Brown University

NIH Research Projects · FY 2026 · 2021-11

Abstract HIV and AIDS continue to be significant public health issues, but with recent advances in treatment, technology, clinical and social support, the research and treatment agenda now explicitly and realistically includes bringing the decades-long pandemic to an end. The President’s Emergency Plan for AIDS Relief (PEPFAR) is an ongoing multi-billion investment to deliver antiviral therapy to those in low- and middle-income countries (LMIC), and has been regarded by many as the most successful public health intervention in modern history, having dramatically reduced both prevalence and incidence of HIV over the past two decades. With both clinical trials and observational studies conclusively demonstrating that immediate treatment with antiretroviral therapy (ART) is the mosteffective way to both treat HIV and prevent the transmission of new infections, retention in HIV care and suppression of viral load through compliance with ART are arguably the most effective methods available for bringing the pandemic to an end, and indeed are encoded in the UNAIDS 95-95-95 benchmarks of having 95% of cases diagnosed; 95% of diagnosed cases initiated and retained on ART; and 95% of treated individuals achieving viral suppression. Clinical decision support systems (CDSS) tailored to the requirements of LMICs have been shown to improve compliance with guidelines and quality of care by a range of healthcare staff. Use of machine learning algorithms allows the development of prediction models for clinical complications and outcomes, which can guide health care staff in early identification of problems and appropriate interventions. The Specific Aims of this proposal therefore are (1) to use a large electronic health record (EHR) database to develop and validate statistical machine learning models to identify patient at high risk for loss to follow up and viral failure; (2) to develop and field test implementation of clinical decision support tools based on these models that will be implemented at the point of care; and (3) to evaluate the efficacy of the decision support tools, in terms of improving patient retention and reducing viral failure, using a randomized comparison at the clinic level. Our project will be implemented at the Academic Model Providing Access to Healthcare (AMPATH), an HIV care program in western Kenya serving nearly 200,000 people with HIV.

NIH Research Projects · FY 2024 · 2021-09

Project Abstract Exposure to environmental chemical mixtures may increase the risk of cardiometabolic disease. Of particular concern are prenatal exposure to perfluoroalkyl substances (PFAS), a class of chemicals used as processing aids for oil/water repellant textiles, fluoropolymer manufacturing, food packaging, cleaning products, and firefighting foams. PFAS exposure is ubiquitous, deriving from contaminated food and drinking water. Over 6 million people in the US have PFAS contaminated drinking water, and many more have low-level exposure. Animal and human studies show that prenatal PFAS exposure may increase the risk of obesity, insulin resistance, dyslipidemia, and hypertension – components of the cardiometabolic syndrome that markedly increase the risk of adulthood cardiovascular diseases. However, few studies have investigated the health effects of PFAS mixtures, and the biological pathways underlying these effects are poorly understood. Guided by our preliminary studies and the hypothesis that biological pathways represented in the serum metabolome are sensitive to early life PFAS mixture exposure and predictive of later life cardiometabolic health, we will use non-targeted high-resolution metabolomics to quantify the associations between prenatal PFAS mixtures, the metabolome, and cardiometabolic disease. Building upon two established and ongoing prospective cohorts of pregnant women and their children from Canada (MIREC Study, n=500) and Cincinnati, Ohio (HOME Study, n=250), we will measure >25,000 features of the serum metabolome at delivery and ages 3-5, and 7-12 years. We will link these data to previously collected or to be measured prenatal PFAS biomarkers and cardiometabolic outcomes at age 7-12 years. We will use sophisticated biostatistical techniques to reduce the dimensionality of these data and discover metabolomic signatures associated with both prenatal PFAS mixtures and cardiometabolic outcomes in MIREC, replicating our findings using HOME. Specifically, we will: 1) characterize trajectories of the serum metabolome in the first 12 years of life; 2) identify features of serum metabolome trajectories in the first 12 years of life that predict adolescent cardiometabolic disease; 3) determine if metabolome features mediate the association of prenatal exposure to PFAS mixtures with adolescent cardiometabolic disease; and 4) determine the chemical identity of metabolome features discovered in Aim 3. This interdisciplinary proposal that includes epidemiologists, clinicians, biostatisticians, and chemists will efficiently leverage two ongoing cohort studies to address these timely aims. Ultimately, the proposed studies will have substantial impact by improving our knowledge of the health effects of PFAS, identifying novel metabolic alterations associated with PFAS mixtures and adolescent health, and improving our understanding of biological pathways affecting cardiometabolic disease. These results are critical to ongoing evaluations of PFAS toxicity and may help identify exposed populations at risk of cardiometabolic disease and potentially ameliorate the effects of PFAS exposure.

NIH Research Projects · FY 2025 · 2021-09

The WHO indicates 10% to 20% of children and adolescents have pediatric mental health disorders, contributing to a projected worldwide economic burden of $6 trillion by 2030. In RI, approximately 19% of children under the age of 17 have mental health challenges that can adversely affect their development, education, peer relationships, and physical health. Sleep is an increasingly recognized contributor to mental health and well-being. In children, inadequate sleep has been linked to diminished mental and physical health. Exposure to greenspace, broadly defined as various forms of vegetation, has been shown to confer numerous health benefits. In this study, we propose to explore the association between exposure to greenspace and mental health outcomes in elementary school children. Aim 1. Sleep and greenspace. Determine how green space utilization (GPS-derived measures of daily activity and environmental features) is related to sleep (duration, timing, regularity) in children. Hypothesis 1.1 Children spending more time in greenspace as derived by GPS (i.e., utilization) will have earlier, longer and more regular sleep than children spending less time in greenspace. Hypothesis 1.2. Greenspace utilization will influence sleep through increased light exposure, higher levels of physical activity measured using accelerometry, and lower levels of stress measured by IL-1 beta. Aim 2. Mental health, greenspace and sleep. Determine whether greenspace utilization is associated with mental health and wellbeing via sleep behaviors. Hypothesis 2.1: Children spending more time in greenspace will have fewer mental health symptoms as measured by validated PROMIS® measures of anxiety, cognitive functioning, psychological stress and wellbeing compared to children spending less time in greenspace. Hypothesis 2.2: Greenspace utilization will influence mental health and well-being through sleep behavior (duration, timing, regularity) assessed using actigraphy. Aim 3. Exploratory Aim. Greenspace, epigenetics, sleep and wellbeing. Explore the potential epigenetic contribution of greenspace on sleep and wellbeing in children. Exploratory Hypothesis 1.1. Patterns of differential DNA methylation between high and low greenspace users may differ in genes associated with stress response, inadequate sleep, light exposure, or physical activity. We will work in Rhode Island, which is currently engaged in expanding access to tree-canopy across the entire state – a unique designation in the US. Thus, the health and policy implications of our study is timely, and can have implications for other states interested in exploring the use green space to improve health among children and their families.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY We propose to develop and refine neural networks gene expression to understand gene regulation in diseases. We will design deep learning frameworks to integrate various datasets (histone modifications, 3D conformation, sequences, and SNPs) and model their relationship with the gene expression. Our proposed models will explicitly capture the underlying structure and complexity of the biological data to learn meaningful connections. For example, we will use a graph-based neural network to model the 3D conformation of the DNA as a graph and learn from the connections between different genomic regions to predict gene expression. One of our critical goals for using these methods is to extract relevant signals that could be contributing to the up- and down-regulation of genes. We will accomplish this goal by applying interpretation methods for neural networks. These methods will allow us to assign importance scores to the input features that contribute the most towards a particular prediction of interest. Comparing these scores for genes across healthy and disease cell lines will provide insights into gene misregulation and serve as a hypothesis driving tool for biological experiments. We also propose a novel Bayesian inference-based interpretation method to improve explanations of graph-based neural networks that could be applied to various tasks. Finally, given the improvement of single-cell technologies and imputation methods, we will extend our deep learning frameworks to model relationships between signals like chromatin accessibility and DNA methylation with gene expression. This direction will allow us to explore the effectiveness of the imputation methods in removing noise and generating high-quality single-cell samples for usage in deep learning modeling of gene regulation. Looking at the modeled relationships across the cell's developmental stages could pinpoint timepoints for potential misregulation in diseases. Therefore, this proposal aims to develop unified approaches that utilize datasets spanning multiple repositories to leverage their collective knowledge and improve our understanding of diseases in a data-driven manner.

