Stanford University

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY/ABSTRACT Suicide is the 2nd leading cause of death among 10-14-year-olds and the 3rd leading cause of death among 15-24 year-olds in the United States. Reducing adolescent suicide rates is an urgent public health objective. Insomnia is a robust yet neglected transdiagnostic risk factor for suicidality and suicide deaths in adolescents that is modifiable using brief, evidence-based behavioral treatments. Despite this, to the best of our knowledge, insomnia treatments have never been studied in combination with suicide-focused treatments in youths. The purpose of the proposed research is to conduct an initial feasibility and preliminary effectiveness trial of combining evidence-based behavioral treatments for insomnia and suicidality/self-harm as a novel approach to adolescent suicide prevention. We anticipate that augmenting a suicide-focused treatment with an insomnia treatment will have a synergistic effect and lead to greater reductions in self-harm (SH) behaviors and suicidal ideation (SI) than suicide-focused treatment alone. We will use dialectical behavior therapy (DBT) as the suicide-focused treatment for the present study and internet-delivered, digital cognitive-behavioral therapy (dCBTI) for insomnia as the sleep-focused intervention. We will begin with a small open trial to obtain input from five youth and their DBT therapists to inform the proposed feasibility trial, adjusting the protocol as needed to enhance youth engagement in dCBTI. We will then use the modified protocol to conduct a pilot RCT with 40 youth, ages 12-18, with insomnia and high suicide risk to 6 months dCBTI plus DBT or to DBT alone. We will assess feasibility, acceptability, and safety of dCBTI + DBT, as well as reductions in insomnia symptom severity, SH, and SI. Following a baseline assessment, insomnia, SI and SH outcomes will be measured every 4 weeks over the 24-week treatment period to allow us to examine time to remission as well as to increase statistical power and mitigate impact of attrition. Exploratory analyses will examine if reduction in insomnia symptom severity mediates any observed between-condition differences in SH and SI. To the best of our knowledge, this will be the first study to explore the effectiveness of combining both an evidence-based insomnia treatment and a suicide-focused treatment for adolescents. We believe the approach of combining two existing evidence-based treatments that target risk factors for suicide is innovative and novel, as well as practical. This approach is consistent with the 2022 NIMH Strategic Plan for Research, Objective 3.2: Develop strategies for tailoring existing interventions to optimize outcomes. By leveraging existing treatments that we already know work and have robust uptake in the real world, we reduce time spent on treatment development and can move faster to dissemination, should the approach prove effective. If dCBTI + DBT is effective, our goal will be to disseminate dCBTI broadly as an adjunct to any suicide-focused treatment.

NIH Research Projects · FY 2024 · 2023-07

PROJECT SUMMARY Understanding the mechanisms and behavioral relevance of synaptic plasticity has been an active area of research for decades. However, how neural plasticity modulates innate behaviors, such as mating behaviors, is largely unexplored. In addition, cellular and molecular mechanisms of presynaptic neural circuit plasticity remain elusive. Both knowledge gaps will be addressed in this proposal, which focuses on the mechanisms of presynaptic plasticity of a hypothalamic circuit that governs male sexual behavior. Male mice improve in their mating performance after sexual experience, but the underlying neural circuit mechanisms are poorly understood. We observed a dramatic increase of presynaptic axonal termini in the projection from bed nucleus of stria terminalis (BNST) neurons expressing tachykinin 1 (BNSTTac1) to preoptic hypothalamus (POA), a circuit that is essential for male mating behavior. We hypothesize that this structural plasticity in BNSTTac1àPOA projections is critical for the enhancement of mating behavior following sexual experience. We will first characterize the cellular (presynaptic bouton dynamics) and electrophysiological (synaptic transmission efficacy) mechanisms of this plasticity with chronic in vivo imaging and slice recording. Further, we aim to dissect the molecular pathways underlying this plasticity with deep RNA sequencing and genetic manipulations. Lastly, we will perform behavioral tests to study how this plasticity modulates the display of male sexual behaviors. Our results will uncover the specific mechanisms modulating a key brain circuit for controlling mating behavior, which may inspire potential therapeutic approaches to alleviate low libido in humans.

NIH Research Projects · FY 2025 · 2023-07

Abstract The vestibular system utilizes specialized hair cells for sensing gravity and head motions. Vestibular hair cells have been broadly characterized into two cell types: Type I and Type II. Clear differences also exist among the zones of vestibular organs, consisting of a central zone surrounded by a peripheral zone of hair cells. How the mechanotransduction machinery varies across these two cell types or zones is poorly understood. Existing evidence suggests that the striolar (central) versus extrastriolar (peripheral) zones serve different functions such as sensing high versus low frequencies. How these functional differences are achieved at the molecular level is not clear. The aim of this proposal is to characterize the mechanotransduction complex in the different hair cells and zones of the utricle, a vestibular organ that is vital for sensing gravity and head motions. We have preliminary data that demonstrate differential expression of transcripts encoding a key component of the mechanotransduction complex: transmembrane channel-like proteins (TMC1 and TMC2). In zebrafish and the mouse, both Tmc1 and Tmc2 genes are expressed in regional gradients that correlate with the striolar and extrastriolar zones of the utricle. We aim to determine the dynamic developmental and adult patterns of Tmc1/2 expression along with other members of the mechanotransduction complex. We also intend to correlate these expression patterns with hair bundle morphology and hair cell physiology. In addition, we will examine these features of TMC expression and other components of the mechanotransduction complex in human utricular hair cells. Determining the extent of conservation of these features among species will be essential for the interpretation of animal models and how they inform approaches to regeneration of vestibular hair cells or other therapeutic methods for vestibular dysfunction in human patients.

NIH Research Projects · FY 2024 · 2023-07

PROJECT SUMMARY Myocardial infarction (MI) is a leading cause of cardiovascular disease and death. After an MI, limited regeneration occurs, and instead, inflammation and scarring cause the affected myocardial tissue to turn fibrotic and thin. This tissue remodeling results in abnormal tissue mechanics and impaired cardiac function, often leading to heart failure and death. Therefore, a promising therapeutic approach is to reduce inflammation and the adverse tissue remodeling of the infarct zone. Unfortunately, many emerging drug candidates to achieve these goals require prolonged dosing over multiple weeks, greatly limiting their clinical translation. To overcome this challenge, I propose the development of a hydrogel that is catheter-injectable and enables the one-time injection of a drug payload into the myocardium for long-term release. This multidisciplinary project merges my expertise in drug delivery, polymeric materials, and cardiovascular bioengineering. Specifically, I propose a nanoparticle-based, therapy-eluting gel that will be retained within the contractile myocardium to locally deliver the chosen therapy at a controlled rate. This hydrogel will address two challenges in cardiovascular therapies 1) retention in the myocardium due to the mechanically active heart and 2) delivery of a sustained therapeutic dose that preserves the bioactivity in the harsh environment of the infarct zone. In this project, I propose to deliver two potential therapeutics investigated in clinical trials to address inflammation and adverse remodeling. Anakinra delivered daily through subcutaneous injection has emerged as a promising candidate to reduce inflammation and prevent cardiomyocyte apoptosis after MI. Fresolimumab has potential to mitigate heart failure after MI by preventing fibroblast activation into myofibroblasts and thereby limiting fibrosis. However, to elicit a therapeutic effect, these drugs must be present for an extended duration via multiple daily injections. Therefore, novel therapeutics like Anakinra and Fresolimumab are limited in efficacy and clinical use and would greatly benefit from materials science approaches that would reduce the need for painful daily injections by enabling them to be delivered locally within the myocardium in a reservoir that can protect their bioactivity, limit their off-target effects, and offer tunable release kinetics that can match the therapeutic window of the chosen drugs. In the K99 mentored phase of this grant, I will develop the catheter-injectable hydrogel and demonstrate retention within the myocardium (Aim 1), tailor the release kinetics of the nanoparticles to achieve both rapid and sustained payload delivery of Anakinra (Aims 2), and demonstrate the therapeutic effect in a preclinical rat model of MI (Aim 3). In the R00 phase, the modular hydrogel technology will be expanded to include a second type of nanoparticle to enable the combinatorial release of Anakinra and Fresolimumab (hydrophobic and hydrophilic drugs, respectively) (Aim 4) and improve heart function quantitatively after an MI by preventing adverse remodeling in a rat preclinical model (Aim 5).

