University Of Pennsylvania

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract Fluorine is an essential constituent of many commercial molecules, including (radio)pharmaceuticals, agrochemicals, and functional materials. Fluorine-19 ( stable isotope) is routinely introduced into pharmaceuticals to modulate pharmacological properties. Many positron emission tomography (PET) imaging agents are labeled with fluorine-18 (radioactive isotope) for studying and monitoring disease, evaluating drug-target engagements, and enriching clinical trials of therapeutics. Critically, PET is continually used to improve disease detection, treatment, and prevention, which is fundamentally consistent with the mission of NIBIB. Despite progress in developing fluorine-18 imaging agents for these applications, more robust, efficient, and reproducible radiosyntheses are required to support and expedite tracer discovery and meet the urgent demand for radiopharmaceuticals from the healthcare and pharmaceutical industries. Therefore, the primary focus of this proposal is to overcome challenges associated with radiofluorination by inventing radiolabeling methods that support the design of PET imaging agents. Specifically, the central claim is that fluorine-18 labeled organic molecules can be rapidly accessed by designing zinc-mediated and metal-free amide C-H radiofluorination radiolabeling reactions. Zinc is an abundant, inexpensive, and non-toxic element that facilitates a-amido C-H radiofluorination reactions, albeit inefficiently, with a limited scope. Over the K99 phase, the candidate collected rigorous preliminary data demonstrating that amide C-H radiofluorination reactions are possible, and this award will study, refine, optimize, and showcase this protocol for PET biomedical imaging applications. Specifically, the ROO proposal is divided into three aims: Aim 1 is to develop a fully optimized amide C-H radiofluorination protocol that delivers stereochemically enriched fluorine-18 labeled amides containing a broad range of valuable fluoroalkyl functional groups. Aim 2 is to demonstrate the feasibility of new amide C-H radiofluorination reactions with bioactive PET imaging scaffolds on a commercial radiosynthesis module for clinical production Aim 3 is to prepare and assess the stability of multiple representative therapeutics containing fluorine-18 labeled amides. Ultimately, the enhancement of PET imaging technology, as described in this proposal, is expected to fundamentally alter the current (radio)synthetic fluorination paradigm and expedite radiofluorination, providing unrealized and rapid access to fluorine-18 labeled pharmaceuticals that support the improvement of patient outcomes and a reduction in healthcare costs for the American people in the long term. Broadly, this project will provide new opportunities to merge radiochemistry and organic/organometallic chemistry, supporting the development of a world-leading radiosynthetic methods program at the University of Pennsylvania.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Insulin controls hyperglycemia after feeding by stimulating glucose uptake and suppressing endogenous glucose production. The liver contributes 90% of endogenous glucose production during fasting, generated through glycogen breakdown and gluconeogenesis, thus insulin’s control of hepatic glucose metabolism is crucial for restoring whole body glucose homeostasis. Insulin acutely suppresses hepatic glucose production and promotes glucose uptake and storage within fifteen minutes of a glucose bolus. This is accomplished through direct and indirect effects on the liver. The direct mechanism by which insulin acutely controls hepatic glucose utilization is unclear, and previous studies suggest it becomes dysregulated with insulin resistance. Our lab and others demonstrated that insulin directly controls liver glucose balance through AKT, a serine/threonine kinase and an obligate insulin signaling intermediate in hepatocytes. The goal of this study is to determine 1) the metabolic pathways AKT controls to acutely regulate glucose utilization and 2) the mechanisms involved and how they becomes aberrant in metabolic disease. Preliminary stable isotope tracing experiments suggest that AKT rapidly increases glucose contribution to glycolytic intermediates and lipogenic precursors within 5 minutes, independent of changes to glycogen metabolism. I have also found that insulin stimulates phosphorylation of an allosteric regulator of glycolysis, PFK2/FBPase2, in hepatocytes at Ser469 and Ser486 in an AKT-dependent manner. Phosphorylation at these residues correlates with increased PFK2 kinase activity. Thus, I hypothesize that insulin acutely shifts glucose balance in the liver from gluconeogenesis to glycolysis postprandially through AKT-mediated PFK2 phosphorylation. I will test whether AKT suppression of gluconeogenesis allows for the increased contribution of glucose to glycolytic intermediates and lipid precursors, and the role of PFK2 phosphorylation downstream of insulin signaling in mediating AKT’s acute effects on glucose flux. Finally, I will interrogate how the AKT-PFK2 pathway contributes to in vivo hepatic glucose utilization in both healthy and insulin resistant states using diet interventions, hyperinsulinemic clamps and adeno-associated virus delivery of phosphomutant PFK2. Overall, this study will determine the acute mechanisms by which insulin directly controls hepatic glucose balance, which may reveal novel therapeutic targets for treating insulin resistance and maintaining glucose homeostasis.