Stanford University

NIH Research Projects · FY 2024 · 2022-09

PROJECT SUMMARY AND ABSTRACT Chronic opioid usage after surgery is a major contributor to the opioid epidemic, which poses a major crisis in public health. 51 million patients undergo surgery each year in the United States. Between 9-13% of surgical patients continue chronic use of opioids, leading to opioid use disorder in 8-12% of cases of chronic use. However, under half of surgical patients report adequate postoperative pain relief, which hinders recovery, increasing mortality, and length of stay. Best outcomes require personalization of treatment from patient to patient, accounting for the detrimental effects of both excessive opioid administration and uncontrolled pain. However, current clinical guidelines on pain management do not provide clear guidance on how best to adjust courses of treatment. Moreover, assessment of pain is reliant upon patient self-report, and is hindered when patients are sedated or have altered mental status. This project seeks to quantitatively understand the relationships which govern the efficacy of post- operative pain management strategies, and to characterize how different real-time physiological measures may be used to assess pain and opioid requirements. This will be accomplished through the analysis of a large dataset of electronic health record data from over 100,000 surgical procedures performed at Massachusetts General Hospital, as well as intraoperative electroencephalogram (EEG) recordings for a subset of several thousand of these procedures. Aim 1 of this project is to model analgesic response to opioids, identifying cases of excessive as well as inadequate opioid usage. We propose to model pain evolution over time using neural ordinary differential equation models, and to use learned dynamics to compute optimal treatment policies. Aim 2 of this project is to identify cases where can be improved through usage of non- opioid treatment modalities. This can also be accomplished through modeling of pain dynamics, or through statistical analyses of the outcomes of cohorts of patients receiving different treatment modalities. Aim 3 of this project is to compute intraoperative correlates of postoperative pain state from EEG data. Signal processing methods as well as deep learning will be used to extract features from EEG data related to sedation, loss of consciousness, and pain. We will also study the relationship between intraoperative interventions and postoperative outcomes. This project has the potential to reduce excess opioid usage and improve pain management, improving post-surgical clinical outcomes and reducing the incidence of opioid abuse disorder. Our results will also provide the ability to objectively assess pain and treatment requirements.

NIH Research Projects · FY 2025 · 2022-09

Project summary Eukaryotic DNA is wrapped around nucleosomes, which form chains of chromatin that are further folded into three-dimensional assemblies. The architecture of these assemblies regulates many nuclear functions, including genome 3D folding and transcription, and ultimately dictates cellular identity. Nucleosomes are a well-known hub of chromatin regulation, most of which is thought to occur via a variety of post-translational modifications on the protruding flexible tails of histones. Based on the assumption that most regulation of chromatin's structure and interactions with other factors occurs at these histone tails, the globular core of nucleosomes has been considered rigid and minimally regulatory. Excitingly, my recent work has revealed a new insight: that the nucleosome core is malleable and that this plasticity regulates chromatin folding and gene repression. I therefore propose that the globular, malleable core of nucleosomes is a hub for genetic and epigenetic regulation as well as a potential novel therapeutic target. To test this provocative hypothesis that challenges the textbook paradigm of chromatin regulation, novel tools capable of probing both in vitro and in vivo atomic-scale dynamics of large macromolecular assemblies such as chromatin must be developed. My lab will close this gap by developing conformation-specific nanobodies (NanoNucs) that act as sensors of distinct nucleosome conformations. NanoNucs will be discovered from a synthetic library containing >2 x 109 distinct nanobodies. We will employ NanoNucs to gain structural and biophysical insights into nucleosome conformational dynamics and to probe and perturb the nucleosome conformational code in cells. Specifically, we will: (i) obtain atomic understanding of nucleosome alternative states by combining NMR, HDX-MS, and cryo-EM; (ii) identify chromatin factors that sense and leverage nucleosome plasticity; (iii) search for nucleosome conformations that are biological or pathological biomarkers; and (iv) develop a novel strategy to manipulate nucleosome shapes and chromatin states in cells. By carrying out this highly ambitious, integrated, and multidisciplinary research program, my lab will unveil the molecular mechanisms and therapeutical potential of the nucleosome conformational code. I anticipate that these high-risk, high-reward investigations will reveal new fundamental principles of genome regulation that shift the long-standing paradigm of rigid histone units and that will broadly impact biomedical science over the short and long terms. Exploring the structural flexibility of nucleosomes represents an opportunity to identify novel therapeutic biomarkers and drugs for diseases linked to epigenetics defects, such as cancer. Ultimately, with critical support from the NIH Director's New Innovator Program, our studies will enrich our knowledge of the function and physiology of chromatin with atomic-scale biophysical insights into the chromatin architecture itself.

NIH Research Projects · FY 2024 · 2022-09

SUMMARY As the most significant risk factor for Alzheimer's disease (AD) and other dementias, aging causes the gradual decline of specific cognitive abilities, like spatial memory, reducing independence and quality of life.1-3 However, the neurobiological mechanisms underlying aging-mediated cognitive decline remain unclear, limiting the development of therapies that extend the brain's healthspan.2 To advance our mechanistic understanding of spatial memory decline in healthy and diseased brain aging, the proposed study will simultaneously characterize and then correlate molecular, cellular, and circuit-level changes in the medial entorhinal cortex (MEC), a brain region critical for spatial memory and impacted by molecular pathology in pre-clinical AD.4,5 In young rodents and primates, MEC neuron firing patterns represent position, speed, head direction, and environmental landmarks, facilitating goal-directed navigation and spatial memory.6-12 How MEC spatial coding changes and functionally supports spatial memory in aged animals is unknown. To address this, I propose to record from MEC neurons at high density using Neuropixels probes as young and aged mice navigate virtual- reality (VR) environments. I will quantify how aging impacts single-unit MEC properties, such as position- and speed-coding fidelity and stability, and, in turn, spatial memory, measured as the rate of learning and alternating between rewarded VR locations (Aim 1). In young animals, theta rhythm organizes MEC activity and supports spatial memory, but its functional status in aged animals is not understood. Thus, I will also analyze how aging impacts theta-rhythmic coordination of activity across populations of MEC neurons (Aim 2). After recording, I will define gene expression changes with age in MEC neurons using single nucleus RNA- sequencing (snRNAseq) (Aim 3). Ultimately, I will correlate altered gene expression with MEC coding and spatial memory dysfunction to identify targets for future therapies to rejuvenate the aging brain and to treat age-modulated dementias like AD. Given my previous experience investigating molecular changes in aging and neurodegeneration that compromise hippocampus-dependent spatial memory, I am well-equipped to execute these experiments. Pursuing these aims will also cultivate new skills necessary for me to excel as future independent investigator, including robustly collecting and analyzing large-scale neural and transcriptomic datasets. I will conduct this work under the sponsorship of Lisa Giocomo, PhD: a global expert in electrophysiology and the neural systems that support navigation and spatial memory. As a collaborator and a co-sponsor, respectively, Saul Villeda, PhD and Tony Wyss-Coray, PhD will contribute expertise leveraging large-scale molecular datasets to generate insights about brain aging. Their collective support and Stanford's rigorous training environment will ensure this project's completion and my development into an innovative physician scientist empowered to develop therapies that ameliorate brain aging and neurodegeneration.

