University Of Southern California

NIH Research Projects · FY 2025 · 2025-07

ABSTRACT - “Chemistry-Enabled Glycoscience” Overall changes in glycosylation are associated with many human diseases. Cancer cells increase the levels of specific capping sugars on their surfaces, while levels of the intracellular glycan O-GlcNAc are lower in Alzheimer's disease. Some of these associative changes are being exploited as potential therapies. However, a deeper understanding of what glycosylation is doing to the biochemistry and function of the underlying proteins is still largely lacking. For example, thousands of proteins are modified by O-GlcNAc but the effects of the vast majority of these modifications are completely unknown. For several reasons - heterogeneity, multiple modification sites, low immunogenicity, etc. - traditional biological tools have limitations for glycosylation. We have built a research program centered around the development and application of chemistry-enabled approaches aimed at unanswered questions in glycoscience. For example, we have played an important role improving and applying bioorthogonal reporters of glycans in living systems. We are also leaders in the application of protein synthesis to generate site-specifically glycosylated proteins for for in vitro and even in vivo characterization. We plan to build upon these successes to a) generate and apply cell/ tissue-selective reporters and inhibitors of glycosylation, b) create activity based probes of monosaccharide biosynthesis, c & d) further understand the effects of O-GlcNAc on pathogenic protein-aggregation, and e) investigate the consequences of mucin glycans on apolipoproteins. In the next five years, we will have created and used new tools for glycoscience in living systems and further unraveled the mechanisms by which glycosylation changes the biology of important proteins in human diseases.

NSF Awards · FY 2025 · 2025-07

The use of modern computing and data infrastructure is critical to harnessing the full potential of instruments, data, and tools offered by state-of-the-art laboratory facilities, but many scientists do not have the necessary knowledge of data management, scientific programming skills, or the ability to use computing resources to bring them to bear for data analysis, leading to new discoveries. This project - CITEAM - addresses the gap by developing an innovative training program targeting the materials science research community that relies on advanced microscopes for research and needs to process and manage large data volumes to make fundamental advances in materials science. CITEAM provides training for microscope data processing, the use of Artificial Intelligence methods in data analysis, and effective data management, thereby reducing time-to-science. The project helps researchers in overcoming challenges in handling large-scale datasets and utilizing novel computing methods and resources. The project increases computing skills, awareness, and literacy for researchers with limited computing expertise, thereby accelerating the scientific innovations in materials science. The CITEAM project brings together a team of researchers with expertise in cyberinfrastructure (CI) as well as in imaging-enabled materials science to develop an innovative training program targeting the materials science community that relies on advanced microscopes (e.g. Transmission Electron Microscopes (TEM)) for research. This project aims at optimizing return on a state-of-the-art investment in physical infrastructure - a new aberration-corrected Transmission/Scanning Electron Microscope (AC TEM/STEM) at UMD. The training program covers several relevant thematic areas - TEM instrument software, image analysis, scientific computing, application of AI in TEM image and data analysis, diffraction and spectroscopy data analysis, distributed computing for microscope data processing, data curation, and FAIR principles. The training program includes an additional element of "training the trainers" by exposing the research facilitators and laboratory staff scientists to advanced CI topics, empowering them to guide others and innovate in the use of CI for materials science. Training is offered for both users and trainers in a multitude of modalities to promote efficient learning - self-paced modules, video lectures, templates and catalogs, office hours, training sessions at annual CITEAM Users' workshop, and tutorials at domain science conferences. CITEAM promotes community building by developing a coordination network comprising similar imaging laboratories, different domain science communities that use advanced microscopes, and experts from national CI resource providers. The CITEAM coordination network helps in adapting and disseminating training materials beyond the participating institutions, ensuring both scalability and sustainability of the program. 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 · 2025-07

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professor Richard Brutchey of the University of Southern California, in collaboration with Professors Elad Gross and Uri Banin of the Hebrew University of Jerusalem, will investigate new strategies to enhance the stability and performance of colloidal gold nanoparticles, which are widely used in medical diagnostics, cancer therapies, and chemical catalysis. Although gold nanoparticles have been employed for decades—such as in immunoassay-based diagnostic tests—their surfaces are typically coated with sulfur-containing organic molecules called thiols, which are prone to degradation when exposed to heat, light, or air. This project will explore a more durable class of organic molecules known as N-heterocyclic carbenes (NHCs), aiming to understand how these molecules bind to gold surfaces and contribute to the development of more robust, stable, and customizable nanoparticles. Beyond laboratory research, the team will conduct immersive nanochemistry workshops for community college students at Cerritos College in Los Angeles County, fostering interest and retention in STEM fields while promoting international collaboration and increasing transfer rates to four-year institutions. This research effort will focus on elucidating the binding behavior of NHCs on gold nanoparticle surfaces in comparison with traditional thiol-based ligands, particularly in terms of binding strength and crystal facet specificity. The team will experimentally quantify the thermodynamics of ligand binding—measuring enthalpy, entropy, and free energy—using variable-temperature solution nuclear magnetic resonance spectroscopy and isothermal titration calorimetry. Additionally, high-resolution infrared nanospectroscopy will be employed to investigate how NHCs and thiols competitively interact with distinct gold nanoparticle facets at the atomic scale. These findings will provide crucial insights into the mechanisms of NHC–gold surface binding, helping enable the rational design of more stable gold nanoparticle systems for targeted applications. 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 2026 · 2025-06

Environmental exposures related to weather, including heat and wildfire smoke, have been related to multiple facets of health and child development. The impacts of these exposures over the life course on cardiovascular health remain largely unknown. Growing evidence indicates that exposure to heat stress and wildfire smoke may lead to adverse cardiovascular health outcomes and mortality in adults. Yet little is known about how such exposures may influence the development of cardiovascular risk factors in younger populations, when prevention strategies may have the greatest long-term health impact. Little to no research has focused on heat stress and wildfire smoke exposures over the critical transition from adolescence to early adulthood, during which adverse patterns of cardiovascular health may be established and preventative strategies may be most effective in reducing chronic disease risk over the life course. Further, such environmental exposures often co-occur, and evidence suggests that their combined impacts may heighten their individual effects, thus considering their independent and joint effects is important to fully capture their likely impacts. Lastly, evaluating the impact of personal lifestyle and neighborhood-level factors at buffering those health risks may inform intervention opportunities. In this proposal, we will investigate whether greater individual and joint exposures to heat stress and wildfire smoke over the life course are associated with cardiovascular health profiles in the MetaAir2 study, a cohort of 400 young adults. repeated carotid artery ultrasounds in childhood and early adulthood, and comprehensive evaluation of measures of cardiovascular risk (blood lipids, HbA1c, blood pressure, body composition) in young adults, we will investigate how exposure to heat stress, wildfire smoke, or their joint mixture from childhood to early adulthood may impact multiple measures of cardiovascular health and preclinical risk factors for disease. We will employ novel statistical methods to evaluate the overall combined role of personal lifestyle factors (e.g. diet, sleep health, physical activity) and neighborhood level factors (e.g. greenness, walkability) at modifying these effects, and then employ a causal inference framework to estimate the isolated, direct causal effects of modifiable factors. This work will inform targeted interventions to reduce cardiovascular health impacts of environmental exposures and protect long-term health over the life course.

