draw upon unique cohorts of patients with well-defined PTLD, healthy controls without a history of Lyme disease, and patients with early Lyme disease followed longitudinally up to 1 year after the end of treatment. Combining advanced, innovative statistical and laboratory methods, the objective of this grant is to identify these factors and examine how they relate to underlying symptom phenotypes among patients with PTLD. To accomplish this goal, we will identify clinically-relevant risk factors associated with post-treatment outcomes in Lyme disease over time. These factors will then be used to develop an assessment score to identify patients at increased risk of developing PTLD in the clinical setting (AIM 1). A longitudinal, multivariate, cross- domain analysis of this sort with the goal of direct translation of findings to clinical practice and the study of fundamental disease pathways in PTLD has not previously been performed. We will also identify novel auto- antibodies that are associated with PTLD through protein array, and examine their relationship with underlying clinical phenotypes (AIM 2). While an autoimmune process has been suspected to underlie the pathogenesis of PTLD, at least for some individuals, adaptive immune recognition of self-antigens is only beginning to be described. Discovery of autoantibodies in PTLD may reveal patient subsets marked by specific clinical features, such as predominant musculoskeletal pain or neurologic symptoms, and identify individuals whose disease is driven by an autoimmune process. Finally, we will study the longitudinal immunometabolic profile of patients with differing clinical outcomes using a novel, high-dimensional flow cytometry approach, and hypothesize that pharmacologic manipulation of perturbed pathways in vitro may be able to normalize a PTLD-associated metabolic signature (AIM 3). The ability of immunometabolism to globally report on the acute cellular environment suggests that interrogating immune cell metabolism in individuals develop PTLD in the future could provide fundamental insights into disease mechanism. Collectively, our studies represent a rigorous approach towards uncovering determinants that are associated with the outcome of PTLD and its underlying clinical phenotypes. The long-term goal of this project is to generate fundamental knowledge to inform the development of innovative therapeutic strategies as well as novel interventions to prevent or reduce the often significant symptom burden and functional impact of PTLD.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY This is a proposal for a five-year career development program to study hormonally-determined metabolic programs as therapeutic targets for prostate cancer. The candidate is currently an Instructor of Oncology at Johns Hopkins University School of Medicine. The proposal builds on the candidate’s previous research and clinical experience and integrates two distinct areas of expertise of her mentors, Dr. Samuel Denmeade and Dr. Erika Pearce, to understand metabolic vulnerabilities induced by high dose androgen in prostate cancer. In spite of recent advances in prostate cancer therapy development, this disease continues to kill more than 350,000 men per year worldwide. Standard-of-care therapies inhibit androgen receptor (AR) signaling, which often leads to adaptive upregulation of AR to drive resistance. We have shown that this upregulation of AR constitutes a vulnerability to high dose androgen and are developing a novel therapy called Bipolar Androgen Therapy (BAT) in which high dose androgen is provided intermittently to result in cycling of serum androgens to minimize adaptations to high or low levels of androgens. To date, our clinical trials indicate that BAT is safe, improves quality of life, and can induce responses in a subset of patients for whom there are very limited therapeutic options. We are now seeking to expand the population of patients who benefit from BAT by identifying metabolic synthetic lethal vulnerabilities induced by exposure to high levels of androgens in the initial phase of BAT. This proposal focuses on identifying metabolic vulnerabilities because (1) a fundamental effect of androgens across numerous tissues in the body, including benign and malignant prostate, is alteration of cellular metabolism and (2) metabolic plasticity is an emerging common pathway of resistance to cancer therapies. Our preliminary data using global metabolomics and a metabolism-focused CRISPR-based genetic screen indicate that high dose androgen dramatically reprograms prostate cancer metabolism resulting in vulnerabilities including de novo polyamine synthesis and nucleotide synthesis. Specific aims proposed will interrogate synthetic lethality of high dose androgen in combination with inhibition of polyamine synthesis (Aim 1) and with inhibition of nucleotide synthesis (Aim 2). Aim 3 will assess efficacy of combination therapies across a highly characterized panel of patient-derived xenograft models of castration-resistant prostate cancer that approximate the diversity of patients with this disease. The outlined career development and research plan will provide the candidate with unique cross-disciplinary skills that will enable her transition to independence as a physician scientist and identify promising combination therapies for treatment of patients with castration-resistant prostate cancer.

