Johns Hopkins University

NSF Awards · FY 2025 · 2025-08

Understanding how energy is stored and explosively released in near-Earth space is critical to protecting modern technologies that depend on satellites, power grids, and communications systems. This project investigates the formation of thin current sheets (TCS), which are narrow regions of intense electrical current observed in Earth’s magnetotail during the quiet buildup phase of geomagnetic substorms. These substorms can lead to space weather disturbances that affect both space-based and ground-based systems. TCSs are thought to be a prerequisite for magnetic reconnection, the explosive process that triggers substorms, but their formation remains poorly understood. This research aims to clarify how specific ion behaviors—particularly when ions have directional energy preferences, or anisotropy—support the development of these thin structures. The project also supports the national interest by advancing scientific knowledge of geospace dynamics, which is essential for forecasting space weather. Additionally, it provides training for undergraduate students and offers early-career development opportunities for the principal investigator. The project uses state-of-the-art Particle-In-Cell (PIC) simulations to explore how ion anisotropy arises and enables the formation of thin current sheets in the magnetotail. Two central science questions guide the research: (1) What role does a realistic driving electric field play in generating ion anisotropy and enabling TCS formation? (2) What impact do anisotropic ions—originating outside the central current sheet—have on transforming a broader current layer into a TCS, either with or without an external driving field? The simulations incorporate novel, data-driven boundary conditions, including electric fields derived from data-mined magnetospheric reconstructions and ion populations informed by satellite observations. These include cold, anisotropic ions likely originating from Earth’s ionosphere and high-energy beams from magnetic reconnection exhausts. By resolving the physics behind TCS formation, this research will enhance scientific understanding of the substorm growth phase and energy release processes in space plasmas. The findings will have broader applications to other plasma environments, such as the solar wind and magnetospheres of other planets. 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 · 2025-08

Summary: Neural computation is a global phenomenon driven by a myriad of local, granular biophysical phenomena at millisecond time-scales. Advancing our knowledge of neural function and dysfunction requires new technologies that can capture granular information over large areas at fast framerates. We propose a new computational imaging approach that combines easily disseminable optics with algorithmic reconstruction algorithms that will advance the capabilities of both in vivo two-photon and light-sheet imaging, reaching the >100 Hz framerate range over large areas and volumes.

NIH Research Projects · FY 2025 · 2025-08

Project Summary/Abstract: Traumatic brain injury (TBI) represents a significant public health concern in the United States, with an estimated annual economic burden of $56.3 billion and a subsequent risk of neuropsychiatric and neurodegenerative diseases. Emerging research has highlighted the significant communication along the brain-gut axis as a driver of increased neuroinflammation. Furthermore, both preclinical and clinical studies have identified serotonin (5-HT) as a key player in the pathogenesis of TBI, with existing literature primarily focusing on brain serotonergic signaling. In our proposal, we aim to address this gap by investigating the role of serotonergic signaling in the gut. Enteroendocrine cells (EECs) are specialized cells that line the intestinal epithelium forming the body’s largest endocrine system and are responsible for producing 90% of the body’s serotonin. Our lab recently discovered a significant reduction in EEC expression and differentiation, as well as a decrease in serotonin synthesis following TBI. Additionally, we have demonstrated that TBI triggers the gut’s inflammatory immunoendocrine axis, as observed by an increase in inflammatory macrophages and decreased serotonin production, indicating a potential interaction between infiltrating macrophages and serotonin production by EECs. Alterations in the gut microbiome further modulate serotonin metabolism, suggesting a complex interplay between microbiota and intestinal serotonin. This proposal will investigate the mechanisms by which serotonin interacts with the various macrophage/microglial populations and how these interactions modulate the brain’s inflammatory response. Serotonin signaling will be restored through two novel approaches: (1) pharmacologically, by supplementing the prokinetic/laxative prucalopride, known to activate serotonin receptors (5HT4 receptor agonist), and (2) genetically, by generating mice that selectively overexpress EECs and serotonin in the gut epithelium. Behavioral outcomes, including spatial learning and memory, risk-taking/anxiety, and depressive-like behaviors, will be assessed at acute and chronic time points. We hypothesize that TBI induces EEC dysfunction and decreases serotonin production, which ultimately worsens brain neuroinflammation by inducing macrophage polarization into a pro- inflammatory state and modulating vagus nerve function. The overarching goal is to enhance serotonin production and suppress the proinflammatory response, with the aim of improving neurocognitive outcomes (Aims 1&2). Furthermore, we aim to utilize novel treatment strategies, such as non-invasive transcutaneous auricular vagus nerve stimulation (taVNS), to improve gut function and reverse brain neuroinflammation post- TBI (Aim 3). Collectively, the proposed studies will identify a key role for serotonin as a paracrine/endocrine hormone mediating the inflammatory response along the brain-gut-brain axis through its effects on macrophages, microbiota and vagus nerve function, with the potential for novel therapeutic interventions for TBI patients.

NSF Awards · FY 2025 · 2025-08

Transposable elements (TEs), also known as ‘jumping genes,’ are DNA sequences that can change or duplicate their position within a genome. Particularly, when a new copy is inserted into a gene by a process called exonization, it creates new genetic material that contributes to new variations and functions within a species and, over time, to the evolution of new species. One class of TEs, called Alu, accounts for thousands of primate- and human-specific proteins, potentially creating ‘programs’ to control essential cell functions such as tissue type and immune response. However, the extent and role of exonized TEs in humans and other species are largely unknown. The project will produce an innovative entirely computational methodology to predict TE exonization for a variety of species and TE families. It will develop a deep learning model that can predict exonization directly from the genome sequence without the need for extensive gene and tissue surveys. It will utilize the model to identify Alu exonization events in humans and several primates and compare them to identify common and specific traits. Lastly, focusing on genome sequences from a multi-ethnic population cohort will help answer questions about the ongoing contributions of Alu insertions to genetic variation in humans. The knowledge, methods and resources generated, including software tools and educational and science popularization materials, will help support biologists in more comprehensively analyzing genomes, contribute to public awareness of this class of gene plasticity events, and provide new tools to understand the molecular bases of human traits. The project will develop a flexible deep learning model that biologists can use to annotate and study transposable element (TE) exonization in a wide range of species and for different TE families. Using the model and existing RNA sequencing data, it will create and comparatively analyze an unprecedented collection of annotations of Alu exonization events and regulatory features in the genomes of humans and several primate species, at different evolutionary time points, including very recent polymorphic Alu insertions observed in a large multi-ethnic population cohort. All methods, annotations and software tools will be available free of charge from public repositories. Additionally, the project will create electronic teaching and training modules on how to use the software, as well as educational art videos on the process and functional implications of TE exonization in biology and as a source of variation in the human population. Lastly, it will create opportunities for training and education from high school through graduate levels through research programs and summer internships. 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 · 2025-08