NSF Awards · FY 2025 · 2025-06

This Research Experiences for Undergraduates (REU) award will provide funding to support American undergraduate students to have an internship at the University of Southern California. Each student will be paired with a professor and work in their lab for a summer. The participating faculty mentors span the spectrum of cutting-edge research topics in robotics and are well established leaders or rising stars in their field. The students will gain research experience in approaching some of the most challenging modern robotics problems. This will help train more students to get engaged in the robotics field, thus ultimately advancing national prosperity due to the prevalence of robotics in daily life. The proposed REU will train eight undergraduates for 10 weeks each year, with the goal of attracting students to robotics who might otherwise have relatively less exposure or opportunity from their home institution. The REU will specifically train students in research methodology by engaging them in authentic research projects. The research projects cover multiple areas of robotics and autonomous systems, including socially assistive robotics, aerial robotics, safety-critical robotics, robot learning, and robot manipulation. The faculty will design projects to make them in scope for a summer, and to enable the students to achieve greater independence as the program progresses. To evaluate the quality of the REU and its effectiveness, the REU will keep in touch and track each student’s progress before, during, and after the REU. This site is supported by the Department of Defense in partnership with the NSF REU program. 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 · 2025-06

This Research Experience for Undergraduates (REU) site will engage 10 undergraduate students per summer at the University of Southern California's Institute for Creative Technologies, a unique multidisciplinary research community that combines leading academic researchers in computer science, psychology, communications, cinematic arts, and medicine with the creative talents of Hollywood and the video game industry. Participants will be immersed in collaborative research teams focused on the institute's core theme of intelligent interactive experiences, with specific projects in natural language dialogue, affective computing, intelligent human perception, adaptive teaming, and learning sciences. These activities will be combined with weekly interactive seminars for training in best research practices, mentorship support, and peer feedback. The research projects will advance the state of the art for creating intelligent interactive experiences, with specific contributions in the areas of natural language dialogue, affective computing, intelligent human perception, adaptive teaming, and learning sciences. The techniques and technologies developed by the researchers create compelling synthetic environments and characters with immediate relevance to a broad range of application domains including training, education, rehabilitation, medicine, and entertainment. Engagement of undergraduate students in summer experiences that emphasize interdisciplinary research will foster participation in computing and introduce undergraduate students to opportunities in science and engineering graduate programs. This effort has the potential to prepare undergraduates to perform independent research, thereby increasing enrollment and retention in computing doctoral programs. 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 · 2025-06

Scientific research and engineering innovations increasingly depend on complex workflows that require coordination across many types of computing resources, ranging from small edge devices to powerful supercomputers. However, the growing complexity of these workflows and the distributed nature of the underlying computing and data cyberinfrastructure (CI) make it difficult for many researchers and engineers to fully access, manage, and benefit from these advanced technologies. The goal of iWMS is to apply new advancements in Artificial Intelligence (AI) techniques to design and implement a workflow management framework that empowers researchers, engineers, and educators to take advantage of the computing continuum for scientific discovery, innovation, and education. The framework promotes progress in science and engineering, powering applications that advance national priorities. The project designs and implements iWMS, an open, modular workflow management framework that integrates AI across the entire workflow lifecycle. In particular, iWMS incorporates AI models to support automated workflow composition, intelligent resource provisioning, performance prediction, real-time anomaly detection, and workflow adaptation. Techniques such as retrieval-augmented generation facilitate workflow discovery and assembly, while machine learning-based planning and monitoring services optimize execution and enhance system reliability. With the framework foundation built on a modular and integrated design, iWMS incorporates new AI methods as they are being developed in academia and industry. iWMS services feature documented APIs, enabling CI developers to contribute to and enhance iWMS over time. The framework is evaluated with real-world scientific applications and deployed across national testbeds and cyberinfrastructure platforms. In addition to delivering robust software tools and AI models, the project produces training materials, sample workflows, and public datasets to support adoption, foster community engagement, support AI research for enhancing CI, and advance the usability and resilience of the national cyberinfrastructure ecosystem. 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 · 2025-06

This grant provides funding for graduate students, post-doctoral scholars, and early-career researchers to attend the 18th US National Congress on Computational Mechanics (USNCCM18) which will be held in Chicago, Illinois, 20-24 July 2025. USNCCMs are the flagship conferences of the US Association for Computational Mechanics (USACM), and the country’s premier computational mechanics meetings. USNCCM18 will provide a forum for bringing together graduate students, post-doctoral scholars, and early-career researchers from academia, national laboratories and industry to confer on the latest advances and emerging frontiers in Computational Mechanics. USNCCM18 will feature 101 minisymposia encompassing a wide range of topics. These will include: Scientific Machine Learning/Artificial Intelligence/Data-Driven Methods; Biomechanics/Computational Biology/Biosystems; Solid Mechanics and Materials; Soft Materials; Fluid Mechanics; Multi-Phase Mechanics and Fluid Structure Interactions; Nanoscale Phenomena; Advanced Manufacturing; Novel Computational Methods/Algorithms; Emerging Computing Paradigms; Geosystems and Climate Science; Verification, Validation and Uncertainty Quantification; Optimization; Scientific Visualization, Extended and Augmented Reality. Additionally, the conference will introduce Late-Breaking Topics’ minisymposia, whose focus will be decided by the Congress Scientific Committee. USNCCM18 is expected to have around 1200 participants. The Congress will have extensive graduate student participation, including: (i) oral presentations in regular technical sessions, and (ii) the Student Poster Competition. The USACM’s recently established Student Chapter will hold a Meet and Greet event. With over 300 members representing universities from across the country, the USACM Student Chapter’s events have become a vibrant and growing feature of the Congresses. There will be a Mentoring Session for post-doctoral scholars and senior graduate students aspiring to careers in academia and research institutions. The vision for this event is to have Assistant and newly promoted Associate Professors present their perspectives to help post-doctoral scholars and graduate students (i) understand the requirements for making successful entries to independent research and teaching careers, (ii) understand the challenges and intricacies of maintaining an independent research group and managing younger research personnel, (iii) successfully navigate the funding landscape, and (iv) interact meaningfully with the Computational Mechanics and larger scientific community. Recognizing the importance of and shared responsibility for equitable representation, USNCCM18 will feature a Networking Event that will be open to all. This event will have keynote lectures by researchers with lived experience in achieving representation and practicing leadership. Also, as at previous Congresses there will be a Future of Research Funding panel and one-on-one meetings for researchers with agency program managers. 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 · 2025-06