NIH Research Projects · FY 2025 · 2022-09

Project Summary/Abstract This grant will support a new postdoctoral training program in cardiovascular and chronic disease prevention that builds on a prior successful 45-year training program at the Stanford Prevention Research Center (SPRC). The program’s objective is to mentor doctoral level scientists in interdisciplinary and translational population- and individual-level behavioral research aimed at preventing CVD and other prevalent chronic diseases. The program strongly emphasizes interdisciplinary behavioral interventions that can advance health. This application coincides with a period of sustained excellence and innovation for SPRC. A new chief, Dr. David Maron, leads a growing faculty focusing on cutting-edge scientific inquiry in a diverse array of interdisciplinary fields, including digital and precision health, community-led participatory research, aging, the microbiome, global health, and healthy people-healthy environments research. The training program faculty represent a range of disciplines, including behavioral and social sciences, medicine, epidemiology, public health, biostatistics, physiology, nutrition science, exercise science, environmental science, communication, and education. In addition to a portfolio of NIH-funded research activities that include observational and clinical trial designs and methods, SPRC has built a Wellness Living Laboratory (WELL) consisting of ~28,000 “citizen scientists” from the U.S. as well as Taiwan and Singapore. WELL’s long- term cohort and array of experimental studies provide additional rich research opportunities for trainees. Postdoctoral training will focus on direct mentored research experiences in a rich, interdisciplinary science environment that totals ~$10 million annually. Fellows work closely with a primary and secondary mentor and join a research team where they learn collaboratively about study design and methods, data collection and analyses, manuscript preparation, and other dissemination mechanisms to speed the translation of research to practice. Formal instruction in grant preparation is provided through a diverse range of didactic and experiential methods. Such SPRC and Medical School training opportunities are complemented by a broad array of resources offered by the Stanford CTSA in addition to career development programs provided by the Stanford Office of Postdoctoral Affairs and other Stanford resources. Fellow selection prioritizes interest in chronic disease prevention, potential for a productive research career and demonstrated scientific excellence and potential. Of the 49 fellows completing the prior fellowship in the past 15 years (2005-2020), 82% (40/49) currently hold research-related positions. We request funding for 4 postdoctoral fellow slots in Year 1 and 7 in Years 2-5 for candidates with a PhD and/or MD.

NIH Research Projects · FY 2024 · 2022-09

Gabriella Chatman & Dr. Kacper Rogala NCI Diversity Supplement | Project Summary | March 31, 2024 Many RAS-transformed cancer cells are able to escape cytotoxic chemotherapy and survive in near-starvation conditions. One adaptation making them hard to kill is their ability to scavenge extracellular proteins and recycle the cellular components using autophagy, both of which are then digested in lysosomes to recover free amino acids. Nutrient transporters, such as SLC38A9, have been shown to act as gates that release digested nutrients back into the cell, which in turn restarts cellular growth programs. Intriguingly, RAS-transformed pancreatic cancer cells with SLC38A9 knocked-out are unable to efficiently form tumors, which presents a novel therapeutic idea of targeting a metabolic vulnerability. In this R00 supplement project, we will expand on that initial discovery from pancreas cancer. First, we will explore whether other cancer types that carry mutations in RAS and Wnt signaling pathways can also perform nutrient scavenging via macropinocytosis. Second, we will test whether an inducible genetic knockout of SLC38A9 hampers growth of macropinocytosis-positive cancer cells that otherwise grow successfully on an extracellular protein diet. Knockout of SLC38A9 will lead to entrapment of macropinocytosis-derived amino-acids within the lysosomes, and our expectation is that this treatment will impair the growth of tumors addicted to protein scavenging, while sparing normal cells that lack this requirement. This supplement will allow us to broadly generalize the anti-cancer strategy that we are establishing in the R00 parent grant. Importantly, the supplement will help us recruit and train a promising post-baccalaureate student who has a great potential for a future career in scientific research.

NIH Research Projects · FY 2025 · 2022-08

Accumulating research has revealed that computations of reward and its prediction occur on multiple levels across a complex set of interacting brain regions, including those that support memory and navigation. Yet how the brain coordinates the encoding, recall and use of reward information to guide navigation and memory remains incompletely understood. Here, we focus on the mechanisms for encoding reward in the hippocampus, a medial temporal lobe structure that serves a key role in supporting navigation and memory. In the hippocampus, place cells fire in one or few restricted spatial locations, providing an internal neural representation of the external world. Place cells are also strongly modulated by reward. For example, place fields (the location where a place cell is maximally active) cluster near reward locations, resulting in an overrepresentation of those locations. However, the circuit and cellular mechanisms by which reward controls place cell representations remains unknown. We propose to examine how the precise spatial and temporal dynamics of dopamine and norepinephrine control hippocampal representations at the level of individual place cells. In our first aim, we will perform simultaneous 2-photon imaging of calcium signals and dopamine or norepinephrine signals in CA1 neurons as animals navigate through virtual environments. We will test the hypotheses that dopamine – in coordination with norepinephrine – can drive place cell representations near rewarded locations and temporally gate place cell representations to provide a signal for reward certainty. In our second aim, we will use the same technical approach to test the hypothesis that dopamine and norepinephrine act as a gating mechanisms for the detection of novelty and determine the temporal dynamics of neuromodulatory-driven novelty detection signals to the hippocampus. In our final aim, we will examine how the ventral tegmental area and locus coeruleus, which release dopamine and norepinephrine, mediate CA1 place cells and drive reward-driven place cell representations. Together, this work will provide new insight regarding the mechanisms of reward-driven changes to hippocampal representations at a spatial and temporal resolution technical innovations have only recently made possible. Moreover, this work will establish an approach and framework for future work examining how neuromodulators control hippocampal representations.

NIH Research Projects · FY 2025 · 2022-08

Project Summary/Abstract Rare genetic disorders are a major cause of human morbidity, frequently affect brain development and cause neurodevelopmental disorders. Here, we propose using Noonan syndrome (NS, 1:2000) as a human model system to provide critical data on the effects of Ras/mitogen-activated protein kinase (RMK)-genetic alterations on the human brain's complex systems-level biology. Three lines of evidence support using NS as a human model system: 1) NS is caused by autosomal dominant mutations of high penetrance in specific genes compared to idiopathic neurodevelopmental disorders genetics of common variance, 2) NS has a larger impact on brain development and thus larger effect sizes than idiopathic neurodevelopmental disorders, 3) NS is associated with increased risk for neurodevelopmental disorders such as attention abilities, learning disabilities, and autism spectrum symptoms. Our lab has recently observed the effect of NS mutations in the PTPN11 gene on human brain structure, specifically the striatum, and brain function, specifically frontostriatal connectivity. However, there is limited data available on the effect of other NS mutations, RAF1 and SOS1, on the developing brain. To address this limitation, we propose determining whether three major NS disease genes RAF1, PTPN11, and SOS1 mutations, are associated with striatal alteration in a gradient of severity. To provide critical data on the relationships between PTPN11 genetic variance and brain development, we will test whether PTPN11 pathogenic variants are associated with altered brain development. Finally, we will test whether whole-brain connectivity can predict attention abilities in NS. This aim will provide a neuromarker for attention abilities (specifically inhibition) in NS. We will perform "deep phenotyping" - imaging studies of the striatum (volume, cellular density, seed-based functional connectivity) and the whole brain (surface area, cortical thickness, white matter, cortical myelin content, and whole-brain functional connectivity) and assess attention (inhibition) in children (7-16 years of age) with RAF1 (n=30), PTPN11 (n=45), and SOS1 (n=30) mutations, and compare them to typically developing controls (n=45). Two innovative aspects of the proposed work are using restriction spectrum imaging (RSI) to map the RMK pathway upregulation effect on the striatum cellular density. Second, we will assess the effect of RAF1 mutations on brain development for the first time. Defining the relationships between the brain and Noonan's genetics will accelerate the use of genetic testing to inform prognosis and treatments in NS. Further, describing these relationships will provide critical data on the role of the RMK in brain development.