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Cells are exquisitely sensitive to the mechanical properties of their environment, altering fundamental processes like adhesion, migration, cell division, and cell fate specification in response to how the polymers comprising the extracellular matrix (ECM) and surrounding cells react to applied forces. Thus, environmental mechanical cues serve as crucial drivers of development, homeostasis, tissue regeneration, and disease progression. To understand the molecular mechanisms underpinning cellular mechanosensing, engineered systems are required that can decouple the influence of multiple confounding parameters, such as matrix stiffness (elasticity), viscous force dissipation, plastic deformation, microstructure, and adhesive cues. While there is an extensive body of literature exploring how cells sense and respond to stiffness and, increasingly, viscous force dissipation, present materials systems used in these studies are only capable of independently controlling one or two mechanical parameters at a time and make use of chemistries that can react with biologically relevant molecules, leading to altered material properties over time and potential off-target effects on cells. My lab leverages interdisciplinary expertise in bioorthogonal chemistries, protein engineered biomaterials, and stem cell biology to develop new platforms to study fundamental mechanisms of cellular mechanosensing under physiologically relevant conditions. This includes developing new chemistries and hydrogel materials to enable simultaneous, independent, and dynamic tuning of matrix stiffness, viscous force dissipation, and presentation of cell adhesive cues within 3D organotypic ensembles of cells. Recent efforts have focused on the development of highly- selective, stimuli-responsive chemistries to alter the stiffness and force dissipation rate of hydrogel materials on demand to model changes that occur in various diseases and during aging. We have also developed new protein engineered materials with genetically encoded viscoelasticity and are applying these materials to develop chemically-defined and highly tunable 3D organotypic culture platforms. In this proposal, we extend our work by developing new bioorthogonal chemistries that will enable tuning of viscoelastic force dissipation without off- target chemical reactivity, permitting casual relationships to be identified in complex systems over long culture durations without deterioration of material properties. We will also introduce new mechanically-labile crosslinking chemistries to provide additional modes of plastic deformation induced by cells. Finally, we will address a limitation of cellular force generation measurement techniques in native-like viscoelastic materials by developing new force sensors through protein engineering and chemoenzymatic modifications. The platforms developed in this proposal will be broadly useful to elucidate the molecular mechanisms by which cells sense and respond to changes in their mechanical microenvironment and to study how these changes drive desired phenotypes during development and tissue regeneration and undesired phenotypes during aging and disease progression.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Lung diseases are one of the leading causes of morbidity and mortality worldwide. Chronic Obstructive Pulmonary Disease (COPD) and other Chronic Lung Diseases (CLDs) are among the most prevalent of these lung diseases worldwide and their prevalence is increasing emphasizing the dire need to develop novel therapies to alleviate the heavy burden of these diseases on the medical care system and to provide better quality of life for this increasing patient population. The Molecular Atlas of Lung Development Program (LungMap3) proposes research teams to expand our growing knowledge of the human lung with specific interest in better defining the spatial, molecular, and cellular changes that occur in human respiratory diseases. For Phase 3 funding, we propose to focus on three emerging concepts and challenges: 1) catalogue the phenotypes of adult human lung diseases at the spatial and single cell level with a focus on COPD, CLDs and more rare diseases that we have access to via our Human Lung Tissue Bank including alpha-1 anti-trypsin deficiency (A1AT), 2) identify molecular defects present in the progenitor cell populations of human CLDs through dynamic integration of single cell analytics with spatial resolution technologies to elucidate disease progression signatures, and 3) develop and implement new ex vivo and in vivo platforms to mechanistically define the molecular and cellular defects that occur during the progression of CLDs. This will require the use of advanced transcriptomic, epigenomic, and bioinformatic approaches to phenotyping cell-cell communication and cell-niche interactions. The Penn LungMAP Research Center Team has an existing pipeline to acquire normal and diseased lung tissue, and we have developed extensive bioinformatic software to interrogate changes in cell fates and states in disease from deep spatial and single cell analysis. The Penn LungMAP Research Center has been extremely productive during LungMAP Phase 2 support, defining novel cell lineages present in the human lung, characterizing aspects of emphysematous disease pathology including COPD, and we have begun to define rare CLDs such as A1AT at a single cell level in addition to providing high quality single cell data from pediatric and adult healthy lung samples for the LungMap DCC web based platform and the lung research community at large. The strategy of the Penn LungMAP 3 Research Center is to phenotype the cellular and molecular changes that occur in CLDs at the single cell level and identify the mechanisms that drive disease progression using novel approaches to integrate progenitor cell niche regulation using carefully validated ex vivo model systems.