NIH Research Projects · FY 2025 · 2021-09

Project Summary Extracellular vesicles (EVs) are critical mediators of intercellular communication, released by cells to transfer bioactive molecules like RNA, DNA, proteins, and lipids. In the context of cellular senescence, EVs play a crucial role in the senescence-associated secretory phenotype (SASP), helping senescent cells communicate with their environment. These vesicles can induce paracrine senescence, promoting inflammation and tissue remodeling in neighboring cells. EVs have been associated with various age-related diseases such as cancer, fibrosis, and neurodegeneration, where their cargo, including specific proteins and RNA, can serve as biomarkers for senescence, offering non-invasive diagnostic potential. The project aims to profile the RNA, DNA, and protein content of EVs from human blood, focusing on markers linked to senescence. We will isolate and sequence these molecules, particularly focusing on senescence- related markers like LINE-1 and pro-inflammatory cytokines. By using super-resolution microscopy (STORM), we will image individual EVs and analyze their cargo. The integration of this data with the broader benchmarking project, which also includes lung and skin tissue analyses, will provide insights into the role of EVs in senescence-related diseases. In Aim 1, RNA, DNA, and protein profiling will be conducted using sequencing and immunoassay techniques, while Aim 2 will involve imaging the content of individual EVs at super-resolution. This will help identify senescence markers, which can be used for further clustering and analysis of EVs. The expected outcomes include identifying enriched senescence markers in EVs and integrating this data with existing datasets to better understand the role of EVs in cellular aging and disease progression.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY The trypanosomatids cause a broad range of severe human illnesses across the entire world. The success of these parasites stems in large part from their ability to adapt their cellular morphology to suit the environments within their mammalian and insect hosts. The extensive range of observed cellular morphologies rely on a set of microtubules that underlie the cell surface, known as the subpellicular array. These microtubules are heavily crosslinked and remarkably stable, but very little is known about how the array maintains its organization or how it duplicates during cell division. During a recent proximity-dependent biotinylation screen in Trypanosoma brucei, we identified two proteins that are essential for shaping the array and assuring that it is duplicated correctly during cell division. The first, an orphan kinesin named Kinesin Localized to the Ingressing Furrow (KLIF), is essential for the segregation of the array into two distinct units at the end of cell division. KLIF is a very effective microtubule bundler in vitro, which suggests that its primary function is to organize microtubules within the array to form a new cell posterior by gathering microtubule plus-ends into a pole. The other, called Posterior And Ventral Edge Protein 1 (PAVE1) is a component of microtubule crosslinks present at the posterior portion of the array and is essential for tapering the array to produce the parasite’s distinctive shape. This proposal will use these proteins to understand how the subpellicular array is assembled and maintains its shape. In Aim 1, the precise track KLIF takes as it ingresses along the furrow will be established using super- resolution and live-cell microscopy. We will study the KLIF RNAi phenotype using EM and live-cell imaging to determine the specifics of the microtubule organizing defect. Full-length KLIF will be expressed to test its oligomerization state and function. In Aim 2, the microtubule-binding properties of PAVE1 and its interacting partners will be studied using biophysical approaches. PAVE1 preference for microtubule plus ends at the cell posterior will be probed using a pulse-chase strategy in conjunction with treatments that alter microtubule dynamics. In Aim 3, immunoprecipitation and proximity-dependent biotinylation will be employed to map the interacting partners of both KLIF and PAVE1 so that the pathways involved in subpellicular array biogenesis can be established. This work will further the fundamental understanding of how trypanosomatids establish and transmit their complex cellular morphologies, which are essential parts of their biology. Pathways involved in these processes that are unique and essential may be potential targets for further drug design.

NIH Research Projects · FY 2024 · 2021-09

PROJECT SUMMARY Brain circuits are dynamic networks of neurons that process information in the form of electrical and chemical signals to form memories and shape behaviors. To investigate how brain circuits instantiate fundamental computations underlying behaviors, we need to map their wiring diagrams coupled with functional analysis at cellular resolution. However, the electrical (voltage) and chemical (e.g. neuropeptides) signals are not directly visible, and current circuit tracing tools are insufficient for meaningful functional analysis. Using protein engineering this proposal aims to develop a toolbox of genetically-encoded fluorescent reporters and tracers specifically tailored to study neural circuits. At the electrical level, voltage sensors can image the precise timing of action potentials and subthreshold voltage not detectable by other means. However, even the latest voltage sensors do not perform well with high-resolution microscopes that use 2-photon illumination for imaging deep in the brain. To overcome these limitations, we are taking a two-pronged approach by evolving amino acids at the mechanistic heart of voltage sensor proteins and by using spectroscopy to aid our protein engineering efforts. We believe directed evolution will improve voltage sensitivity and 2-photon functionality >10 fold, enabling us to image currently invisible signals, like synaptic potentials, deep inside the brain. At the chemical level, neuropeptides are highly expressed in almost all cortical neurons, but their role and impact in animals can only be inferred because current detection methods, like microdialysis, are invasive and lack spatiotemporal resolution. We are using phage display to evolve nanobodies capable of recognizing neuropeptides and coupling their conformational changes to fluorescence changes from reporter molecules. These sensors will provide visualization of neuropeptide release at cellular resolution throughout an animal’s brain during behavior paradigms that mimic human health and disease states. At the cellular connectivity level, current tools for circuit- mapping, like rabies virus, exhibit substantial neurotoxicity, prohibiting meaningful functional analyses. We are engineering proteins with a natural propensity to assemble into structures capable of delivering a genetic payload to specific cells to produce more effective and less toxic tools to map and manipulate brain circuits. Effective and robust tools to map the brain will bridge functional and structural analysis and finally allow long- term studies of neural networks based on their connectivity. Overall, the optogenetic tools developed in this proposal will translate the chemical and electrical signals between neural circuits into fluorescence that can be easily measured. Consequently, they can be used to unravel the functional basis and causes of neuronal disorders at a level of detail that has not been accessible to date and empower us to develop novel treatments.