NIH Research Projects · FY 2026 · 2023-07

PROJECT SUMMARY The goal of this project is to provide the building blocks for an independent research program focused on the neural basis of reward-based memory across distributed brain networks. Humans and other animals experience events in the moments they occur while the brain has evolved powerful neural processes to re-activate the neurons encoding these events in the ‘time in-between’. Reactivation of task-relevant neuronal ensembles occur during both wake and sleep states, and enable the binding and compression of neuronal representations in a temporal window compatible with neuronal plasticity. The role of awake and sleep reactivations in supporting episodic, hippocampus-dependent memories is well established. However, reactivation have been reported to also occur beyond the hippocampus, in both cortical and subcortical structures, and in both hippocampal- dependent and -independent tasks. This leads to the exciting possibility that reactivations may be a fundamental mechanism underlying memory formation and consolidation, and that they occur brain-wide, distributed among regions encoding different modalities and variables. However, their role in cue-driven, goal-directed sensorimotor tasks remain largely unexplored and evidence of multiregional reactivations is weak, in part because of technical difficulty to investigate neuronal population activity across multiple simultaneously recorded brain circuits. This proposal aims at testing the role of multi-region neuronal reactivations during wake and sleep in forming and consolidating associative networks to support reward-based learning. In the K99 phase, Dr. Drieu will focus on the role of multi-regional reactivation in cue-guided, goal-directed learning. She will test the hypothesis that the simultaneous reactivation of stimulus-, action-, and reward-selective neurons across brain regions during the waking state forms associative networks (Aim 1) subsequently reactivated during sleep for consolidation (Aim 2). In the R00 phase, Dr. Drieu will address whether transient synchronous activity spanning multiple brain areas in different brain states participate in the transition from cue-driven, allocentric memories to egocentric memories (Aim 3). To achieve these goals, Dr. Drieu will perform high-density, multi-site neuronal recordings using Neuropixels 2.0 combined with advanced closed-loop optogenetic methods in freely moving rats. The technical and scientific skills that Dr. Drieu will develop during the training period of this project will not only be crucial for the accomplishment of her immediate scientific goals, they will also become the pillars for the research she will develop in her own independent laboratory in the field of reward-based learning and memory. This training will be complemented by intense career developmental activities and mentorship that will prepare her for the practical aspects of laboratory management, teaching and fund raising. Overall, Dr. Drieu’s future research will provide new insights into the neural mechanisms involved in memory formation. This will lay the groundwork to better understand whether and how these mechanisms go awry in pathologies associated with reward-related disorders such as addiction, and with memory deficits such as Alzheimer’s disease.