NIH Research Projects · FY 2024 · 2024-09

Abstract Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease of unknown cause marked by dysfunctional wound healing and aberrant fibrotic remodeling of the lung that claims the lives of more than 40,000 Americans each year. The median age of IPF is 66 years and patients have an average life expectancy of 3 years. The scientific discovery into this disease has been slow and has resulted in only two FDA approved medications that do not reverse or cure the disease. Our emerging conceptual understanding of IPF highlights the significant role of alveolar epithelial type II cell (AT2) cell dysfunction in underlying susceptibility, disease severity, and disease progression. We have previously demonstrated in preclinical SftpcI73T murine and patient- specific induced pluripotent stem cell (iPSC) models a time dependent metabolic reprogramming promoting a loss of mitochondrial function in the AT2. Our preliminary data has also revealed the emergence of a recently characterized aberrant AT2 cell stated marked by the inability to complete differentiation into the alveolar epithelial type I cell (AT1). Finally, and relevant to the observation in humans, we have observed increased mortality and increased transitional cell accumulation in aged SftpcI73T mice. Together these observations suggest a potential link between metabolic reprogramming, the aging process, and AT2 progenitor cell biology. The biology of this aberrant progenitor cell within the alveolar niche has become a high impact question that requires further elucidation. To address this unmet need, we will utilize an aged murine SftpcI73T model of IPF that closely recapitulates many aspects of the human disease and permits temporal modeling of subclinical events in its pathogenesis. Furthermore, we will apply novel genetic approaches including a lineage trace model of the AT2, multiple viral constructs to manipulate key metabolic enzymes in the AT2, and an AT2 specific murine model allowing us to knock out genes of interest. Founded in this compelling preliminary data, the overall goal of this project is to identify the mechanism by which aging increases susceptibility to disease progression and alters alveolar homeostasis. We hypothesize that that aging exacerbates defects in cell quality control and metabolism to disrupt AT2 progenitor function and enhance aberrant transitional cell accumulation. We will test this hypothesis in two specific aims: 1) In-vivo application of the SftpcI73T fibrosis model to characterize the impact of aging on mitochondrial quality control and metabolic disruption in transitional AT2s throughout fibrogenesis. 2) In reductionist SftpcI73T models, determine the effect of aging and/or senescence on AT2 progenitor capacity, AT2-AT1 transition, and the AT2 profibrotic phenotype. 3) Define the role of AT2 derived lactate on AT2 transition cell dysfunction and fibrotic remodeling in aged models of fibrosis The findings from this study will expand our understanding of AT2 progenitor function and link age associated changes with metabolic dysfunction in IPF pathogenesis. Beyond the scope of IPF, epithelial dysfunction is a key aspect of chronic and acute lung disease, particularly in light of the COVID-19 pandemic.