NIH Research Projects · FY 2024 · 2021-09

PROJECT SUMMARY Chitotriosidase (chitinase 1; Chit1) is the major true chitinase in humans. It can be found in the circulation of normal individuals and is further increased in a variety of diseases characterized by inflammation, tissue remodeling and/or fibrosis including bacterial or fungal infections, lysosomal storage diseases (Gaucher’s), sarcoidosis, chronic obstructive lung diseases (COPD) and interstitial lung diseases. However, specific role of Chit1 in the pathogenesis of these diseases have not been elucidated. Recently we reported that Chit1 augments the effects of transforming growth factor-β1 (TGF-β1), a critical mediator of tissue fibrosis in health and disease, contributes to the pathogenesis of interstitial lung disease associated with Scleroderma (SSc-ILD). However, the mechanisms that Chit1 uses to regulate fibrotic tissue responses and the importance of these mechanisms in idiopathic pulmonary fibrosis have not been clearly defined. In preliminary studies, we demonstrate that Chit1 enhances profibrotic macrophage activation, TGF-β1-stimulated fibroblast proliferation, myofibroblast differentiation, extracellular matrix gene expression and protein accumulation. Importantly, these effects are mediated by the ability of Chit1 to inhibit TGF-β1 induction of its feedback inhibitor, Smad7. Chit1 interacts with TGF-β receptor associated protein 1 (Tgfbrap1) and Forkhead Box O3 (FoxO3) with Tgfbrap1 playing a critical role in Chit1 enhancement of TGF-β1 signaling and effector responses and FoxO3 playing a critical role in TGF- β1 induction of Samd7. Through extensive drug library screening, we identified Kasugamycin (KSM) as a small molecule that strongly inhibits Chit1 enzyme activity and tested its therapeutic effect in bleomycin induced pulmonary fibrosis. In this evaluation, KSM showed an impressive anti-fibrotic effect in both preventive and therapeutic conditions. These findings led us to a hypothesis that Chit1 and its interacting partners are potential therapeutic targets for the intervention of pulmonary fibrosis and KSM can be developed as a new class of therapeutic drug for the patients with pulmonary fibrosis. To test this hypothesis, we will Aim 1. Define the specific role and mechanism of Tgfbrap1 in Chit1 mediated pulmonary fibrosis. Aim 2. Characterize Chit1 regulation of FoxO3 and Smad7 in TGF-β stimulated pulmonary fibrosis. Aim 3. Characterize the therapeutic use of Kasugamycin (KSM) as a Chit1 inhibitor in pulmonary fibrosis.

NIH Research Projects · FY 2025 · 2021-09

Abstract Bladder cancer is the second most common genitourinary malignancy in the US with approximately 80,000 new cases and 17,700 deaths each year. It is a heterogeneous set of diseases that range from locally treatable superficial tumors that are generally not life-threatening but require chronic management, to advanced disease that requires multimodal invasive treatments and has higher risk of distal metastasis and death. It is the ninth most expensive cancer overall in the US, and, per diagnosed patient, the most expensive cancer to manage. Risk factors for bladder cancer broadly include chemical and environmental exposures such as cigarette smoking and chemical carcinogens that are ingested or found in the workplace, as well as genetic abnormalities and chronic bladder irritation. Outcomes for bladder cancer have remained relatively stable in the last two decades. However, opportunities abound to improve the prevention, detection, and management of bladder cancer. The advent of novel biomarkers, and novel treatments, including immunotherapies (checkpoint inhibitors), gene therapies, and antibody-drug conjugates may have a large impact in coming years. Bladder cancer is amenable to population modeling because it has high morbidity, mortality, and cost, is likely preventable by minimizing smoking and toxin exposure, and the emergence of novel promising biomarkers and treatments. The long-term goal of our research program is to improve the effectiveness and efficiency of population- and person-level approaches to bladder cancer prevention, detection, and management given current knowledge and constraints. The overall objective of the current proposal is to address major questions in the surveillance, treatment, prevention, and diagnosis of bladder cancer by means of comparative mathematical modeling. We will address six specific aims: We will (1) complete the development, calibration, and validation of two independent population models of bladder cancer; (2) explain secular trends in bladder cancer incidence in relation to trends in tobacco use in key population subgroups and estimate the impact of the 1964 Surgeon General’s smoking recommendations; (3) assess the effectiveness of smoking cessation, reduction and prevention interventions for the prevention of bladder cancer incidence and mortality; (4) assess the effectiveness and cost-effectiveness of generic and tailored/patient-centric surveillance policies for patients with non-muscle invasive bladder cancer; (5) assess the comparative effectiveness of treatments for organ-confined bladder cancer; and (6) assess the effectiveness of screening for bladder cancer among high-risk subgroups.

NIH Research Projects · FY 2024 · 2021-09

Title: Dissecting epitranscriptomic signal from complex tissues PROJECT SUMMARY: “RNA epigenetics” or “epitranscriptomics” has emerged in recent years as an exciting and active research field to study post-transcriptional regulation of gene expressions. The RNA modifications play important roles in gene expression regulation, and are involved in neurodevelopment and a number of neurological diseases. Methylated RNA Immunoprecipitation Sequencing (MeRIP-seq) is a newly developed technology for transcriptome-wise profiling of the RNA epigenetic modifications. MeRIP-seq leads to an expansion of applications in both basic and clinical research, but faces a number of challenges in analysis with its unique data characteristics, including 1) the presence of technical artifacts due to sequence content and sample preparation procedures unique to MeRIP; 2) lack of appropriate methods for identification and comparison of RNA methylated regions; and 3) lack of methods to account for the heterogeneity of tissue samples. In this proposal, we will address these challenges and develop a series of novel statistical methods for MeRIP-seq data preprocessing and analyses. They include a data normalization procedure to remove technical bias, accurate and efficient methods for RNA methylation site detection and comparison, and signal deconvolution methods to draw cell type specific inferences based on data from tissue samples. All methods developed in this project will be implemented and released as free, open source software to benefit the epigenomics research community, including basic scientists working on genetics, epigenetics, gene regulation and cell development, as well as clinicians looking for disease biomarkers.