NIH Research Projects · FY 2026 · 2022-08

Project Summary The NIMH research domain criteria (RDoC) reconceptualizes mental health research along a series of key cross-disorder dimensional constructs. However, these dimensions were determined in a top-down fashion by relatively small groups of researchers. We propose a data-driven approach that tests the validity of the key RDoC constructs of attention, cognitive control, and working memory. We will evaluate these constructs using multiple cognitive tasks per construct to examine their relationship to brain networks and their ability to predict real-world behaviors that are relevant to mental health. Finally, we propose an augmentation to the RDoC framework by adding new units of analysis: contrasts and practice. The current RDoC matrix maps directly from task paradigms to constructs and subconstructs, which is problematic because supposedly distinct constructs can sometimes map to exactly the same set of tasks. To address this, we propose a new RDoC unit of analysis called a “contrast”, which better reflects the usual logic of experimental design. We will identify mappings between cognitive systems constructs and contrasts through consultation with domain experts. We will then acquire a large-scale dataset to test both exploratory and confirmatory models for RDoC cognitive system constructs. Finally, we will evaluate whether these RDoC cognitive systems constructs are predictive of related real-world outcomes. The RDoC matrix links constructs to both behavioral measures and neural circuits, but the present mappings between cognitive systems constructs and brain systems are sparse and inconsistent. We will use a dense- sampling fMRI acquisition of 65 subjects each completing 10 scanning sessions on the same battery of tasks as the behavioral study, to develop a precise data-driven atlas of neural engagement at each level of the matrix, from contrasts to subconstructs to constructs. We will then validate the behaviorally-derived models using neural data, both between subjects and within subjects. We will also perform fully exploratory analyses to identify whether the data-driven neural circuit structure on these tasks diverges from the RDoC matrix. A long history of research in both and animals has shown that repeated practice on a task changes the way that the task is performed and the brain systems that support performance. We will leverage our behavioral and brain imaging samples to evaluate whether the structure of the cognitive systems domain remains constant with practice. In parallel we will also apply exploratory methods to assess the consistency of structural models estimated either early in training or after extensive practice. Overall, this project expands the RDoC matrix with two new units of analysis (contrasts and practice), and validates the constructs of attention, cognitive control, and working memory across both behavior and neural circuits.

NIH Research Projects · FY 2025 · 2022-08

Cognitive decline begins in early stages of Parkinson’s disease (PD) and progresses to dementia in 75% of people with PD after ten years. Dopaminergic medication and deep brain stimulation (DBS) provide long-term improvement of cardinal motor symptoms in PD, but cognitive decline remains largely unaddressed and untreated, despite a long window for potential intervention before dementia occurs. Pre-clinical evidence indicates that intermittent DBS of the Nucleus Basalis of Meynert (NBM) offers the potential to stabilize deterioration of the cholinergic system and its negative impact on cognitive and cognitive-motor function in individuals with mild cognitive impairment and PD. We propose to apply the three predictors of a successful outcome for motor (dopaminergic) DBS to cognitive-motor (cholinergic) DBS: 1) select well-characterized candidates before the stage of dementia 2) optimize target selection, lead location, and volume of tissue activated (VTA), and 3) use intermittent neurostimulation patterns. We will utilize the UG3 phase to establish the feasibility of a novel approach to target the NBM for DBS via tractography modeling and translate novel patterned stimulation technology, in partnership with Boston Scientific and their research based Chronos software, for a first in human study. We will obtain an Investigational Device Exemption to use Chronos for the first time in human subjects and in a novel DBS target (i.e., NBM fiber bundles). Only after successful completion of the UG3 milestones related to these aspects of the project will we then transition to the UH3 phase of the study which will consist of a small pilot clinical trial investigating the safety, tolerability, and effect of combined STN and intermittent NBM DBS. Ten individuals with PD with cognitive impairment in at least one domain, but who do not have dementia, will undergo implantation of STN + NBM DBS. A vertical approach targeting the central anterior NBM region will be used in 5 participants, and a novel lateral approach targeting the lateral efferent fiber bundle outflow of the NBM will be used in the other 5 participants. Participants will receive standard high-frequency continuous STN stimulation and 1 hour/day of intermittent (60 Hz, 20 sec on, 40 sec off/minute) NBM stimulation. Behavioral and cognitive measures will be measured every 6 for up to two years with the primary outcomes at 12 months. An independent scientific outcome will use fluorodeoxyglucose (FDG)-positron emission tomography (PET) to assess the effect of continuous or intermittent NBM stimulation on cortical blood flow and glucose metabolism.

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY / ABSTRACT Attention-Deficit/Hyperactivity Disorder (ADHD) affects 8-10% of US children. Primary care providers (PCPs) care for most children with ADHD but quality gaps in ADHD treatment, with sociodemographic disparities as a potential driver, may lead to life-long morbidity and/or unnecessary treatments. There is an urgent need to develop quality measures for ADHD treatment, as a prerequisite for mitigating disparities and improving health outcomes. The objective of this proposal is to leverage recent advances in machine learning (ML) methods – enabling the analysis of electronic health record (EHR) data of an entire patient population – to develop robust quality measures for ADHD treatment, and to prepare for quality improvement interventions. This K23 proposal will accelerate Dr. Bannett’s transition into an independent physician scientist, towards his long-term goal to improve community-based primary health care for children with developmental and behavioral disorders. His multidisciplinary team of mentors include Heidi Feldman (ADHD research mentor), C. Jason Wang (health care technology & health services co-mentor), and Grace Lee (quality improvement & implementation science co- mentor). This nationally recognized team of physician scientists will assure Dr. Bannett achieves his goals, to (1) apply machine learning techniques to assess quality of care while mitigating bias, (2) advance research skills in advanced statistics and in qualitative methods, (3) build expertise in quality improvement and implementation science methods, and (4) enhance professional skills and transition to independence. Dr. Bannett’s clinical and research experiences, his mentoring team, and the environment at Stanford, position him to achieve the proposal’s aims. Building upon his experiences in analyzing EHR data and successes in piloting a natural language processing pipeline, Dr. Bannett has the following specific aims: (1) to develop guideline- based quality measures that combine ML analysis of free text with structured EHR data to assess PCP treatment of children aged 4-11 years with ADHD, (2) to assess PCP adherence to evidence-based guidelines for ADHD treatment and to detect disparities in care and minimize related bias in ML models, (3) to prioritize quality improvement interventions aimed at improving ADHD care and mitigating disparities that family and clinician stakeholders consider feasible, acceptable, and important. Aligned with the NIMH’s strategic plan, this proposal will (1) strengthen collaboration between stakeholders to continuously improve evidence-based practices in primary care settings, (2) identify and prioritize targets for planned PCP- and systems-level quality improvement interventions aimed at standardizing ADHD care and mitigating disparities, and (3) apply novel technologies that provide real-time feedback and continuous monitoring of high-quality ADHD care. With future R01 funding, Dr. Bannett will cross-validate developed quality measures in a national network of pediatric healthcare systems, and, in parallel, implement data-driven quality improvement interventions.