The groundswell of available data and computation power to learn from data has produced advanced automation across many domains, but cybersecurity has lagged these trends. Cybersecurity data sharing comes primarily in the form of indicators of compromise (IoCs) that describe patterns or artifacts that have already been classified as associated with malicious activity. Identifying malicious activity and distilling one or more IoCs from it, however, is often a manual process that is slowed and/or decayed by the siloed viewpoints of different organizations. This project's broader significance and importance are in pioneering a new approach to organizational data sharing that prioritizes support for targeted queries on the operational states of other organizations to overcome these siloed viewpoints. This project's novelties are in identifying opportunities for organizations to diagnose events by posing and responding to such queries and in developing technologies to do so, while simultaneously protecting operational privacy for the organizations. The technical core of this project is a new approach to intrusion detection enabled by cross-organization queries, supported by specialized cryptographic protocols to pose queries and receive responses in a way that minimizes collateral leakage. The project also contributes novel mechanisms to motivate participation in these data exchanges, and to prioritize the partners to which queries should be posed to receive the highest-quality answers. This project couples these technical advances with engagement with the operational cybersecurity community via the Workshop on Security Operations Center (SOC) Operations and Construction (WOSOC) and with foci on integrating this research into educational efforts at the investigators' institutions and in engaging students in research. In doing so, the project strives to align its technical vision with the needs of the operational community and to produce students who can effect this vision within it. 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 2026 · 2025-06

SUMMARY The long-term goal of this study is to increase our understanding of the immune mechanisms involved in the pathogenesis of allergic diseases and asthma. Allergic asthma is a chronic inflammatory disorder that is characterized by airway hyperreactivity (AHR) and driven by Th2 cytokine production. Group 2 innate lymphoid cells (ILC2s) secrete high amounts of Th2 cytokines and contribute to the development of AHR. This project is motivated by our published results (Maazi et al., Immunity), demonstrating that ICOS is extensively used by activated ILC2s to maintain their homeostasis and effector functions. We originally discovered that the lack of ICOS resulted in decreased proinflammatory cytokine secretion contributing to a reduced induction of AHR in models of experimental ILC2-driven asthma and ILC2-humanized mice. However, recently, we discovered that these effects are associated with a phenotypical change characterized by IL-10 secretion. Our preliminary results suggest that this regulatory gain of function associated with ICOS predominantly occurs via a metabolic reprogramming of ILC2s. From current evidence and preliminary data, we hypothesize that modulation of ICOS on ILC2s will reprogram ILC2 metabolism and induce an anti-inflammatory phenotype capable of regulating ILC2-dependent AHR. Importantly, our laboratory and others have reported that ILC2s are the only cells that express both ICOS and corresponding ligand ICOS-L. We therefore leveraged ICOS:ICOS-L bispecific blocking antibody-based strategies to selectively reduce ILC2-derived type-2 cytokine secretion while also promoting that of IL-10, without affecting the function of other ICOS-expressing cells. In Specific Aim 1, we intend to determine the necessity of specific transcription factors in IL-10 production in ILC2s. Moreover, we will investigate the role of ICOS on DNA methylation of the il10 locus through modulation of the Tet3 pathway. Since the lack of ICOS dysregulates metabolic checkpoints signaling and gives rise to augmented glycolysis, in Specific Aim 2 we intend to assess the role of ICOS on ILC2 metabolism. We will examine the capacity of targeted combinatorial metabolic and functional interventions to reprogram ILC2s and induce a regulatory phenotype. We will investigate the effects of ICOS inhibition on mitochondrial health, function and its relation to ILC2 activation. Finally, in Specific Aim 3 we intend to focus on the translational approach of our findings by investigating the role of ICOS on human ILC2s in a cohort of well-defined patients with allergic asthma at USC. We will investigate whether selective blockage of ICOS: ICOS-L axis on human ILC2s can ameliorate AHR in humanized mice without affecting the function of other ICOS-expressing human cells such as Tregs in vivo. To conduct these studies, we have assembled a team of scientists including leading experts in costimulatory molecules and a clinical pulmonology team at USC to complement our laboratory’s extensive experience. Since ILC2s are the only cells reported to express both ICOS and ICOS-L, we believe our results will provide a platform for the design of novel, selective, and mechanism-based therapeutic approaches for the treatment of patients with asthma.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY Autoimmune diseases, affecting over 23 million Americans, occur when the immune system attacks the body's own tissues. Traditional treatments often involve non-selective immunosuppressants, leading to severe side effects. Recent advancements in biologics, such as IL-23 monoclonal antibodies, have improved treatment selectivity by targeting pathogenic cells like IL-17 producing Th17 cells. However, these therapies can increase infection susceptibility due to the dual role of IL-23-dependent Th17 cells in autoimmunity and infection control. Although pro-autoimmune and anti-infection Th17 cells were previously perceived as indistinguishable, the FDA- approved drug clofazimine (CLF) was identified as the first pro-autoimmune Th17-selective inhibitor without affecting anti-infection Th17 cells. However, CLF has adverse effects compromising patient compliance. One strategy is to continue screening small molecule compounds or FDA-approved drugs, while another approach involves designing and synthesizing inhibitors based on the specific targets of CLF in pro-autoimmune Th17 cells. Thus, the objective of this proposal is to establish a high-throughput drug screening pipeline to identify selective inhibitors of pro-autoimmune Th17 cells and to generate reagents for determining the cellular targets of CLF. The rationale is that creating a high-throughput screening system and facilitating CLF target identification will accelerate the discovery of small molecule inhibitors that selectively target pro-autoimmune Th17 cells while sparing anti-infection Th17 cells. This approach will address the urgent need for treatments with better efficacy and safety profiles for autoimmune disease patients. Aim 1 focuses on establishing a high-throughput drug screening pipeline by generating and validating a novel reporter mouse model. Aim 2 involves generating biotinylated CLF to identify its molecular targets in pro-autoimmune Th17 cells, enabling the pull-down of CLF- interacting proteins for identification by mass spectrometry. The significance of this study lies in its potential to discover highly selective inhibitors for pro-autoimmune Th17 cells, thereby reducing the adverse effects associated with current treatments for autoimmune diseases. The innovation of this project includes the development of a novel high-throughput screening pipeline and the creation of biotinylated CLF for precise target identification. These advancements could revolutionize the therapeutic landscape for autoimmune diseases, offering more effective and safer treatment options.