NIH Research Projects · FY 2026 · 2021-09

This project will design and launch the Puerto Rico Panel Study of Income Dynamics (PR-PSID), a longitudinal panel survey advancing the NIH mission by generating the first population-representative longitudinal data on health outcomes and differentials in health outcomes among Puerto Ricans, a historically underserved U.S. population. Puerto Rico has among the nation's highest rates of physician-diagnosed chronic conditions: hypertension, diabetes, coronary heart disease, asthma, arthritis, and cancer are all markedly elevated relative to U.S. states, and mental health and psychiatric conditions diagnosed by medical providers have worsened dramatically following Hurricane Maria, the 2020 earthquakes, and the COVID-19 pandemic. The PR-PSID questionnaire is comprehensive in its health coverage, capturing: physician-diagnosed chronic conditions (stroke, heart attack, coronary heart disease, hypertension, asthma, chronic lung disease, diabetes, arthritis, cancer, memory loss, learning disorders, and emotional or psychiatric conditions) with medication and treatment status; ADL and IADL functional disability scales; a reproductive and maternal health module covering contraceptive use and method, pregnancy intentions, prenatal care access, delivery payment source, and breastfeeding; and childhood health histories from birth through age 18. Gathering data on these indicators will support research into the developmental origins of chronic disease across the life course and help identify intervention points for solutions to reduce chronic disease rates in Puerto Rico. PR-PSID will adapt instruments, sampling procedures, and fieldwork protocols from the Panel Study of Income Dynamics (PSID), producing data directly comparable to U.S. PSID data and enabling longitudinal research on differentials in health outcomes, the Hispanic health paradox, and the health consequences of migration, disaster exposure, and poverty across the life course. Our three specific aims are to develop survey instruments and a sampling frame; pilot test the questionnaire and protocols; and implement the baseline wave and distribute data free of charge to the research community. PR-PSID will be the only representative family panel survey in Puerto Rico capturing the full range of health, social, economic, and demographic processes, and its public-use data will fill a critical gap in Puerto Rico's health research infrastructure, informing interventions to reduce differentials in health outcomes and improve health for this historically underserved U.S. population.

NIH Research Projects · FY 2025 · 2021-08

Many people in recovery from opioid use disorder (OUD) experience barriers to treatment access, low social support, and high psychosocial stress. Peer support is a key component of many evidence-based OUD recovery programs: it improves recovery capital, improves treatment engagement, improves perceived social support, and reduces psychosocial distress, particularly when used in conjunction with other evidence-based treatments such as medication for opioid use disorder (MOUD). This grant, submitted in response to PA 20-237, therefore proposes a randomized controlled trial of a novel mobile peer support app platform among a national sample of 1300 patients in recovery from OUDs, as an adjunct to usual care. Our previously piloted online-only recruitment and follow-up strategy – in which we meld patient-reported outcomes with administrative datasets – allows strategic recruitment of often-excluded participants from across the United States, including those facing the highest barriers to treatment. The mobile app-based peer support intervention, provided as an individual-level enhancement of existing treatment and recovery programs, will allow individuals in OUD recovery to access a tailored, anonymous, peer-moderated support group 24/7. The app is augmented with natural language processing tools capable of automatically ‘flagging’ critical or clinically relevant content, thereby creating a scalable system to keep groups safe and constructive. Participants will be followed for 6 months through both self-report and administrative outcomes. The study’s primary outcome is self-reported recovery capital, complemented by objectively measured administrative data on retention in treatment programs from our community and governmental partners in a sub-sample of 650 patients from RI and IN. Hypothesized secondary outcomes are mitigation of psychosocial distress, including depressive symptoms, stress, and loneliness, as well as objective adverse events of emergency department visits and opioid overdoses. Finally, we will explore whether state- and county-level variables moderate efficacy. SIGNIFICANCE: OUD is a major public health problem. If this mobile app demonstrates efficacy among a large national sample of patients, it has the potential to augment existing treatment programs and improve recovery capital.

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY Cognitive control allows us to flexibly guide our actions based on our goals. Central to most prominent theories of cognitive control is the control representation. For control to be successful, this representation is maintained in working memory by the prefrontal cortex (PFC) where it allows the same input to map to different responses depending on the context. Convergent evidence has found that the PFC encodes multiple task-relevant features of a task. However, little is known about the computational features of these control representations based on how they organize this information. This is a fundamental gap in our understanding. Here we focus on one such property, termed representational dimensionality. In technical terms, representational dimensionality refers to the number of axes needed to explain the variance in activity of a neural population across its inputs. Theoretical neuroscience has demonstrated that the dimensionality of a neural population determines a fundamental computational trade-off. A low dimensional representation will discard irrelevant information and form abstractions over its inputs. It is therefore suitable for generalization to new situations. A high dimensional representation encodes multiple mixtures of inputs into highly separable firing patterns without overlap. Understanding how generalizability and separability relate to cognitive control function promises gains on some of the most fundamental problems in control, including context-guided behavior, interference resolution, multitasking, and controlled-to-automatic behavior. The goal of this research program is to link the computational properties of high dimensional control representations to cognitive control function. Our overall hypothesis is that PFC forms high dimensional representations of task features which are needed in behavioral circumstances benefitting from separability. This hypothesis is motivated by theoretical neuroscience and foundational studies that have tested the dimensionality of PFC representations in animal models. However, no study in humans has studied high dimensional codes in PFC and no evidence in any species links dimensionality to cognitive control function. Through an NINDS R21 (NS108380), we have developed and refined two novel, complementary methods for estimating representational dimensionality from fMRI and EEG data. Using these approaches, we have found preliminary evidence that the dorsolateral PFC (DLPFC) forms a high dimensional code relative to other brain areas. We also find evidence from EEG that separability of high dimensional codes improves efficient, flexible behavior and may aid stable readout. Thus, we build on these initial observations to establish the nature, functional significance, and temporal dynamics of high dimensional control representations in the human brain.

NIH Research Projects · FY 2024 · 2021-08

ABSTRACT Artemisinin combination therapies (ACTs) are the mainstay antimalarial treatment combating Plasmodium falciparum malaria around the world. While resistance is widespread in Asia, it has not yet been observed in Africa where the majority of the global morbidity and mortality occurs. Artemisinin and ACT resistance in Africa would be a serious setback as there are no next-generation antimalarials ready for deployment. Recent reports in Rwanda of validated artemisinin resistance are of grave concern. A recent therapeutic efficacy study in Rwanda found a high prevalence of patients with delayed parasite clearance, which was associated with a validated artemisinin resistance mutation R561H in the K13 gene. Thus, it appears Africa is moving closer to fully formed resistance, as seen in Southeast Asia. New evidence shows that this mutation has arisen within Africa and was not spread from Asia, and thus, represents biology unique to Africa. Given the potential devastating consequences of frank artemisinin resistance spreading across the continent, this proposal is designed to improve our understanding of the mutation and its biology, its origin, its past and ongoing spread and the factors that impact the spread. Understanding these dynamics is critical to predicting the long-term effectiveness of ACTs and to evaluating and formulating effective control efforts. In this proposal the first goal is to understand the extent of spread and how quickly it is changing with time. We will leverage an extensive collaborative network within Rwanda and in surrounding countries to perform large scale sampling and genomics studies across Rwanda and neighboring areas in other countries over time to map and study the spread of resistance. This will be accomplished using high-throughput targeted sequencing allowing us to genotype tens of thousands of samples. Using the generated rich genotyping and spatial data, we will also ask questions about parasite migration and factors that may be impacting the spread. Our second goal is to look for other mutations that may further support resistance to artemisinin or partner drugs. Based on our knowledge from Southeast Asia, there are often compensatory mutations that increase the fitness of artemisinin resistance mutations in K13. To detect compensatory mutations we will perform genome wide association studies and longitudinal analyses. Our third goal is to study the relative fitness of mutant and wild type parasites examining mutant and wildtype parasites in vivo using new statistical methods to examine polyclonal infections; and in vitro competition assays, as well as mosquito feeds, to examine differences in fitness in both the human blood stage and during transmission. Our final goal is to use the information from the above aims to build a model and predict the future spread of resistance. Together, this study will provide a comprehensive view of evolving resistance in Rwanda and provide actionable information for public health.