NIH Research Projects · FY 2025 · 2022-08

Sepsis causes an estimated one in five deaths globally, including approximately 190,000 deaths per year in the United States. Given the complexity and heterogeneity of the condition, a “one-size-fits-all” approach to sepsis care, which is largely the approach taken by clinical guidelines, is unlikely to be most effective. Yet, it is not feasible to conduct a randomized controlled trial (RCT) among each patient subgroup that can be formed from the hundreds of possible combinations of important sociodemographic (e.g., age group) and clinical (e.g., comorbidities or cause of sepsis) characteristics of patients. Observational studies in electronic health record (EHR) data could circumvent this feasibility constraint thanks to the large size and “real-life” representativeness of EHR data. However, such observational studies have the critical disadvantage that they are thought to merely yield associations rather than causal effect estimates, because they make the untestable and frequently implausible assumption that all confounders were perfectly measured and adjusted for in the analysis. The objective of this New Innovator Award is to develop and test a new study design for clinical research on sepsis – machine-learning-facilitated regression discontinuity (ML-facilitated RD) – that would allow researchers to determine causal effects for common sepsis care interventions in large-scale EHR data without needing to rely on confounder adjustment. ML-facilitated RD combines machine learning with a novel causal inference technique (regression discontinuity) to improve the robustness of the technique for causal effect estimation, its ability to reliably determine causal effects for each of a large number of highly granular patient subgroups, and to ascertain the optimal threshold in continuous variables (e.g., in mean arterial pressure) at which the intervention of interest should be initiated in each patient subgroup. We will additionally develop RD such that it can be applied to the multi-factorial decisions that are common in clinical care for sepsis. This project has two steps. In the first step, we will develop these methodological innovations with the aid of extensive simulation exercises. In the second step, we will test the feasibility and validity of ML-facilitated RD for each of 12 common clinical interventions for sepsis in each of 15 EHR datasets from a variety of clinical settings. The key innovation of this project is that it aims to establish a study design for EHR data on sepsis that uses a fundamentally different approach for causal effect estimation than current state-of-the-art methods. By providing a new tool to clinical researchers for determining the causal effects of clinical interventions for sepsis in routine care and among highly granular patient subgroups (including which threshold in continuous clinical measurements is optimal for initiating these interventions in each subgroup), this research would constitute a major step forwards in individualizing care for sepsis. It would also establish an important foundation for further methodological innovation and adaptation to allow ML-facilitated RD in EHR data and similar causal inference approaches to be used in other areas of clinical medicine.

NIH Research Projects · FY 2025 · 2022-08

Abstract Among the BRAIN Initiative’s most important achievements are the genetic identification of many new neurons- types and the creation of genetic tools to access these cell types. However, uncovering the functional roles of these neuron types and how they cooperate across brain areas to generate mammalian behavior remains an outstanding challenge. Thus, inventing ways to monitor how large populations of genetically identified neurons interact across multiple regions of the brain is crucial if we are to comprehend global brain dynamics. Today, electrical recording methods can track neural activity across multiple areas but cannot easily target neurons of specific types. Widefield and two-photon mesoscopes can image the dynamics of identified neuron-types across millimeter-scale regions of cortical tissue but cannot access the distributed sets of cortical and subcortical regions that comprise the major nodes of the brain’s sensory, cognitive, or motor circuits. To clear this impasse, we invented the ‘Octopus’, a robotic imaging system with multiple articulated optical arms, each a two-photon microscope, that can be flexibly positioned around the brain to record neural activity concurrently in multiple superficial or deep areas of a head-restrained behaving rodent or primate. We designed, built, and tested an initial version of the Octopus with 4 arms, each of which has 5 mechanical degrees of freedom and a micro-optic probe at its tip for two-photon imaging. The design of the arms is based on ideas from surgical robotics and uses remote center-of-motion kinematics to provide a versatile repertoire of robotic arm movements. Using this system, a visual neuroscientist can concurrently image neural activity in the lateral geniculate nucleus, visual cortex, superior colliculus, and pulvinar, and a motor neurophysiologist can image activity in the motor cortex, basal ganglia, cerebellum, and motor thalamus. In this project, we will enhance the optical and mechanical design of each Octopus arm and prepare the system for wide dissemination through open-source and commercial routes. Each arm will gain the optical functionality of a state-of-the-art, two-photon microscope for imaging large-scale neural ensemble activity. Specifically, each arm will incorporate optogenetics and allow dual-color two-photon imaging over an 800-µm- wide field of view. These capabilities will allow neuroscientists to monitor two genetically identified neuron- types in each of 4 brain areas, to perturb the dynamics of these cells with optogenetics, and to observe the effects of these manipulations on animal behavior and activity in the other 3 areas. We will also streamline the mechanical design to simplify the initial assembly of the Octopus for new users and to endow the robot arms with additional dexterity. The new design will also be motorized and will provide users with highly intuitive means of precisely steering the robot arms. Finally, to iteratively improve the performance and usability of the Octopus and to validate its readiness for dissemination as a groundbreaking new technology, we will work closely with 7 beta-tester labs to implement multi-area neural imaging studies in awake behaving mice and marmosets.