NIH Research Projects · FY 2025 · 2023-07

Recent advances in screening and treatment have increased the number of lung cancer (LC) survivors (~571,340 LC survivors as of 2019). However, studies have shown that these survivors have a high risk for developing second primary lung cancer (SPLC), with the median 10-year SPLC risk of 8.36% after surviving 5 years from the initial diagnosis. Further, survivors with SPLC have significantly higher mortality vs. those who remain with single primary LC. Many unaddressed challenges exist: (1) While prior studies identified several risk factors for SPLC, these are mostly measured and fixed at the time of initial diagnosis, with findings focused on survivors who have ever smoked. However, SPLC risk is likely to be influenced by dynamic changes of various factors (e.g., smoking cessation), and our preliminary data show that SPLC risk remains just as high among survivors who never smoked. (2) Nevertheless, current epidemiologic data mainly used for SPLC do not offer detailed data measured after initial diagnosis, (3) nor have risk factors or predictions been evaluated for never-smoking survivors. (4) Further, limited trial evidence exists to address the important clinical question of whether and how to continue CT screening after IPLC diagnosis among LC survivors, which requires a long-term follow-up that is often not feasible in clinical trials. (5) Importantly, data on detailed screening for LC survivors are typically lacking in most population-based data. We plan to address these multiple challenges by leveraging electronic health records (EHRs) and novel analytical approaches to generate evidence to inform clinical decisions. Our long-term goal is to improve LC outcomes by focusing on SPLC utilizing large EHR data combined with novel statistical methods that integrate patient data measured after initial diagnosis. Our Specific Aims are: (AIM 1) to use a novel 3-way linkage to establish an integrated shared database for LC (i.e., Oncoshare-Lung) using EHRs from community-based and academic healthcare systems (with an ethnically diverse population with a high proportion of Asian never smokers) linked to the California Cancer Registry (CCR) ; (AIM 2) to provide a set of clinical decision tools for efficiently managing LC survivors by developing a novel statistical framework for predicting dynamic SPLC risks by capturing data measured after IPLC diagnosis; and (AIM 3) to evaluate the feasibility and utility of a novel causal inference method to assess efficient screening strategies for SPLC in LC survivors using EHRs. We will apply a new causal inference method that explicitly emulates the target trials (hypothetical randomized trials to answer the question of interest) in estimating the effects of continuing CT screening in long- term LC survivors under varying eligibility criteria. We expect that the completion of this research will fill the critical gaps in SPLC by providing: (1) clinical decision tools to assess individuals’ dynamic SPLC risks to identify high-risk survivors for tailored surveillance, (2) new analytic pipelines to evaluate efficient screening criteria for SPLC, and (3) a well-curated database for high-impact translational research for LC outcomes and surveillance in an ethnically diverse population that provides a unique opportunity to examine critical questions in SPLC.

NIH Research Projects · FY 2024 · 2023-07

Project Summary/Abstract Immune modulation holds tremendous promise for the treatment of cancer, autoimmune disease, metabolic disease, and infectious disease. New ways to generate antigen-specific T and B cells inexpensively and with minimal reactogenicity are badly needed. Certain bacterial strains from the gut microbiome elicit a potent, specific adaptive immune response. The underlying mechanisms could guide new therapeutic strategies in which bacteria-specific immune responses are rationally altered or re-directed. The gut is the site of a wide variety of microbe-microbe and microbe-host interactions. However previous papers have characterized microbial strains of the microbiome under artificial conditions of mono-colonization. This approach can identify strains that are capable of modulating immune cells, but it is unknown how a strain functions in the presence of other members of the complex microbiota. This knowledge gap hinders a logical design of a microbial therapeutic. My long-term research objective is to develop new technologies to understand the “physiological” gut ecosystem at the level of molecular mechanisms so that I can identify immune modulatory bacteria from the microbiome and build new therapeutics. In this proposal, I will establish a “physiological” gut by colonizing germ-free mice with a complex defined gut community (104 strains) and profile T cell responses to each strain individually. In Aim1, I will identify a set of bacteria-reactive TCRs and their stimulatory strain by single cell technologies, so that I can provide a big picture of the strain-T-cell interactions at the single TCR level. In Aim2, I will identify and characterize a bacterial antigen common to multiple strains. In Aim3, the result of T cell profiling will be used to “design” therapeutic bacterial communities in which inflammatory strains will be dropped out for building a tolerogenic community to treat colitis in an IBD mouse model. The successful completion of this project will “decode” a strain-by-strain view of immune modulation by the gut microbiome and provide a molecular basis for “designing” the new therapy that logically modulates immune response to treat IBD and other devastating systemic disorders. Support from the K99 and mentors will complement my expertise in immunology with state-of-art technologies in microbiology and single cell biology. I will accomplish this with training from Dr. Michael Fischbach (primary mentor, bacterial genetics), Dr. Daniel Mucida (co-mentor, single-cell biology and T cell biology), Dr. Justin Sonnenburg (advisory committee, metagenomic analysis), and Dr KC Huang, (advisory committee, a synthetic microbial community). The training and mentorship I receive during my K99/R00 award will provide a critical stepping stone for me to achieve my academic goal of establishing a vibrant independent research program that can answer an important question in the gut ecosystem for establishing a new therapeutic.