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY Substance use (SU) is most commonly initiated during adolescence. Earlier age of onset is associated with more significant and persistent adverse outcomes, such as impaired psychosocial and educational functioning, myriad health consequences, and long-term struggles with SU and addiction — underscoring the critical need to identify and intervene on SU as early as possible. Thus, the public health need to increase availability and quality of evidence-based interventions for adolescents (ADOL) who are using substances cannot be overstated, especially in Rhode Island where ADOL are not receiving substance use disorder treatment that they need at higher than national averages. This proposal not only aims to increase access to interventions for ADOL using substances but also improve brief interventions for ADOL by co-addressing pain in an innovative pre-surgical context. Acutely painful procedures, such as wisdom tooth extraction, are an opportune time to identify SU behaviors and engage ADOL in brief intervention due to shared risk factors between SU and pain and the potential for exposure to prescription opioids. Aim 1 is to adapt and integrate pre-existing evidence- based brief interventions for adolescent SU (MET-CBT) and acute pain coping (CBT) into a pre-surgical brief intervention (PS-BI) for ADOL and their parents. PS-BI will be developed by the PI and her interdisciplinary mentorship team in conjunction with feedback from key informants (e.g. ADOL, parents, and dental providers). Aim 2 will evaluate PS-BI in a pilot randomized controlled trial (RCT) versus a control condition of current best practice among ADOL (age 15-18 years) who use cannabis (and other substances) undergoing wisdom tooth extraction. Key outcomes for the pilot RCT (Aim 2) are feasibility and acceptability. Ecological momentary assessment (EMA) methods will be used to elucidate associations between pain, craving, and SU (Aim 3) and explore if those associations are attenuated by PS-BI (Exploratory aim). This will be the first test of within- person associations of hypothesized precursors (e.g., pain intensity), substance craving, and use in the perioperative context among ADOL who use substances. A highly structured training plan will ensure execution of the proposed research aims. Specifically, the PI will receive advanced training in (1) intervention development and clinical trial methods, (2) integrated SU interventions for ADOL, (3) EMA, (4) advanced statistical approaches, including longitudinal data analysis, and (5) mentoring and leadership skills to combine with her expertise in pediatric psychology, interdisciplinary collaboration in medical settings, and pediatric pain. Training will be guided by a stellar mentorship team with highly relevant expertise and long-standing track records of successful mentorship. The proposed research and training plan is further supported by the rich training environment at the Center for Alcohol and Addiction Studies at Brown University. Through this K23, the PI will obtain specialized training to launch her independent research focused on developing, evaluating, and implementing innovative interventions for adolescent SU and pain in integrated care settings.

NIH Research Projects · FY 2025 · 2021-07

PROJECT SUMMARY SKILLS TO ENHANCE POSITIVITY IN ADOLESCENTS AT RISK FOR SUICIDE Rates of suicide and suicidal behavior in adolescents have been steadily increasing over the past two decades. Unfortunately, reviews of published randomized controlled trials (RCTs) for adolescent suicidality conclude that treatments to date have been minimally efficacious, particularly when compared to adult trials. The preponderance of interventions focus on crisis intervention, underling psychiatric disorders, regulating negative affect, and reducing cognitive distortions. However, our pilot work and other recent data suggest the importance of considering how low positive affectivity may be a mechanism that contributes to suicidal behaviors independent of other risk factors. Therefore, we developed an intervention, Skills to Enhance Positivity (STEP; MH R34101272), premised on the Broaden and Build theory of positive affect, to increase attention to, and awareness of positive affect and experiences. Results from our pilot RCT (N=52) with inpatient suicidal adolescents found that compared to a Healthy Habits / Enhanced Treatment as Usual (ETAU) condition, those randomized to STEP had 50% fewer individuals reporting a suicidal event, 50% fewer suicidal events overall, and a larger decrease in participants reporting active suicidal ideation (SI) over follow up (49% STEP vs. 19.2% ETAU). STEP also appears to have engaged the target mechanism as STEP participants had faster reaction times to positive probes on an attentional bias task compared to ETAU, and only those in the STEP condition reported significant pre-post differences on gratitude and satisfaction with life. These promising results in which we were able to demonstrate engagement of the target (positive affect) and a decrease in clinical outcomes (suicidal events) suggest the need to test the clinical effectiveness of STEP by having clinical staff implement the intervention. Furthermore, recognizing the need to speed translation, we propose a Hybrid Type I Effectiveness-Implementation design. Specifically, we propose to test the effectiveness of STEP in reducing suicidal events and ideation in 216 adolescents, admitted to inpatient psychiatric care due to suicide risk. Participants will be randomized to either STEP or ETAU. STEP involves 4 in-person sessions (3 individual, 1 family) focused on teaching psychoeducation of positive and negative affect, mindfulness meditation, gratitude, and savoring. Digital health messages with mood monitoring prompts and skills reminders will be sent daily for the first month post-discharge and three times a week for the following two months. ETAU condition will receive daily reminders to log into a safety resource app. We hypothesize that those randomized to STEP (vs. ETAU) will have less suicide events, ideation, and depression, and experience increased positive affect and attention to positive affect, and decreased negative affect, and attention to negative affect, as measured by implicit tasks and self-report measures. Effectiveness aspects of the design include using clinical staff as interventionists and having very few exclusion criteria for participation. Implementation aspects include data to inform strategies to increase uptake in real world practice.