NIH Research Projects · FY 2025 · 2023-07

Overweight and obesity are highly prevalent in the U.S. and are associated with increased breast cancer risk, reduced treatment efficacy, and increased risk of recurrence, medical comorbidity and mortality. Breast cancer survivorship is increasing, and is associated with weight gain, increased fat mass, insomnia, and disease risk, making breast cancer survivorship a major healthcare priority. Weight loss is a standard treatment guideline for individuals with breast cancer with overweight/obesity; however, achieving clinically significant and sustained weight loss is challenging in general, and particularly for those who have undergone breast cancer treatment. While several trials have tested the effects of behavioral weight loss (BWL) in breast cancer survivors, a significant percentage of patients do not achieve clinically significant weight loss. Insomnia disorder is also highly prevalent in individuals with breast cancer and, like obesity, predicts breast cancer risk, progression and death. Research demonstrates that inadequate sleep may directly contribute to obesity and impair weight loss efforts via many behavioral and biological pathways. Several studies demonstrate that cognitive-behavioral therapy for insomnia (CBT-I) is efficacious in treating breast cancer survivors. One approach that has yet to be tested in a large scale study, however, is adding an intervention to improve sleep quality before a BWL intervention. Our preliminary data suggest that CBT-I may enhance weight loss outcomes in women with early stage breast cancer (ESBC). Although the complex, inter-related mechanisms linking sleep, obesity and dietary/physical activity behaviors are only beginning to be explored, we hypothesize that improving insomnia will catalyze weight loss efforts and enhance the effects of BWL on dietary and physical activity behaviors. We propose a randomized controlled clinical trial to test whether a 6-session CBT-I intervention delivered over 8-weeks combined with a one-year BWL intervention (CBT-I+BWL) delivered via telehealth (audio-video) is superior to a sleep education control condition (EDU) combined with BWL (EDU+BWL) among 250 adult female survivors of ESBC who are overweight or obese and have insomnia. Assessments will be conducted at randomization, after CBT-I/EDU, and at 3-, 6-, and 12-months of BWL. We have the following aims: Aim 1: Evaluate the short (3 mo), intermediate (6 mo), and long-term (12-mo) effects of CBT-I+BWL compared to EDU+BWL on weight loss (% TWL 12-months, primary) and body composition (secondary). Aim 2: Evaluate the extent to which 12-month weight loss is mediated by pre to post sleep treatment changes in sleep parameters (Sleep Efficiency, SE; Total Sleep Time, TST). Exploratory Aim 3: Determine whether CBT-I+BWL alters caloric intake, diet quality and/or physical activity relative to EDU+BWL and evaluate the extent to which these factors are associated with sleep continuity and weight loss at 3, 6 and 12-months. This novel approach to addressing sleep disturbances in weight loss treatment has the potential to substantially impact the treatment of obesity and to advance the management of survivors of ESBC.