NIH Research Projects · FY 2026 · 2024-09

Project Summary Colorectal cancer (CRC) patients with a high body-mas index (BMI) have poor efficacy to chemotherapy, creating an urgent need to design targeted therapy for this group of cancer patients. During obesity, the excess visceral adipose tissue (AT) deposited around major organs in the abdomen triggers systemic metabolic dysregulation and creates an environment conducive to cancer development, particularly colorectal cancer (CRC). Obese AT secretes more extracellular vesicles (EVs) compared to non-obese AT, which can be taken up by distant tissues. EVs are lipid-membraned vesicles that carry cargo from the parent cell and are important for inter-organ communication. Unbiased proteomic analysis revealed that obese EVs (OB-EVs) and non-obese (N-OB) EVs are distinctly different in terms of their cargo, with an enrichment of the glycolytic enzyme triose phosphate isomerase 1 (TPI1) in OB-EVs. Consequently, OB-EV treatment of CRC cells resulted in higher TPI1 levels compared to N-OB EV treatment. Functionally, OB-EVs increased basal glycolysis of human and mouse CRC cells and enhanced the ability of CRC cells to form 3D tumoroids and spheroids. CRC cells can aberrantly increase glycolysis to support tumor growth and aggressive, however, it is not known whether these pro- tumorigenic effects can get enhanced during obesity. In the F99 portion of this grant, I will determine if the cargo from AT-derived EVs is utilized by CRC cells to change their metabolism and promote a pro-tumorigenic phenotype, and whether it is enhanced during obesity. I will use a novel mouse model of intestinal tumorigenesis lacking EV secretion from adipocytes that will be challenged with obesity to elucidate the role of OB-EV cargo in CRC development. The goals of this project are to 1) confirm whether OB-EVs transfer TPI1 to CRC cells and its regulation on glycolysis and 2) determine the oncogenic role of OB-EV and TPI1 in CRC development in vivo. The results from this study will help advance the field of EV biology in cancer during obesity and identify potential targets for cancer therapeutics in obese CRC patients. In the K00 portion of this grant, I will expand on elucidating the impact of AT-derived EVs on the immune population of CRC TME. Obese CRC TME is known to be immunosuppressive with increased infiltration of M2- like macrophages. However, there is a lack of studies enumerating the underlying molecular players mediating the observed phenotype. Therefore, I propose to determine whether OB-EVs reprogram macrophages in the obese TME to an immunosuppressive M2-like phenotype to promote tumor progression. I will seek K00 labs with comprehensive expertise on tumor immunology and associated signaling pathway to provide me with the training I require to complete my project and characterize the impact of obesity in CRC TME.

NIH Research Projects · FY 2025 · 2024-09

Anterior cruciate ligament (ACL) injuries are one of the leading causes of training and sports related injuries and contribute to post-traumatic osteoarthritis. Torn ACLs are commonly reconstructed, instead of repaired, utilizing a tendon graft that is passed through bone tunnels created in the femur and tibia positioned at the native ACL footprints. Even with advancements in surgical technique and rehabilitation strategies, graft failure and recurrent knee instability are unfortunate complications. Additionally, rehabilitation following surgery is critical to a successful outcome, with premature return to activity resulting in an increased risk of graft failure and reinjury. Consequently, there is an unmet clinical need to improve and expedite treatment of these debilitating injuries, to get patients back to their active lifestyles while minimizing the risk of graft failure. Recreating the zonal tendon- to-bone insertion site (i.e., enthesis) is critical to restoring normal function following these injuries. Zonal enthesis formation involves anchoring collagen fibers, synthesizing proteoglycan-rich fibrocartilage, and mineralizing this fibrocartilage. The hedgehog (Hh) signaling pathway is critical to the formation of this zonal insertion during growth and development by promoting the formation of unmineralized and mineralized fibrocartilage zones of the enthesis. Recent studies by our group demonstrate that this pathway has a similar role in producing fibrocartilage within zonal attachments in the bone tunnels following ACL reconstruction. Therefore, our long- term goal is to develop therapies that leverage this pathway to improve repair outcomes and expedite recovery. The objective of this proposal is to locally deliver a small molecule Hh signaling agonist to increase the formation of zonal tendon-to-bone attachments. We will conduct an extensive in vitro release study to test the duration and bioactivity of SAG released from our innovative BiLDS scaffolds in Aim 1. We will then translate this novel delivery system to treat NZW rabbits following ACL reconstruction in Aim 2 via localized delivery of the agonist in the bone tunnels. Our hypothesis is that delivery of the agonist will stimulate the local progenitor cells to proliferate and then differentiate into fibrochondrocytes in the attachments. To test this hypothesis, in Aim 2, we will assess the extent of tunnel integration by measuring proliferation of the progenitor pool, zonal attachment formation via mineralized cryo-histomorphometry, and integration strength via anterior-posterior drawer and uniaxial mechanical testing. Additionally, we will determine the long-term effects of agonist release on joint health by measuring changes to the synovium and articular cartilage. Finally, we will use activity monitoring post-surgery and longitudinal in vivo MRI imaging to track the animal rehabilitation and healing response. Successfully harnessing the Hh pathway therapeutically could result in a paradigm shift in treatment of these debilitating injuries and could also more broadly inform future tendon-to-bone healing therapies.