NIH Research Projects · FY 2025 · 2023-07

Project Summary Surprisingly little is known about the regulation of B cell tolerance during infection; thus, the overarching goal of our studies is to characterize autoantibodies in COVID-19, focusing on their inflammatory capacity and abnormal regulation of B cell tolerance during infection. The scale of the COVID-19 pandemic, synchrony between infection and autoimmune manifestations, and mobilization of resources has allowed us to generate large numbers of banked samples paired with well-annotated clinical data - creating a once-in-a-lifetime opportunity to study the mechanisms involved in regulation of B cell tolerance and generation of IgG autoantibodies (AAb) and pro-inflammatory immune complexes (IC). The pathogenic roles of AAb in COVID-19 are now widely recognized with anti-cytokine antibodies targeting type I interferons identified in ~10% of critically ill patients, and rare in those with milder disease. More than half of patients in our COVID-19 cohorts have evidence of at least one AAb; the overwhelming majority of those who are AAb positive during SARS-COV-2 infections have no known cause for autoimmunity. The clinical correlates and immunologic basis of this loss of tolerance and aberrant AAb formation in infection are as yet unexplored. Elucidating the role of Fc glycosylation and impairments in the establishment of B cell tolerance in development of AAbs has not yet been attempted but may lead to a paradigm shift in our understanding of the immune and autoimmune responses to both COVID-19 and viral infection more broadly. Hence, in cohorts totaling >1300 patients with acute COVID-19 infection and >3000 samples, we propose to test the hypothesis that patients with severe infections and poor outcomes have pathogenic IgG AAb that may appear over the course of hospitalization and become part of the antibody repertoire even in convalescence. We will also test whether IgG AAbs in patients with severe COVID-19 have different Fc domain repertoires and glycosylation that favor inflammation. Finally, we postulate that serum AAb in patients with COVID-19 result from the activation of naïve self-reactive clones that escape early B cell tolerance checkpoints. We will determine if naïve B cell selection defects are induced by infection or are likely already present at the time of acute infection. Hence, our work may ultimately inform the role of early immune-modulating interventions not only in COVID-19, but in severe infections and ARDS more broadly, particularly pneumonia in ICU settings.

NIH Research Projects · FY 2024 · 2023-07

PROJECT SUMMARY / ABSTRACT Senescence is a state of permanent cell cycle arrest, and can occur during development (programmed senescence), or be triggered by a variety of stressors, like telomere shortening (defined as replicative senescence), oxidative stress DNA damage, and oncogene activation (stress-induced premature senescence). Senescent cells remain metabolically active and secrete high concentrations of signaling molecules into the tissue microenvironment (known as Senescence-Associated Secretory Phenotype, or SASP). These secreted factors can activate immune systems to initiate clearance of senescent cells, which contribute to tumor suppression, would healing and tissue homeostasis. When the immunosurveillance fails to eliminate senescent cells, their accumulation causes inflammation and contributes to a variety of diseases, including cancer, metabolic disorders, fibrosis, diabetes, brain disorders, osteoarthritis, and kidney disease. These complex and important roles in ageing and diseases prompt extensive interest in developing imaging methods to detect senescence cells. A number of optical imaging probes have been developed by targeting senescence-associated beta-galactosidase (SA-b-gal) activity. However, their use in vivo is limited due to poor penetration and scattering photons in living tissues. Several SPECT, MRI, and PET probes have been reported to address this limitation, but they displayed either poor cell permeability and/or sensitivity. In the case of PET tracers, they generally suffer from a lack of efficient signal retention mechanism. This research proposes to develop a novel PET tracer for in vivo imaging of senescence in a mouse model of cancer by targeting a novel lysosomal enzyme and using an in celluo probe assembly retention strategy. There are two Specific Aims: 1) synthesize the PET tracer and assess its capacity to detecting senescence in cell culture; 2) validate the PET tracer in animal models of therapy induced senescence. This project would provide a more specific and sensitive PET tracer for imaging cell senescence in vivo and for future translation into human studies.

NIH Research Projects · FY 2025 · 2023-07

ABSTRACT Over the last decade we characterized and studied the properties of various tRNA derived small RNAs (tsRNAs). In recent years, we have focused on one class commonly referred to as 3’tsRNAs (derived from the 3’end of mature tRNAs) because they are the least well studied but appear to play a role in tissue regeneration (e.g., liver regeneration) and hyperproliferative states including cancer. Here we plan to establish the potential of targeting the 3’tsRNAs for therapeutic purposes. Recently, we established that one specific RNA, the 22nt CAG-Leucine 3’tsRNA, which when down regulated by the addition of antisense oligonucleotides in rapidly dividing but not quiescent cells inhibit ribosome biogenesis. Loss of this specific tsRNA limits the translation (at the elongation step) of at least one ribosomal protein mRNA. This results in a block in rRNA processing and rapid cellular apoptosis. In contrast, the addition of a 3’tsRNA mimic increases cellular proliferation and can complement the ribosome biogenesis defect in cells. We propose to further identify other 3’tsRNA-mRNA interactions and establish their biologic and molecular function and develop gene therapy and oligonucleotide antisense delivery technologies to pursue the therapeutic potential of manipulating 3’tsRNAs in animals. Although the tsRNAs are expressed in many tissues, we will focus these studies on the liver including liver cancer. This work will provide new information related to 3’tsRNA function in gene regulation and cellular homeostasis in health and disease states, as well as establish their potential therapeutic value by the proposed preclinical human xenotransplant murine animal models. In the amended application, we removed all the studies related to screening for improved LNPs outlined in previous specific aim 3 as suggested by the reviewers.

NIH Research Projects · FY 2025 · 2023-07

Hundreds of millions of ultrasound (US) exams are performed each year worldwide. Typical limitations of conventional US imaging include operator dependence, limited field of view, limited contrast, and diffraction- limited resolution. Volumetric imaging has the potential to create an operator-independent acquisition protocol, and ultrafast US acquisition has opened new opportunities to address field-of-view and contrast issues. Our extended aperture approach applied here addresses spatial resolution limitations as well. With high resolution, real-time imaging capabilities and the lack of ionizing radiation, US has great promise for imaging pediatric patients; in particular, for children under 3 who cannot be imaged with MRI or CT without anesthesia, the development of a high-resolution volumetric US scanner would be transformative. In particular, we set out to image the pediatric liver and kidney within ~0.1 second, which requires a technological leap. New ASIC switch matrices will enable high speed acquisition and GPU-based partial beam formation enables the visualization of the 3D data. Reconstruction of the 3D vascular structure facilitates image-based recognition of the anatomical location of a lesion. Ultrafast SVD Doppler imaging allows the visualization of very small blood vessels with blood flow velocities as low as 4 mm/s. Abdominal pain is very common in children and US is frequently used to determine the cause. Accurate volumetric measurements of the kidney are problematic due to patient motion and operator-dependent scanning. Assaying the liver and abdomen, particularly in the context of trauma are similarly important. Thus, we seek to create this real-time imaging tool with resolution that exceeds CT and MR but without the need for anesthesia or radiation. Using 1024 active system channels with integrated GPU beamformers, we will create 2 transducers to span the needs of children for this technology, with spatial resolution at 5 cm (~300 (azimuth) x 600 (elevation) x 300 (depth) µm) that should exceed that offered by MRI or CT by several fold. The array will be realized using tiled modules that can be switched in a mode-dependent fashion to accomplish B-mode imaging, color Doppler and contrast imaging. Over the past four years, Stanford University and the University of Southern California have designed an adult extended-aperture abdominal- imaging system, and demonstrated the improved spatial resolution, field of view and contrast that can be achieved. We exploit these tools here to develop a dedicated pediatric volumetric scanner. Our aims to accomplish this are to 1) create and integrate acoustic/electronic transducers to implement signal buffering and multiplexing; and 2) develop volumetric software and conduct pediatric imaging studies as a proof of concept. We will develop the software and systems, test the system components on adult volunteers and phantoms, and develop 3D volumetric processing. We will image a cohort of pediatric patients spanning 3D kidney volumetric mapping, detection and mapping of previously detected liver lesions. In each case, MRI will provide the gold standard.