NIH Research Projects · FY 2025 · 2022-08

Cancer is one of the most profound human health challenges of our time, with 18.1 million new cases and 9.5 million cancer-related deaths worldwide in 2018, each predicted to increase by more than 60% by the year 2040.1 Chimeric antigen receptor (CAR) T cell therapy has revolutionized oncology through engineered targeting of antigens on previously untreatable cancers. However, less than half of patients on CAR T cell therapy experience long-term disease control, and CAR T cells have not mediated sustained responses in solid tumors.2 T cell exhaustion has been extensively characterized and linked to CAR T cell dysfunction, but the role of senescence is still poorly understood.3 Senescent T cells have been shown to manifest defective killing abilities and the development of negative regulatory functions.4 Moreover, levels of telomerase have been shown to control the lifespan of human T cells, with increased levels delaying senescence.5 My central hypothesis for this project is that T cell senescence limits the efficacy of adoptive cell therapy, and I can delineate telomere-dependent and -independent roles of telomerase in T cells and identify senescent markers predictive of CAR T treatment response and correlated with patient characteristics. In the proposed work, I will: (i) define senescent features in CAR T cells and correlate with exhaustion and functionality, (ii) utilize genetic engineering to interrogate the impact of telomerase activity on T cell function and phenotype, and (iii) correlate T cell senescent features in apheresis and CAR T infusion product with clinical measures. Collectively, the proposed work will investigate CAR T senescence as a stratifying and predictive clinical correlate, providing mechanistic insights informing increasingly effective CAR T cancer treatments. The fellowship training will take place at the Stanford University School of Medicine, with premier research and clinical resources that emphasize interdisciplinary research and innovation. As a graduate fellow in the Stanford Medical Scientist Training Program (MSTP), Stanford Chemistry, Engineering, and Medicine for Human Health (ChEM-H) Chemical-Biology Interface (CBI) training program, and Stanford Interdisciplinary Graduate Fellowship (SIGF), I am supported to uniquely integrate immunology, chemical biology, and computational strategies to advance CAR T therapies for the treatment of cancer. Dr. Crystal Mackall is the ideal sponsor for this proposal due to her expertise in T cell biology and translational cell therapies, her federally funded programs in developing and characterizing immunotherapies, as well as her dedication to physician-scientist career mentorship. Collaborator Dr. Steven Artandi brings expertise in cell senescence and telomerase dynamics, and collaborator Dr. Sean Bendall brings expertise in single-cell, high-content computational analyses.

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY/ABSTRACT Poor access and insufficient patient education regarding OAB chronicity, expected outcomes, costs, and potential side effects lead to unrealistic patient perceptions about therapy and suboptimal therapy duration, particularly in vulnerable populations. This thus leads to poor treatment access, adherence, and undertreatment. My long-term goal is to develop as an independently funded investigator and international leader who will pioneer interventions that improve OAB therapy access, adherence and outcomes, thereby reducing the burden of this chronic condition. The overall objective for this K23 proposal is to design an innovative, stakeholder-informed strategy that incorporates barriers to treatment (such as social determinants of health) and improves patient access to therapy options and therapy adherence. The central hypothesis is that unmet patient expectations and knowledge due to lack of access and suboptimal provider-to-patient OAB healthcare delivery are a barrier to treatment adherence. This central hypothesis will be tested pursuing two specific aims: 1. Evaluate an adapted UI mobile health tool for use in a diverse, multicultural population of women with OAB and identify barriers and facilitators to access, treatment adherence and engagement from multiple key stakeholders. 2. Conduct a pilot study to evaluate the usability and feasibility of using a mobile health tool to improve OAB knowledge, engagement and treatment plan adherence in a diverse group of women with OAB. The rationale for the proposed research is that its completion is expected to provide a strong evidence-based framework for the continued development and future implementation of cost-effective, evidence-based interventions to improve OAB therapy access and adherence. Combined these results are expected to have an important positive impact by positioning me to submit a competitive R01 application proposing a randomized controlled efficacy trial for improving therapy access, adherence, and OAB outcomes during the fourth year of this award.

NIH Research Projects · FY 2024 · 2022-08

Project Summary We propose a novel regulatory T (Treg) cell therapy to treat IPEX syndrome, a rare autoimmune monogenic disease. IPEX is a life-threatening disease caused by loss-of-function FOXP3 mutations leading to dysfunctional Treg cells. The only current curative treatment for IPEX is allogeneic hematopoietic stem cell transplantation (allo-HSCT), which is only available to a minority of patients. The proposed product, CD4LVFOXP3 consists of autologous CD4+ T cells that have undergone lentiviral vector (LV)-mediated gene transfer of wild-type human FOXP3 leading to persistent high FOXP3 expression and acquisition of Treg cell phenotype and function. CD4LVFOXP3 were granted Orphan Drug designation in October, 2020. Based on the etiology of IPEX, our hypothesis is that the administration of autologous CD4+ T cells converted into CD4LVFOXP3 Treg-like cells by LV-mediated FOXP3 gene transfer, will reduce the immune dysregulation and the autoimmune manifestations. CD4LVFOXP3 is functionally equivalent to Treg cells and therefore, offer a novel cell therapy approach that circumvents the requirement for generalized immune suppression (IS) and could improve the clinical status of participants. This First-Time-in-Human (FTiH) Phase 1 clinical trial will test the feasibility of the manufacturing and the safety of the administration of CD4LVFOXP3 (Aim 1) in minimum of 20 up to 36 evaluable human participants with IPEX, who meet eligibility criteria. The secondary objective is to evaluate the impact of the CD4LVFOXP3 infusion on clinical manifestations. The dosing rationale has been developed with a conservative approach based on initial cell doses used in previous clinical trials with Treg cells of different origins. CD4LVFOXP3 also express membrane NGFR (CD271) encoded within the same LV construct that contains the FOXP3 gene. allowing ex vivo purification and traceability enabling further studies of CD4LVFOXP3survival, phenotypic stability and functional characteristics. Thus, during this clinical trial, we will perform exploratory studies to build knowledge on the CD4LVFOXP3 pharmacokinetics (PK) (Aim2) and pharmacodynamics (PD) (Aim 3) by monitoring the immune phenotype and function of patient immune cells. The possibility to provide functional autologous Treg-like cells is expected to be of benefit to all eligible IPEX patients. CD4LVFOXP3 could: 1. improve control of clinical manifestations resulting in the reduction of IS and related side effects, and 2. diminish the need for allo- HSCT, or allow patients to be transplanted in a more stable clinical condition, resulting in improved allo-HSCT outcomes. Successful completion of this clinical trial in patients with IPEX using CD4LVFOXP3 Treg-like cells as a functional replacement for FOXP3 mutated Treg cells, addresses a significant unmet medical need while also providing proof of safety and preliminary indications of benefit in controlling autoimmune disease manifestations. As such, data from this trial could lead to expanded application of autologous CD4LVFOXP3 to other Tregopathies and/or other more common autoimmune disorders, such as inflammatory bowel disease (IBD), type 1 diabetes (T1D), cytopenia and atopic dermatitis, all of which have overlapping disease manifestations in IPEX patients.

