Stanford University

NSF Awards · FY 2025 · 2025-09

The aim of this project is to investigate how exchanges between inventors and patent examiners affect the development of technology and its value once patented, and more generally the translation of research to use. The patent examination process may involve rejections of applications’ claims based on obviousness or novelty, while inventors may respond with arguments for inventions’ distinctiveness; they also may adjust technologies in response. This research investigates this process through innovative AI-assisted analysis of all publicly available patent applications at the United States Patent and Trademark Office. It measures how patent applications evolve via the examination process; it measures examiners’ and applicants’ interpretations and counterinterpretations of patent claims; and it models how these interactions affect what gets patented, the long-run value of patented technology, and the strategies examiners and applicants learn through multiple examinations. Results from this study inform improvement in translation of research to patents and from patents to technologies that improve our lives. The research is conducted in three interrelated studies of the patent examination process. Project 1, “Invention Evolution,” measures how patent claims are transformed during prosecution, utilizing a blend of AI and machine learning techniques such as natural language processing, and qualitative coding. Project 2, “Pluralistic Interpretation,” applies a combination of natural language processing and qualitative coding to measure how examiners interpret prior art and application claims, and how applicants offer counter-interpretations in their rebuttals. Finally, Project 3, “Learning to Patent,” integrates findings from the previous two projects to address questions about examiner and inventor learning. It fits panel multinomial logic models to explain how examiner and applicant interactions change emergent technological claims; how these interactions, in turn, relate to the long-run success of patents; and finally, it models how parties develop strategies that lead to more efficient and effective patent execution. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Harnessing the power of physics-informed artificial intelligence (AI), this CAREER project aims to improve our understanding of how polar ice sheets flow, critical processes that influence global sea-level change. By developing new deep-learning tools that can extract hidden physical properties from satellite data, the research addresses challenges in bridging the gap between modeling and observations for predicting future ice-sheet changes. The project will not only advance scientific understanding but also foster broader impacts by making cutting-edge AI methods accessible to the glaciology and Earth science communities. It will support education and training and strengthen the integration of research and teaching. This project will make physics-informed AI tools open source and more accessible to the polar research community. The methods developed could be applicable to a wide spectrum of data-driven research, thus offering significant potential for scientific discoveries in the wider geoscience community in the era of big earth science data. The future prediction of mass loss from ice sheets and their sea-level impact depends on knowledge of ice viscosity and the friction beneath the ice sheets. However, both ice viscosity and basal friction are challenging, if not impossible, to measure at the ice-sheet scale. Traditionally, the inversion of these two quantities involves solving inverse problems via partial-differential-equation-constrained optimizations. In recent years, deep-learning methods have emerged as powerful tools for both solving inverse problems and emulating physics-based simulations. This project will develop deep-learning algorithms for inverse modeling of ice sheets and ice shelves. The goals of the project include: (1) DIFFICE.jax, an open-source physics-informed deep-learning algorithm to infer continent-wide ice-shelf viscosity structure, facilitating scientific discoveries regarding ice rheology; and (2) Neural Inverse Operator (NIO), a novel open-source algorithm to substantially accelerate probabilistic predictions of basal tractions, enabling ice-sheet-wide basal traction inversion with uncertainty quantification. To foster a collaborative community at the rapidly evolving intersection between AI and glaciology, this project will include a summer school and a workshop to facilitate knowledge exchange and identify key challenges and emerging themes in this new field. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

This project aims to fill the gap in foundational knowledge between well-established sampling and estimation methods and Artificial Intelligence (AI)-inspired ones, referred to as ‘generative sampling.’ Generative AI algorithms are capable of producing plausible instances of objects from complex distributions, such as ‘naturally occurring’ sentences or ‘naturally occurring’ images. Rather than learning a probability distribution, these methods typically learn an ‘algorithm’ to generate samples with the desired distribution. This project has two main goals: (1) Determine the fundamental computational and statistical limitations of generative Artificial Intelligence (AI) methods, addressing what the classes of outputs (probability distributions) can and cannot be generated by these methods; (2) Design algorithms to accelerate the generation process. The project also involves training activities in this area through the involvement of undergraduate and graduate students in this research and the development of topics courses. More specifically, the project’s focus is on denoising diffusions, their generalization via stochastic localization, and related approaches. It appears that the scope and limitations of these methods are dictated by subtle properties of the target probability distribution. For instance, it can happen that a distribution can be sampled in polynomial time, and yet reasonable polynomial time generative processes, e.g., all denoising diffusions in a broad class, fail to sample correctly. The project aims to determine fundamental limitations both in terms of computational resources at generation time (computational bottlenecks) and the required sample size to estimate the denoiser (statistical bottlenecks), as well as optimal parallel generation algorithms when efficient generation is possible. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