Surgeons need expert feedback to improve their skill throughout their career. But expert feedback is not easily available to surgeons after they complete training. Expert feedback typically takes the form of natural language, i.e., surgeons learn from experts’ verbal teachings. Recent advances in artificial intelligence (AI) have created a tremendous potential for technology that can provide surgeons with expert-like language-based (i.e., narrative) feedback on any surgery they perform. This project aims to leverage current AI models and develop new ones that analyze videos of surgical procedures and generate expert-like narrative feedback. The AI models will include those that analyze language (i.e., large language models) and videos plus language (vision language models). This project will focus on cataract surgery as a prototype procedure to develop the AI models and evaluate them in additional procedures including surgery of the sinuses around the nose and surgery to remove a lobe in the lung. The overall goal for this project is to develop AI models that provide an expert analysis of a surgical video that includes description, interpretation, and reasoning about what is observed in the surgery and prediction of how the procedure evolves over time. To achieve this goal, this project consists of the following specific aims: (1) To develop a unified framework of vision language and large language AI models to generate expert analyses of surgical videos; (2) To develop methods for the AI models to continuously learn from techniques such as data augmentation, pretraining, and incorporating expert feedback; (3) To develop methods for synthesizing surgical videos from expert analyses to address the challenges in creating sufficiently large datasets needed to train the AI models; and (4) To create a dataset that enables this research. The expected impact of this work is to allow surgeons to learn more skill quickly and reduce variation in patient outcomes resulting from different skill among surgeons.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY Since the industrial revolution, western diets have undergone significant transformation. These changes have been associated with increased rates of metabolic disease. Changes in gut microbiota have been linked to increased rates of these diseases, both in humans and mammalian models. However, the mechanism that links the composition of the microbiome to onset of these metabolic diseases is unclear. One proposed mechanism is the increase in lipid absorption observed both in fish and mammalian models, which has been linked to the presence of specific bacterial species. However, a mechanism remains elusive. This proposal aims to study the question of how the microbiome influences lipid absorption in the fruit fly Drosophila melanogaster. Drosophila was selected for this project because of its small, tractable microbiome, relevance to human gut biology, and the existence of a powerful library of existing genetic tools, such as RNAi, overexpression and fluorescent protein lines. Using a combination of high-pressure liquid chromatography, and fluorescent microscopy, I have preliminarily shown that the microbiome of Drosophila melanogaster increases lipid absorption of the fluorescent fatty acid analog BODIPY-C12. In this proposal, I plan to verify this phenotype and establish causative microbes and timing of lipid absorption (Aim 1),and investigate the mechanism of this increase in lipid absorption by conducting a small RNAi screen on host genes thought to be involved in lipid absorption, specifically focusing on the hypothesis that microbial-mediated pH drives changes in the activity of these genes (Aim 2). Successful completion of the proposed aims will strengthen the link between microbial colonization and increased lipid absorption observed previously in vertebrates (I), discover genes important for lipid absorption in Drosophila (II), and establish Drosophila as tractable model for understanding lipid absorption (III).

NIH Research Projects · FY 2026 · 2025-08

Human immunodeficiency virus (HIV) and opioid use disorder (OUD) tend to be correlated and often co-occur with other substance use and mental health disorders. Treating OUD in PWH is critical to improve HIV outcomes and overall health. Buprenorphine, methadone, and naltrexone are efficacious medications for OUD (MOUD). In practice, adherence to MOUD is challenging. The impact of real-world MOUD use patterns is unknown, including the degree to which co-occurring substance use disorders (SUD) and mental health disorders, and and co-delivery of other SUD and mental health treatments (behavioral therapy and pharmacotherapy) modify the effect of MOUD among PWH. The Johns Hopkins HIV Clinical Cohort (JHHCC) is a cohort of PWH in Baltimore, Maryland. JHHCC participants consent to share their medical records and regularly self-report substance use and mental health symptoms. The clinic has a substance use treatment program that includes office-based buprenorphine and naltrexone. Chesapeake Regional Information System for our Patients (CRISP) is the regional health information exchange. We propose to comprehensively characterize OUD treatment, co-occurring substance use and mental health disorders, and HIV and overdose outcomes among PWH by linking JHHCC’s rich data on HIV outcomes, substance use, and mental health symptoms with CRISP’s area-wide records of controlled substance prescriptions, laboratory results, and hospitalizations and emergency room (ER) visits. In Aim 1, we will describe patterns of MOUD use among PWH with OUD as well as the associations between these patterns and co-occurring SUD or mental health disorders, and co-delivery of other SUD and mental health treatments. In Aim 2, we will estimate the effect of MOUD initiation and persistence on viral suppression, and explore whether this effect is modified by the aforementioned factors. In Aim 3, we will estimate the effect of MOUD use patterns on subsequent opioid overdose and all-cause mortality in PWH and again check for modification by co-occurring SUD or mental health disorders, and co-delivery of other services. These aims will improve our understanding of real-world use and effectiveness of MOUD therapy and the degree to which its effectiveness is modified or can be enhanced by comorbid conditions and medical care for mental health disorders. These insights are critical to integrating HIV and OUD care. The close relationship between OUD treatment and HIV care within the Bartlett Clinic underpins the proposed research and will facilitate the incorporation of our findings into clinical care.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY (See instructions): Humans and other animals exhibit a critical behavioral phenomenon in the control of movement: they switch between two distinct modes-fast, exploratory "active sensing" and slower, goal-directed "task control." This proposal aims to uncover the computational, behavioral, and neural mechanisms that regulate these two modes. We hypothesize that animals use internal estimates of sensory uncertainty to decide when to switch between modes, with uncertainty thresholds triggering transitions between exploratory and goal-driven behavior. To test this, we will use a uniquely tractable animal model-weakly electric fish performing a refuge tracking task-in which behavior, sensory feedback, and neurophysiology can be measured and manipulated in real time. The project comprises three specific aims: (1) develop computational models and theoretical tools to identify how and why animals switch between active sensing and task control modes; (2) conduct high-throughput behavioral experiments to quantify how sensory salience and feedback influence mode switching and control strategies; and (3) perform neurophysiological recordings to identify neural correlates of locomotor control policies and mode switching in the brain. This multidisciplinary effort integrates control theory, machine learning, and neuroscience to reveal the computational strategies underlying the regulation of active sensing and task control. Our findings have the potential to transform our understanding of biological motor control, identify mechanisms for assessing sensory uncertainty, and advance strategies for movement control in complex environments.