NSF Awards · FY 2024 · 2024-09

Nontechnical description Quantum confined structures such as quantum wells and quantum dots (QDs) are a key element in a majority of modern electronic and opto-electronic devices ranging from lasers to high-speed photodetectors, and more recently in quantum information sciences where quantum dots form the basis for spin-qubits or quantum light sources. While III-V and II-VI semiconductors have been researched extensively over the years and offer promise to applications, their widespread utility is limited by challenges associated with light extraction from the material and ability to integrate with a silicon platform. The emergence of two-dimensional (2D) materials has revolutionized the conception and design of electronic heterostructures from that of buried interfaces within lattice matched III-V multi-layer structures to atomically thin van der Waals stacks with arbitrary control over stacking. The project takes this concept further to develop 2D analogues of QD structures via the fabrication of compositionally modulated dots with deep-subwavelength (< 20 nm) dimensions embedded within atomically thin monolayer transition metal dichalcogenide sheets that can be easily integrated into device structures. The research investigates controlled synthesis of the 2D QD structures with varying composition; atomic-scale analysis of structure, chemistry, and defects; and exploration of their electronic and nanophotonic properties. The project forms the thesis research of two Ph.D. students who are co-advised by the principal investigators (PIs). Undergraduate students from the PIs and partner institutions participate in the research during the academic year or through summer research programs. Graduate and undergraduate students are exposed to a rich collaborative research environment through interactions and internships with researchers at government lab facilities. Technical description The development of bright, tunable, easy to scale and integrate quantum light courses stands as a paramount objective for applications ranging from quantum information processing to quantum sensing and metrology. Quantum dots (QDs) and defect emitters are particularly promising candidates for scalable quantum systems since they are based on a semiconductor platform which leverages existing infrastructure. Quantum emitters based on 2D transition metal dichalcogenides (TMDs) are of particular interest due to their ultra-thin nature and van der Waals bonding, which enables high light extraction efficiency and hetero-integration via layer stacking. Approaches pursued thus far to achieve quantum emission from 2D TMDs include controlled defect/impurity introduction, strained nanostructured surfaces and twisted bilayers. This project focuses on the development of a new class of 2D quantum emitters based on in-plane 2D TMD quantum dots embedded within wafer-scale continuous monolayer sheets. The research focuses on two dot/matrix combinations: MoSe2/WSe2 and MoS2/WS2 (Type II band alignment) and MoSe2/WS2 and ReS2/MoS2 (possible Type I alignment). The work encompasses studies of TMD epitaxy on single crystal substrates focused on tuning the size, shape, density and uniformity of dots and the dot/matrix interface providing insights into the fundamental mechanisms of TMD nucleation, lateral growth and heterointerface structure. Comprehensive exploration of the electronic and optical properties of the samples enables new insights into exciton confinement and charge transfer in in-plane heterostructures. A combination of scanning probe based near-field electronic (surface potential and conductance mapping) and optical techniques (Raman and photoluminescence (PL)) are used in conjunction with far-field spectroscopy (reflectance, ellipsometry and PL) and gated measurements to determine the nature of band alignment and exciton confinement in these heterostructures. The project provides fundamental insights into quantum confinement in in-plane TMD heterostructures and lays the groundwork for future development of TMD QDs monolayers for quantum light emission. 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 · 2024-09

ABSTRACT Historically, sperm were largely disregarded as contributors of non-genetic information due to their significantly reduced cytoplasmic contribution to the zygote relative to eggs. However, recent studies have demonstrated that sperm can transmit non-genetic information to offspring, thereby modulating inherited phenotypes. Specifically, the microRNA (miRNA) content of sperm is altered by changes to paternal diet and exposure to stress and various toxins. While several studies have causally demonstrated that the microinjection of specific sperm miRNAs can induce changes in offspring phenotypes, the molecular mechanism of action of sperm miRNAs in early development remains unknown. The primary functions of miRNAs are to downregulate messenger RNA (mRNA) transcripts via destabilization, decay, and translational repression. My preliminary data shows that a single miRNA has the ability to downregulate dozens of mRNA transcripts during early embryonic development. I hypothesize that sperm miRNAs play an important role in modulating early development by altering embryonic gene expression via the contribution of double-stranded miRNAs to the zygote during fertilization. To test this hypothesis, I will determine the effects of sperm miRNAs on early development by injecting miRNAs into mouse eggs chemically induced to develop in the absence of sperm (parthenotes). This system will allow me to study how a single component of sperm, miRNAs, mechanistically function during early embryonic development in the absence of all other contents of sperm. I will microinject parthenotes with individual sperm miRNAs upregulated upon stress exposure (Aim 1a) and important for embryonic development (Aim 1a) and quantitate the transcriptome throughout early development using single- embryo RNA-sequencing (RNA-seq) to determine how miRNAs regulate embryonic gene expression. In Aim 2a, I will selectively digest either single- or double-stranded sperm miRNAs to systematically analyze which sperm miRNAs are delivered to zygotes as duplexes using small RNA-seq. In Aim 2b, I will use small RNA- seq to probe whether sperm acquire precursor miRNAs during maturation. Duplex molecules will have increased stability and enhanced functionality to regulate embryonic gene expression due to their increased efficiency of loading into AGO. Together, my project will provide novel insight into the functions of sperm miRNAs by providing a comprehensive and mechanistic understanding of how they regulate early embryonic development.