NIH Research Projects · FY 2024 · 2023-07

ABSTRACT Head and neck squamous cell carcinomas (HNSCCs) are an aggressive form of cancer that is difficult to treat due to the complexity and heterogeneity of the tumors. Resistance to drug and radiotherapy resulting in disease recurrence is common as HNSCCs are genetically very heterogeneous among patients. Studies of the HNSCC genome, transcriptome, and metabolome have revealed new altered targets, but translating these findings to clinical improvements in treating patients is a long road ahead. Therefore, there is a critical need to innovate strategies to facilitate precision in clinical decision-making. Recent studies by Gevaert Lab (Advisor) and Sunwoo Lab (Co-mentor) have shown HNSCCs can be classified into various subtypes with distinct genetic and epigenetic signatures. It is urgently important to know if these subtypes respond differently to the standard-of- care treatments. This proposal will test if the drug and radiation response in patient-derived tumor organoids (tumoroids) is correlated with DNA methylation patterns in these patients. Aim 1 will establish a high-throughput automated HNSCC tumoroid platform by precise bioprinting tumoroids in 96- and 384-well plates to generate self-assembled identical tumoroids, which will capture tumor heterogeneity of patients. Aim 2 will establish a methodology to perform high-throughput tumoroid screening using 18-F-Fluorodeoxyglucose (FDG), a radioisotope used for clinical imaging of cancer. The FDG influx rate inside tumoroids will be compared to the standardized uptake values (SUV) of the patient tumors (from positron emission tomography (PET) scans) for validation. Aim 3 will examine the standard-of-care and emerging treatment response among the five heterogeneous HNSCC subgroups. I hypothesize that DNA (hypo/hyper) methylation plays a key role in HNSCC treatment resistance to drugs and immunotherapy. This knowledge will significantly improve the future treatment plans and overall survival rate of HNSCC patients. In addition, this project will have two significant innovations: 1) An automated high-throughput strategy to generate HNSCC tumoroids for drug, radiation and immunotherapy screening. 2) A high-throughput screening strategy of tumoroids with gold-standard clinical imaging biomarkers, which are used in clinic for accurate assessment of treatment response. These innovations will enable higher clinical relevance, speed, and automation while reducing variability in both measurement and analysis in organoid-based head and neck cancer research. My career development activities at Stanford University will ensure gaining knowledge and expertise in head and neck cancer, bioprinting, strengthening scientific networks, improving study design skills, and achieving scientific and professional independence. With the successful completion of aims, a future prospective R01 grant will advance the technology further to make it more clinically relevant and suitable for identifying new drug and immunotherapy targets of head and neck cancers. In summary, the project will allow us to measure the sensitivity to standard-of-care treatments for HNSCC subtypes based on their epigenetic footprints and pave a way to develop an effective and precision therapy for these patients.

NIH Research Projects · FY 2026 · 2023-07

ABSTRACT Alzheimer’s disease (AD) is characterized by progressive neurodegeneration and the aggregation of amyloid-b (Ab) and tau. The selective vulnerability of different brain regions and some cell types to AD pathology has been established. However, much remains unknown regarding the disease-relevant mechanisms underlying this differential response. We have previously used single-cell transcriptomics to perform an unbiased characterization of vulnerable and resistant neuronal subtypes in the human AD brain (19 excitatory and 24 inhibitory subtypes; ~490,000 nuclei, multi-region dataset). This characterization revealed early transcriptional changes in inhibitory interneurons, particularly in a population expressing the receptor tyrosine kinase c-Kit. Using our novel method to isolate by FACS and profile neuronal somas with tau aggregates, we also quantified the susceptibility of 20 major neocortical neuronal subtypes to the formation of neurofibrillary tangles (NFTs). Although interneurons proved generally resistant to NFT formation, they were not spared from death. Our work in the human brain highlights the existence of shared and distinct Ab- and tau-associated pathogenic mechanisms as well as the need for a multidimensional approach to characterizing vulnerability in AD. This proposal seeks to further characterize cell type-specific signatures of vulnerability to Ab and tau proteinopathies in newly developed knock-in (KI) humanized mouse models of AD. We will test the hypothesis that early changes in specific populations of GABAergic inhibitory interneurons, including c-Kit cells, are associated with network dysfunction, early protein aggregation, and cognitive deficits in humanized AD mouse models. To model pathogenic interactions between Ab and tau, we will use mouse models expressing humanized Ab without or with familial AD (FAD) mutations and mouse models expressing human MAPT without or with a mutation associated with tauopathy. In Aim 1, we will apply combined single-cell RNA- and ATAC-seq to tau-bearing and tau-free somas from mice characterized behaviorally and electrophysiologically by chronic EEG/EMG recordings and by standard and machine learning-analyzed behavior. In Aim 2, we will use spatial multiomics with single- cell and subcellular resolution to map cell-type-specific vulnerabilities and cell-cell interactions in relation to Ab and tau proteinopathies. In Aim 3, we will determine if Ab and/or tau alter the molecular, cellular, and circuit properties of vulnerable c-Kit interneurons. In all aims, we will integrate our multiomics and functional data and compare our mouse and previously-generated human data to identify evolutionarily conserved or species- specific cell type behaviors. The completion of these aims will provide a human disease-relevant, large-scale multiomics dataset instrumental to unravelling the mechanisms of neurodegeneration associated with Ab and tau proteinopathies.

NIH Research Projects · FY 2025 · 2023-07

Restrictive Cardiomyopathy (RCM) is an autosomal dominant form of cardiomyopathy characterized by profound diastolic dysfunction yet normal or near-normal ventricular dimensions, wall thickness, and systolic function. RCM patients have fewer treatment options and notably poorer outcomes than those with other forms of cardiomyopathy. This is especially true in pediatric-onset RCM, for which the only definitive therapy is heart transplantation, often in childhood. Mutations that cause RCM predominate in the sarcomere, which is the contractile unit of cardiac muscle cells. Since the dysfunction is intrinsic to cardiomyocytes, human in vitro induced pluripotent stem cell (hiPSC)-derived cardiomyocytes are well-suited to modeling the RCM and evaluating therapeutics strategies. To date, however, there are no reported investigation of hiPSC-derived cardiomyocyte models of RCM. This proposal, therefore, seeks to use hiPSC-based models of familial, pediatric RCM to elucidate pathological features, determine whether certain mutations cause distinct pathogenetic mechanisms, and evaluate the therapeutic potential of two newly approved drugs that have shown promise for treating diastolic dysfunction in other forms of heart disease. Preliminary studies generated a patient-derived, hiPSC-based model of RCM caused by mutations in cardiac Troponin-T (TNNT2). We found that heightened Ca2+ sensitivity of force generation and increased fibrosis might underlie disease pathogenesis. Besides TNNT2, mutations in other sarcomeric mutations also cause severe pediatric RCM, and some are hypothesized to induce disease by distinct pathophysiological mechanisms. Therefore, AIM 1 of this proposal is to develop hiPSC models of RCM caused by diverse gene variants, and identify distinct and common mechanisms of contractile dysfunction. Our hypothesis is that RCM is a heterogeneous disease and distinct gene variant-specific mechanisms converge to elicit hallmark clinical features of RCM. Independently, AIM 2 is to evaluate mavacamten mecarbil and sodium-glucose cotransporter-2 inhibitors (SGLT2i) for efficacy in treating contractile dysfunction in RCM using the hiPSC models. Mavacamten and SGLT2i are newly approved for other forms of heart disease. Mavacamten, by decreasing actin-myosin cross- bridging, might be therapeutically effective for RCM independently of genetic etiology. In contrast, SGLT2 inhibitors (SGLT2i), which operate by inhibiting multiple proteins and decrease intracellular [Ca2+] in cardiomyocytes, might show selectivity for gene mutation depending on pathogenic mechanism. Characterizing the basic disease mechanisms of RCM and evaluating the efficacy of candidate therapeutics is a critical step towards improving management of this challenging disease.