NSF Awards · FY 2025 · 2025-08

The numerous molecular interactions that support life must be highly regulated in the cell to achieve selectivity and precision. A newly identified method with which cells achieve this is via the sequential assembly of filamentous signaling platforms which are composed of a specific class of proteins. These large, supramolecular structures adopt distinct architectures, and shape complementarity plays a key role in recognizing their specific partners. Their assembly provokes a “signal” which triggers a cellular response. The filamentous signaling hubs can condense into large organelle-like entities, which can be vital for preventing any crosstalk with unrelated signaling pathways. This project aims to investigate how filamentous signaling platforms assemble and operate at the molecular level. This information is fundamental to understanding the coordination of the complex network of cellular processes. The PI directs the Biophysics Research for Baltimore Teens (BRBT) program, an outreach program in which high school students from Baltimore and the surrounding areas can be part of current research efforts. Specifically, this project will investigate how filamentous signaling platforms execute a cell-death pathway. The research strategy includes computational methods such as Rosetta, Electron Microscopy, single-molecule force measurements, and quantitative assays in both cell-free and cell-based systems. The first goal is to determine how architectural complementary dictates the interacting partners within a specific group of signaling filaments. The second goal is to investigate the mechanical forces involved in assembling such filamentous structures on DNA. The third goal is to elucidate how different regulators target and inhibit specific signaling components in these pathways. The outcome here will delineate structural, biochemical, physical mechanisms by which filamentous assemblies preserve the signaling specificity at different stages of the cell-death pathway. 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 · 2025-08

Project Summary: Neurofilament (NF) proteins are intermediate filament proteins expressed by neurons that are essential for axonal organization, support, transport, and synaptic function. NFs consist of three subunits, NF-H (Heavy), NF- M (Medium), and NF-L (Light), and their assembly and disassembly are regulated through phosphorylation by a complex network of second messenger kinases and phosphatases. NF hyperphosphorylation and aggregation are pathologies associated with several neurodegenerative diseases, such as Amyotrophic Lateral Sclerosis (ALS) and ALS/Frontotemporal dementia (FTD), and are detected in plaques and tangles in Alzheimer’s Disease (AD). NF hyperphosphorylation slows axonal transport and is implicated in neurodegeneration and loss in pre- clinical mouse models of ALS, suggesting contributions to neurodegenerative disease etiology. However, the signaling pathways that specifically disrupt NF phosphorylation dynamics and increase NF phosphorylation are unresolved. Bridging this gap in knowledge would clarify fundamental processes of NF biology and may clarify initiating pathways involved in NF pathophysiology in disease. Preliminary studies here identify a signaling pathway that operates on the cell surface that, when disrupted, leads to NF hyperphosphorylation and neurodegeneration. Glycerophosphodiester phosphodiesterase 2 (GDE2 or GDPD5) is one of three vertebrate- specific enzymes that act at the plasma membrane to cleave the glycosylphosphatidylinositol (GPI) anchor that tethers some proteins to the membrane and the only one expressed in neurons. Notably, GDE2 distribution and function are disrupted in ALS, ALS/FTD, and AD, suggesting potential contributions of GDE2 failure to disease pathology. Mice lacking GDE2 (Gde2KO) show robust increases in NF protein phosphorylation and age- progressive neurodegeneration, suggesting the overarching hypothesis that GDE2 regulates signaling events at the cell surface to regulate NF phosphorylation to ensure appropriate neuronal function and survival. Preliminary gain- and loss-of-function studies in cultured neurons and in vivo suggest the model that GDE2 regulates NF phosphorylation dynamics through cleavage and inactivation of the GPI-anchored protein RECK (Reversion- inducing Cysteine-rich protein with Kazal-like motifs). This model will be tested in this proposal in three Aims. Aim 1 will utilize in vitro and in vivo models to determine if RECK mediates GDE2-dependent regulation of NF phosphorylation and survival. Aims 2 and 3 will utilize structure-function studies, proteomic screens, and functional assays to determine the surface mechanism and downstream kinase pathways by which increased RECK surface activity promotes NF phosphorylation. Outcomes from these studies are expected to provide new insight into the fundamental regulatory mechanisms of NF phosphorylation and have the potential to shed light on disease-relevant pathways that are causal for NF abnormalities associated with disease.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY/ABSTRACT Prostate cancer (PCa) is the most commonly diagnosed type of cancer and the second leading cause of cancer related deaths among US men. The proposed project aims to improve prostate image-guided interventions (IGI) with a novel ultrasound probe and robot developed by our team, ProBot. We propose a Phase 1 clinical trial to evaluate the safety and feasibility of the new device at biopsy. We also propose to improve the technology and expand it to focal therapy of PCa. ProBot is an entirely new concept including a novel ultrasound probe and robot kinematics specifically designed for prostate IGI. A novel feature is that it does not change the deformation of the prostate gland, allowing more accurate MRI-ultrasound co-registration and needle targeting. In addition to accurate MRI targeted biopsy (TB), at systematic biopsy (SB), instead of using the usual template plan, our innovative software optimizes the plan to ensure appropriate biopsy spacing and obtain diagnosis representative of whole gland histology. ProBot will also be uniquely capable of transrectal (TR) and transperineal (TP) biopsy and focal therapies. ProBot is ready for immediate clinical assessment as proposed. It is a refined prototype and has already attained approval by the FDA for clinical trial evaluation. We recently completed 2 TR biopsy cases with ProBot with IRB approval. We propose to extend the approval for TP biopsy and perform the trial for TR and TP biopsies. Focal therapy is a promising, minimally invasive treatment strategy to selectively treat localized PCa while minimizing the side effects associated with whole gland treatment options. Focal therapies aim to deliver ablative energy to PCa lesions sampled at biopsy. Repeatably targeting a lesion between biopsy and therapy may be improved if the same device, such as ProBot, is used to guide both procedures. As a research aim, we also propose to further develop ProBot for percutaneous interstitial ablative treatment, an innovative approach to be integrated with ablative technology and tested in a future trial. ProBot is a small, lightweight (1.3Kg ultrasound probe and robot), inexpensive to manufacture device that could ultimately provide a cost-effective solution for PCa care. The ProBot allows hands-free operation of its ultrasound probe at 3D image scanning and needle targeting. This device could reduce the level of physician training and skill currently needed while minimizing the variability in outcomes among physicians, and ultimately improve the accuracy of biopsy targeting and reliability in the results of biopsy. An early-stage clinical trial is required to evaluate the safety and feasibility of the new device and biopsy approaches.