NIH Research Projects · FY 2025 · 2021-07

SUMMARY Changes in reproductive hormones across the menstrual cycle may be a key biological source of symptom variability in psychopathology. Strong individual differences in neural sensitivity to normal hormone changes can result lability of a wide range of emotional, interpersonal, and behavioral symptoms; however, the biobehavioral mechanisms underlying these effects are not yet well understood. Borderline personality disorder (BPD) is a severe and costly psychiatric condition comprising labile symptoms across many domains of functioning. Our pilot data suggest three distinct biologically based mechanisms may produce cycle-based symptom exacerbation, contributing to symptom lability: 1) reactive and interpersonal symptoms due to irritability from changes in progesterone (P4) levels, 2) depressive symptoms due to impaired cognitive functioning and increased rumination during estrogen (E2) withdrawal, and 3) risk-taking symptoms due increased reward responsiveness during E2 peaks (ovulation). The objectives of this research are to test a model of three RDoC-consistent biologically-based mechanisms underlying how the menstrual cycle exacerbates psychopathology. A sample of 170 women ages 18 to 45 with ≥3 BPD symptoms will be recruited from specialized clinical services and social media. Participants will be comprehensively assessed for BPD and exclusion criteria (e.g., use of hormone-based medication or hormonal conditions). Participants will complete well-established assessment measures of BPD and other psychopathological symptoms and diagnoses during a baseline laboratory visit within the within the first few days of the start of their menstrual cycle. Then, they will provide complete questionnaires about BPD symptoms and proposed mechanisms every evening for two complete cycles. During one cycle, they will complete tasks targeted to key cycle phases, based on menses onset and ovulation test results, and daily urine samples for hormone assay each morning. Specific Aims. Aim 1 is to evaluate whether shifts in hormones across cycle predict within-person changes in symptoms consistent with proposed triadic hormone sensitivity theory, with rising levels of P4 predicting increases in rejection sensitivity, interpersonal conflict, and impulsive reactivity to stress, decreasing levels of E2 predicting increases in depression, hopelessness, and suicidal ideation, and peaks in E2 (ovulation) predicting increases in proactive aggression and substance misuse. Aim 2 is to evaluate whether proposed psychological mechanisms mediation associations between hormonal changes and symptom effects, with increased irritability expected to mediate P4 effects, decreased cognitive functioning expected to mediate E2 withdrawal effects, especially for individuals with greater rumination-proneness, and increased reward responsiveness expected to mediate ovulatory effects. An exploratory Aim 3 will examine the extent to which presence of these three forms of hormone sensitivity are associated. Findings will inform development of individualized, transdiagnostic interventions to mitigate the impact of cycle-based symptom exacerbation.

NIH Research Projects · FY 2025 · 2021-07

Participation in regular physical activity (PA) has numerous health benefits including reduced risk of all-cause mortality,1-7 cardiovascular disease,8-12 diabetes,13-16 and cancers of the breast17-19 and colon,20-23 as well as energy balance.24 However, only 54% of U.S. adults meet national guidelines of expending > 1000 kcals/week through PA,25 and as few as 10% meet guidelines when objective assessments of PA are used.26 Thus, there is a need to improve adherence to PA programs using innovative approaches. Economic incentives have been shown to be powerful motivators for behavior change and for improving health outcomes.28-37 While there is evidence suggesting the general efficacy of incentive programs for increasing PA,38 research has not yet demonstrated the optimal format for incentive programs. Nonetheless, spurred by organizational incentives (i.e., tax breaks) provided by the Affordable Health Care Act, major insurance companies are now offering economic incentives for regular attendance at fitness facilities in the absence of empirical support. Thus, we propose to conduct an RCT to examine the efficacy of the exercise incentive program currently offered by three major US insurance companies39-41 consisting of a $200 rebate on fitness facility membership fees for at least 50 confirmed visits to the fitness facility (maximum 1/day, verified by objective swipe-card data) over 6 months. In the context of the RCT, we will also compare the insurance-based standard incentive program to a second, loss-frame incentive condition in which the same incentive schedule is used, but with participants told (and reminded during the course of the program) that $200 of their membership fee is being held and will be returned or forfeited depending on whether they use the gym at least 50 times in the next 6 months. The proposed RCT will be conducted in a community setting at the Greater Providence YMCAs. Aim 1. Conduct an RCT (N=330) comparing (a) the widely used insurance-based Standard incentives program (n=110), (b) a Loss-framed incentive program (n=110), and (c) no-incentive Control (n=110). Each participant will be enrolled for two consecutive 6-month periods for a total of 12 months per participant. The primary outcome will be number of visits to the fitness facility. Secondary outcomes will include total moderate-to-vigorous PA (MVPA) over 7-day periods at 3-month intervals through accelerometers and self-reported MVPA. We hypothesize that the two incentive conditions will result in higher attendance at the YMCA and more PA, with the Loss-framed incentive program outperforming the Standard insurance-based program. Aim 2. Examine habit formation and anticipated regret as putative mediators and household income and age as moderators of the incentive-based programs. Aim 3. Conduct a within trial cost-utility analysis from a societal perspective to quantify (a) the incremental costs per quality-adjusted life year (QALY) gained, (b) cost per change in YMCA attendance, and (c) cost per incremental change in PA. We will additionally apply a productivity model to estimate the economic impact of the intervention on future household and labor force participation.

NIH Research Projects · FY 2025 · 2021-07

Taylor, Martin | K08 (PA-20-203) | PROJECT SUMMARY / ABSTRACT This proposal details a five-year training plan for the development of a research program focused on elucidating structural, mechanistic, and allosteric determinants of mTOR Complex 2 (mTORC2) signaling. Phosphorylation of the signaling kinase Akt on Ser473 by mTOR Complex 2 (mTORC2) is a critical regulated intracellular step in insulin and other growth factor signaling. Ser473 phosphorylation activates Akt and is required for Akt’s downstream metabolic effects, such as glucose transporter upregulation, which are dysregulated in diabetes, and proliferation and growth, which are dysregulated in cancer. Therapeutic modulation of mTORC2 is therefore of interest in the treatment of both diabetes and cancer but is not yet possible due to similarities between mTORC2 and the better-understood effector complex mTORC1, which shares key components mTOR and mLST8. mTORC2 also activates other substrates with less-defined roles in ion channel homeostasis, apoptosis, cell motility, metastasis, and insulin receptor sensitivity, and its activity is modulated by a series of allosteric interacting proteins including the small GTPases Rho and Ras. However, despite the central role of mTORC2- Akt signaling, we have little information about how this critical reaction is catalyzed by mTORC2, how mTORC2 recognizes Akt and other substrates, or how these interactions are modulated allosterically. This project therefore seeks to develop a detailed structural and mechanistic understanding of mTORC2 recognition of its substrates, using novel enzymologic assays, protein engineering, and a combination of biochemical, chemical, proteomic, and structural biology approaches that will also develop proof-of-concept inhibitors and potentially activators of mTORC2. My proposed studies will: (i) provide detailed structural and mechanistic insight into mTOR Complex 2 kinase signaling (ii) develop tools, reagents, and techniques applicable to other systems of interest, including mTORC1 (iii) provide ample opportunities for mechanistic and translational follow-up for my transition to independence. I am a practicing gastrointestinal pathologist and physician scientist seeking K08 support for mentored research under the guidance of Dr. David Sabatini and Dr. Philip Cole. This mentored period of 80% research and career development and 20% clinical time will ensure I acquire the skills required to become a successful independent principal investigator. Drs. Sabatini and Cole are internationally recognized mentors, together training ~40 successful independent investigators. My training will occur at two world-class institutions, the Whitehead Institute for Biomedical Research, and Massachusetts General Hospital Department of Pathology. Both are rich with opportunities for young scientists to train, pursue highly impactful science, and foster long-lasting collaborations. I will also be guided by a committee of researchers that are all leaders in their fields: Dr. Joseph Davis (MIT, structural biology of large protein complexes and cryoEM data analysis) and Dr. Yi Shi (University of Pittsburgh, crosslinking mass spectrometry as applied to large protein complexes and nanobody generation). The support of this K08 award will allow me to focus on maturing my research and strengthening my career development during this critical last stage of mentored training. At the conclusion of my award period, I will be optimally positioned for achieving success as an independent physician scientist.