NIH Research Projects · FY 2025 · 2023-07

Congenital heart disease (CHD) affects 1/100 babies and is the leading cause of infant mortality in the U.S. Pulmonary artery (PA) stenosis is common in CHD patients and is particularly challenging to treat when occurring in the periphery of the PA tree. Peripheral pulmonary stenosis (PPS), often consisting of numerous vessel narrowings at proximal and distal bifurcation levels, can lead to persistent RV hypertension, RV failure, and even death. Most institutions treat PPS patients with stenting and angioplasty limited to the proximal (central and lobar) PAs only. These catheter-based interventions, however, are often ineffective at reducing right ventricular pressures and are associated with poor and unpredictable outcomes. Comprehensive surgical reconstruction, involving patch augmentation of ALL stenoses (central, lobar, segmental PAs), can achieve long-term RV pressure reduction with low morbidity and mortality, but requires >10-hour procedures and specialized expertise available only at select institutions. Because treatment strategies continue to be debated nationally, and outcomes remain poor, there is a pressing unmet need for novel clinical decision support tools. We aim to develop two complementary modeling methods to support clinical decision making in CHD patients with PPS: 1) a mechanistic multiscale model of pulmonary fluid solid growth melding fluid structure interaction (FSI) and vascular growth and remodeling (G&R), and 2) a real-time uncertainty-aware digital twin model for virtual treatment planning to aid clinicians in identifying optimal treatment strategies. To accomplish these goals, we propose three specific aims: (1) Characterize mechanical and immunohistochemical properties of PA tissue in human PPS patients via biaxial testing and histology; (2) Develop and validate a computational modeling framework (melding hemodynamics and G&R) capable of predicting post-treatment hemodynamics in PPS; and (3) Develop and validate a fast, interactive Bayesian modeling framework for virtual treatment planning under uncertainty to aid near real-time clinical decision making for PPS, leveraging reduced order models. Our proposed study will tightly integrate modeling and experiments to improve physiological fidelity and clinical relevance of patient-specific models in an understudied patient population. The biaxial mechanical characterization of pediatric human PA tissue will provide much needed data on tissue properties in CHD which are currently absent from the literature. This project assembles an interdisciplinary team of engineers with expertise in hemodynamics modeling, cardiovascular biomechanics, mechanical characterization of biological tissues, and uncertainty quantification, and clinicians with expertise in pediatric cardiology/pulmonary vascular abnormalities, cardiothoracic surgery, and cardiac catheterization. Our translational objectives are to: (1) systematically compare treatment options for PPS and thus challenge the current standard of care and, (2) ultimately optimize treatments for individual patients, thus reducing unnecessary procedures and potential harm and improving long-term outcomes in this complex pediatric population.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY Public health departments increasingly use predictive modeling to guide decisions and resource allocation for the control of infectious diseases in the United States, especially during the COVID-19 pandemic. These novel predictive models offer promise to better identify high-risk populations to precisely deploy interventions such as vaccination, yet there is limited evidence on how these models are used by public health departments and whether they translate into policy that reduces infectious diseases. The major scientific problem I seek to address is to identify whether, and to what degree, predictive models can be incorporated into public health practice and translated into policy by public health departments to improve the control of infectious diseases. By leveraging a key collaboration with the California Department of Public Health (CDPH) and rich epidemiologic data sources, I will address a key public health challenge of how to optimally allocate limited resources for targeted vaccination against pertussis, seasonal influenza, and hepatitis A. The goal is to target vaccines to the highest-risk locations and populations to reduce the number of outbreaks and infections. My hypothesis is that public health departments can effectively incorporate predictive mathematical models on optimal targeting of vaccination into their policy decisions. I will apply my expertise in predictive modeling and infectious diseases to develop open-source, predictive modeling tools for county public health departments to allocate targeted vaccination to the highest-risk populations, and study the step-by-step implementation of these models in public health use. My broad, long-range goal is to evaluate the causal public health impact of using predictive models to guide decisions on vaccination in public health departments. In Aim 1, I will develop and validate predictive models to optimally target vaccines to high-risk locations and populations (age, demographic and risk factor) for pertussis, seasonal influenza, and hepatitis A. The model will provide comparative effectiveness and costs of various targeted vaccination strategies, and an overall vaccine recommendation specific to the county and infectious disease. In Aim 2, I will apply methods from implementation science to optimize the user experience for public health officials to maximize usability, communication, and uptake of model-based vaccine recommendations. In Aim 3, I will implement the predictive models of targeted vaccination in California public health departments and measure implementation outcomes in a pilot study. This work will provide the foundation for a future innovative trial with CDPH that randomizes county public health departments and evaluates whether using model-based predictions on optimal vaccine allocation can causally reduce cases and outbreaks. This proposed work has the potential to unlock new scientific directions of translating predictive models into common practice in public health, which can then be applied across many infectious diseases.

NIH Research Projects · FY 2025 · 2023-07

Project Summary Ventricular tachycardia (VT) and fibrillation are leading causes of cardiac arrest, dizziness, syncope and hospitalization in the United States and worldwide. However, the management of patients at risk for VT remains suboptimal despite scientific discoveries from basic to population science. In particular, there is no framework to estimate which patients with VT are likely to respond to anti- arrhythmic medications or ablation. Therapy is thus empirical. There is great excitement to use analysis of “big data” to personalize VT therapy, but this has not yet improved outcomes. This project develops a novel computational approach to personalize VT therapy that combines machine learning in large registries with computational models. Machine learning will be applied to data across biological scales that span bedside, laboratory and non-invasive imaging, to predict which patients are likely to respond to therapy. Computer models will be used to estimate if a given patient's heart is likely to support VT before versus after therapy. We will validate results in large external registries from different Institutions. We have 3 specific aims: (1) To develop a computational pipeline to predict response to VT ablation using bedside, laboratory and non-invasive imaging; (2) To use machine learning of clinical data and non-invasive imaging to identify which patients with VT will respond to anti- arrhythmic medications in a large database; (3) To combine computational approaches to estimate the relative likelihood that a given patient will respond to various forms of therapy. Results from each Aim will be tested in independent external registries. We will probe computational models to identify clinical phenotypes that could be applied at the bedside. This project will provide immediate clinical impact for patients with VT. We will combine machine learning with physics-based computer models in large registries at Stanford and External centers. We will reduce computational bias using FAIR methods (Findable, Accessible, Interoperable, and Reusable), and make tools freely available per the 2018 NIH Strategic Plan for Data Science. Our team comprises experts in clinical and basic electrophysiology, imaging, machine learning, bioengineering and statistics. The project is very feasible.