NSF Awards · FY 2025 · 2025-08

Modern artificial intelligence (AI) systems provide a versatile toolkit for identifying solution maps for a variety of problems in a data-driven fashion -- some prominent application domains include imaging, signal processing, recommendation systems, and partial differential equations. In this paradigm, one is given a training dataset consisting of input-output -- inputs representing problem instances and outputs representing solutions -- and the objective is to learn a solution map that can be applied to future test inputs. For example, in image classification, the inputs correspond to images, and the outputs correspond to labels indicating the presence or absence of a person. While remarkably successful, a major drawback of this paradigm concerns the size or dimension of the training examples. Specifically, one can expect the size of the input problem instances in the training set to be different from that of the problem instances encountered at test time; indeed, even expecting all the data in the training set to lie in the same dimension is often unreasonable. For example, when learning image classifiers, contemporary methods usually require the training set to consist of images of the same size. Moreover, the model trained cannot handle larger or smaller images. A more natural learning objective is to identify an algorithm instead -- a sequence of solution maps that gracefully handles inputs of increasingly larger size. This project advances a research program to learn such an algorithm from training data consisting of inputs of different sizes, allowing for learned algorithms to be deployed on inputs of any size (including those not present in the training set). To achieve this goal, the project utilizes a framework based on representation theory that facilitates the specification of parameterized families of sequences of solution maps, i.e., parameterized families of algorithms, with the parameters given by invariants in a sequence of group representations. The learning problem identifies the best element from such a parameterized family to minimize training error. At test time, one can simply apply the solution map that takes in the dimension of the test instance. Central to this development is the recently identified phenomenon of representation stability in the algebraic topology literature, which provides the mathematical underpinning of the framework. The project tackles approximation-theoretic, statistical, and computational research questions that arise from our framework, along with high-impact applications to imagining inverse problems and protein folding. The framework will provide a mathematical basis for training AI systems on low-dimensional training data while still being applicable to high-dimensional test data, thus offering the possibility of significant energy savings and making ML systems more sustainable. Furthermore, the research is integrated with a comprehensive educational component. The principal investigators will mentor high school students through the Johns Hopkins Center for Educational Outreach and undergraduates through the Caltech Student-Faculty Programs Office. 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 · 2025-08

Project Summary Dr. Alexander Hillel is a faculty member in the Department of Otolaryngology-Head & Neck Surgery at the Johns Hopkins School of Medicine where his clinical practice is dedicated to the medical and surgical management of subglottic stenosis. Through the support of a R01 Research Project Grant, he and co-Investigator, Dr. Ramana Sidhaye, seek to better understand how the dysfunctional epithelial barrier contributes to the spontaneous fibrosis seen in idiopathic subglottic stenosis (iSGS). iSGS is a rare but life-threatening disease that exclusively affects healthy, peri-menopausal women. In iSGS, scar forms in the upper airways narrowing the subglottic larynx, and resulting in shortness of breath and communication disability. Specifically, the investigator team will focus on E-cadherin, an apico-adherens junction protein in epithelium, as the cause for barrier dysfunction in iSGS. The deficiency in E- cadherin creates a permeable barrier allowing for common antigens to pass through the epithelium and trigger fibrosis. This proposal will study how the loss of E-cadherin in epithelial cells leads to scar formation in a mouse model and by using human epithelial cells and fibroblasts isolated from iSGS patient biospecimens. It will also study a novel surgical procedure that restores the epithelium after excising scar tissue to assess if E-cadherin is the critical protein involved in preventing scar from reforming. Finally, the proposal will investigate improving saccharide binding to E-cadherin, through a process called fucosylation, as a novel therapy to restore E-cadherin and epithelial barrier function. Through a combination of in vitro and in vivo modeling, participation from patients with iSGS, and assessment of a novel surgical procedure, the investigator team is uniquely poised to transform our understanding and treatment of iSGS.

NIH Research Projects · FY 2025 · 2025-08

Medications for opioid use disorder (MOUD) like buprenorphine and methadone are vitally important to prevent overdose-related morbidity and mortality, and early evidence suggests that drug treatment co-located with mental health care (MH) may be particularly effective at retaining people who use opioids (PWUO) in care. However, lack of transportation and long travel times are two of the most cited reasons for not initiating drug treatment, though travel time has not yet been explored for initiating MOUD with co-located MH. My long-term career goal is to become an independent public health investigator whose primary line of research focuses on understanding neighborhood and place-based factors contributing to mental health and substance use-related outcomes for all Americans. My long-term research will be primarily through an urban health lens and using varied quantitative methodologies. Toward this goal, I propose further training in 1) spatial analysis and GIS; 2) place- based determinants of health; 3) mental health service modalities for PWUO; 4) multilevel modeling; 5) dissemination to stakeholders. The proposed research will use these newly developed skills, along with ecological and individual-level data from PWUO, to meet the following aims: 1) Characterize potential spatial access to outpatient medications for opioid use disorder with and without co-located mental health services in Baltimore, MD and five similar U.S. cities; 2) Determine the association between spatial accessibility to MOUD and co-located mental health services and overdose mortality in Baltimore, MD and Milwaukee, WI; 3) Explore the relationship between objective and subjective accessibility on a) MOUD treatment uptake and retention with and without co- located mental health care, and b) non-fatal overdose among a cohort of PWUD (n=600) in Baltimore, MD. To accomplish these aims, I will draw on the proposed training and guidance from my primary mentor, Dr. Susan Sherman (dissemination training). My mentorship team also includes experts in substance use and mental health service utilization (Dr. Mojtabai), spatial analysis (Dr. Curriero) specifically applied to health care access (Dr. Desjardins), and place-based health determinants and multi-level modeling (Dr. Linton). My prior training, experience conducting relevant research, and the expert mentoring team strongly positions me to accomplish these aims.