NIH Research Projects · FY 2025 · 2025-06

Project Summary Neuropathic chronic pain affects ~20 million Americans and bears more than US$500 Billion burden on the US economy. Moreover, the widespread use of addictive opioid painkillers for chronic pain is the major root of the opioid abuse epidemic threatening the whole society. As only one in four patients with neuropathic pain experiences pain relief with the current treatment options, the discovery of new approaches to treating neuropathic pain is an unmet medical need with a major impact on society. Targeting pain in peripheral nerves is a key paradigm for effective and safe analgesia, which can naturally bypass the CNS-mediated side effects and addiction. One of the most promising and advanced peripheral targets, angiotensin AT2 receptor is involved in regulations of neuronal membrane excitability and neurite outgrowth of peripheral sensory neurons. Inhibition of AT2R in PNS has shown effect in preclinical models of neuropathic pain, as well as in phase II clinical trials, where the EMA401 drug candidate demonstrated analgesia in patients with post-herpetic neuralgia and diabetic neuropathy. However, EMA401, which had modest potency and suboptimal drug-like properties, was terminated in May 2019 due to off-target hepatotoxicity at high therapeutic doses. The lack of suitable candidates in the pipeline strongly differentiated from EMA401 calls for the development of new highly potent and safe AT2R antagonists for neuropathic pain. We have established a structure-based drug discovery platform and used it to identify and optimize a novel lead series of AT2R antagonists, highly efficient in two murine models on neuropathic pain. Our best lead series compound showed better potency and in vivo efficacy than EMA401, as well as better ADMET and PK profiles, in mouse, rat and dog with minimal liver accumulation. Here, we propose additional optimization of the lead analogs focusing on eliminating a platelet depletion side effect - the last remaining liability of our current candidate. Our preliminary results have identified a first backup compound that maintains high efficacy without significant platelet depletion, showing the feasibility of separating the therapeutic from the side effect. At the UG3 stage, we will employ medicinal chemistry optimization of the lead analogs, coupled with the previously established screening funnel and validated murine platelet counting assays to identify the best new candidate for preclinical development. At the UH3 stage, we will continue preclinical studies, IND submission, and Phase 1 clinical studies toward the characterization of this novel safe and effective neuropathic pain treatment.