NIH Research Projects · FY 2025 · 2024-09

Modified Project Summary/Abstract Section This project addresses the growing clinical and public health burden of glaucoma-related vision loss. Glaucoma is a complex, progressive disease that often goes undetected until substantial vision impairment has occurred. Current diagnostic approaches are limited by the complexity of the disease, the variability in patient presentation, and the fragmented nature of healthcare data. This research aims to develop a clinical decision support tool leveraging artificial intelligence (AI) to enhance diagnostic precision and facilitate earlier and more accurate intervention. Three core challenges will be addressed. First, the development of a multi-modal AI framework capable of integrating diverse data types, such as structural retinal imaging and visual field measurements, collected longitudinally across patient visits. This integration is expected to improve the accuracy and reliability of glaucoma detection and functional loss prediction. Second, the research will optimize the interface between clinicians and the AI-based tool to support informed clinical decision-making. Model interpretability and performance transparency will be emphasized to ensure safe use in a range of clinical scenarios. The incorporation of advanced uncertainty estimation methods will provide insights into prediction confidence and support appropriate usage. Third, the study will evaluate model performance across diverse data distributions to ensure consistency and generalizability in clinical applications. By systematically analyzing the impact of data heterogeneity, the project will inform model development strategies that improve clinical utility across populations and care settings.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Disabilities, including those due to a stroke, are common among older adults worldwide, affecting about 36% of adults 65 and older in the USA.1 As the world’s population ages, the need for effective, affordable, accessible rehabilitation will increase. This need is particularly acute in low and middle income countries (LMICs), which carry 90% of the global stroke burden.2 Limited healthcare resources in LMICs necessitate practical solutions such as community-based rehabilitation and affordable robotics that allow caregivers to help with rehabilitation. My goal is to improve community-based robotic therapy by implementing a joint learning paradigm for individuals with varying levels of motor and cognitive impairment. Haptic interaction or the transmission of tactile information using sensations such as vibration, touch, and force feedback between individuals can improve rehabilitation. Haptically connected individuals in a multiplayer game may experience the social and motivational advantages as well as the implicit communication channel afforded by a haptic connection to a partner. The goal of this project is to determine how individuals with varying motor and cognitive impairments communicate and learn during haptic interaction in order to better design haptic feedback for multiplayer rehabilitation robot games. The rst specic aim is to leverage an affordable robotic rehabilitation platform to study how age and stroke-related motor and cognitive impairments inuence motor learning when individuals are haptically connected to a partner. Healthy older adults and older adult stroke survivors will learn a robot-based motor task with a 1-week follow-up assessment. I expect that a haptic connection to a partner with similar or less motor impairment will result in greater motor learning, especially for those with age or stroke related cognitive impairments, than learning individually. I also expect that a haptic connection to a partner with greater motor impairment will reduce motor learning. The second aim is to develop a model of sensorimotor communication using inverse optimal control techniques that accounts for motor and cognitive impairments. This model will reveal how age and stroke related motor and cognitive impairments mediate different sensory feedback channels (e.g., visual, haptic). Finally, the third aim is to develop an adaptive dyadic controller that balances differing partner ability levels in a robot-based haptic dyad. This adaptive dyadic rehabilitation robot will enable older adults with motor and/or cognitive impairments to interact and support each other’s rehabilitative efforts. This project will help answer fundamental questions about how motor and cognitive impairments inuence sensorimotor communication, providing design insight for robotic rehabilitation. Done in the context of a pre-doctoral training plan, this work, which helps to develop an independent researcher at the intersection of robotics and rehabilitation science, will be completed within Mechanical Engineering, Physical Medicine and Rehabilitation, and the General Robotics, Automation, Sensing, and Perception (GRASP) laboratory at the University of Pennsylvania.