NSF Awards · FY 2025 · 2025-08

Organoid intelligence (OI) is an emerging field that aims to harness the computational power of brain organoids for biocomputing and biomedical research, seeking to generate computing devices with substantially lower energy requirements than conventional digital electronics. Brain organoids are lab-grown brain tissues, each about the size of a small grain of sand, that can naturally form networks. This project seeks to incorporate reward-based learning mechanisms into brain organoids to enable more complex and adaptive behaviors and increase training efficiency. By connecting the organoids to tiny electronic shells and using chemical signals, the research team will teach them to play simple video games and guide small robots. Throughout the project, bioethicists will monitor every step to ensure responsible and ethical conduct of research and to keep the public informed about both benefits and concerns. The work will train multiple students, create open-source hardware and software, and launch community courses that invite citizen scientists to learn about biological computing. Success of this project could pave the way for computers that use a million times less energy than today’s artificial-intelligence (AI) systems and open fresh paths for studying disorders such as Alzheimer’s disease. This project seeks to advance organoid intelligence through engineering three-tier brain assembloids that couple cortical, dopaminergic, and striatal regions inside self-folded shell micro-electro-fluidic arrays (SMEFAs). These interfaces can deliver millisecond-precision electrical stimulation and micromolar-resolution neuromodulator gradients while recording three-dimensional neural activity. The central hypothesis of this research is that reward-modulated spike-time-dependent plasticity (R-STDP) will enable data-efficient, continual reinforcement learning in biological networks. The goal of Thread 1 is to develop standardized culture protocols and validate long-term SMEFA stability. Under Thread 2, real-time closed-loop software will be created that maps environment observations to stimulation codes and decodes action signals from high-density recordings, benchmarking OI against deep-reinforcement learning baselines on curricula of Atari-like tasks and embodied robot control. In Thread 3, an experimental neuroethics program will be embedded that defines measurable capacities (sentience, agency, evaluative cognition) and implements tiered safeguards in any case of evidence of consciousness. This project will explore the fundamental mechanisms of biological learning and is expected to develop new biocomputing architectures and to create a framework for experimental neuroethics. The work should position OI as a transformative, sustainable architecture for next-generation adaptive systems. 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 · 2025-08

PROJECT SUMMARY/ABSTRACT The complement system and its careful regulation play critical dual roles in maintaining healthy pregnancy – combating infection and allowing tolerance of the semi-allogenic fetus. The trigger of complement activation and pathway(s) involved in pregnancy remain elusive. Complement dysregulation or excess activation is implicated in pregnancy loss, preterm birth, and development of pre-eclampsia and the HELLP syndrome. Sickle cell disease (SCD) is a thromboinflammatory disorder with high rates of adverse pregnancy outcomes (APOs), including severe pre-eclampsia, preterm birth, fetal growth restriction, and fetal loss. Complement activation is implicated in SCD-related organ damage, though the role of complement in SCD pregnancies has not been explored. In the US, maternal mortality in women with SCD is ~10 times higher than in black pregnant people without SCD, highlighting the need for translational studies to address these pathobiologic mechanisms. Dr. Gerber has initiated prospective collection of serial blood samples and clinical data during pregnancy in SCD and generated exciting preliminary data suggesting that classical complement is triggered by IgM in pregnancy. This proposal employs the bioluminescent modified Ham (bmHam), a novel, functional assay of membrane- directed complement activation that has the ability to test specific complement pathways using targeted inhibitors. We will prospectively collect serial samples from healthy pregnant women (controls) and women with HbSS disease during pregnancy. We will define the pathway and triggers of increased complement activity in controls and pregnant women with HbSS disease. Using the bmHam, we will compare differences in complement activity by trimesters between pregnant women with HbSS disease and controls. We also will test the association between increased complement activity and the development of APOs in women with HbSS disease. Lastly, we will evaluate the influence of SCD genotype (e.g., HbSS, HbSC) on complement activity in non-pregnant women of reproductive age to determine expansion of our pregnancy cohort. Elucidating the role of complement activation as a mechanism and biomarker for APOs in SCD pregnancies will provide a tool for risk stratification and potentially early intervention strategies to be tested in future clinical trials. This mentored research and career develop award will facilitate Dr. Gerber’s long-term goal of becoming a translational investigator in classical hematology with a focus on thromboinflammatory disorders during pregnancy. Dr. Gerber’s interdisciplinary team of mentors and advisors have extensive expertise in complement- mediated disorders, bioassay development and translational research methods, reproductive health in SCD, maternal fetal medicine, placental biology, and biostatistics. The additional proposed experiential and didactic training in reproductive research methods, longitudinal cohort analysis, prospective cohort study design and biomarker testing, and clinical trial design will enable her to transition to an independent investigator at the intersection of hematology and women’s health bridging clinical and laboratory researchers.