NIH Research Projects · FY 2026 · 2023-07

ABSTRACT People with opioid use disorder are often forced to undergo withdrawal during incarceration due to lack of opioid treatment in custody, contributing to their elevated risk of drug overdose and other negative health outcomes in the weeks after release. Providing access to medications for opioid use disorder (MOUD) in correctional settings is a promising strategy to reduce overdose risk, but jails have not widely adopted this strategy. Achieving maximal public health benefits will require that MOUD programs are adopted across local jails that vary substantially in their resources and capacity and that jails ensure transition to treatment providers in the surrounding community after release. In 2019, the Maryland legislature passed the first U.S. law requiring all local jails in the state to provide all forms of MOUD and create linkages to care after release. The legislation created a phased implementation of the program starting in 2020. The staggered implementation presents a natural experiment to evaluate how the implementation of the programs in jails affect a variety of post-incarceration outcomes overall, and across different facilities and local environments. We propose a mixed-methods evaluation of the Maryland law. Aims 1 and 2 will analyze a data warehouse that links statewide correctional records, hospital, prescription monitoring program, behavioral health, and medical examiner data. Aim 1 will consider overall impacts of exposure to the jail MOUD program using non-experimental methods that compare changes in post-release outcome before and after jails implement the program. Aim 1B will use implementation measures reported to the state to assess whether outcomes differ in jails with high versus low levels of implementation based on monthly reports of program participation. Aim 2 will examine assess the contribution of variables at the individual and community level (e.g., social stressors, access to treatment) to explore the contribution of geography to heterogenous outcomes. Aim 3 will provide complementary implementation evidence focusing on 8 jails. We will conduct in-depth, semi-structured interviews with 40 program leaders (e.g., jail staff, community providers) and 40 formerly incarcerated individuals to explore barriers and facilitators to providing MOUD in jail and post-release. Together, study Aims will provide new evidence about how statewide jail initiatives may increase MOUD and improve health among people leaving jails. This information can guide future efforts in jails in Maryland and other states.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY Cardiovascular disease (CVD) is the leading cause of death among kidney transplant (KT) recipients with a functioning allograft. KT patients face a 3- to 5-fold higher risk of CVD morbidity and mortality than the general population, and within three years of kidney transplantation, 11% of these patients will have had a myocardial infarction. Evidence suggests that this increased risk is driven by multiple intersecting pathways contributing to CVD, including the metabolic side-effects of immunosuppression medications, a history of chronic kidney disease and volume overload, current allograft function, chronic and acute inflammation, and socioeconomic factors such as housing and income. Despite this, a KT-specific CVD-risk prediction model incorporating known risk factors has not been developed. Existing datasets lack the ability to capture granular CVD events, fully characterize contributions of longitudinal biomarkers, or incorporate traditional, transplant-specific, and socioeconomic factors in their risk estimation. Furthermore, current studies predict disparate composite CVD outcomes confusing the interpretation of predicted risk and highlighting the lack of a standard CVD outcome to assess burden in this population. Finally, beyond potential risk miscalculation, existing models remain largely unused in the clinical setting as they require manual input of data into an online calculator. To address this, we have leveraged a unique health records platform within our institution to identify a cohort of KT patients and retrospectively capture their highly granular longitudinal data to assess CVD risk. We have successfully used this platform to build risk prediction models for two other patient populations and embedded clinical tools into the health record for use in real time. Thus, my proposed research strategy is to 1) quantify the cumulative incidence of CVD events in our KT population and define the optimal compositive outcome to assess meaningful risk, 2) identify and characterize risk factors associated with CVD after KT accounting for time-varying disease states, longitudinal biomarker trajectories, and socioeconomic factors, and 3) implement and pilot-test an individualized CVD-risk prediction tool embedded in our health record. The proposed work will generate a comprehensive and transportable risk-prediction tool specific to the KT population with implications for dissemination across multiple institutions. Our findings will allow patients and providers to engage in shared decision-making and identify targets of intervention that will ultimately improve outcomes in this unique population. This work will be immediately applicable to KT patients burdened with excessive CVD risk and their physicians who must optimize the balance between maintaining allograft health and minimizing cardiovascular disease.

NIH Research Projects · FY 2026 · 2023-07

Project Summary Memory systems evolved to inform the continual learning and decision making of organisms as they explore and engage with an enormously complicated world. Humans in particular have a remarkable ability to recount complex sequences of events: we can easily reconstruct a narrative about the past hour or day purely from memory. In such real-world remembering, semantic and causal associations become exceedingly important, defining a web of relational connections across time to guide recall. For example, your day might contain two "hub" events: a dinner party that requires visiting several shops to pick up supplies, and a morning phone call saying that your child has a fever and needs to go home; each spawns a multitude of events that make up your day. Rich associations among these moments form an “event network” whose local and global properties shape recall; your decisions guide how each event will unfold. While studies show that relations between simple items are important for memory organization and its accompanying neural computations, no existing models consider the higher-order structure of networks composed from inter-related naturalistic events. Even among naturalistic studies, most use passively-viewed movies or stories; participants have no choices to make or goals to pursue. This lack of attention to the higher-order network properties and volitional aspects of real- world experiences has hindered efforts to identify the cortical dynamics that underlie ecologically meaningful memory processes. We seek to understand how memory encoding and retrieval of realistic events is implemented, in terms of cortical representations and interactions between brain systems. Doing so requires paradigms with two critical attributes. First, the stimuli must be sufficiently complex. Memory researchers have long focused on reductive scenarios with isolated stimuli that intentionally destroy semantic and causal connections. In contrast, our experiments use realistic events that are richly associated with each other and will naturally generate a diversity of event network structures. Second, participants must take an active role in creating their memories. Organisms in the real world can volitionally interact with their input stream: at a crowded party, you can choose to explore the kitchen or the living room, talk to the biologist or the musician, leave early or stay until dawn. We will test how participants' volitional behaviors, as they interact with and actively seek information about their environment, shape event networks and neural representations of events. Altogether, these experiments will provide novel frameworks and tools to examine how emergent higher-order structure in natural experiences governs the neural mechanisms underlying encoding and recall. By advancing the level of ecological validity and stimulus complexity in human memory research, we expect to help uncover brain-behavior relationships not apparent in simpler paradigms, and increase the translatability of laboratory findings to real-world applications.