The goal of this project is construct a rigorous framework for timelike Liouville theory. Timelike Liouville theory is a theory of quantum gravity with a "wrong sign" in the exponent, which makes it impossible to put it in the setting of ordinary probability theory. This project will aim to develop an extension of probability theory that accommodates Gaussian distributions with negative variance, and apply this extension to construct rigorous timelike Liouville theory. This project involves graduate students. While spacelike Liouville theory has received intense attention in the probability community over the last two decades, the timelike theory - which is closer to a true theory of quantum gravity - has remained beyond the reach of rigorous mathematics. The main reason, as in quantization efforts for other theories of gravity, is the appearance of Gaussian integrals with the "wrong sign" in front of the quadratic term. If the quadratic term comes with a positive sign, ordinary measure theory does not give the tools to make sense of it in a way that is consistent with physical calculations. This project will provide a rigorous framework for doing that, which has been outlined in near-complete detail in the project description. The long-term goal of this effort would be to derive the timelike DOZZ formula in the new rigorous setting, which has eluded mathematical understanding until now. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Synthetic biology can be used to create and improve treatments for many diseases. Genetic techniques are used to modify T cells to create CAR-T cells that can kill some types of cancer cells. Gene therapy offers the promise of curing genetic diseases for which there are no treatments. A significant problem with these technologies is the variability of gene delivery to the targeted cells. Viral particles are often used to deliver the desired genes. A cell could be infected by a single viral particle, or many, meaning the cell could receive one or many copies of the gene to be expressed. The variability in the resulting response of the infected cells means the treatment results could vary widely. The objective of this project is to develop protein circuits that can self-regulate. This would remove the effect of infection variability on cellular performance, and thereby even out the therapeutic effectiveness. The reproducibility this would introduce would accelerate the development process for new biotherapeutic strategies. This project will develop dosage-controlled synthetic circuits by implementing proteolysis-based incoherent feedforward loops (IFFLs). The primary goal is to create self-regulating circuits that maintain consistent performance regardless of delivery variations. The approach combines proteolytic regulation with secreted protein engineering. The research will proceed in two phases: first, establishing the technical foundation using synthetic reporters to develop and characterize the basic circuit components, followed by demonstrating functional feasibility using cytokine outputs. An iterative strategy of computational modeling and experimental validation to optimize circuit design and performance will be employed. The methodology includes developing proteolytic control mechanisms, engineering secreted protein systems, and implementing circuit-on-circuit dosage control through careful characterization and tuning of individual components. The experimental approach will systematically progress through several key stages. Initially, individual proteolytic regulatory elements will be designed and optimized, establishing their kinetic parameters and dose-response characteristics. These components will then be integrated into IFFL circuits, carefully validating their function using fluorescent reporters. Computational modeling will guide the design process and help predict circuit behavior under various conditions. The project will advance to testing with therapeutic proteins, specifically cytokines, as output molecules. This phase will include extensive characterization of circuit performance in therapeutically relevant cell types and delivery vectors. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY As anti-cancer treatments have become more effective, treatment-related cardiovascular toxicity has emerged as a significant clinical challenge. Doxorubicin, a widely used and cost-efficient anthracycline in first-line chemotherapy, is particularly limited by its substantial cardiovascular toxicity through poorly understood mechanisms. This proposal aims to elucidate these mechanisms and identify potential protective compounds using an integrated approach. In Aims 1 and 2, we will employ CRISPR interference and activation (CRISPRi/a) screens of druggable genes in human induced pluripotent stem cell (iPSC)-derived 2D cardiomyocytes (CMs) and 3D vascularized cardioids (vCOs) to identify cell type-specific causative genes in doxorubicin-induced cytotoxicity. We will validate these findings across multiple iPSC-derived cardiovascular cell types (i.e., CMs, endothelial cells, cardiac smooth muscle cells, cardiac pericytes, and cardiac fibroblasts) and in 3D engineered heart tissues, assessing various cell type-dependent functional parameters. In Aim 3, we will leverage gene-drug interaction databases and molecular docking to identify promising small molecules, particularly from the Drug Repurposing Hub, that can mitigate doxorubicin-induced cardiovascular toxicity. Next, we will evaluate candidate compounds in iPSC-derived cardiovascular cells and in a PANC1 pancreatic cancer xenograft mouse model, assessing their ability to rescue doxorubicin-induced cardiovascular dysfunction. Finally, by integrating gene perturbation programs, cell type-specific phenotypes, and altered pathological signaling pathways, we will elucidate the mechanisms underlying doxorubicin-induced cardiovascular toxicity. The successful completion of this study will not only facilitate the development of novel cardioprotective therapies for cancer patients receiving anthracycline-based treatments but also establish a powerful platform for evaluating drug-induced cardiovascular toxicity beyond cardio-oncology.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT The ability to rapidly induce fully active proteins of interest (POIs) upon drug administration anywhere in the body would be widely useful for developmental biology, synthetic biology, and gene and cell therapies, but existing drug-regulated protein activation methods have limitations in speed, dynamic range, generalizability across proteins, and applicability across tissues. The overall goal of this proposal is to overcome these limitations by developing a novel approach, named Split Protein Ligation Activated by Steroid Hormone (SPLASH), focusing on achieving lower background, faster induction, and plug-and-play generalizability for diverse POIs. The innovative design of SPLASH involves sequestering an intein-extein fusion with the T2 mutant of the estrogen receptor hormone-binding domain (ERT2), so that 4-hydroxytamoxifen (4-OHT) can release it to trans- spice with a complementing intein-extein fusion, resulting in the production of any POI. As an example, SPLASH will be applied to improve the Cre recombinase, addressing issues of leakiness and low induced activity. This work will leverage recent atomic-level understsanding of the steps in steroid hormone receptor sequestration and release by heat-shock complexes, and recent advances in developing fast trans-splicing inteins with broad extein sequence-specificity. SPLASH will be the first method to use a steroid hormone to regulate trans-splicing, and will also introduce a transformative application for fast-splicing inteins. SPLASH will be rationally generated and optimized in two Aims. Aim 1 will focus on generating a functional SPLASH prototype by optimizing topologies, HBD-intein linkages, and intein split sites through bacterial-free library construction and expression. Aim 2 will develop SPLASH-Cre to demonstrate SPLASH utility, evaluating performance in vitro and in vivo using a bioluminescent Cre reporter, and comparing it with untagged Cre and the existing Cre-ERT2. Successful completion of this project will establish SPLASH as a robust method for creating proteins rapidly upon drug administration, providing a versatile tool for basic research, synthetic biology, and gene and cell therapies. The proposal aligns with the R21 focus on technology development, utilizing interdisciplinary approaches and state-of-the-art knowledge to address a crucial need in biomedical research.