NIH Research Projects · FY 2025 · 2023-07

Project summary The role of lactate in energy metabolism has been of considerable biochemical and physiologic interest. Beyond its classical description as glycolytic end-product, lactate’s more recent emerging roles include inter-organ metabolic fuel, receptor ligand, and protein post-translational modification. Given that some of these roles have only been identified, or further expanded upon, in the past few years suggests that we are still in the early stages of understanding the diversity of lactate functions in energy homeostasis. We have recently reported that lactate metabolism into a downstream metabolite, Lac-Phe, generates a blood-borne signaling molecule that mediates tissue crosstalk and suppresses feeding and obesity (Li et al., Nature 2022). Ablation of Lac-Phe biosynthesis in mice increases food intake and obesity after exercise, demonstrating the physiologic relevance of this pathway. Our data uncover an unexpected and underappreciated aspect of lactate – as a precursor for a circulating lactate-derived signaling metabolite – in energy homeostasis. Because of this fundamentally new insight, here in this proposal we focus entirely on additional biochemical and physiologic studies of Lac-Phe and this downstream pathway of lactate metabolism. Building on a large body of published preliminary data, as well as unpublished studies in cells and in mice, this proposal will test the central hypothesis that Lac-Phe is a tightly regulated, lactate-derived signaling metabolite that engages specific cell surface molecules to regulate energy balance. In Aim 1, we will determine the specific cell populations that produce Lac-Phe in vivo and their contribution to whole-body energy balance. This Aim is enabled by our newly generated conditional, Cndp2 floxed allele which allows for cell type-specific ablation of Lac-Phe biosynthesis. In Aim 2, we will determine the role of a kidney solute carrier in the downstream metabolism of Lac-Phe. Preliminary studies demonstrate this solute carrier exhibits robust Lac-Phe transport activity in cells. Finally in Aim 3, we will determine the structural features and downstream molecular targets that mediate Lac-Phe’s effects on food intake. We have identified candidate cell surface molecules that are engaged by Lac-Phe. Successful completion of this proposal will provide a detailed and molecular understanding of Lac-Phe biochemistry and physiology, thereby establishing a scientific foundation for developing new therapeutics that target the Lac-Phe pathway for obesity, type 2 diabetes, and metabolic diseases.

NIH Research Projects · FY 2026 · 2023-07

Project Summary/Abstract The human brain function relies on the formation and maintenance of precise neural circuits among more than 100 subtypes of neurons. These circuits are mediated by synapses, the characteristics of which vary depending on neuronal subtype. Synaptic dysfunction plays a critical role in most, if not all, human brain disorders. Thus, understanding synaptic diversity and its developmental origin are crucial for us to understand how the brain functions and how it goes awry in mental disorders. During brain development, synapses undergo profound changes to become mature and fully functional. Maturation of glutamatergic synapses involves changes in the postsynaptic density (PSD), a highly sophisticated protein complex composed of >1,000 proteins. However, the compositional changes of the PSD in development were not well characterized. My preliminary data revealed the temporal dynamics of >1,000 PSD proteins during cerebral cortex development, providing initial insight into mechanisms of synapse maturation. Moreover, integrative analysis of the developing PSD proteome and single- cell RNA-seq data suggested that different neuronal subtypes undergo divergent synapse maturation processes. However, we know little about the compositional diversity of neuronal subtype-specific synapses or the different maturation processes they go through. In addition, synapse maturation, diversity, and specificity can be controlled by transcription, but the underlying gene regulatory programs remain elusive. This information is particularly relevant to mental disorders like autism spectrum disorder, in which genetic mutations converge on transcription regulation and synaptic transmission. Thus, the specific aims of this project first seek to uncover the compositional diversity of neuronal subtype-specific synapses in the developing cerebral cortex using a novel chemogenetic method (Aim 1, K99 phase). The second aim is to decode the disease-relevant gene regulatory mechanisms that generate this diversity by applying single-cell genomics and machine learning approaches (Aim 2, K99 phase). Finally, using the training, tools, and preliminary data from the K99 phase of my proposal, I will launch an independent research project that focuses on investigating the effects of neuronal activity on synapse maturation and plasticity at neuronal subtype resolution (R00 phase). Results from these studies will provide insights into synapse diversity, its regulatory mechanisms, and its dysregulation in autism. My long-term goal is to study the functional importance of synapse diversity on neural circuits and behaviors and develop targeted therapies to alleviate synaptic dysfunction in mental disorders in patients. Additional training obtained during this award in developmental neurobiology (with Dr. Arnold Kriegstein), synaptic biology (with Dr. Robert Edwards), chemogenetics (with Dr. Alice Ting), and advanced machine learning (with Dr. Jingjing Li), combined with my previous experience in rodent models, proteomics, and single-cell genomics will provide me with a solid foundation for an independent research career to achieve my goal.

NIH Research Projects · FY 2026 · 2023-07

PROJECT SUMMARY Glaucoma, the most common worldwide cause of irreversible blindness, is characterized by progressive dysfunction and death of retinal ganglion cells (RGCs). We recently employed confocal scanning laser ophthalmoscopy (cSLO) to successfully obtain in vivo Ca2+ imaging with mouse RGCs expressing jGCaMP7s, a genetically encoded calcium indicator. Thousands of ON, OFF, and ON-OFF RGCs with characteristic responses to light stimulation are readily detected in living animals through this non-invasive in vivo imaging platform. Here we seek to develop a more advanced, first-of-its-kind two-photon (2P)-SLO platform with patterned stimulation and multiple detection channels. Through a multidisciplinary collaboration with expertise in in vivo optical imaging, RGC pathophysiology, and retinal neural circuitry and visual processing, we will use complementary imaging techniques and state-of-the-art analysis protocols to understand naïve RGC physiology in real time. We recently extended our original mouse silicone oil-induced pupillary blocking and ocular hypertension (SOHU) model to recapitulate phenotypes of two forms of glaucoma: a chronic model with moderate IOP elevation and mild RGC neurodegeneration; and an acute model with greatly elevated IOP and severe neurodegeneration. Importantly, SO removal reduces IOP to normal almost immediately, allowing better exploration of the effects of IOP lowering treatment and combined treatment with neuroprotection strategies. Thus, we will determine the longitudinal functional and metabolic changes of glaucomatous RGCs, under clinically relevant models, both before and after IOP normalization and/or neuroprotective treatments. These data will deepen our understanding of the pathophysiology of glaucoma, towards finding much-sought biomarkers to better predict progression, and create more relevant endpoints for developing treatment to restore RGC physiology in vivo.