NSF Awards · FY 2025 · 2025-08

The team aims to unlock critical new knowledge of hearing in noisy environments. Noise represents a major challenge to the daily lives of humans and other animals: Rockets, airplanes, jackhammers, munition blasts, motorcycles, rock concerts, farm and industrial equipment, recreational vehicles, and other sources of intense sound interfere with social communication and can permanently damage hearing. While human-driven changes to the sound environment now occur at an unprecedented scale, the impact of loud noise on hearing appears to differ across species. Some animal species, such as echolocating bats, have evolved specializations that render them more resilient to noisy acoustic environments, while other species, such as mice, are susceptible. The research team aims to understand what specializations of the auditory system confer hearing protection in some species and with this knowledge, identify potential interventions to reduce the effects of noise damage on hearing in humans and other animals. This project includes an interdisciplinary educational opportunity to equip students with broad knowledge and skillsets that will prepare them to make transformative contributions in basic science, technology, and noise pollution policy. The team also plans community activities to raise awareness of noise impacts on hearing in humans and other animals and to encourage the use of protective earplugs and earmuffs in noisy settings. This project will yield a scientific foundation for policy makers to evaluate the impacts of noise in the environment and make informed recommendations. Anthropogenic noise poses a threat to a vast array of species that rely on acoustic signals to survive in their natural habitats, and holds implications for biodiversity conservation, ecosystem health, and environmental policies. This research project aims to identify the neural mechanisms that render some organisms susceptible to anthropogenic noise and others resilient, and to unlock new interventions that can mitigate the effects of noise damage on hearing in humans and other animals. They bring together a multidisciplinary team to understand the impacts of anthropogenic noise on (1) efferent auditory pathways and (2) neural coding in the peripheral and central auditory systems. The team’s collective expertise in animal bioacoustics, auditory neuroscience, neuroanatomy and sensory ecology allow them to identify and analyze the factors that promote resilience in neural pathways to environmental noise. The project will establish a blueprint for the research community to analyze the impact of anthropogenic noise on animal hearing and provide a scientific foundation for policy makers to mitigate these disruptions and preserve the delicate balance of our auditory environments. This project is supported jointly by Division of Integrative Organismal Systems in the Directorate for Biological Science of NSF and the Kavli Foundation. 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 · 2025-08

The ongoing, indeed once again increasing, burden of malaria is well-recognized, as is the steadfast threat of drug resistance that drives discovery efforts for new antimalarials. Drug combinations to enhance efficacy and to thwart the emergence of resistance are now considered a requirement for antimalarial therapy. Elegant genetic and inhibitor studies have revealed the sequential multistep process of merozoite invasion into erythrocytes, and have identified as essential the linkage of highly conserved reticulocyte-like binding protein 5 (Rh5) to basigin, its red cell membrane protein receptor. This proposal explores the consequences of combining human anti-Rh5 monoclonal antibodies with small molecule inhibitors, against asexual falciparum malaria parasites in vitro. Selected monoclonals will target Rh5 epitope communities that are known to inhibit parasite growth. Small molecule choices will include representative inhibitors for every phase of merozoite invasion. Combinations will be evaluated for additivity, synergy or antagonism. Findings from these experiments will guide further studies.

NIH Research Projects · FY 2025 · 2025-08

Project Abstract/Summary Insects are guided by their chemosensory systems of smell and tase. A multitude of behaviors, such as foraging, mating, navigation, and oviposition rely on smell and taste. For disease vectors such as mosquitoes, their chemosensory systems guide host-seeking (attraction to humans) and biting. As such, the chemosensory systems of insects are excellent targets for behavioral control, and strategies that target insect smell and taste could have significant and widespread benefits from reducing mosquito biting to preventing crop destruction by invasive pests. The chemosensory systems of insects rely on the expression of 3 different receptor family members: the Odorant Receptors (ORs), the chemosensory Ionotropic Receptors (IRs) and the Gustatory Receptors (GRs). Of these three, IRs represent one of the most ancient and abundant chemosensory receptors on the planet. IRs likely diverged ~600 million years ago from an ancestral ionotropic glutamate receptor (iGluRs) to take on new roles as a multi-functional chemosensory receptor family. Chemosensory insect IRs are a complex between an IR co-receptor and a ‘tuning’ IR that binds to a chemical ligand. The IR co-receptors Ir8a and Ir25a share protein homology to iGluRs which contain a large amino- terminal domain. In contrast, the tuning IRs lack this domain. The structure of mammalian iGluR complexes has been solved by the Twomey group using cryo-EM. The structure of chemosensory IRs remains unknown. A key limitation has been harvesting functional chemosensory IR-complexes for cryo-EM analyses. The expression of IR complexes in cell culture systems does not lead to functional complexes, likely reflecting defects in IR complex formation or cellular trafficking. To address these limitations, we assembled a team of insect sensory biologists and structural biologists. Using transgenic Drosophila that express an N-terminal tagged functional Ir8a co- receptor (EGFP:Ir8a), we will: Specific Aim 1, develop methods to harvest functional Ir8a receptor complexes directly from ~10,000,000 Drosophila antenna, and Specific Aim 2, purify EGFP:Ir8a complexes from Drosophila tissues using nanobodies to EGFP followed by cryo-EM analyses on the complexes as previously done for iGluR complexes. These experiments have the potential to establish Drosophila as a viable in vivo tissue source for chemosensory receptor purification. This work will also reveal the cryo-EM structure of chemosensory IRs, their stoichiometry, and provide clues as to how this receptor complex evolved from iGluRs to be gated by a variety of chemicals. This could lead to innovative new strategies to target these receptor complexes to control insect behaviors.