NSF Awards · FY 2025 · 2025-09

With the support of the Chemical Measurement and Imaging Program in the Division of Chemistry, Professors Andrew J. Mannix and Felipe Homrich da Jornada of Stanford University will develop new microscopy and quantum simulation tools to directly observe how individual chemical bonds respond to light absorption at the atomic scale. When materials absorb light, they may enter an excited state that alters their structure and electronic properties, influencing performance in technologies such as digital cameras, night vision systems, solar cells, light-emitting diodes, and quantum sensors. However, directly visualizing these structural changes at the level of individual atoms has remained out of reach. This project will advance a new form of photo-induced force microscopy capable of mapping where light is absorbed and how atomic bonds deform in response, enabling direct imaging of excited-state structural changes in molecules and semiconductor materials. By comparing these measurements with advanced quantum simulations, the research will help guide the design of materials that more efficiently capture or emit light. These advances could benefit imaging, sensing, energy, and quantum technologies. The project will also contribute to workforce development by training graduate and undergraduate students in experimental and computational methods, creating instructional materials for chemistry and materials science courses, and participating in public outreach. Methods and results will be disseminated through open-access publications, enabling widespread implementation using existing nanoscale imaging platforms. More specifically, this project will develop a novel implementation of photo-induced force microscopy (PiFM) that operates at cryogenic temperatures and in ultra-high vacuum, enabling sub-angstrom spatial resolution of optically induced forces in individual molecules and atomically thin materials. The technique will combine tip-enhanced optical excitation with mechanical force detection via a quartz tuning fork sensor to directly measure bond-level structural distortions following electronic excitation. These measurements will be quantitatively compared to excited-state force maps generated by ab initio quantum simulations based on many-body perturbation theory and real-space force projection. This integrated experimental–theoretical framework will enable chemically specific analysis of how light absorption perturbs bonding configurations, charge localization, and vibrational coupling. Initial studies will target benchmark chromophores such as pentacene and perylenes, on both metal substrates (e.g., Au) and weakly screening van der Waals substrates (e.g., graphene and hexagonal boron nitride). These platforms will enable targeted investigation of the chemical origins of substrate hybridization and plasmonic enhancement, and how these factors shape the photoinduced force (PiF) spectra. By revealing the atomic-scale mechanisms of excited-state relaxation and reorganization, the project will advance fundamental understanding of excited-state chemistry and light–matter interactions in both molecular and solid-state systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Metastasis accounts for the majority of cancer patient deaths and even though immune checkpoint blockade has proven effective in many malignancies, metastatic disease remains resistant to therapy. Cancer metastasis is an inefficient process, requiring cancer cells to disseminate from primary tumors to distant sites, surviving the stress of migration and evading clearance by circulating immune cells. As a result, metastasis is a selective event, leading to the establishment of metastatic tumors that often consist of just a few clones. Unlike the diverse primary tumor from which they derived, these clones must be capable of adapting to new tissue environments and evading continuous immune surveillance. We hypothesize that even amidst clonal selection during cancer metastasis, cells acquire diverse phenotypes upon subsequent outgrowth that allows them to adapt to their environment and evade innate and adaptive immune responses. Utilizing our family of lymph node metastatic cell lines, we will perform analyses of clonal diversity by viral integration site mapping, profiling diversity across nine rounds of in vivo selection. We will further perform single cell transcriptomics, allowing the diversity of phenotypes to be uncovered in relation to the clonal composition of each cell line. Expanding these analyses, we will perform analogous experiments using human head and neck squamous cell carcinoma specimens, validating whether amidst low genomic clonality tumors can support diverse phenotypic fates. As we have described previously, metastasis to lymph nodes can induce immune tolerance that permits further dissemination of cancer cells. We further hypothesize that these diverse phenotypes of metastatic cells drive unique lymphocyte phenotypes and clonal responses, such that the two antagonize one another. To address this hypothesis, we will perform phenotypic and immune repertoire diversity profiling by spectral flow cytometry and single cell genomics of murine tumors of varying clonality and the patient tumors already assessed for clonality and phenotype. The resulting relationship between tumor clonality, T cell phenotype, and T cell clonal diversity will address whether tumors and lymphocytes evolve antagonistically, adopting varied fates and clonal architectures in an attempt to outcompete the other side. We will finally perform similar immune analyses of a metastatic cell line evolved in the absence of lymphocyte pressure, validating whether ongoing coevolution of tumors and lymphocytes is occurring during cancer metastasis. These experiments will address the mechanisms of antagonism and adaption at the tumor-immune interface during cancer metastasis and identify potential avenues of therapeutic intervention to enhance immune responses against metastasis, such as delivery of vaccines containing diverse antigens to increase lymphocyte diversity.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Pulmonary neuroendocrine cells (NECs) are rare airway neuroepithelial cells with diverse sensory, signaling, and stem cell functions. NECs have recently become one of the better studied rare cell types of the mammalian lung, most notably through mouse studies. Ours and others’ single cell anatomical mapping, lineage studies, and transcriptional profiling in mice have led to a rich understanding of their development molecular diversity, and stem cell and airway repair function, and physiological studies show their function as specialized sensors that modulate breathing. In contrast to this rich understanding of mouse NECs, little is known about human NECs, including their anatomical distribution, structures, progenitor cell function, and response to airway injury and role in repair. Because NE diseases originating from proximal airways have distinct clinical, histologic, and molecular features from those found in the distal airways, we constructed a foundational cell resolution anatomical map and generated initial molecular and proliferative profiles of human NECs to identify NE progenitor cells within their ‘niches’, and to uncover the origin of diverse human NE proliferative disorders. We have discovered extensive anatomical, histological, and molecular diversity in PNECs not modeled in mouse. Using precision cut lung slice (PCLS) cultures from normal adult human lung, we find that a subset of healthy adult human NECs proliferates in distal NEBs. This enables functional interrogation of these putative NE progenitors (NEPr), which we propose to identify and characterize here. We hypothesize that human distal airway NEBs harbor a specialized subset of molecularly and functionally distinct NE progenitors, and we predict human progenitors are activated by airway injury and controlled by a similar mitogenic pathway as in mouse. Here, we propose to use acute injury models to activate NEPr in human lung precision cut lung slice cultures and in whole donor lungs to reveal their molecular profiles and their ‘niches’ by spatial transcriptomics. We predict NEPr are a prominent source of human NE proliferative disorders and pathologies of the distal airways, such as diffuse idiopathic pulmonary neuroendocrine cell hyperplasia (DIPNECH), which we propose to examine here by single cell and spatial transcriptomics. Finally, we will identify the mitogenic pathway regulating distal human NEPr, which could provide therapeutic target(s) for DIPNECH and other distal NEPr disorders. Identification and characterization of NEPr in distal airways would establish a foundation for elucidating their roles in repair and disease, and for creating human organoid and human induced pluripotent stem cell (iPSC) models that accurately model distal human neuroendocrinopathies. This work also provides a strategy for identifying and characterizing the NEPr and associated diseases in other regions of the human lung.