NIH Research Projects · FY 2024 · 2024-09

Project Summary The requested instrumentation in this proposal is an ultra-high resolution mass spectrometer coupled to an ultra-high performance liquid chromatography system that will be used for lipidomics, metabolomics, isotope tracing, and structural elucidation experiments. Specifically, we are requesting funds for a Thermo Scientific™ Orbitrap™ IQ-X™ Tribrid™ Mass Spectrometer coupled to a Vanquish dual column liquid chromatography system, to expand our technological capabilities and offerings to its user base. This instrument will be housed in the Translational Biomarker Core (TBC) in the Center of Excellence in Toxicology (CEET) at the Perelman School of Medicine of the University of Pennsylvania (Penn). The TBC currently serves over 80 investigators from Penn and beyond. These collaborations range from fee-for-service customers to extensive grant-based collaborations. Until 2016, the TBC only offered targeted quantification assays and proteomics methodologies. In 2016, the Core acquired a Dionex™ Ultimate™ HPG-3400RS ultra high-pressure liquid- chromatography (UPLC) that was interfaced with an Orbitrap QE-HF that was running proteomics using a nano- flow-LC in the Blair laboratory. With limited instrument time, the Core developed its lipidomic platform by combining the HRMS raw data with Lipids Search (Thermo) software for lipids identification. This assay is one of the most requested assays offered by the Core, and through collaborations, we have now more than 300 lipids standards used for calibration curves. During the University restrictions due to Covid-19 in spring 2020, we ran the 600 metabolomics standards commercially available, building a library for Compound Discoverer 3.2 (Thermo). The metabolomics workflow was used for several successful grant submissions during the last two years. The Core would like to expand its capabilities to run these types of highly multiplexed and untargeted omics routinely, to expand technological capabilities, and fit offerings to its user base needs. This proposal highlights the need of omics assays from 29 users (28 with NIH funding). Additionally, the core has established ongoing collaborations with institutes and centers at Penn including Children’s Hospital of Philadelphia (CHOP), the Institute for Translational Medicine and Therapeutics, and the Institute of Immunology. Given the focus of the users on the identification of novel small molecule biomarkers of inflammation and related chronic diseases such as cancer and diabetes, this mass spectrometer is urgent and vital for our research projects. Expertise in the Core includes staff that is responsible for instrument maintenance, sample preparation, method development, and data analysis, including large data sets that require the use of bioinformatics software for differential analysis. Furthermore, having a dedicated HRMS instrument will complement the recent expansion of our Core staff. It will allow method development time to expand core capabilities and the continuation of a more extensive education and training arm of our mission, to provide our expertise in LC-HRMS analysis, experimental planning and training to collaborators who are interested in better understanding mass spectrometry applications.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Transcranial magnetic stimulation (TMS) is currently approved by the FDA for the treatment of depression, obsessive compulsive disorder, and smoking cessation. Despite evidence that TMS improves symptoms by modulating brain connectivity, the few published studies that have measured brain connectivity before and after neuromodulatory TMS have been population-, dose-, and pattern-specific, with connectivity effects that are limited in scope to a handful a priori regions of interest. Accordingly, there is a critical need for generalized, comprehensive model that explains how functional brain connectivity changes at the whole-brain level following neuromodulatory TMS. Therefore, the objectives of this grant are to 1) develop a model using whole- brain estimates of the TMS-induced electric (e)-field to predict changes in resting state functional connectivity following neuromodulatory TMS, and 2) validate this model in a large cohort of healthy volunteers receiving multiple doses of either intermittent or continuous theta burst stimulation (iTBS and cTBS, respectively). Our central hypothesis is that changes in functional connectivity will vary systematically with the current density at the cortex, operationally defined using e-field modelling. We have pilot data suggesting that the variability in pre-post rsFC changes following TMS can be predicted using estimates of the current density at the cortex with a medium to large effect size. Our approach will be to measure rsFC in healthy volunteers before and after each of 3 doses (5 sessions/dose; 600 pulses/session) of iTBS or cTBS. Stimulation will be delivered to the left dlPFC, and targeting will be individualized based on fMRI data collected during the Sternberg working memory paradigm. Our primary outcome measure will be the percent of variability in pre-post rsFC accounted for by our model. Our rationale for this approach is that by collecting resting state data pre and post these doses of iTBS and cTBS, we will be able to quantify the effect of pattern (i.e. cTBS vs. iTBS) and dose (i.e. number of pulses) on functional connectivity changes. This work is innovative because it uses a novel application of e-field modelling to predict changes in rsFC data following TMS administration.