NIH Research Projects · FY 2025 · 2023-07

Project summary/abstract Sterols lipids, including cholesterol, are important for mammalian cell physiology. These molecules modulate the fluidity of biological membranes and are therefore implicated maintaining membrane integrity, stress tolerance, fusion events, etc. Sterols are also involved in intra- and intercellular signaling and are trafficked to sub-cellular membranes. Whereas decades of research have provided molecular insights into eukaryotic sterol synthesis, transport, regulation, and function, similar understanding of sterols is lacking for bacteria and archaea. While it is thought that archaea do not make or use sterols, some bacteria do make and transport sterols; many others are known to engage with sterols produced by eukaryotes. These bacteria include the pathogenic spirochetes (Borrelia burgdorferi, Treponema pallidum), Mycobacteria, Chlamydia, Rickettsia, and gut microbiota. For pathogens, the acquisition of sterols from the host is critical as they colonize and construct their cell envelopes. For gut microbes, interactions with cholesterol can alter the host lipid metabolism, thereby contributing to cardiometabolic diseases and dyslipidemia. Despite the preponderance of research about microbial interactions with these lipids, lacking are molecular insights into how the interactions occur and how they are regulated. We will address this knowledge gap, which we posit will reveal novel targets for therapeutic interventions in bacterial colonization and aberrant sterol lipid metabolism. Given that some bacteria produce sterols de novo, we reasoned that achieving an understanding of sterol handling in bacteria that make them could reveal insights into their handling in bacteria that use them. We therefore focused on Methylcoccus capsulatus, a bacterium reported to produce sterols nearly 40 years ago. Recent studies reported a significant divergence in sterol biosynthesis in M. capsulatus. We have since added to those reports one showing that sterol trafficking is also substantially different. We identified three proteins that traffic sterols: BstA, BstB, and BstC. BstA is a member of the resistance nodulation division family of transporters that work as transporters for a wide range of bacterial metabolites. BstB is a periplasmic binding protein with homologs involved in phosphonate transport. Finally, BstC is an outer membrane associated lipoprotein belonging to a family of transporters whose substrates are not known. The overall structures of the Bst proteins are markedly different from eukaryotic sterol transporters. However, they all contain ligand sites that are similar in the presentation of hydrophobic and hydrophilic residues. We posit that a modified structural genomics approach wherein the focus is on ligand sites instead of overall structure/sequence would enable the identification of functionally homologous proteins in bacteria. This work will use bioinformatics, quantitative ligand binding analyses, and structural approaches to identify and characterize sterol trafficking proteins in bacteria that make sterols, pathogens that hijack sterols, and gut flora that modulate host sterol metabolism.

NIH Research Projects · FY 2025 · 2023-07

Project Summary: Measuring and Predicting Appropriate Antibiotic Use to Combat Resistant Bacteria Antimicrobial resistant infections already cause over 2.8 million illnesses and 24,000 deaths per year in the US alone. The Centers for Disease Control and Prevention (CDC) identify antibiotic prescribing stewardship as the most important action to slow resistant infections. Our objective is to produce the methods for clinical decision support systems to reduce both over and under use of broad-spectrum antibiotics. We will test novel methods to measure and predict better antibiotic choices on urinary tract infections (UTIs), the most common human bacterial infection that accounts for 25- 50% of antibiotic prescriptions with resistance already exceeding 20% for common antibiotics. The key challenge is that prescriptions for antibiotics are almost always guesses before definitive test results are available. This actionable, arbitrary, and ascertainable process where an important decision (antibiotic prescribing) depends on humans predicting a verifiable result (diagnostic culture results) is ideally suited for innovative machine learning that can produce Personalized Antibiograms that predict antibiotic susceptibility for individuals based on patterns learned from large collections of prior examples. Major scientific barriers to progress in combating antibiotic resistant bacteria include the limited personalization of conventional tools for prescribing guidance, overly optimistic retrospective evaluations of predictive models, and the lack of measures for effective diagnostic antibiotic prescribing decisions. With the combined expertise of our multi-site team (Stanford, UT Southwestern, Harvard), we will overcome these barriers and achieve the objectives of this proposal through the following aims: (1a) Multi-site data harmonization and sharing of electronic health records for suspected UTIs (1b) Develop and validate Personalized Antibiogram prediction models for microbial culture results (2) Prospective validation of antibiogram models with real-time electronic health record integration (3) Develop and validate automated methods for electronic phenotyping UTIs (4) Develop and validate a measure of antibiotic appropriateness and desirability

NIH Research Projects · FY 2026 · 2023-07

PROJECT SUMMARY Acute and chronic musculoskeletal (MSK) pain are important health concerns across the lifespan, and surgery is a chief inciting event for subsequent persistent pain. Eighty percent of adolescents undergoing major MSK surgery report severe acute pain, and 20% develop chronic postsurgical pain. Having chronic pain in childhood and adolescence increases risk for a continued negative trajectory of MSK pain and poor health outcomes in adulthood, contributing to the national pain crisis. This K24 award will provide critical support for Dr. Rabbitts, a NIAMS-supported Associate Professor of Anesthesiology and Pain Medicine at the University of Washington (UW). The candidate's programmatic research has focused on developing innovative methods to identify biopsychosocial contributors to acute and chronic pain following MSK surgery in adolescents. During the course of this award, she will complete currently supported research: R01AR073780 which aims to increase understanding of the transition from acute to chronic postsurgical pain and the causal mechanisms involved, and UH3HD102038 (HEAL clinical trial) which evaluates the effectiveness of an mHealth perioperative psychosocial intervention to reduce acute and chronic pain in adolescents undergoing major musculoskeletal surgery. The candidate will expand her interprofessional mentoring program to build a strong and diverse cohort of pain scientists equipped to develop and implement long-term solutions to the MSK pain crisis through prevention. This K24 will also allow extension of the candidate's perioperative research program through training in sleep methodologies and building new collaborations to forge a novel research direction focused on sleep. The specific aims of the two new research studies proposed are to: 1) test pain processing as a mediator in the relationship between adolescent sleep immediately following surgery and subsequent MSK pain at 2 months after spine surgery, and 2) to determine feasibility of peri-operative melatonin in youth undergoing MSK surgery. The four projects will provide mentees with rigorous methodological training in a broad range of pain research assessment and intervention methods. This will capitalize on the wealth of opportunities available at SCRI and UW to actively engage promising trainees in the candidate's role as a physician-scientist, including via the SCRI Pediatric Pain Research Postdoctoral Fellowship and the UW T32 Training Program in Anesthesiology and Perioperative Medicine Research. Release from clinical activities provided by this award will allow the candidate to expand mentees at the fellow level, while enhancing mentorship skills, to equip a new generation of pain researchers with necessary scientific and professional skills, resiliency, and commitment to pain science, to make a sustained impact on the pain crisis. The K24 will also accelerate the candidate's research momentum informing the Type II renewal of her R01 and a new U01 efficacy trial of perioperative melatonin, which will be critical to her career objectives to achieve a deep understanding of contributing mechanisms and intervening to prevent acute to chronic MSK pain transition.