NIH Research Projects · FY 2025 · 2023-07

SUMMARY Glioblastoma is the most common primary brain tumor with substantial genomic, molecular and phenotypic heterogeneity, but uniformly dismal outcomes despite the current standard treatment of concurrent temozolomide chemo-radiotherapy (CRT). Given the pace of disease recurrence and the challenges associated with obtaining tumor tissue, there is an unmet clinical need for the real-time, noninvasive assessment of GBM responsiveness to CRT. As demonstrated previously, most cancers shed tumor-derived fragmented DNA into biofluids, including plasma and cerebrospinal fluid (CSF), and these cell-free molecules can be quantified as a measure of disease burden. The approach, named “liquid biopsy”, has recently emerged as a breakthrough diagnostic and monitoring tool for diseases such as cancer, with the added benefit of being minimally invasive. Through the sampling and analysis of biofluids, a number of promising glioma biomarkers, derived from tumor-derived DNA in plasma (ctDNA) and CSF (CSF-tDNA) (together called rtDNA), have been reported as diagnostic strategies for gliomas. Meanwhile, numerous previous studies have demonstrated that protein-based amide proton transfer (APT) MRI can accurately identify tumor burden and genetic markers (such as IDH, MGMT status) in gliomas. The goals of this proposal are to combine ctDNA and CSF-tDNA with APT MRI to resolve the diagnostic challenges associated with discriminating treatment effect from tumor progression and to develop an efficient and reliable deep-learning framework for post-treatment monitoring. We propose the following specific aims to be performed: (1) correlate ctDNA and CSF-tDNA levels with protein-based APT MRI characteristics when monitoring GBM treated with CRT; (2) determine the accuracy of combined rtDNA/APT indices in identifying GBM recurrence; and (3) develop a transformer pipeline using rtDNA and mpMRI to assess GBM prognosis. The success of this aim will help to understand the dynamic patterns of rtDNA/APT throughout the treatment course for individuals with GBM. If our rtDNA/APT investigation is successful, the results would dramatically improve the care of patients treated with CRT and spare many patients from undergoing surgery for diagnostic purposes.

NIH Research Projects · FY 2025 · 2023-07

The sympathetic nervous system is a key regulator of whole body physiology. A dysfunctional sympathetic nervous system is linked to a growing list of human disorders including chronic heart failure, hypertension, and insulin resistance. Despite decades of research on sympathetic neurons, satellite glia, the major glial cells in sympathetic ganglia, have remained an enigmatic component of the system. Satellite glia tightly ensheathe sympathetic neuron cell bodies. In recent work, we revealed a role for satellite glial cells in restricting neuron activity to thereby modulate sympathetic output to peripheral organs. Our findings suggest that sympathetic neurons and their surrounding satellite glia should be considered as structural and functional units that orchestrate the formation and functioning of the sympathetic nervous system. However, satellite glia are a vastly under- studied cell type in the nervous system, with limited understanding of their development, neuron-glia communication, and how they contribute to neural circuits. This application addresses this knowledge gap by seeking to define how sympathetic neuron-satellite glia units are established during development, and how perturbations in this process impact neuronal connectivity and function. Based on our preliminary results, we hypothesize that target-derived neurotrophin signaling in sympathetic neurons instructs contact-based interactions with neighboring satellite glia during development. The goal of this application is to test this hypothesis and define the molecular underpinnings of this bi-directional neuron-satellite glia interactions using genetic mouse models, neuron-glia co-cultures, biochemistry, and imaging. Our studies will establish a fundamental knowledge of how these poorly studied glial cells contribute to nervous system connectivity and function and will inform new strategies for treating disorders linked to sympathetic dysfunction.