NIH Research Projects · FY 2025 · 2025-06

ABSTRACT The best hope for cure for urothelial carcinoma is successful treatment of muscle invasive bladder cancer (MIBC). PD-1/PD-L1 antibodies produce modest response and synergistic combinations remain elusive. Emerging data in bladder cancer (BC) suggests that up to 40% of patients express no or low levels of Nectin4, and ephrinB2 expression seen in 60% of patients is associated with immunotherapy resistance. Sacituzumab govitecan, a once promising ADC in BC failed to meet its primary endpoint in a phase III trial against docetaxel. These data indicate a significant unmet need in BC. Several trials of immunotherapy and chemotherapy combinations thus far have not exceeded the 20+ year old pathologic complete response (pCR) rate of 38% for MVAC, suggesting an efficacy ceiling limit for the current approaches- See Table 3. We propose a phase II randomized trial of a synergistic combination of a novel agent- sEphB4-HSA, an EphrinB2 inhibitor, and pembrolizumab in EphrinB2 expressing and Nectin4 low/non expressing BC patients. This population does not benefit from enfortumab vedotin and is resistant to immunotherapy. In a single arm phase II trial (N=70, Sadeghi et al, JCO 2022), this combination more than doubled the expected overall survival, progression free survival, and objective response rate among EphrinB2 expressing tumors when compared to pembrolizumab alone results from Keynote-045. These data show synergy between EphrinB2 inhibition and PD- 1 blockade. Our preliminary data among 16 EphrinB2 positive MIBC patients show a pCR rate of 62.5%. sEphB4-HSA blocks bidirectional signaling between EphrinB2 and EphB4, both of which are transmembrane ligand-receptor proteins frequently expressed in BC but not normal bladder. EphB4 receptor tyrosine kinase promotes tumor initiation, migration, and cell survival. EphrinB2 expression in tumor vessels promotes angiogenesis and may function as a gatekeeper of immune cell traffic across tumor vasculature. sEphB4- HSA overcomes the barrier to immune cell traffic into the tumor and synergizes with pembrolizumab. Under aim 1, we investigate sEphB4-HSA and pembrolizumab combination in MIBC to determine clinical outcomes, pCR, and recurrence free survival. Aim 1 focuses on prospectively correlating clinical outcomes with EphrinB2, Nectin4, and PD-L1 expression, tumor DNA mutation profile and RNAseq, to determine mechanisms of induction of EphrinB2 and how it confers resistance to treatment. Under aim 2, we will investigate the immune cell number, type including antigen presenting cells and their phenotypes, and activation status in the context of their location in the tumor, perivascular, and stroma compartments of the tumors through spatial digital analysis for proteome using 500 markers and unbiased gene expression at single cell level in situ. We will further investigate whether this regimen enhances adaptive immune response by examining clonal and oligoclonal expansion of T cells by T cell receptor analysis.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT Periodontal disease is a chronic infection that results in the host inflammatory responses destroying the periodontal ligament, cementum, alveolar bone and gingiva that anchor the tooth in the jaw. Previous studies have shown that periodontal ligament cells (PDLCs) can be directed to differentiate to osteoblasts, fibroblasts and cementoblast-like cells in vitro and in vivo. The canonical Wnt/β-catenin signaling pathway has been demonstrated to stimulate cell proliferation and osteogenic differentiation of PDLSc. Wnt signaling is required for periodontal homeostasis. Lastly, a commercial product Emdogain, consisting largely of alternatively spliced and processed porcine amelogenins, was shown to induce bone, cementum and periodontal ligament regeneration in primates and humans. We sought to identify the biologically active peptide(s) in Emdogain responsible for activating these differentiation pathways, anticipating such bioactive molecules would make possible a much more targeted approach to periodontal tissue regeneration. We have identified one of the amelogenin splicing isoforms, Leucine-rich Amelogenin Peptide (LRAP) to induce osteogenesis in various adult and embryonic stem cell types. Moreover, LRAP is expressed in the periodontium, with cementum defects and enhanced osteoclastogenesis being observed around tooth roots of amelogenin knockout mice which lack LRAP expression. LRAP treatment significantly reduces the expression of RANKL, a key regulator of osteoclastogenesis, in periodontal ligament cells. Furthermore, LRAP stimulates the proliferation and migration of periodontal ligament cells, as well as affects bone turnover in vivo. Cell signaling involves not only the binding of growth factors and cognate receptors, but also their clustering on the cell membrane. However, little or no work has been directed thus far toward investigating how biomaterials can serve to enhance growth factor or peptide signaling by increasing diffusion of cell surface receptors within membrane lipid rafts. Therefore, a better understanding of the cellular and molecular mechanism(s) operating at the material-cell membrane interface during cell signaling has the potential to change the paradigm in designing future biomaterials and regenerative medicine therapeutics. Previously, we discovered that peptide amphiphile (PA) nanofibers with controlled supramolecular β-sheet cohesion could alter cell membrane raft mobility, resulting in enhanced osteogenic signaling. Recently, we have developed a PA molecule with a cholesterol tail to potentiate canonical Wnt receptor signaling by modulating lipid raft/caveolar dynamics. In this proposal, we will test the hypothesis that the effect of LRAP on periodontal tissue regeneration is mediated by activating the canonical Wnt/β-catenin signaling pathway and the signaling effect can be potentiated by PA molecules through increased receptor sensitivity. Combining PA molecules with the small peptide LRAP may afford more effective interventional strategies to clinicians for regeneration of tooth supporting tissues lost to periodontal disease.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY Adverse childhood experiences (ACEs), including abuse, household dysfunction, and neglect, are pervasive in resource-limited settings in the United States (US) and globally and exert consequences on mental and behavioral health across the lifespan. Preliminary data from rural Uganda, the site of the proposed research, are consistent with this literature, demonstrating robust associations between ACEs and adult depression symptom severity, major depressive disorder, and suicidality. Yet researchers have raised concerns about the accuracy with which ACEs are retrospectively reported. The theory of mood congruent memory biases suggests that individual factors at the time of assessment (e.g., affective states) may influence reporting. A second limitation of this literature is that the cumulative disadvantage operationalization of ACEs obscures our understanding of the pathways linking ACEs and depression. Without this information, the field lacks the empirical scaffolding needed for the design of targeted intervention programs that can effectively address the mechanisms through which ACEs influence depression. The fellowship candidate of this proposed F31 award seeks to achieve the long-term goal of becoming an independent investigator with expertise in identifying risk and protective factors for mental health and in developing novel peer-delivered and social network interventions that harness positive social and cultural dynamics to increase access to evidence-based mental health care in low resource settings. Three training objectives are proposed: (1) psychometric and longitudinal data analysis, (2) advanced social network analysis, and (3) psychological symptom network analysis. This training will be consolidated through secondary analyses of sociocentric social network data from the co-sponsor’s population-based cohort study in a rural region of southwestern Uganda (N=1,772). Three specific aims, tightly linked to the training objectives, are proposed: (1) determine the test-retest reliability of retrospectively-reported ACEs and estimate correlates of changes in reporting over time; (2) estimate the co-symptomatology network of depression symptoms and ACEs; and (3) assess the extent to which individual social network characteristics are associated with the structure of the co-symptomatology network. The key innovation of this F31 application is that it proposes the first study to integrate a psychological symptom network analysis with rich sociocentric social network data. The fellowship candidate will receive individualized mentorship by a team of sponsors and consultants with complementary expertise—paired with focused coursework, workshops, meetings, and readings—thereby ensuring acquisition of the statistical skills needed to accomplish these aims. The findings are expected to have significant public health impact by informing the design of accessible, resource-efficient interventions that target central ACEs and depression symptoms in similar rural and low-resource settings in the US. Moreover, the fellowship candidate will develop advanced statistical expertise directly applicable to broader mental health research in US populations.

NIH Research Projects · FY 2026 · 2025-05

ABSTRACT Arthrofibrosis is a debilitating fibrotic joint disorder, which causes excessive scar tissue formation within the joint and surrounding soft tissues after injury and/or surgery leading to painful restriction of joint flexion and extension that persists despite rehabilitation. Damage to the joint resulting in chronic inflammation activates proliferation and differentiation of progenitor cells, also known as fibro-adipogenic progenitors, into highly specialized pro- fibrotic cells that deposit excessive amounts of disorganized collagen causing contraction. Estimated rates of arthrofibrosis induced by knee surgery, such as anterior cruciate ligament reconstruction or total knee arthroplasty, affects a significant number of suffering patients with prevalence ranging from 12%-35%. Unfortunately, there is a significant gap in knowledge of the molecular and cellular biology and pathophysiology of arthrofibrosis, which limits mechanism-based therapies. Thus, to date, there is no available non-surgical, non- invasive treatments to prevent or cure arthrofibrosis and management only includes treating the symptoms and not the underlying cause. Pathogenesis of organ fibrosis is mediated by the aberrant activity of pro-inflammatory, pro-fibrotic cytokines, including IL-6 family that signal through gp130 transmembrane protein. Alas, specific cellular and molecular mechanisms that trigger fibrotic processes and responses downstream of gp130 remain elusive. Our previously published data demonstrates that manipulation of gp130 signaling upstream prevents fibrosis development after joint injury rats in vivo. In our recent study, we have identified a signaling residue within gp130 receptor that is responsible for triggering inflammatory and fibrotic responses in the joint and other tissues in vitro and in vivo. The study also suggests that fibrotic outcomes are induced by a gp130-mediated arginine metabolism and hence, the current grant application is designed to investigate the significance of this circuit in arthrofibrosis. To illuminate on this mechanism in depth, we will employ several new genetic mouse lines to ablate central players in arginase metabolism including Arg2, Odc1 genes in fibrogenic cells in a murine model of arthrofibrosis. First, we will investigate whether polyamine production by ARG2/ODC1 enzymes, which catalyze abnormal ECM synthesis upon tissue injury, can promote knee arthrofibrosis after post-traumatic joint injury in vivo. In parallel, we will employ our generated CRISPR/Cas9 mutant mouse with a point mutation in gp130 intracellular domain to test whether local delivery of polyamines to the knee will lead to arthrofibrosis in the injured mice. Furthermore, we will assess the contribution of different progenitor populations to arthrofibrosis in mice, and lastly, will elucidate whether the mechanism of gp130-induced fibrosis is conserved in human fibroprogenitors. The experiments in this proposal are designed to define the role of the arginine metabolism downstream of gp130 and determine whether genetic modulation of this mechanism can prevent or halt fibrosis progression in vivo after injury.