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY/ABSTRACT Everett Moding, MD, PhD is an Assistant Professor of Radiation Oncology at Stanford University School of Medicine. His long-term goal is to use his combined expertise in clinical and research medicine to make important discoveries in radiation and cancer biology that lead to better treatments for patients with sarcomas. He hopes to develop a translational research program using analysis of human tumor and blood samples to identify critical mediators of radiation resistance that can be validated in preclinical models and leveraged to enhance the efficacy of radiation therapy. The goal of this career development award is to provide support and mentorship to enable Dr. Moding to develop a successful independent research program. The proposal will be carried out under the mentorship of physician scientists Maximilian Diehn, MD, PhD, an expert in genomicsbased biomarkers, Ash Alizadeh, MD, PhD, an expert in tumor immunology and transcriptomic analysis tools, and David Kirsch, MD, PhD, a leader in radiation biology and mouse models. The training plan incorporates formal coursework, seminars, conferences, and programs along with informal hands-on and practical activities to expand Dr. Moding’s knowledge and expertise in 1) computational and systems biology, 2) tumor immunology and sarcoma biology, and 3) laboratory management, mentoring, and grantsmanship. Soft tissue sarcomas (STS) are a diverse group of mesenchymal tumors primarily managed with surgery and radiation therapy for localized disease. Although half of patients with high risk STS develop metastatic disease after initial therapy, there are no biomarkers to identify patients at risk of relapse. In addition, up to two-thirds of patients with STS develop local recurrences after radiation therapy alone, but the underlying genetic alterations that mediate radiation resistance are unknown. By analyzing tumor and peripheral blood samples collected from 102 patients enrolled on the SU2C-SARC032 phase II clinical trial, this research proposal aims to 1) establish personalized circulating tumor DNA analysis as a biomarker in patients with STS, 2) build a prognostic model integrating tumor microenvironment profiling, circulating tumor DNA analysis, and traditional risk factors to improve prediction of patient outcomes, and 3) use circulating tumor DNA analysis and tumor sequencing to identify genetic alterations that mediate the response of sarcomas to radiation therapy for rapid functional validation in novel preclinical platforms. This proposal will lay the groundwork for future prospective randomized trials using circulating tumor DNA analysis and tumor genomics to enable personalized treatment approaches in patients with STSs that improve the probability of tumor eradication while minimizing treatment-related toxicity.

NIH Research Projects · FY 2025 · 2022-08

The role of peripheral versus brain myeloid immunity in cognitive decline of aging and Alzheimer’s disease Aging is characterized by the development of detrimental immune responses, where sustained pro-inflammatory responses promote end-organ damage, including frailty, vascular disease, metabolic syndrome, and cancer. The brain is also highly vulnerable to aging, as demonstrated by the high prevalence of cognitive decline and Alzheimer’s disease (AD). The preponderance of myeloid loss-of-function variants in human genome-wide association studies (GWAS) had led to a focus on understanding the role of brain microglia in aging and in AD. However, the majority of myeloid cells exist outside of the brain, and the role of the peripheral myeloid compartment in the development of age- and AD-associated cognitive decline has not been formally tested. In this application, we will use novel approaches to test the role of the peripheral myeloid system and contrast that with the role of microglia in the development of cognitive decline associated with aging and accumulation of amyloid in preclinical murine models of aging and AD. We will test whether age-associated changes in the peripheral myeloid system alone are sufficient to promote cognitive decline, and conversely, whether microglial dysfunction alone can cause cognitive decline, independent of the peripheral myeloid system. To separate out the peripheral from brain myeloid systems, we will use a novel bone marrow transplantation approach and a complementary genetic strategy targeting microglia to compare the relative contributions of each myeloid compartment to age-associated cognitive decline and cognitive decline associated with accumulation of inflammatory amyloid-ß peptides. Using the TREM1 (Triggering Receptor Expressed on Myeloid cells-1) pathway as a representative, myeloid-specific pathway expressed in both compartments, we will parse out the relative contributions of peripheral myeloid cells versus brain microglia to age- and AD-associated cognitive decline and define immune-metabolic mechanisms of action underlying these contributions in Aims 1 and 2. In Aim 3, we will determine the function of TREM1-mediated immune responses in human myeloid cells. Understanding the relative contributions of the brain microglial vs peripheral myeloid compartments to age- and AD-associated cognitive decline will inform development of effective, disease-modifying therapies.

NIH Research Projects · FY 2025 · 2022-08

Coronary artery bypass graft (CABG) surgery is the gold standard treatment for patients with diffuse, multi-vessel coronary artery disease, with >350,000 surgeries performed each year in the USA. Due to the limited availability of arterial grafts, saphenous vein grafts (SVG) are used in >95% of patients. Despite advances in surgical technique and post-surgical management, SVG stenoses and occlusions occur at alarmingly high rates: 5-10% of SVGs fail within one month after surgery, 25% within 12-18 months, and 40-50% within 10 years, resulting in significant morbidity and mortality. Currently, there are no clinically available means to prevent SVG failure following CABG beyond optimal medical therapy. Mechanical stimuli, including hemodynamic loads and associated vessel wall deformations and stresses, are known to contribute to the cell-mediated structural changes leading to SVG failure, yet, the precise mechanobiological mechanisms remain poorly understood. In preliminary studies, we quantified mechanical stimuli in CABG simulations, identifying hemodynamic markers associated with SVG stenosis. Importantly, we introduced the first computational growth and remodeling (G&R) framework that can delineate adaptive vs. maladaptive responses of vein grafts, incorporating optimization to accelerate parameter estimation. With this model, we then predicted that an external bioabsorbable sheath, present over a short post-operative period, could mitigate intermediate-term graft failure. Our scientific premise is supported by a preliminary in vivo ovine study. Our collaborative multi-disciplinary team will address this critical unmet need through tightly integrated computational model-driven design, experimental, and clinical approaches to uncover arterialization mechanisms and evaluate a novel bioabsorbable sheath device for SVG failure prevention. In Aim 1, we will develop the first G&R model of SVG arterialization incorporating inflammation. We will inform and validate the model with data from a longitudinal rabbit surgical study, in which we will perform surgery to interpose a jugular graft in the carotid artery. In Aim 2, we will synthesize these data and models into a first-of-its-kind 3D fluid-solid-growth (FSG) simulator to predict SVG disease progression, validated against an independent subset of animal data. To further inform our models, we will characterize human SVG tissue with biaxial tissue testing. We will increase rigor by incorporating uncertainty quantification. In Aim 3, we will design, optimize and evaluate a novel external sheath device for the prevention of SVG failure, integrating in silico and large animal in vivo studies. We will rapidly 3D print sheath designs from a unique class of bioabsorbable elastomeric materials with tunable degradation rates. This proposal brings together a multidisciplinary team with expertise in cardiovascular simulation, vascular mechanobiology, optimization, imaging, biomaterials, additive manufacturing, and clinical cardiovascular care as well as a track record of joint publications, funding, and open-source software. Our ultimate goal is to improve outcomes of CABG patients via prediction and prevention of SVG failure, for whom there are limited treatment options.