NIH Research Projects · FY 2025 · 2025-09

The goal of this project is to use a newly developed, transparent ultrasound transducer together with in vivo optical imaging to study the direct effects of ultrasound on retinal ganglion cell (RGC) activity. Ultrasound stimulation of the eye has been demonstrated to preserve RGCs after optic nerve injury, making it a promising strategy for neuroprotection and vision preservation. Although the physical mechanisms of ultrasound stimulation have been explored in the ex vivo retina, its range of effective parameters in vivo and underlying biophysical mechanisms are not well understood. Due to the optical accessibility of the retina, RGC activity can be noninvasively monitored in vivo using Ca2+ imaging with genetically encoded calcium indicators. However, conventional ultrasound transducers are opaque and will block the light path for Ca2+ imaging by microscopy. To address this limitation, we have developed a novel class of transparent ultrasound transducers that facilitates in vivo Ca2+ imaging while providing ultrasound stimulation. With this new tool, we will study the mechanisms and therapeutic efficacy of ultrasound retinal stimulation. We propose to determine effective parameters for ultrasound retinal stimulation, and test its physical mechanisms and clinical applications for neuroprotection using in vivo 2-photon imaging and animal models. A multi-disciplinary team with complementary expertise is assembled to perform the proposed aims. The team consists of experts in transducer fabrication, ultrasound neuromodulation, retinal physiology and optic nerve disease. Ultrasound is an emerging, noninvasive technology explored for vision-preserving therapies. To apply ultrasound retinal stimulation in a safe and predictable manner, a detailed understanding of the effects of ultrasound on neural activity is required. By using new technology, this project addresses a critical need to understand the effects of ultrasound neuromodulation in the retina and other nervous systems in vivo, and also carries significant translational potential. Information about how ultrasound modulates RGC activity should allow us to develop safer and more effective ultrasound-based therapies for optic nerve disorders and retinal degenerations.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Glaucoma, the most common worldwide cause of irreversible blindness, is characterized by progressive dysfunction and death of retinal ganglion cells (RGCs) and degeneration of optic nerve (ON). There is a significant unmet clinical need for neuroprotectants. Our previous studies of ON traumatic injury and glaucoma demonstrated that axon injury induce neuronal endoplasmic reticulum (ER) stress in RGCs. We were able to protect the injured RGC somata and axons if we blocked the detrimental effects of ER stress by manipulating two key downstream molecules in opposite ways: a) deletion of CCAAT/enhancer binding protein homologous protein (CHOP), and/or b) activation of X-box binding protein 1 (XBP-1). Using complimentary cell-based high throughput screening (HTS) of small molecule libraries, we identified multiple series of chemical modulators of ER stress (CHOP inhibitors and XBP-1 activators), which are promising neuroprotectant candidates. We will further optimize these chemical ER stress modulators, determine their in vivo efficacies in clinically relevant mouse glaucoma models, and illustrate their mechanism of action. We expect the results through these studies will identify preclinical drug candidates and provide essential information for clinical application of ER stress modulation, and establish translational strategies for safe and effective clinical management of glaucoma patients.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Atrial fibrillation (afib) is a very common arrhythmia that affects up to 1 in 4 people over the age of 40 in their lifetime, leading to major complications such as stroke and heart failure. There is growing evidence that a proportion of afib cases result from an atrial cardiomyopathic process in which the fundamental contractile function of the myocytes is altered, yet the fundamental mechanism is not well understood. Therapeutic approaches to treating afib have largely focused on electrical modulation and structurally isolating the abnormal rhythm, but this approach does not address the underlying pathology of the atria, and, unsurprisingly, many patients have recurrence due to further progression of atrial remodeling. Therefore, it is critical to study the fundamental contractile function in atrial cardiomyocytes to gain further insights into the mechanism of afib. Here, we propose to study known genetic causes of afib in atrial cardiac myosin using the human recombinant α-cardiac myosin system and state-of-the-art biochemical and biophysical assays we have developed with the β-cardiac myosin platform. In Aim 1, we will construct the α-cardiac myosin heavy chain (MYH6), essential light chain (MYL4), and regulatory light chain (MYL7), and compare their function with the β-cardiac myosin. We will make several structural variations of the wildtype α-cardiac myosin using the heavy chain and light chains above to perform a comprehensive analysis. In Aim 2, we will produce mutant α-cardiac myosin found in familial afib cases with mutations in MYH6 (R721W, E933Δ). Some of these mutations (MYH6 R721W and E933Δ) are seen in patients with hypertrophic cardiomyopathy when the same location in β-cardiac myosin is mutated. We will determine their effect on myosin activity and overall sarcomere function. Our experimental platform will be the first to comprehensively study the human α-cardiac myosin with various mutations using the recombinant protein to carry out sophisticated biochemical and biophysical analysis. The results from this study will lead to critical preliminary data for an R01 grant to further study the mechanism of afib and will help develop novel therapies for this very common cardiovascular disease.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Otitis media (OM), or infection of the middle ear, is the one of most common illnesses diagnosed in children in the United States and is the leading reason for pediatric antibiotic prescriptions. Acute OM is most commonly caused by the bacteria Streptococcus pneumoniae, Haemophilus influenzae, Moraxella catarrhalis and Staphylococcus aureus, while Pseudomonas aeruginosa is the most common cause of chronic OM. Diagnosis of OM currently relies on otoscopy, which has low sensitivity and specificity and is unable to differentiate bacterial infection from other causes of inflammation. These limitations result in over-diagnosis and over- prescription of antibiotics, contributing to increased antimicrobial resistance (AMR) and subsequent treatment failures. Therefore, there is a significant unmet need for improved diagnostic tools for OM that can enable faster and more effective treatment decisions and reduce the potential for AMR development. Photodynamic therapy (PDT), is a promising antimicrobial treatment option in which light-activated photosensitizers induce cell killing. However, prior applications of PDT to bacteria have been untargeted or used non-covalent methods of targeting, raising the risks of off-target toxicity and resistance development. Covalent targeting of enzyme active sites has the potential to address these current shortcomings and result in probes capable of both imaging and treatment applications. The overall objective of this proposal is to engineer a covalent theranostic probe targeting bacterial D,D-carboxypeptidases (DD-CPases) as a novel tool for imaging