NIH Research Projects · FY 2025 · 2025-05

Abstract Prostate cancer (PCa) incidence is highest in African Americans and lowest in Asians. These long-standing racial/ethnic differences have yet to be explained. Genome-wide association studies of PCa have provided support for common and population-specific genetic effects for PCa and for a genetic basis of the underlying population differences in risk. To further progress in understanding the genetic basis of PCa across populations, we propose to substantially augment the size of genetic association studies in men of European, African, Asian and Latino ancestry to create the largest genetic database of PCa ever assembled in these populations, with substantially greater statistical power for novel discovery of risk alleles for PCa as well as aggressive disease. More specifically, we will expand studies in men of African ancestry from 10,368 cases and 10,986 controls to 34,000 cases and 74,000 controls, in men of Asian ancestry from 8,610 cases and 18,809 controls to 20,000 cases and 40,000 controls, in men of Latino ancestry from 2,714 cases and 5,239 controls to 10,000 cases and 20,000 controls, and in men of European ancestry from 82,000 cases and 61,000 controls to 117,000 cases and 517,000 controls, with all studies imputed to a multiethnic whole-genome sequence reference panel (e.g. TOPMed). In Aim 1, we will search for novel common risk alleles for overall and aggressive PCa in ethnic-specific and multiethnic analyses. Within known and newly discovered risk regions, we will conduct multiethnic fine- mapping using novel Bayesian statistical approaches that incorporate functional annotations and biology with statistical evidence to identify independent markers of risk as well as the most promising functional candidates. In Aim 2, we will create the first multiethnic genome-wide SNP-eQTL prostate reference panel for men of European, African, Asian and Latino ancestry using whole-transcriptome RNA sequencing of ~1,000 histologically normal, fresh-frozen prostate tissue specimens. We will characterize eQTLs in the sample and impute gene expression in men of European, African, Asian, and Latino ancestry to perform a multiethnic transcriptome-wide association scan (TWAS). In Aim 3, we will construct and evaluate a polygenic risk score (PRS) across populations, using known and novel risk variants from Aim 1 and TWAS loci from Aim 2. PRS validation testing will be conducted in three independent multiethnic cohorts (>38,000 PCa cases from ATLAS, All of Us and CCPM). We expect findings from this study will make a major contribution to our understanding of genetic susceptibility to PCa and lead to better risk models that more accurately predict a man's risk of developing PCa and are efficacious across racial/ethnic populations.

NSF Awards · FY 2025 · 2025-05

This project develops scalable and accurate solutions for Temporal Graph Machine Learning (TGML), for analyzing dynamic and evolving relationships in large-scale data. TGML has broad applications, including cybersecurity, traffic forecasting, climate modeling, and knowledge discovery. As real-world data continues to grow, there is a pressing need for advanced computational techniques to efficiently process dynamic graphs in real time. The project leverages distributed heterogeneous computing systems that integrate multi-core processors, Graphics Processing Units (GPUs), Field Programmable Gate Arrays (FPGAs), and high-bandwidth memory technologies. The research will result in a robust cyber infrastructure toolkit that enables efficient training and inference of TGML models, allowing researchers and practitioners to analyze large-scale temporal graphs with improved accuracy and scalability. The project supports the national interest by promoting technological advancements in artificial intelligence and high-performance computing, fostering innovation in multiple scientific and industrial domains. Current TGML frameworks struggle with scalability and performance on heterogeneous computing platforms, creating a need for solutions that can efficiently leverage diverse hardware architectures while maintaining accuracy and robustness. To address this, the project develops novel algorithmic techniques, including adaptive mini-batch and neighbor sampling, hyper node memory for efficient storage, and sparse temporal attention mechanisms for scalable computation. These innovations enable performance portability across multi-core processors, GPUs, and FPGAs, ensuring that TGML applications can efficiently scale to large dynamic graphs. The project builds upon prior research in graph analytics and high-performance computing, integrating hardware-aware optimizations tailored for dynamic graph processing. Additionally, to maximize impact, the project fosters collaborations with key industry stakeholders, including AMD, Intel, and NVIDIA, to integrate optimizations into their AI software ecosystems. It also partners with NSF-supported cyberinfrastructures for large-scale validation, ensuring compatibility with widely used ML frameworks, and engaging with cloud service providers for scalable deployment. The project demonstrates end-to-end applications in domains such as smart grids and social networks, working closely with domain experts to ensure practical relevance and impact. 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 2026 · 2025-04

The overall goal of Southern California Superfund Research and Training Program for PFAS Assessment, Remediation, and Prevention (ShARP) is to develop problem-based, solution-oriented scientific knowledge and innovative technologies to address the issue of poly- and perfluoroalkyl substances (PFAS) water contamination in Superfund and other sites. PFAS are a class of persistent and ubiquitous chemicals contaminating more than 3,000 sites across the U.S., including at least 245 EPA-identified Superfund sites. PFAS exposure can affect liver health and partly explain the excess burden of metabolic dysfunction-associated steatotic liver disease (MASLD) in the U.S. We will strengthen the Superfund Research Program (SRP) and complement current SRP Centers by establishing the first Center that specifically addresses PFAS in relation to their effects on liver disease. The Center will lead four highly interactive Research Projects that integrate biomedical and environmental engineering research related to the SRP mandates with the following objectives: (1) Develop advanced techniques to evaluate the effect of PFAS on liver disease (MANDATE 1) and the molecular mechanisms of PFAS hepatotoxicity (MANDATE 2) in human 3D liver spheroid models (PROJECT 1) and in human longitudinal studies (PROJECT 2); (2) Develop novel PFAS characterization techniques on samples from environmental reservoirs (water, soil, and air) and a predictive PFAS groundwater model for mobilization of PFAS plumes from a PFAS-contaminated Superfund site because of groundwater recharge (MANDATE 3/PROJECT 3); and (3) Develop advanced processes for microbial, chemical, and thermal defluorination to allow definitive PFAS treatment, with application to Superfund sites (MANDATE 4/PROJECT 4). The Research Programs are led by collaborative multidisciplinary teams and supported by four Cores: The Community Engagement Core (CEC) will foster communication and support the translation of Center research findings to inform prevention strategies. The Data Management and Analysis Core (DMAC) will optimize the use of the complex data generated by the research projects and serves as an incubator to accelerate cross-project integration and discoveries. The Research Experience and Training Coordination Core (RETCC) will support the training of the next generation of scientists in environmental health and engineering, translational research and key stakeholders’ engagement. The Administrative Core supports the translation of the Center’s research findings to key SRP end-users. In summary, our system-based integrated approaches, the central role of the stakeholders, the strong institutional support, and our team’s successful experience working together, will enable us to address urgent concerns regarding water quality and human health in populations affected by PFAS exposures and Superfund sites.