NIH Research Projects · FY 2024 · 2022-08

PROJECT ABSTRACT Significant rates of psychological distress have been found in patients across a range of genetic counseling settings, including cancer, cardiology, prenatal and medical genetics. In many cases, these needs are profound and unmet. Such data suggest that genetic counselors providing clinical care should routinely assess patients’ emotions and psychological impact. Accreditation boards for genetic counseling require this skill to achieve certification, but there is no standard definition of a “psychosocial assessment” in genetic counseling nor universal instruments to facilitate it. Those tools that do exist are questionnaire-based or specific to a clinical indication, eg. hereditary cancer. We can look to other healthcare settings, such as social work and primary care, to borrow tools which standardize the psychosocial assessment and which may be applicable in genetic counseling. One such tool developed in primary care is the BATHE method: a structured technique consisting of four questions that explore patients’ main presenting concerns, emotional affect and coping, paired with guidance for empathic responses. Evidence from the primary care literature shows the BATHE method reduces patient anxiety and improves patient empowerment. Providers find it concise and easy-to-learn, allowing for a person-centered interaction without increasing consultation time. These characteristics combined make it an attractive tool to pilot in genetic counseling, which provides patient-centered care while balancing information delivery and support. For these reasons, we request funding through this NHGRI R21 mechanism to better characterize the current state of psychosocial practices and pilot an innovative standardized way to provide such an assessment in genetic counseling. These goals are in line with the NHGRI’s 2020 Strategic Vision to promote patient empowerment around genomic information and train a workforce that is scalable and efficient. First, this study will describe the current practices of psychosocial assessments in genetic counseling, using descriptive content analysis of transcripts of a purposive sample of genetic counseling sessions at Stanford Medicine. Second, this study will pilot a psychosocial assessment tool (the BATHE method) in genetic counseling to assess its feasibility and acceptability by genetic counselors. Exploring patients’ perspectives, patient-related outcomes, and influence of cultural differences are crucial, and the current study lays the groundwork for this subsequent research. At the conclusion of our study, the findings from our aims will inform the development of a genetic counseling-specific standardized psychosocial assessment. The ultimate goal of this research is to build a foundation for investigation of patient outcomes in response to psychosocial counseling approaches.

NIH Research Projects · FY 2024 · 2022-08

PROJECT SUMMARY/ABSTRACT In motor neuron diseases, neuromuscular junctions are lost and motor neurons degenerate resulting in progressive paralysis and death. Post-transcriptional gene regulation by microRNAs (miRNAs) is hypothesized to be disrupted in motor neuron diseases due to inherited mutations in proteins involved in miRNA processing, such as TDP43, FUS, and SMN. Yet, the role of specific miRNAs in human motor neuron gene regulation and function is not well characterized. I previously discovered that a single miRNA, miR-218, is uniquely enriched and abundantly expressed in mouse motor neurons. Furthermore, mice lacking miR-218 exhibited deficits in neuromuscular synaptogenesis and die due to muscle paralysis – phenotypes associated with motor neuron disease. Subsequent studies have implicated miR-218 dysregulation as a mediator of motor neuron disease in humans. However, the relationship between miR-218’s repression of target gene pathways and motor neuron phenotypes has not been resolved, and the biological role of miR-218 has not been previously investigated in humans, leaving an important translational gap in our knowledge of human motor neuron gene regulation and function. In response to this challenge, we in the Pasca Lab have recently developed a three-dimensional, human induced pluripotent stem (hiPS) cell-derived model of human motor neuron development and function, called cortico-motor assembloids, by fusing cortical, spinal, and skeletal muscle spheroids. Dr. Amin proposes using this novel system to model the impact of miR-218 upon motor neuron development, target pathways, and human specific-features of post-transcriptional gene regulation. This proposal will leverage Dr. Amin’s existing proficiencies in motor neuron development, miRNA biology, and advanced transcriptomics and will enable new career development training in stem cell biology and human brain organoid models with mentor Dr. Sergiu Pasca. Dr. Amin will utilize the exceptional research environment and resources available at Stanford University. He will be supported by his advisory committee comprising of Dr. Howard Chang, an expert in non-coding RNA mediated gene regulation, Dr. Aaron Gitler, an expert in motor neuron biology and disease pathways, and Dr. Richard Reimer, a practicing neurologist and expert in disease pathogenesis. Completion of this proposal will pave the way for further investigations into the therapeutic modulation of miR-218 and its target mRNAs in human motor neuron disease.

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY / ABSTRACT Lung transplantation (LT) recipients suffer from life-threatening pulmonary infections that can trigger acute rejection and death. Although vaccination is the most effective way for preventing infections, vaccine efficacy is limited in immunocompromised solid organ transplant recipients. Two recent JAMA studies suggest that most transplant recipients fail to mount antibody responses to SARS-CoV-2 mRNA vaccines; anti-metabolite immunosuppressants further dampened this response. To facilitate more effective vaccination strategies, there is an urgent unmet need to understand vaccine responses in immunosuppressed LT recipients. Adopting a system vaccinology approach, this grant characterizes complex vaccine-elicited immune responses to address the problem of deficient vaccine immunogenicity in LT recipients. As the COVID-19 pandemic heightens focus on the vulnerability of LT recipients, the creation of a vaccine-oriented biobank to facilitate system biology analyses can strengthen the newly-formed NIH LT Consortium. In this proposal, we unite physicians/scientists from Stanford, Inova-Fairfax, and Houston Methodist to build a vaccination-oriented biorepository as the focus of a clinical center (CC). Responding to the RFA to explore center-specific hypotheses, our CC seeks an answer to the pressing question: ‘how do LT recipients respond to vaccinations?’ The grant hypothesis is that a vaccination-oriented biorepository will facilitate the holistic analysis of influenza vaccine-induced immune responses in LT recipients from geographically distant regions and that the use of an anti-metabolite immunosuppressant predicts reduced protective innate and adaptive responses in these patients. In Aim 1, biospecimens from patients immunized by vaccines against COVID-19, varicella-zoster, pneumococcus, and influenza will be prospectively collected and banked to generate the biorepository. To address hypothesis-driven questions achievable with a modest budget, Aim 2 uses system vaccinology tools to evaluate the influenza vaccines, the most common vaccinations administered to LT patients. Aim 2a characterizes humoral and innate immunity, Aim 2b focuses on cellular immunity, and Aim 2c builds a vaccine response network with bioinformatics tools. Aim 2 will also assess whether the use of an anti-metabolite as immunosuppression reduces influenza vaccine immunogenicity. The rationale for focusing on influenza over COVID-19 is that most patients will be vaccinated against the latter when this project begins. However, our CC is well-equipped to test other types of vaccinations when future initiatives are available. In addition to fostering interactions and shared resources within the LT Consortium, the main purpose of the Stanford CC is to improve vaccine designs, adjuvants, and administration protocols in at-risk LT patients through an improved understanding of immune responses. Information gleaned here can inform and improve vaccination efforts for all immunosuppressed patients.

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY: Primary care is often the last area in medicine to benefit from new technologies. Additionally, most machine learning tools are created without relevant data from primary care practices. Algorithms built in hospital settings are typically not directly applicable to primary care. These issues have been highlighted as reasons why machine learning may not drive meaningful changes for primary care. Leveraging large-scale, high-quality primary care health data is critical to create genuine solutions for improving health outcomes with algorithm development. Our innovative approach to these challenges is to create a first-of-its-kind overarching algorithmic framework for primary care. In the initial phase, we will focus on intervening on the data in order to generate counterfactual outcomes to represent a desired equilibrium. The second stage builds novel penalized regression estimators to enforce constraints for prediction. Our goal is to create reusable tools that advance the provision of health care to benefit all populations in primary care. We will accomplish this by developing generalizable methodology that follows a rigorous pipeline for algorithms. Our specific aims are to: (1) develop and test novel data intervention methods that rely on microsimulations for generating counterfactual outcomes, (2) develop and test new penalized regression approaches, (3) test the performance of the new algorithmic framework for a high-impact primary care application in chronic kidney disease and (4) create open-source computational tools, tutorial vignettes, and a synthetic data resource for reproducible research and dissemination. The proposed research will yield a statistically innovative reusable algorithmic framework unifying data intervention and penalized regression with robust testing in a chronic kidney disease study of quality of care. This primary care application will leverage rich registry data collected in usual care settings across the United States from multiple payers. Our approach centers robustness with rigorous methodological design, including comparisons to alternative existing estimators and standard practice in comprehensive simulation studies and national, real-world registry data. Addressing health outcomes in primary care—a hub of continuous, coordinated care—has the potential for substantial impact on improving public health via the health care system. The broad applicability of our framework and creation of reusable computational tools will facilitate deployment in many practical settings.