and treating bacterial OM using PDT. All five common OM-causing bacteria have a DD-CPase and humans lack homologs. Therefore, the primary aims of this project are to: (1) develop a covalent activity-based probe (ABP) suitable for imaging and treatment of the five primary OM-causing bacteria; (2) demonstrate that a single covalent probe can be used to image and kill the five most common OM-causing bacteria in vitro, and (3) use the top probe to confirm imaging and killing of the two most common OM-causing bacteria in vivo. Success with these aims will result in a strategy for diagnosis and treatment of OM that will reduce AMR development, reduce treatment failures, and prevent progression to chronic OM and its associated complications. In addition, the training plan outlines a comprehensive strategy for career advancement for the applicant, Dr. Emily Woods, under the mentorship of the sponsor, Dr. Matthew Bogyo. Dr. Woods will engage in a variety of seminars, courses, and experiences to develop her scientific and academic skills and enable her transition to independence. Overall, the proposed studies are expected to generate a novel tool for improved diagnosis and treatment of bacterial OM.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT Mammals, including humans, evolved complex lipid transport and processing machinery to acquire and produce lipids and fatty acids to be used as building material for membranes, fats for energy storage or molecules for cell-cell signaling. Our deep knowledge of the physiology of lipid transport and processing is central to our understanding of human physiology but also cardiovascular disease, regulation of hormones, energy homeostasis or cancer. While humans evolved one version of lipid transport and processing machinery there exist a plethora of alternatives realized in non-model organisms. As a whole they can provide us with a breadth of general concepts that can be exploited to manipulate lipid transport and processing to improve human health. Plasmodium has evolved to replace the lipid transport and processing systems that its host-Red Blood Cell has removed in the process of specialization on oxygen transport. As the Red Blood Cell lost its lipid transporting and processing organelles, endoplasmic reticulum, Golgi apparatus and mitochondria, Plasmodium exapted (evolved to work in a new environment) its own proteins to take on new functions in the human host cell. Plasmodium thus features an independently evolved lipid transport and processing machinery compatible with human physiology. Our goal is to identify and characterize function of these analogous proteins, unrecognizable in sequence when compared to known analogues. To understand the range of lipids transported by Plasmodium, we will quantify lipid uptake dynamics of fluorescent lipid analogs. This allows us to construct a lipid uptake matrix (compartment vs lipid) that can be used identify activity of lipid transport and processing proteins. Novel lipid transport and processing proteins will be identified using the structural lipid interacting pocket predictor and proximity biotinylation of proteins at membrane contact site regions implicated in lipid transport. Proteins will be functionally characterized in vivo for their role in Plasmodium’s ability to transport and process lipids supported by in vitro characterization of lipid binding using recombinant proteins. Finally, the identified lipid transport and processing proteins will be characterized in a human cell line by localization to organelles and quantification of their impact on the cell’s lipid metabolism. In summary, our work identifies and characterizes an alternative version of the human lipid transport and processing machinery allowing us to recognize and conceptualize general principles of lipid handling to understand human physiology and expanding the design space to manipulate the human lipidome.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT California’s Central Valley has one of the highest incidence of end-stage kidney disease in the United States. This region shares climate, topography, and agricultural activity with international regions experiencing epidemics of chronic kidney disease among agricultural workers, termed chronic kidney disease of unknown etiology (CKDu). It remains unclear whether agricultural workers in California are also vulnerable to a disproportionate risk for chronic kidney disease. In her post-doctoral training period, Dr. Marimar Contreras Nieves aims to investigate potential environmental and occupational exposures related to kidney disease in California’s Central Valley by: 1) leveraging existing data on temperature records and incident kidney disease, and 2) leading primary data collection among patients undergoing dialysis in Central Valley. She will use existing data from the United States Renal Data System (USRDS) to obtain zip code tabulation area end-stage kidney disease incidence, and test its association with 5-year antecedent temperature maximums using data from the PRISM Climate group, accounting for geographic distribution of age, sex, race, ethnicity, occupation, income, comorbid medical conditions, and air quality. In addition, Dr. Contreras Nieves proposes a case-control study to recruit a total of 600 patients, with cases being patients with unexplained ESKD, who will be matched by age and sex to controls with known causes of ESKD from dialysis units in pre-identified hotspots of unexplained ESKD. She will administer a questionnaire to ascertain patients’ residence and workplace history, clinical history, agricultural work history, pesticide and groundwater exposure, and healthcare access. Dr. Contreras Nieves’s multidisciplinary team of mentors will include as primary mentor nephrologist Dr. Shuchi Anand, as co-mentors geochemist Dr. Penny Vlahos and biostatistician Dr. Maria Montez-Rath, and as collaborator Dr. Sam Heft-Neal, who will work together to position Dr. Contreras Nieves as an expert in environmental health and community-engaged research in nephrology. In summary, this proposal will provide Dr. Contreras Nieves with the mentorship, training, and research experience to develop a career development award proposal at the intersection of environmental health and kidney disease.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Cardiac fibrosis, a hallmark of aging, leads to tissue stiffness, impaired cardiac function, and heart failure, significantly reducing quality of life in elderly populations. Despite its clinical burden, no FDA-approved therapies exist for treating cardiac fibrosis, underscoring an urgent need for innovative solutions. This UG3/UH3 study aims to discover and validate novel antifibrotic compounds by leveraging cutting-edge technologies, including human induced pluripotent stem cells (iPSCs), artificial intelligence (AI), and advanced preclinical models. The UG3 phase will focus on high-throughput screening (HTS) of over 225,000 compounds using iPSC-derived cardiac fibroblast (iPSC-CF) reporter lines to identify lead candidates. The ADMET-AI platform will filter these candidates for favorable drug-like properties and low toxicity. In the UH3 phase, selected compounds will undergo robust in vitro and in vivo validation. This includes testing in “cell villages” for population-scale evaluations and 3D cardiac organoids to assess efficacy and safety in tissue-like environments. The top two hits, including a repurposed drug and a novel compound, will be tested in aging mice to examine their therapeutic potential in restoring cardiac function and reducing fibrosis. This multidisciplinary approach integrates fibrosis research, AI/ML tools, and iPSC technology to address a critical unmet need in aging cardiovascular health. By targeting senescent fibroblasts and employing innovative drug screening platforms, this UG3/UH3 study has the potential to advance the discovery of effective antifibrotic therapies, paving the way for clinical translation and improving outcomes in aging populations.