NSF Awards · FY 2025 · 2025-04

Summary Smartphones have transformed daily life since their introduction, with ever-improving applications such as high-quality video streaming driving an increasing demand for higher per-user data rates and network throughput. One of the ways to satisfy this demand is by expanding the available spectrum for cellular operators. However, using new spectrum introduces the risk of interference with legacy services and systems, i.e., systems that are already operating in the targeted frequency bands. Assessing and mitigating such interference is essential in determining whether – and if so, which - new parts of the spectrum can be made available for enhancing cellular systems and thus improve service to smartphone users. Currently, there is special interest of the cellular industry in the so-called upper midband, a range of frequency bands (i.e., spectrum) that lie between the traditional cellular bands and the millimeter-wave bands already used for 5G cellular. However, this portion of the spectrum is also used by legacy services, including satellite communications. Transmissions of cellular systems operating in the same spectrum in which ground stations communicate to the satellites can lead to significant interference and thus deterioration of quality for those – very critical – satellite links. It is important to note that interference to satellite systems is not only caused by direct radiation from terrestrial transmitters, but also by “upscattering” of terrestrial radiation by buildings, trees, cars, etc., that contributes to the total amount of arriving interference. The primary objectives of this project are to first quantify this upscattering through extensive measurements, and then to use this data to develop new methods for reducing its impacts. Potential mitigation strategies to minimize interference include adjusting the transmission power of cellular transmitters, and by optimizing the transmission direction. The ultimate goal is to find approaches that allow us to use more spectrum – and thus satisfy the demand of American consumers – without significantly disrupting existing critical satellite communications. A key scientific component for reaching this goal is an innovative measurement approach that captures the upscattering effects without needing to send a satellite into space, or gain access to the receiver functionalities of existing satellites. The different capabilities and transmission characteristics of base stations and user equipment of the cellular system are taken into account by two related but distinct measurement setups. Using these setups, the project performs extensive measurements in both urban and suburban environments (which, due to high user density, create the most interference), and create an extensive database as well as a measurement-based interference simulator. The project furthermore explores interference mitigation techniques that employ machine learning to find combinations of beamforming and transmission settings that provide a balance between maintaining reasonable cellular capacity and keeping interference to satellites within specified limits. These techniques account for the fact that the observables, namely the interference level at the satellites, are much less than the number of underlying parameters influencing them, such as user equipment location, power settings, and beamforming approach. The results of this project are of great interest to the Federal Communication Commission (FCC), as well as the American cellular and satellite industries, providing valuable insights for spectrum management and interference mitigation. 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 · 2025-04

Abstract An estimated 43 percent of children under age 5 in low- and middle-income countries (LMICs) will not reach their full developmental potential due to poverty, stunting, or inadequate psychosocial stimulation. Parenting interventions that promote responsive caregiving can effectively improve early childhood development (ECD) outcomes in LMICs, at least in the short-term. Yet to date, 93 percent of parenting interventions globally have exclusively focused on mothers, and longer-term follow-ups show early impacts fade out over time. Parenting interventions that that solely target mothers overlook the potential gains from engaging fathers, who can influence children’s outcomes directly, via increases in responsive caregiving and reductions in harsh discipline, and indirectly, via improvements in maternal and family wellbeing stemming from increased emotional support and participation in household tasks, and reduced intimate partner violence (IPV). Engaging couples to achieve whole-family behavioral changes could lead to larger program impacts than engaging only mothers, given that fathers are often the household head with significant decision making power and influence on family dynamics in LMICs. Since familial support can play a key role in supporting long-term behavior change, interventions that engage both parents may also stand the best chance to sustain impacts over time. Our proposal asks: Does engaging both parents as couples lead to larger and more sustained improvements in parenting behaviors and ECD outcomes relative to engaging only mothers? We will develop and experimentally test Msingi Bora Familia (MBF), a responsive parenting and family wellbeing intervention that integrates father- inclusive, gender-equitable and family-focused curricula into Msingi Bora (MB), a NICHD-funded responsive parenting intervention by our team. MB significantly improved short-term maternal parenting behaviors and ECD, but impacts after two years were smaller. We will test MBF in a 3-arm cluster randomized controlled trial in which 120 villages and 1,200 households with young children from rural Kenya will be randomly assigned to: (1) a control group; (2) mothers-only; or (3) “couples” (though we allow for myriad family configurations). We will test the relative effectiveness and cost-effectiveness of treating only mothers versus engaging both parents. We will collect baseline and follow-up surveys on measures of child cognitive and socioemotional outcomes, paternal and maternal caregiving behaviors and mental health, experience of IPV, attitudes towards gender roles, social norms, and quality of the couple’s relationship. A second follow-up survey two years later will test for sustained impacts on parental and family measures, as well as ECD outcomes. We will collect cost data during implementation to estimate the relative cost-effectiveness of each intervention model, and explore the mediating pathways of change to inform the generalizability and sustainability of the different intervention models. The goal of our study is to produce rigorous evidence on the distinct role of fathers on children’s development, and to test if their inclusion improves the effectiveness and sustainability of parenting interventions in LMICs.