NIH Research Projects · FY 2025 · 2025-08

SUMMARY Metabolic enzyme velocity (the product of activity and abundance) is shaped by the need of growing cells to maintain metabolic flux while avoiding the accumulation of toxic intermediates and limiting inefficient biosynthesis. Imbalances in enzyme velocity play a significant role in metabolic disease, and changes in enzyme expression are often associated with drug resistance. Nonetheless, the connection between metabolic enzyme expression, intracellular abundance, and cell growth rate is poorly characterized. Our long term goal is to create a genome-scale model that quantitatively relates E. coli gene expression to growth rate phenotypes across both common laboratory and host-associated conditions. We envision using this model for antibiotic discovery, biosynthetic pathway engineering, and to interpret the effect of mutations in clinical isolates. Recently, we developed a new modeling approach that predicts the growth rate effects of combinatorial variation in E. coli gene expression and environment from sparsely sampled experimental training data. The basic strategy is to first quantify the growth rate effects of gradated changes in gene expression across multiple environments and genetic backgrounds of interest. Then, we use these data to parameterize a machine-learning model describing the connection between gene expression and growth rate. We found that the model can predict the effects of at least four combinatorial perturbations in gene expression and environment when trained on experimental data considering only pairwise perturbations. The central goal of this grant is to now apply and extend this approach to quantitatively understand the connection between enzyme abundance, growth rate, and antibiotic resistance in E. coli. More specifically, we will: (1) identify and model the metabolic factors influencing trimethoprim resistance in E. coli, (2) quantify the stoichiometric constraints on relative enzyme expression and abundance in 16 central metabolic pathways, and (3) apply new sequencing-based tools to simultaneously quantify gene knockdown effects and growth rate across core metabolism. Together, this work will test hypotheses about the modular organization of metabolism and yield a deeper understanding of the connection between metabolism and antibiotic resistance. Moreover, our work in Aim 3 will generate a genome-scale collection of barcoded strains for interrogating the dynamic connection between gene expression and growth rate across environments.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY Chronic obstructive pulmonary disease (COPD) is a leading cause of death in the United States, with a disproportionately high prevalence among individuals with low socioeconomic status (SES). Hospitalizations for acute exacerbations of COPD (AECOPD) are common and come with a high risk of rehospitalization. Among individuals hospitalized with COPD, 20% are rehospitalized within 30 days, and low SES is associated with increased risk of rehospitalization. Multiple causal mechanisms have been proposed for the association between low SES and COPD morbidity. Specifically, adverse dietary patterns and food insecurity can affect COPD morbidity and may be acutely worse following hospital discharge. Previous interventions aimed at preventing rehospitalization through COPD-specific treatments have had mixed results, and the American Thoracic Society (ATS) has recommended programs expand beyond solely focusing on guideline- recommended care for COPD to include issues related to social determinants of health. To investigate diet as a potentially modifiable factor linking SES to COPD morbidity, we propose to study the association of diet quality and food insecurity with rehospitalization risk in 120 individuals hospitalized for AECOPD. We will assess diet quality after hospital discharge in terms of general quality, using the Alternative Healthy Eating Index-2010, as well as specific patterns associated with COPD morbidity, such as low omega-3 fatty acid intake. We will additionally examine food insecurity, a household’s economic and social conditions resulting in limited or uncertain access to adequate food, which is related to SES and may influence diet quality and rehospitalization risk. Furthermore, we will conduct semi-structured interviews with a subset of participants to identify contributors to diet quality and food insecurity during the transition from hospital to home. Finally, we will conduct a randomized trial of prepared meal delivery following hospital discharge among 36 individuals admitted for AECOPD to determine if such interventions can improve diet quality, affect biomarkers associated with COPD morbidity, and potentially decrease rehospitalization rates. Completion of the proposed aims will elucidate the role of dietary factors on rehospitalization risk in COPD and inform the design of a larger randomized controlled trial of diet intervention following hospitalization for AECOPD. We will leverage infrastructure created for an ongoing cohort study of individuals hospitalized for AECOPD at the Johns Hopkins Bayview Medical Center as well as the Johns Hopkins COPD Precision Medicine Center of Excellence. My ultimate career goal is to be an independent clinical researcher focusing on interventions that address health disparities in COPD. My career development plan includes expert mentorship, formal coursework, and hands- on experience to develop new skills in cohort and clinical trials design, nutrition research, and qualitative research methods.

NIH Research Projects · FY 2025 · 2025-08

The goal of the proposed fellowship is to prepare the applicant, Valerie Ganetsky, for an independent research career focused on improving access to medication for opioid use disorder (MOUD) treatment for individuals with opioid use disorder (OUD), particularly for pregnant and parenting women. This fellowship will help Valerie prepare for a career as an independent investigator by providing opportunities for individualized training aimed at achieving four key goals: (1) to attain proficiency in analyzing large administrative claims datasets to investigate OUD health services, (2) to apply advanced quantitative statistical methods to examine critical issues within OUD health services, (3) to lead qualitative research to explore the perceptions of relevant stakeholders within the OUD treatment paradigm, and (4) to integrate her prior clinical expertise with advanced research training to disseminate scientific findings and inform evidence-based policy and practice interventions. To achieve these goals, Valerie will engage in activities such as mentored research, didactic and informal training through coursework and seminars, experiential learning through participation in national organizations and action groups, and dissemination of research findings through manuscript development, grant writing, and presenting at academic conferences. Throughout the training period, Valerie will benefit from a wealth of resources at the Johns Hopkins Bloomberg School of Public Health and a strong mentorship team with complementary expertise in substance use health services research, the use of administrative claims datasets, advanced causal inference methods, qualitative methods, and perinatal substance use policy issues. The mentored research will employ a multi-method approach to examine the association between buprenorphine dose trajectories and OUD-related outcomes among pregnant and postpartum women, particularly during an era when high-potency synthetic opioids dominate the illicit drug supply. This research aims to fill several gaps in the literature. First, the role of buprenorphine dosing as a potential strategy for improving OUD outcomes in pregnant and postpartum women has been notably understudied, highlighting the timeliness and significance of this research. Second, this proposal represents the first use of group-based trajectory modeling (GBTM) to examine buprenorphine dose changes during pregnancy and their impact on postpartum OUD-related outcomes. GBTMs will allow the applicant to identify distinct buprenorphine dose trajectories, identify subgroups more likely to follow certain trajectories, and examine how different trajectories influence outcomes. Third, this research will incorporate qualitative methods to explore previously unexamined attitudes, beliefs, and prescribing practices among buprenorphine treatment providers in Maryland. The proposed research is well-aligned with NIDA’s Strategic Plan Goal 4.2 to support research on developing and testing strategies for overcoming barriers to access and continuity of care.