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Malaria in pregnancy is one of the leading causes of infant death globally. Placental malaria (PM) is the main mechanism by which malaria in pregnancy causes birth complications, such as preterm birth, stillbirth, and low birth weight. During PM, Plasmodium falciparum (Pf)-infected red blood cells sequester to syncytiotrophoblasts (STB) within the placental intervillous space, stimulating maternal immune cell recruitment and leading to other placental pathologic changes. With increasing gravidity, the severity of PM decreases and birth outcomes improve as pregnant women acquire Pf-specific antibodies (Abs) against a variant surface protein – VAR2CSA – after repeated Pf exposures. Previous work shows that neutralizing Abs against VAR2CSA are important for protection but do not entirely prevent neonatal complications, which suggests a key role for Ab-mediated effector functions. Work by our group and others demonstrates that Ab-mediated effector functions are crucial for naturally acquired immunity to malaria in children. We hypothesize that myeloid cell state, phagocyte localization at the maternal-fetal interface, and Ab repertoire adapt with repeated Pf exposure in a gravidity-dependent manner, and that Ab-dependent phagocytosis (ADP) is necessary for limiting PM pathogenesis and improving neonatal outcomes. To test this hypothesis, we will leverage an extraordinary biobank of plasma and placental tissue collected from pregnant women enrolled in the DPSP clinical trial (U01 AI1431308). In Aim 1, using novel spatial proteomic (MIBI-TOF) and transcriptomic (NanoString DSP) imaging approaches, we will determine how Pf parasitemia and gravidity shape myeloid cell - STB spatial relationships that drive Pf clearance in placental tissue. We will test whether, with increasing gravidity, inflammatory maternal myeloid cell infiltration will decrease, and maternal phagocytes will preferentially localize to the Pf-infected STB. In Aim 2, we will utilize in vitro models to determine how gravidity-induced Ab modifications influence Fc-mediated protection from malaria in pregnancy. Together, successful completion of these aims will inform vaccine development and therapeutic strategies to reduce the global burden of malaria in pregnancy.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY In both autologous and allogenic islet transplantation, islets need to pass through the following steps: Step 1 - Isolation: When islets are extracted from the pancreas, they are subject to chemical and physical digestion steps that places them under significant stress, leaving them in a “fragile state” with metabolic dysfunction that makes them highly susceptible to any further injury. Step 2 - Implantation: When delivered into the liver via infusion into the portal vein, islets encounter a relatively hostile microenvironment which is hypoxic and contains high concentrations of metabolites, as well as being subject to an instant blood-mediated inflammatory reaction (IBMIR) that involves activation of the complement and coagulation cascades. Step 3 - Engraftment: Once islets settle within hepatic sinusoids, they need to remodel the extracellular matrix (ECM) and form new connections with the host tissue as well as develop a new vascular supply from branches of the hepatic artery to meet their ongoing metabolic demands. Unfortunately, these processes collectively place significant stress on islets, resulting in almost 60% of them being lost within the first 2-3 weeks following transplantation. One promising approach to help rescue and protect islets through these steps is to use mesenchymal stem/stromal cells (MSCs). Our data supports the use of umbilical cord derived MSCs (UC-MSCs) as an optimal candidate for islet transplantation, given they can be easily derived and expanded, are relatively homogenous across donors, and have an enhanced anti-inflammatory and immunomodulatory capacity. However, they unfortunately express tissue factor (TF) which will reduce their ability to be used with islets when administered into the portal vein given this will exacerbate the IBMIR. Recently, we developed a novel approach using pulsed focused ultrasound (pFUS) to reproducibly prime UC-MSCs (pUC-MSCs), resulting in them having an enhanced bioenergetic capacity, reduced expression of TF and enhanced expression of ECM remodeling and angiogenic factors. Interestingly pFUS also increases the synthesis and secretion of extracellular vesicles (pUC-EVs; a novel and clinically scalable cell-free therapy), with these vesicles also demonstrating a reduced ability for activating the coagulation cascade. We have also demonstrated the ability of pFUS to stimulate islet function and viability, in addition to priming sites of islet transplantation where sonicated tissue resulted in improved islet engraftment. Hence, in this proposal, we aim to validate these clinically scalable therapies (i.e. pUC-MSCs and pUC-EVs from different human donors to ensure reproducibility) and our novel technology (i.e. pFUS for islet and organ priming) to improve the functionality of isolated islets (Aim 1 – addressing Step 1), their survival following implantation into the liver (Aim 2 – addressing Step 2), and their subsequent engraftment (Aim 3 – addressing Step 3). Finally, we will also examine if pUC-MSCs and pUC-EVs can rescue islet function post transplantation, especially when given directly into the liver via locoregional delivery into the hepatic artery.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract: Catheter embolization is a critical treatment for multiple diseases, including hepatocellular carcinoma, uterine fibroids, renal cell carcinoma, and massive hemoptysis in cystic fibrosis. However, current embolization endpoint assessment is subjective, relying on intermittent X-ray imaging to evaluate blood flow qualitatively in the treated artery. Current X-ray embolization endpoint assessment methods are operator-dependent and not quantitative, leading to potential undertreatment or overtreatment. Our research aims to develop a novel method for quantitative flow assessment within the treated artery, providing a more accurate evaluation of embolization treatment. I propose integrating electrochemical impedance spectroscopy (EIS) sensors into catheters for real-time monitoring of embolization. Catheter sensing of embolization will reduce reliance on high-radiation techniques like quantitative digital subtraction angiography and avoid impracticalities associated with Doppler guidewires and intraoperative MRI flow assessment. In this project, I will miniaturize sensor catheter technology to microcatheters, that are commonly used for embolization and are able to track through small blood vessels. In addition, I will evaluate feasibility of new methods for continuous blood flow determination by the sensor catheters. Upon completion, this project will enhance the clinical translatability and utility of catheter embolization by realizing sensor microcatheters potentially providing continuous blood flow sensing. This innovation will have broad applications in intravascular flow sensing, benefiting fields such as interventional radiology and cardiology, ultimately improving the safety and efficacy of catheter procedures.