NIH Research Projects · FY 2024 · 2023-07

PROJECT SUMMARY Mental disorders affect one in four people worldwide (~2 billion people), with the cost of mental health conditions projected to reach $6 trillion by 2030. Unfortunately, mental disorders are difficult to diagnose, monitor, and treat. Repeated triggering of daily stress can also lead to chronic stress, associated with higher risks of mental disorders, weakening immuneresponse, and cardiovascular diseases. Despite the mental health crisis, available resources and access to care scarcely begin to meet the need. Moreover, there are no objective tests or scalable technologies for detecting chronic stress. To advance precision mental healthcare, we need continuous, predictive, and quantitative measurements of mental states for stress, anxiety, and depression. Wearable devices can transform mental health care due to their ability to monitor previously inaccessible biodata. However, there are limited wearable devices designed for mental health monitoring. In the proposed research, I will tackle the mentioned problems in mental health monitoring by developing platform technologies based on skin-like wearable biosensors. The focus of the proposed study is to create a soft and wearable biosensor that can measure multiple mental health biomarkers wirelessly in real-time, providing quantifiable metrics to assist diagnosis, treatment, monitoring, and prevention of mental disorders. Two new technologies will be developed: a soft and wireless patch to measure mental health-related physical biomarkers on the skin and a new organic biosensor platform to monitor chemical biomarkers in sweat. First, I will design a soft and wireless sensor patch to monitor skin conductance changes in response to acute stressors and circadian rhythm. The designed skin conductance sensor patch, composed of intrinsically stretchable and soft materials, will provide seamless integration with skin and accurate measurement with high signal-to-noise ratios. Second, I will fabricate a soft chemical biosensor to monitor the stress hormone in sweat using organic field-effect transistors. A highly sensitive and selective aptamer chemical biosensor will be utilized in a skin-like organic material system. Both alone and combined, the skin-like wearable systems will allow continuous quantitative monitoring of mental health biomarkers, assisting in the prevention and treatment of mental disorders. Professor Zhenan Bao, Professor Leanne Williams, and Stanford University provide the tools and expertise needed to accomplish the proposed research. Working with Professor Bao, a leading scientist in the field of intrinsically stretchable materials, I will acquire scientific skills in the design, fabrication, and characterization techniques of organic materials and bioelectronics. In addition, I will gain experience working with human subjects during this postdoctoral training. For this reason, I am working with Professor Williams, my co-mentor, who is a leading professor in psychiatry and behavioral sciences. Moreover, I will obtain training in psychiatry and electrical engineering by taking classes at Stanford. This environment provides the expertise needed to accomplish the proposed research and provide me with the appropriate training to pursue a career in academic research.

NIH Research Projects · FY 2024 · 2023-07

PROJECT SUMMARY/ABSTRACT BRAFV600E mutations are common in anaplastic thyroid cancer (ATC, 50-75% positive), which is refractory to standard treatment and has high mortality rates. Monotherapy with BRAF inhibitors is ineffective in patients with BRAFV600E-mutant ATC. Although, combination therapy using a BRAF inhibitor, and a mitogen-activated protein kinase (MEK) inhibitor is more effective than BRAF inhibitor monotherapy, acquired resistance is common because BRAF and MEK act on the same downstream target and largely the same pathway. A feature of resistance to BRAF inhibition or combined BRAF and MEK inhibition is increased sensitivity to agents that induce ferroptosis (a distinct mechanism of programmed cell death dependent on iron). Moreover, it has been shown that treatment-resistant (including BRAF inhibitor-resistant) cancer cells (persister cells) are associated with a mesenchymal state that is dependent on GPX4 (a gatekeeper and suppressor of ferroptosis) and show increased sensitivity to ferroptosis induction. Our unpublished preliminary data show that ferroptosis induction is more pronounced in BRAFV600E-mutant than wild type ATC cells and that combination BRAF inhibition and ferroptosis induction has synergistic activity in causing cell death in BRAFV600E-mutant ATC cells. The long-term goal is the development of novel science-based treatment strategies for ATC that improve patient outcomes. The overall objective in this application is to determine the safety and preclinical therapeutic efficacy of combined BRAF inhibitor and ferroptosis induction treatment in BRAFV600E-mutant ATC. The central hypothesis in this proposal is that combination therapy with BRAF inhibitor and ferroptosis induction will have synergistic/additive anti-cancer activity in BRAFV600E-mutant ATC. The rationale for this project is that determination of the safety and preclinical therapeutic efficacy of ferroptosis induction with BRAF inhibition is likely to offer a strong scientific basis for translation of this novel combinatorial treatment strategy to the clinic. The central hypothesis will be tested by pursuing two specific aims: 1) Evaluate the safety and anticancer activity of targeting ferroptosis in combination with BRAF inhibition in BRAFV600E-mutant ATC in vitro and in vivo; and 2) Evaluate the efficacy of combined ferroptosis induction and BRAF inhibition compared to combination BRAF and MEK inhibition. The research proposed in this application is innovative, in the applicant’s opinion, as it represents a significant departure from the current strategy of targeting BRAF only or a single signaling pathway in BRAFV600E-mutant ATC to the concept that combined treatment with a BRAF inhibitor and ferroptosis induction will result in more robust and synergistic/additive anticancer activity. The proposed research is significant because it is expected to provide a strong scientific justification for future studies that could provide a new mechanism-based treatment regimen for BRAFV600E-mutant ATCs that could result in durable response. Ultimately, such knowledge has the potential of offering new opportunities for the development of novel therapeutic strategy for BRAFV600E-mutant ATC.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY Type 1 diabetes is characterized by the loss of β-cell mass and decreased insulin production capacity. Thus, developing a pharmacologic method for stimulating the expansion of β-cell mass has substantial potential therapeutic value. Recently, our group and others have successfully developed highly potent small-molecule inducers of human β-cell proliferation; however, the growth-promoting activity of these molecules is non- selective. Consequently, the potential for inducing off-target cellular proliferation is a primary barrier to the safe use of these regenerative compounds in humans. Herein, a novel, generalizable prodrug strategy for the selective delivery of regerative therapeutics to the β-cell will be developed. The strategy leverages a unique biologic activity of the β-cell to convert latent prodrugs into bioactive daughter compounds. Building on prior success, progress will be furthered by incorporating relevant advances made in the broader field of targeted drug delivery into this new prodrug strategy; including the incorporation of molecular linkers used in antibody- and small molecule-drug conjugates that ensure compounds are fully latent prior to bioactivation and are unscarred following bioactivation. Additionally, the cellular mechanisms of prodrug activation will be elucidated. This work will deliver a robust, milestone-based data package for β-cell targeted drug delivery that includes a deep understanding of prodrug bioactivation, structure-activity relationship data, pharmacokinetic characterization, cell-type-specific activity and in vivo efficacy with a human islet-based preclinical model. The replicative activity of target (β-cells) and off-target tissues will be assessed following short-term and long-term compound exposure; studies critical to demonstrating the sustained specificity and efficacy of this β-cell targeted therapeutic delivery strategy. These studies have the potential to deliver safe, potentially transformative, first-in-class lead compounds for regenerative treatment of diabetes. Critically, the developed technology may be used for β-cell- targeted delivery of nearly any therapeutic.