NIH Research Projects · FY 2025 · 2022-08

Opioid overdose deaths remain a major public health problem in the US. It is now recognized that surgery and post-operative pain are major contributors to persistent opioid use and dependence. Inadequate management of intraoperative nociception can lead to increased post-operative pain, which can lead to increased opioid utilization, chronic pain, opioid dependence, and opioid abuse. In this perioperative setting a major challenge is that patients are either unconscious (in the operating room) or heavily sedated (in the post-anesthesia care unit) and cannot report their pain levels. In these scenarios, anesthesiologists and nurses can only guess the opioid requirements for their patients, as they have no means to measure opioid drug effects in real-time. A real-time measurement of opioid drug effects, if it existed, would allow anesthesiologists and nurses to precisely titrate opioids and could significantly improve post-operative pain management and subsequent rates of opioid utilization, dependence, and overdose. Over the past two years my laboratory has developed a real- time biomarker for opioid drugs that could be used to provide more precise titration of opioid drugs and for drug discovery applications. In this project we propose to investigate the mechanisms underlying this biomarker and develop further translational science to support clinical application of this biomarker.

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY Soil-transmitted helminth infections and diarrhea are responsible for a large burden of morbidity and mortality among children under 5 years and are associated with increased growth faltering, anemia, impaired child development, and mortality. The primary public health interventions to prevent enteric infections are household water, sanitation, and hygiene (WASH) interventions. However, recent WASH intervention trials found only modest impacts on enteric infection prevalence in children. Observational studies have found that children in households with concrete floors have a lower prevalence of diarrhea and soil-transmitted helminth infection than those in households with soil floors. However, these findings may be strongly confounded by household wealth. We propose a randomized trial in rural Bangladesh to measure whether installing concrete floors in households with soil floors reduces child enteric infection. We will randomize 800 eligible households with pregnant women and install concrete floors before the birth cohort is born. We will collect follow-up measurements when children are ages 6, 12, 18, and 24 months. Our team is comprised of experts in environmental and infectious disease epidemiology, including Bangladeshi scientists. We have extensive experience implementing large-scale health intervention trials in Bangladesh and other low resource settings. Aim 1 is to measure the effect of household concrete floors on household fecal contamination and child soil contact and ingestion over time. The primary endpoint is Ascaris lumbricoides prevalence at any follow-up measurement. Secondary endpoints include prevalence of other soil-transmitted helminths and diarrhea. Other outcomes include maternal quality of life and stress. Aim 2 is to measure the effect of household concrete floors on household fecal contamination and child soil contact and ingestion over time. We will detect soil- transmitted helminths (N=800) in floor swabs and E. coli in floor, child hands, and sentinel toy samples in a random subsample (N=220). In a subsample (N=60), we will conduct video observations to estimate the frequency of child soil contact and ingestion. We will estimate the incremental cost-effectiveness ratio for both maternal and child outcomes using disability adjusted life years. This trial will determine whether concrete floors reduce enteric infection, and investigate mechanisms for how floors impact health, or if they do not, why. Household concrete floors are an innovative potential health intervention that may have additional benefits that we will measure in this study, including reducing the bandwidth tax that low-income families experience by making it easier to maintain a hygienic home environment, and in turn improve quality of life. Our findings will provide rigorous, policy-relevant evidence about whether concrete flooring installation should be delivered as a public health intervention to reduce child enteric infection. More broadly, this study marks a paradigm shift in intervention design for improving child health by expanding its scope to include housing improvements.

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY This proposal describes a career development program to prepare Dr. Lu for an independent research career that focuses on developing computational and experimental methods to improve cancer detection, diagnosis, and treatment. This program will provide Dr. Lu with new expertise in single-cell spatial omics, integrating with her background in machine learning-based image computation (gained as a graduate student) and clinical single- cell drug imaging (gained as a postdoctoral researcher) to advance our understanding of the mechanism that drives drug resistance of pancreatic cancer. Dr. Lu will be mentored by Dr. Garry Nolan, who invented the CODEX technology for highly multiplexed single-cell imaging, and co-mentored by Dr. Eben Rosenthal, a physician-scientist who pioneered the first-in-human clinical studies for fluorescence-guided cancer surgery, and Dr. Robert West, who developed the Smart-3SEQ technology for spatial transcriptomics. The K99 phase of Dr. Lu’s training will consist of (i) structured mentorship by the primary mentor and co-mentors, (ii) close interactions with advisory committee and collaborators, (iii) technical and academic training, (iv) a provocative research project, and (v) a program of career transition. Elucidating the role of the tumor microenvironment (TME) in drug resistance is critical to developing effective cancer therapies, but quantifying the drug delivery and action together with host environment factors within clinical tumors remains technically challenging. Antibody-based therapeutics, such as antibody-drug conjugates (ADCs) and immune checkpoint inhibitors (ICIs), are especially susceptible to blockade by TME barriers. The overall objective of this project is to identify the TME factors driving drug resistance in pancreatic ductal adenocarcinoma (PDAC) by integrating single-cell geospatial mapping of therapeutic antibodies with the deep spatial profiling of the TME. The central hypothesis is that periostin and tumor-associated macrophages (TAMs) play a key role in inhibiting drug delivery and response in PDAC. The central hypothesis will be tested by pursuing three aims: (Aim 1) establish a computational spatial omics platform by integrating CODEX and Smart-3SEQ to chart the baseline architecture of PDAC TME in an unbiased way; (Aim 2) combine single-cell drug imaging with spatial omics to determine the impact of stromal barriers to antibody delivery into PDAC and evaluate whether inhibiting periostin improves the delivery of anti-EGFR antibodies and ADCs in patient-derived xenograft mouse models; and (Aim 3) examine the role of chemotherapy in altering the phenotype and function of TAMs in human and mouse PDAC; identify chemo-induced alterations in TAM-ICI interactions in PDAC patients infused with a fluorescent anti-PD-L1 antibody; and validate whether inhibiting TAM-ICI interactions improves response to ICI plus chemotherapy in a transgenic mice model of PDAC. This project will provide novel computational tools to quantify cell-cell and cell-drug interactions in clinical tumors, offer new mechanistic insights on drug resistance in pancreatic cancer, and lead to new treatment strategies to improve patient survival.