NIH Research Projects · FY 2025 · 2025-09

ComponentAutoimmune diseases comprise a large set of disorders that together afflict almost 50 million Americans; four out of five patients with autoimmunity are women. The mission of the Specialized Center of Research Excellence on Sex Differences in Autoimmunity (SCORE-X) is to serve as a national resource in understanding sex as a biological variable in autoimmunity. SCORE-X has three objectives. Objective 1 is to drive innovation and intellectual leadership of sex biased autoimmunity. Human organoids and spatial proteomics will be employed to dissect the newly recognized role of female-specific XIST RNA protein complex in driving autoimmunity. Objective 2 is to enable translational interdisciplinary advance of sex-biased autoimmunity, focusing on the diagnostic and prognostic opportunities from the recent discovery of anti-XIST RNP antibodies in patients with autoimmune diseases. Objective 3 is to enhance collaborative, and research educational opportunities. SCORE-X will create and coordinate research projects, pilot programs, and educational programs to support the SCORE consortium, and broadly disseminate new insights, technologies, and resources developed at SCORE-X. SCORE-X will promote training and education in sex differences in autoimmunity through the establishment of a Pilot grant program for early stage investigators and integrated educational program along the entire training pipeline. The end result will be a national resource for transformative advance in the mechanistic understanding, clinical translation, and educational opportunities for sex differences in autoimmunity.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Coronary artery disease (CAD) is the leading cause of death worldwide, but therapeutic options beyond lipid lowering strategies remain lacking for due to the critical knowledge gap linking genetic risk factors to disease mechanisms. Smooth muscle cells (SMCs) play a critical role in atherosclerosis development. These cells undergo a phenotypic transition process, where they dedifferentiate and migrate out of the blood vessel media and contribute to the fibrous cap. Furthermore, SMCs have been identified as the primary source of genetic susceptibility to CAD. Dr. Daniel Li’s (PI) preliminary data prioritizing transcription factors involved in phenotypic transition using probabilistic cell fate mapping has identified the ZEB transcription factor family (ZEB1 and ZEB2) as key genes driving this process. ZEBs regulate cell proliferation and plasticity, while human genetics has associated both genes with CAD risk. The genetic risk signal near ZEB2 can be explained by its role as an epigenetic regulator of SMC fate. However, the cellular mechanism(s) by which ZEB1 influences disease risk are unknown. ZEB factors share conserved DNA binding domains but have low homology in protein interaction domains, allowing the recruitment of diverse epigenetic regulators. Furthermore, they have reciprocal cellular transcriptional profiles in atherosclerosis-relevant cell types. The primary objective of this proposal is to characterize and establish the causal role of ZEB1 in atherosclerosis development. The central hypothesis is that ZEB1 acts as a counter-regulatory factor to ZEB2 via epigenetic mechanisms to maintain a differentiated smooth muscle state in the setting of vascular wall stress. Aim 1 will use a translational Zeb1 knockout mouse model to determine the transcriptional, epigenetic, and plaque phenotype of SMC lineage cells. Aim 2 will use functional genomics and proteomics to determine how ZEB factors differentially regulate SMC transcriptional processes via epigenetic mechanisms. The results of this study will elucidate the underlying mechanisms by which two novel but potentially counter-regulatory CAD genes drive the phenotypic transition of SMCs. In parallel, Dr. Li will complete a comprehensive training plan to 1) advance his background in bioinformatic tools for genetics and genomics, 2) develop expertise in the use and applications of proteomics, 3) build upon scientific and communication skills, and 4) further develop his scientific writing and grantsmanship skills and transition to academic research independence. This research proposal will be guided by Dr. Quertermous, a world leader in cardiovascular genetics, and an advisory committee consisting of world-renowned experts in computational genomic methods, proteomics, cardiovascular epidemiology, and vascular biology. Through this project, Dr. Li will develop the skillset to become an independent investigator dedicated to deciphering the genetic risks in atherosclerosis and translating these findings towards clinical practice.