NIH Research Projects · FY 2025 · 2021-07

SUMMARY When selecting cancer therapy, physicians generally begin with first-line treatment options and monitor patient progress on a watch-and-wait basis, following a set of guidelines based on clinical trials from a large patient population. But this traditional method has been questioned on whether it provides individual patients with the optimal treatment. To better find a matching treatment individually, a concept called precision cancer medicine or personalized cancer medicine has been studied. Among other approaches, functional precision medicine directly tests chemotherapy options on tumor cells biopsied from a patient to find the best matching treatment for the specific patient. This promising approach, however, has not been widely adopted by clinicians because the tumor microenvironment in a lab differed from the one within the patient’s body, leading to inconsistent drug responses between the sample and patient, and the quantity of biopsied cells is generally insufficient for a reliable number of options to be tested. The first problem is being addressed by recent advances in three- dimensional (3D) cell culture techniques, which better mimic the body’s microenvironment in a lab. But the second problem, the limited number of testable options, is mainly due to limitations in the current assay techniques that assess chemosensitivity in 3D culture. With most current assays, a sample can only be tested once, and multiple drugs with different mechanisms of action cannot be simultaneously tested by a single assay. Combined, these limitations exponentially reduce the number of testable options when involving multiple assessment time points to design a sequential therapy or when increasing the number of drugs to test a combination therapy. Here, we will develop a new technique for the assessment of chemosensitivity in 3D culture, by maximizing the potential of a label-free 3D microscopy technology, called optical coherence tomography (OCT). The majority of prior OCT research measured only one or two types of signals and showed the signals corresponding to only a single type of cell viability disruption process in each study. But this approach has led to a concern about specificity (i.e., other types of processes than the one tested in the study can generate similar OCT signals). This low specificity, along with unclear mechanisms of viability assessment, have prevented OCT methods from being adopted for the promising concept of functional precision medicine. Therefore, we will develop at least 18 different types of OCT signals and establish their sensitivity and specificity to four major types of viability disruption processes. The feasibility of this approach has been strongly supported by a pilot study where we imaged and analyzed more than 6,000 3D-cultured cell spheroids. This R01 project will image and analyze up to 100,000+ spheroids for an unprecedentedly systemic investigation of the comprehensive range of OCT signal types.

NIH Research Projects · FY 2025 · 2021-07

PROJECT SUMMARY/ABSTRACT Background: Male sex workers (MSWs), or men who exchange sex for money, goods, drugs, or other items of value with other men, are at exceptionally high risk for HIV infection. Pre-exposure prophylaxis (PrEP) is effective at reducing HIV acquisition among HIV uninfected individuals, but its efficacy is highly dependent on uptake and excellent adherence. However, uptake of and adherence to PrEP among those who might benefit the most from using PrEP, such as MSWs, remains suboptimal. A successful PrEP uptake and adherence package must be responsive and tailored to MSWs’ distinct psychosocial and contextual circumstances. Overview of Proposal: The current proposal is a culmination of over 10 years of research with this population, including qualitative research, epidemiological assessments and programmatic work. These formative data led to an NIMH-funded R34 (MPIs: Biello, Mimiaga, Chan), which allowed our interdisciplinary team and community partners to collaborate on the development and pilot testing of a theory-based intervention— “PrEPare for Work”—to address 1) access to and uptake of PrEP at local PrEP clinics/providers via strength- based case management using principles of motivational interviewing (e.g., focusing on values, strengths and change efforts, making reflective and empathetic statements), and 2) provide cognitive-behavioral therapy- informed PrEP adherence counseling (e.g., problem-solving skill-building) with personalized, daily text message reminders to optimize PrEP adherence among MSWs. The pilot RCT demonstrated the feasibility, acceptability and preliminary efficacy of “PrEPare for Work”. Conceptual Model: The “PrEPare for Work” intervention is based on Social Cognitive Therapy (SCT), which specifies a core set of mechanisms that influence health behavior with a primary emphasis on self-regulation and self-reflection, including self-efficacy. Overview of Study Design: We now propose to test the efficacy of the “PrEPare for Work” package in the Greater Providence area and in Los Angeles County using a two-stage randomization design. Stage 1: 500 MSW will be equally randomized to receive either the “PrEPare for Work Stage 1 intervention” (strength-based case management and facilitated PrEP linkage) or standard of care to evaluate successful PrEP uptake (verified by real-time tenofovir urinalysis; prescription data) within 2 months. Stage 2: those who initiate PrEP (n~156; ~55% from Stage 1 intervention arm and ~20% from Stage 1 SOC arm) will be equally re-randomized to the “PrEPare for Work Stage 2 intervention” (1-on-1 skills training, problem solving, and motivational interviewing adherence counseling and personalized, daily text messaging reminders) or SOC to assess PrEP adherence (tenofovir concentration in hair sample) and retention in PrEP care (appointments attended) over 12 months. We will also examine the degree to which improvements in PrEP uptake and adherence occur in the context of the conceptual mediators (e.g., PrEP motivation, self-efficacy) and moderators (e.g., race/ethnicity, substance use, perceived HIV risk) of the intervention. Intervention cost-effectiveness will be assessed.