NIH Research Projects · FY 2025 · 2025-08

Project Summary/Abstract The origin recognition complex (ORC) plays a critical role in DNA replication initiation by facilitating the ATP- dependent loading of MCM2-7 helicases onto DNA to form pre-replicative complexes. This process, known as origin licensing, ensures that DNA replication is tightly controlled and occurs only once per cell cycle. However, in cancer cells, this replication control system is often disrupted, contributing to uncontrolled proliferation. Cancer cells that are highly proliferative or harbor mitotic checkpoint defects often exhibit a strong dependency on replication initiation factors such as ORC, making them particularly vulnerable to inhibitors targeting this process. Consequently, ORC represents an attractive therapeutic target for cancer treatment. Despite its importance, there are currently no approved small molecules that specifically target ORC. The development of such inhibitors could selectively induce replication stress and cell death in cancer cells with minimal impact on normal cells. This paradigm is exemplified by a previously identified replication licensing inhibitor, called RL5a, which I have biochemically established to inhibit ORC-DNA binding. A promising avenue for targeting ORC involves the use of rapafucins, a novel class of macrocycles inspired by the natural product rapamycin, designed to target difficult- to-drug protein-protein interactions. Rapafucins have shown potential in cancer-related targets, making them an excellent candidate for developing selective ORC inhibitors that exploit cancer-specific vulnerabilities. In the present proposal, I aim to identify and characterize novel inhibitors of ORC to disrupt origin licensing and selectively target cancer cells. My approach integrates high-throughput biochemical screening with structural and functional studies to uncover the mechanisms underlying ORC inhibition. I have established the utility of the rapafucin library using a pilot microarray screen of a subset (~20%) of the full library, identifying several compounds that selectively bind to ORC and inhibit its binding to DNA. In Aim 1, I plan to conduct high- throughput biochemical screens of the rapafucin library to identify additional compounds that inhibit ORC-DNA binding as well as ORC ATPase activity. Promising hits will be evaluated for their ability to selectively impair the growth of cancer cells, particularly in those with known initiation factor dependencies to identify rapafucin leads with a favorable therapeutic index. In Aim 2, I will use cryo-EM to determine high resolution structures of ORC in complex with RL5a, as well as with rapafucins identified from the microarray that inhibited ORC-DNA binding or impaired cancer cell growth. These structural studies will provide detailed insights into the binding modes of these inhibitors and help identify key residues involved in ORC-inhibitor interactions. My planned work will further establish a pipeline for determining how any new hits obtained as part of Aim 1 also act on ORC. Ultimately, these combined effects will lay the foundation for the development of effective therapies that target the replication initiation process in cancer cells.

NIH Research Projects · FY 2025 · 2025-08

Black or African American (AA) males are more likely to be diagnosed with advanced prostate cancer and are nearly 2.5 times more likely to die from the disease than European American (EA) males. This increased mortality may be due in part to a more aggressive molecular phenotype of the tumors of AA individuals. Key somatic genomic driver alterations in prostate cancer occur at differing frequency in AA and EA males, potentially contributing to differences in clinical outcomes. Likewise, many known somatic genomic driver alterations that are currently used in prognostic tests are more common in EA than AA males. Our preliminary studies indicate that p27 genomic alterations by somatic mutation and/or deletion are an unexpectedly common occurrence in primary prostate cancer, with subclonal complete loss observed in close to one out of every five cancers that we assessed. This finding would place p27 as one of the most frequently mutated/deleted genes in primary prostate cancer. Furthermore, subclonal p27 loss in primary prostate cancer was associated with worse outcomes including the development of biochemical recurrence and metastasis after radical prostatectomy, specifically in AA individuals. We hypothesize that the prevalence of p27 hemizygosity (p27+/-) and homozygous loss (p27-/-) has been underestimated in both primary prostate cancer and metastatic disease, and may contribute to worse prostate cancer outcomes in AA males. Our objective is to perform a systematic analysis of p27 alterations in both primary and metastatic prostate cancer in large, comprehensive cohorts. We ultimately aim to understand how subclonal p27 loss mediates worse prostate cancer outcomes. Furthermore, our study will lay the foundation for future clinical studies and/or clinical trials that will associate p27 loss in metastatic disease with treatment response to therapies for advanced prostate cancer including AR axis-targeted therapies, bipolar androgen therapy, and chemotherapy. Finally, we aim to assess a potentially modifiable risk factor (e.g., chronic inflammation) in driving subclonal p27 loss and prostate cancer aggressiveness.

NIH Research Projects · FY 2025 · 2025-08

The primary objective of this K99/R00 application is to develop Dr. Sandipan Pramanik’s (PI) research skills to improve our understanding of disease burden among children under age 5 in low and middle-income countries (LMICs). The K99 phase of the proposed research will support PI in accomplishing four training objectives. This will enable his seamless transition into an independent global health investigator, enhancing mortality surveillance through impactful solutions that integrate multi-source data. First, he will broaden his understanding of factors impacting child and neonatal mortality in LMICs, along with foundational statistical and demographic surveillance methods. Second, by conducting field visits, he will gain firsthand experience and insights into on-site data collection, method/software implementation, and associated challenges. He will also arrange direct studies to acquire knowledge on different causes of death (CODs) diagnoses (such MITS, verbal autopsy (VA)), and their medical background. Third, by visiting collaborators, he will enhance his expertise through research presentations and discussing competing/complementary methods. Fourth, he will seek professional development opportunities, emphasizing grant writing and collaboration. Based on the training objectives and utilizing unique access to essential rich data sources (CHAMPS, COMSA), this proposal is timely and pivotal for enhancing mortality estimates, focusing on children under age 5. With the acquired skills from training, the PI will be well-positioned to successfully achieve the three research aims, expanding VA-calibration applicability. Utilizing paired MITS-VA COD data and tackling systematic bias and heterogeneity, Aim 1 will develop a concise country-specific VA misclassification modeling framework, enhancing mortality estimation covering detailed causes. In a first, Aim 2 will design efficient Bayesian tests to effectively compare hypotheses about different effects in VA misclassification. In contrast to classical tests, this will facilitate more efficient and clear statistical decision-making. Using national-level estimates, Aim 3 will create a novel statistical downscaling framework. This will enhance inference for sub-populations at the sub- national level, including age groups, sexes, and geographic regions, ensuring coherence with population-level estimates. Complementing Aims 1–2, it will also distribute open-source software and apply proposal outputs to various projects and grants, with immediately improved mortality estimates in Mozambique and Sierra Leone. This proposal will accelerate the worldwide effort to improve child mortality surveillance. It also aligns with the US government and international community’s objective to assess the effectiveness of age and disease- specific interventions, such as malaria vaccine2 or azithromycin3, in combatting the primary causes of mortality among them. The collaborative efforts between the Departments of Biostatistics and International Health at Johns Hopkins, involved in initiatives like COMSA in Mozambique and CHAMPS, offer an ideal environment to receive the research support and resources to attain his training and research objectives.