NSF Awards · FY 2025 · 2025-09

Despite popular discourse about how generative artificial intelligence (AI) tools might increase efficiencies in education, it is yet to be determined how--or even if--AI tools for teachers are having that envisioned effect. There is currently a baseline assumption that AI should increase teacher efficiency through offloading. However, there is limited research to support such claims, and there is reason to believe that AI could increase workload or cause unexpected shifts in teacher responsibilities due to the unique demands of classroom teaching. Researchers need new methodological approaches to understand generative AI's impact on teacher experience and daily work. By exploring and refining research instrumentation to study how AI affects teaching, this project will inform efforts to improve educational practice and ensure that new technologies support rather than burden teachers. The resulting instrumentation will be made publicly available to support broader investigations into how emerging technologies shape the teaching profession. The goal of this ECR: Level I project is to examine, adapt, and deploy instrumentation that can help researchers investigate generative AI's impact on teacher work and generate necessary information to guide future decisions. Most immediately, the instrumentation will enable closer scrutiny of assumptions about teacher efficiency with AI. The project centers on experience sampling method (ESM), a technique originating from psychology that involves repeated brief random digital surveys to capture what people are doing, when they are doing it, in what context, and how they are thinking about it. Although advocated for in education research, ESM remains largely underexplored for studying teachers. With widespread access to mobile devices, ESM is more feasible than in previous decades, but requires intensive design and testing to ensure it fits the realities of classroom teaching. Over three years, this pilot study will adapt ESM for use with teachers and, in parallel, examine the extent and nature of efficiency changes as a result of a partnering school district's commitment to supporting teacher use of generative AI. The district serves over 10,000 K-12 students, offering a meaningful test case for understanding AI-related changes in practice. The research will focus on two key questions: (1) What attributes and parameters do teachers consider in their perception of their work allocation, and how could those be sampled given unique challenges associated with the work and schedules of classroom teaching? and (2) How effectively does digital ESM obtain a record of teachers' activities as sampled in comparison to human observation and retrospective recall? The work will begin with collaborative design with teachers to determine appropriate approaches and queries for ESM that respect privacy and workload. It will then compare ESM data to other observational techniques to evaluate the data quality of this new approach. The resulting instrumentation and validated protocols will contribute new tools for education researchers to test assumptions about technology's impact on teacher work, advancing the field's interest in expanding the use experience sampling methods for studying educational practice. This project is funded by the EDU Core Research (ECR) and Innovative Technology Experiences for Students and Teachers (ITEST) programs. It supports the ECR program, which emphasizes fundamental STEM education research that generates foundational knowledge in the field. It supports ITEST program goals to build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in STEM and information and communication technology (ICT) careers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-09

Since 2007, we have annually tracked the dynamics of immune system changes with the Stanford Ellison Longitudinal Aging (SELA) cohort, which consists of ~150 young (20-40) and old (60+) individuals of various ages for which we determined cell subset phenotypes and cytokine responses at high resolution, whole blood gene expression, serum cytokines, HAI response to annual flu vaccination, and a standardized clinical evaluation. Given the length of time and the depth of profiling, the SELA cohort is a unique resource. Using a novel systems approach which leverages the high-dimensional and longitudinal nature of the data allowed us to gain increased insight into immune-aging and describe an individual’s immune baseline homeostatic state as shifting slowly along a continuum and a trajectory, well beyond what can normally be obtained from cross-sectional analyses. We utilized this to build a reliable metric of immune-age (IMM-AGE), which captures a life-long process of change in immune cell subset composition and cell responses in a single value. IMM-AGE only partially correlates with chronological age and yet has prognostic clinical value with respect to all-cause-mortality in healthy older adults beyond well-established risk factors. In addition, using SELA we have identified several strong links between cardiovascular disease and immune-based predictive markers, correlative to IMM-AGE, that offer better and earlier detection than existing standard clinical tests. Understanding human immune variation and aging through the lens of a quantitative patterned process led us to testable hypotheses which we will explore here. Specifically, our two research projects address two questions – (1) what drives immune-aging; and (2) how does it relate to immune response, disease severity, and treatment? To answer these questions we will continue the longitudinal profiling of SELA, now with more epigenetic and environmental data, and recruit additional cohorts: a healthy twin cohort (ages 40-60), a current gap in SELA and one informative of early immune aging; a cohort of older adults vigorously exercising and living well which can be leveraged to distinguish features of biological aging and those modifiable by lifestyle and for which we have measured immune parameters in 2011; and two additional cohorts, first of heart transplant subjects and second of subjects in the Women’s Health Initiative with retrospective information on cardiovascular state. These latter cohorts will allow us to test hypotheses raised from our published studies on the relation of immune-aging to cardiovascular disease and its connection to flu history, an observed epidemiological association whose mechanism has been unclear to date. Last, we will use post-vaccination samples from SELA collected over 12+ years to map flu-specific B and T cell response history and test whether this information, coupled with immune- age, can help predict flu vaccine responses in older adults, a currently unsolved problem with major clinical implications. Insights of this work will lead to refinement of the metric, its connection to human physiology, and provide a means to assess how immune-aging plays a role in the chronic and acute age associated conditions.

NIH Research Projects · FY 2025 · 2025-08

Innate allorecognition and KIR/LILR/HLA associations in kidney transplantation Kidney transplantation is a life-saving treatment for patients with end-stage renal disease. Despite significant improvements in short-term renal allograft survival, long-term graft survival remains suboptimal due to chronic rejection. We hypothesize that innate allorecognition - the sensing of human leukocyte antigen (HLA) in the graft by killer Ig-like receptors (KIR) and leukocyte Ig-like receptors (LILR) on recipient NK cells and monocytes – is a key driver of chronic rejection. We propose to test the hypothesis by investigating associations between HLA/KIR/LILR genetic variations and clinicopathological allograft outcomes in 2,000 donor/recipient kidney transplant pairs derived from curated North American (Pittsburgh and San Francisco) and French (Paris and Lyon) patient cohorts that are ethnically diverse. We will perform high coverage short-read and HiFi long-read genomic DNA sequencing to obtain high resolution HLA and KIR/LILR typing, respectively. The related KIR and LILR gene families reside adjacent to each other in a region on chromosome 19 that spans <1Mbp. Low coverage whole genome sequencing will also be performed to infer genomic ancestry, donor/recipient relatedness, and polymorphisms that influence allograft outcomes. Finally, NK cell and monocyte analysis in blood and allografts will be conducted on a subset of patients to gain mechanistic insights. The work will be executed by a multidisciplinary team that includes experts from transplant nephrology, immunology, tissue typing, pathology, and biostatistics & bioinformatics. The uniqueness of the proposal derives from the high quality, long-term, clinicopathological data available for the cohorts; serially banked bio- samples; accurate assembly of the KIR/LILR region through HiFi long-read sequencing; concurrently available whole genome data; and the innovative scope of the proposal, which extends the concept of allorecognition beyond T, B, and NK cells to monocytes. Information gained could be readily implemented in the clinic to improve donor/recipient matching or patient risk stratification and to provide genetic underpinnings for therapeutic targeting of innate immune pathways in transplantation.