NSF Awards · FY 2025 · 2025-04

Being able to predict behaviors of other people is important to successfully navigate the social world. Prior research shows that one major way to achieve this is by learning about other people’s personality traits. This project explores how individuals learn not only about others’ personality traits but also about the situations that inform people’s actions, and in turn use situational learning in decision making. Impacts of this project include research training opportunities for graduate and undergraduate students, and dissemination of findings to the public. This project aims to characterize how individuals learn about situations and explore how different life experiences influence this process. The research team leverages behavioral methods, advanced neuroimaging techniques and computational modeling to (1) identify the neural and cognitive mechanisms involved in situational and trait learning and to (2) examine the role that situational and trait learning play in reasoning and decision-making across different contexts. 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 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT Osteoarthritis (OA) is a leading cause of disability worldwide with no disease-modifying therapies available. One of the hallmarks of OA is cartilage degeneration with abnormal chondrocyte differentiation. It is known that chondrocytes can respond to various signaling via the G protein-coupled receptors (GPCRs), which represent the largest class of targets for drug development. However, due to the lack of relevant animal models, we have a limited understanding of how GPCR-mediated signaling pathways regulate chondrocyte homeostasis and OA pathogenesis. In this project, we will investigate the molecular regulatory mechanisms of a cartilage-enriched GPCR named ADGRG6 in maintaining cartilage and joint homeostasis. Our preliminary studies show that ADGRG6 is highly expressed in healthy cartilage, but its expression is gradually reduced under OA conditions in both human patients and trauma-induced OA mouse models. Loss of Adgrg6 in cartilage lineages leads to OA-like joint structural changes associated with impaired Gs signaling and reduced SOX9 expression. In contrast, overexpression of Adgrg6 in cell cultures leads to a chondroprotective effect in vitro. Based on these findings, we hypothesize that ADGRG6 is required for postnatal joint cartilage maintenance. We will test our hypothesis with three specific aims: in Aim 1, we will investigate the chondrocyte-specific role of ADGRG6 with genetic deletion; in Aim 2, we will elucidate the functional link between ADGRG6/Gs signaling and SOX9 with cell cultures and genetic mouse models; in Aim 3 we will determine if ADGRG6 agonism can protect mice from OA development. Completion of this project will reveal the molecular mechanism of a cartilage-enriched GPCR in regulating joint homeostasis. These insights will support future strategies for targeting GPCRs for OA therapeutics.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT Dental enamel is the most highly mineralized tissue in mammals and has no self-repair mechanism if damaged. The major components to enamel are calcium (Ca2+), inorganic phosphate (PO43-; Pi) and hydroxide (OH-). While several mammalian Pi cellular import channels are known, little is understood of Pi transcellular and intracellular movements, and even less is known as to Pi cellular export as it relates to bone and teeth mineralization. In enamel development two distinct formative stages are recognized; an extracellular protein matrix-rich “secretory-stage”, immediately followed by the rapidly mineralizing “maturation-stage”. Preliminary data indicate PiT1 is expressed in secretory-stage amelogenesis. Published data show that the Pi importer NaPi2b, and the Pi exporter Xpr1 are both expressed during maturation-stage, suggesting that these proteins contribute significantly to enamel mineralization. This leads to the hypothesis of this grant application that “active transcellular and intracellular Pi movements dictate enamel mineralization processes”. If this can be shown, a major paradigm shift in our basic understanding of enamel formation would transpire, including the genetic controls involved in enamel biomineralization. To study the process of Pi movements in amelogenesis we have access to five unique mouse models: K14-Cre, Odam-IRESCre, floxed Slc20a1/PiT1 (f PiT1), floxed Slc34a2/NaPi2b (f NaPi2b) and floxed Xpr1 (f Xpr1) mice. In five Specific Aims we will: SA1) perform in situ hybridization (ISH), RT-PCR, and immuno-fluorescence (IF) to study Cre-recombinase expression in Odam- IRESCre heterozygous and homozygous mice; SA2) examine the contributions of PiT1 on secretory-stage enamel mineralization; 3) examine the contributions of NaPi2b (Slc34a2) and Xpr1 (Slc53a1/Xpr1) in maturation-stage amelogenesis by breeding Odam-IRESCre mice with respective floxed mutant mice strains; SA4) use transmitted polarized light microscopy, reflected metallography, SEM, EDS, fracture toughness and microhardness testing, performed on PN8 week fully mature mandibular incisor enamel, to study the architecture/organization and mechanical properties of mutant teeth and in these same samples define the atomic composition of the mineral composition; and SA5) ameloblast-like cell (ALC) culture will be examined to study the dynamics of mineralization using siRNAs silencing of Slc20a1, Slc34a2 and Slc53a1/Xpr1 coupled with Alizarin Red and von Kossa staining, and alkaline phosphatase activity, and also coupled with a thorough total in silico RNA-seq analysis. In this study the clear focus is on the roles of PiT1, NaPi2b and Xpr1 in enamel formation. With a recently developed enamel-specific Odam Cre-recombinase mouse line (Odam-IRESCre) we are now in a unique position to study Pi-related activities in amelogenesis. The roles of Pi transporters in teeth have had little prior attention, but for all dental researchers and practicing dentists, controls of Pi movements in enamel Hap formation must be understood to better define amelogenesis.

NIH Research Projects · FY 2026 · 2025-04

Project Summary A central yet unrealized goal of modern neuroscience is to map all the neural circuits within the brain and the changes that occur during development, learning, aging, and in disease states. Towards this end, we recently developed a rationally designed method for anterograde transsynaptic tracing from excitatory presynaptic neurons that is monosynaptic, activity-dependent, and non-toxic and provides genetic access to postsynaptic cells. This rational approach has many advantages over traditional methods based on viruses' intrinsic transsynaptic labeling capabilities. We have shown that in our method, the tracer is released presynaptically and binds to a postsynaptic protein before being taken up by the postsynaptic cell. The tracer can be fused to Cre or other recombinases, allowing genetic labeling and access to the postsynaptic cell. Here, using a similar approach, we will develop a new method for anterograde tracing from inhibitory neurons. This will represent the first method capable of tracing from genetically determined inhibitory starter cells in an anterograde direction, monosynaptically, and without retrograde transmission or toxicity. This method will be particularly valuable because other methods of anterograde tracing that depend on bulk labeling or electrophysiological activation of postsynaptic cells cannot be used for tracing circuits that originate from inhibitory neurons. In addition, we will develop an analogous tracer for cholinergic circuits, which cannot currently be efficiently traced by viruses either in the anterograde or retrograde directions. Finally, we will develop a method for labeling and providing genetic access to cells that have been either excited or inhibited by specific presynaptic neurons over a prescribed time period. This application takes advantage of the unique activity dependence of the transsynaptic labeling techniques that we have developed.