NIH Research Projects · FY 2025 · 2021-07

The goal of understanding psychiatric disorders and advancing psychiatric treatments requires basic knowledge of not only what environmental, genetic and epigenetic factors underlie function and dysfunction, but also how these factors alter the circuit-level computations that are the proximal neural events to behavior. The advent of research in this area holds the promise of linking core computations of neural circuits to complex human behavior, with the ultimate goal of developing comprehensive, multilevel transdiagnostic models of neuropsychiatric disorders. Consequently, the emerging field of computational psychiatry is central to the NIMH mission. Despite its importance, there are very few opportunities to pursue training in this area. Consequently, the proposed training program seeks to take recent PhDs, with strong backgrounds in fields such as neuroscience, engineering, applied math, and computer science, and provide them with the tools to make important contributions to the nascent field of computational psychiatry. The proposed Training Program in Computational Psychiatry (TPCP) will take place at Brown University where there is a critical mass of basic researchers on the main campus and clinical researchers in the Department of Psychiatry and Human Behavior to conduct such a training program. We propose enrolling six fellows (3 per year) in the TPCP with the goal of training, more efficiently and effectively, nonclinical research fellows capable of collaborating with clinical researchers to advance knowledge of psychiatric disorders and treatments. The program embraces an apprenticeship model in which fellows work with a primary research trainer in a computational field and a secondary research mentor in clinical psychiatry. In this apprenticeship model, the trainer works closely with the fellow and a secondary clinical psychiatry mentor, who is conducting research in areas such as neuroimaging, neurostimulation, and digital phenotyping. These research areas are especially conducive to addressing important issues in computational psychiatry, whether they be model/theory-driven or data-driven. The proposed didactic program will include both core seminars and an individualized curriculum including fellow-selected courses in neuroscience, computer science, engineering, applied mathematics, or psychiatric disorders. All fellows attend core seminars on grant writing, responsible conduct of research, and rigor and reproducibility. The short-term final product is an NIH grant application on a computational psychiatry topic. The long-term goal is to produce a new cohort of academics who can conduct research in computational psychiatry and train the next generation of graduate students in this emerging field of inquiry.

NIH Research Projects · FY 2025 · 2021-07

PROJECT SUMMARY: POSTDOCTORAL TRAINING IN SUICIDE RESEARCH Suicidal behavior is a major public health problem with over 47,000 deaths by suicide in the United States in 2017 and over 1,400,000 suicide attempts. Unfortunately, rates of suicide deaths and attempts have increased in recent years. There have been multiple calls for increased research on all aspects of suicidal behavior ranging from basic experimental to clinical trials to implementation efforts. Yet the cadre of researchers necessary to conduct this vitally needed research is limited. There is currently only one other T32 postdoctoral training program focused exclusively on suicide research, with only six training slots. Thus, there is a pressing need for more training in suicide research. Brown has a established cadre of suicide researchers including 10 senior level researchers, as well as 5 junior level suicide researchers. These faculty’s research focus covers a broad range of suicide research, spanning basic and predictive research, intervention, and implementation science. Other faculty at Brown offer a wide range of expertise in research areas that are highly complementary to important questions in suicide research, such as sleep, genetics, implementation science, big data, and statistics. Our faculty has extensive experience training new investigators; one of the MPIs of this application (Dr. Miller) led a very successful T32 (T32MH067553) in “Treatment Research” for 10 years. Other senior investigators have successfully mentored a number of postdoctoral fellows. Finally, Brown has a well established and successful infrastructure for research training, including five other NIH funded T32 programs (none of which focus of suicide). This postdoctoral training program will be directed jointly by Drs. Ivan Miller and Lauren Weinstock. Drs. Miller and Weinstock are established investigators with a history of conducting suicide research. With a plan to enroll three new postdoctoral fellows (PhDs and MDs) per year for a 2-3 year postdoctoral fellowship experience, the research training plan will be based on the apprenticeship model. Based on the fellow’s interests and overlap with faculty’s expertise, each fellow will be assigned to a senior suicide researcher as a Primary Mentor. Each fellow will also have a Co-Mentor, either a junior suicide researcher or a senior researcher with complementary expertise. Developed collaboratively between fellow and Mentor(s), the research training program will typically include five components: (1) supervised participation in the ongoing work of an established research team led by the primary mentor; (2) development of an independent research application to be submitted by the end of the first training year; (3) participation in a formal didactic program including seminars on suicide research, research design, and ethics; (4) data analysis and manuscript preparation from existing faculty data; and (5) an independent research project conducted over two years, supervised by the primary mentor, that will include formulation of the question, data analysis, and manuscript preparation.

NIH Research Projects · FY 2025 · 2021-07

Enter the text here that is the new abstract information for your application. This section must be no longer than 30 lines of text. The Graduate Program in Molecular Pharmacology & Physiology is a small  program with a strong set of courses and activities, as well as extensive mentoring mechanisms.  Leadership of the program is by a group of three accomplished MPIs with complementary strengths and expertise that guarantee effective oversight of the program. The request is for 4  T32 slots per year; the total number of students in the program is 20. This training program in  "Interdisciplinary Training in Pharmacological Sciences" will replace our current NIGMS  pharmacology T32, ending in June of 2021. The training in our program focuses on fundamental  principles of pharmacology, rigor and reproducibility, and cutting-edge quantitative methods. Our  trainees participate in many activities that promote interaction, collaboration and professional  development. Here we propose a number of new initiatives in the curriculum, professional  development, program oversight and recruitment. A recent innovative initiative we are developing in the program is the establishment of summer internships at Pfizer pharmaceutical company  labs; these internships will give our trainees the unique opportunity to experience first-hand the  scientific environment in a pharmaceutical company and make informed decisions for their future  careers. Our current admissions and recruitment practices have yielded a group of students with broad interests in the field and retention for the program overall is 95% over the last 15 years.  The career outcomes of the students are excellent, with 52% of students staying in academia  (25% faculty, 27% currently postdocs) often at top institutions, about 25% as scientists in  pharmaceutical or biotechnology companies, and the remainder in a variety of science and  medicine-related careers. Thus, our program has been training a group of students with broad interests in the field who have become successful in different areas of science; the new initiatives proposed in our  T32 application will further enhance our unique program and improve the quality of the training.

NIH Research Projects · FY 2025 · 2021-06

Project Summary We have been successful at isolating primordial germ cells (PGCs) from echinoderms at different times in their developmental progression. We are now in a position to test the interactions of PGCs with specific elements of their environment to determine how they become the gametogenic stem cells. A strength of this model system is an ability to analyze PGC in vivo, and to compare the different mechanisms between sea urchins (an acquired system of specification) and sea stars (an induced system of specification). Culturing them both gives us strong leverage in analysis. We have attempted benchtop culture, manipulations, and passages, with little success. These cultures quickly become contaminated and the expensive media and isolation success is for naught. The research supported by this request is focused on understanding the mechanisms of formation of primordial germ cells during embryogenesis, how they form during early development, and how they regenerate when the originals are removed. Our work leverages embryos from a sister group to chordates – the sea star and sea urchin. While not common organisms for biomedical research, these echinoderms have many strategic benefits for revealing unique perspectives in the biology of germline formation and regeneration. Millions of synchronous embryos from a single male/female cross allow biochemical and metabolic analysis of the germline, the resultant embryos have ideal transparency for in vivo longitudinal imaging, they develop rapidly, are easy to manipulate (single cell drop-mRNA-seq, optogenetics, cell and tissue transplantations) and they are well suited to complementary gene perturbation approaches (CRISPR/Cas9, morpholino antisense oligonucleotides, MASO), and small molecule perturbations. The existing deep genomic and reagent resources for these animals, coupled with their tractable experimental characteristics, yields a unique system for understanding primordial germ cell biology with defined molecular and morphological endpoints, in live embryos with longitudinal analysis, distinct metrics of quantitation, and transgenerational evaluations.