NSF Awards · FY 2024 · 2024-09

The Artificial Intelligence-driven RNA BioFoundry (AIRFoundry) addresses critical challenges in RNA technology research by establishing a user-friendly, open-access platform. This initiative integrates cutting-edge AI for RNA design, synthesis, and delivery, while also promoting knowledge sharing and reproducibility. AIRFoundry harnesses the potential of RNA by extending its impact beyond healthcare to fields such as agriculture, biotechnology, and environmental remediation. AIRFoundry combines AI tools, automation, and microfluidics to uncover fundamental design principles that will accelerate RNA-based innovations. AIRFoundry serves three key functions: 1) optimizing RNA design, synthesis, and efficiency; 2) guiding and assisting researchers in developing effective delivery vehicles, like lipid nanoparticles, to transport RNA to intended targets; and 3) generating new knowledge towards establishing relationships between RNA design, delivery vehicles, and their activity in biological systems. Furthermore, AIRFoundry emphasizes education and seeks to broaden participation in RNA research by training the next generation of scientists from diverse technical and geographical backgrounds while ensuring that its advanced technologies are accessible to a wide range of users, from academic researchers to small businesses. This collaborative, multidisciplinary environment fosters innovation, accelerates advancements in RNA research, and democratizes RNA technology, ultimately empowering a diverse workforce to address global challenges like climate change and food security. The Artificial Intelligence-driven RNA BioFoundry (AIRFoundry) directly addresses critical roadblocks in RNA research by establishing a comprehensive framework that integrates cutting-edge artificial intelligence (AI) to uncover, share, and apply fundamental design principles of RNA and delivery vehicles. AIRFoundry operates through three distinct multidisciplinary research groups (MRGs) working in tandem with technology innovation groups (TIGs) that serve a wide range of users, from academic researchers to small businesses. MRG-1 optimizes RNA design and synthesis through integration of cutting-edge biochemical methods and Bayesian optimization models to efficiently navigate the vast design space of RNA molecules, rapidly identifying optimal sequences for desired functionalities. MRG-2 advances the field of delivery vehicles by employing AI-refined design rules for lipid nanoparticles (LNPs). By establishing the fundamental structure-activity relationships for LNPs, researchers can tailor these delivery systems for specific RNA cargos and target cells, ensuring efficient cellular uptake and maximizing performance across a broad set of applications. MRG-3 leverages AI to augment human expertise and decision-making across the entire RNA design, synthesis, and delivery workflow. AI algorithms will be trained on large datasets that comprise RNA sequences, LNP compositions, and biological responses. This knowledge base will empower researchers to make informed decisions at every stage of development, accelerating discovery and optimizing RNA-based technologies. Complementing these MRGs, a set of TIGs focuses on translating fundamental research into technologies to support the AIRFoundry and its users. TIG-1 focuses on automating RNA production, integrating robotics and chromatography to enhance the high-throughput synthesis and scalability of diverse RNA molecules for research and application. TIG-2 tackles the development of robust and rapid production of multiple LNPs with precisely controlled structures, enabling high-throughput screening and optimization of LNP properties for targeted RNA delivery. TIG-3 focuses on developing cross-cutting tools that integrate knowledge sharing, simulations, data management and in-line sensing for seamless collaboration within the AIRFoundry platform. By harnessing the collective expertise of scientists and engineers from diverse fields such as RNA biology, AI, microfluidics, process engineering, and data management, AIRFoundry aims to establish a preeminent platform for RNA technology advancement and democratization. Integrating AI-driven discovery and optimization with cutting-edge microfluidics and automation, AIRFoundry promises to revolutionize RNA research and to open a wide variety of new applications. This project is jointly supported by Divisions of Emerging Frontiers (EF), Biological Infrastructure (DBI), and Molecular and Cellular Biosciences (MCB) in the Directorate for Biological Sciences (BIO), Division of Chemistry (CHE) in the Directorate for Mathematical and Physical Sciences (MPS), and the Directorate for Technology, Innovation and Partnerships (TIP). 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 2024 · 2024-09

This project studies interacting particle systems at the interface of probability, combinatorics, statistics and applied mathematics. Interacting particle systems naturally emerge in various physical systems, and their behaviors—such as global fluctuation and relaxation rate— are crucial in understanding these systems. Beyond pure mathematics, interacting particle systems have been widely used for random sampling, due to their flexibility and high accuracy. This project will develop new tools and techniques for advancing the study of interacting particle systems. The project will also provide valuable educational opportunities for students at several levels, including a summer school and workshops focusing on the interactions of probability, mathematical physics, and machine learning theory. These initiatives seek to bring together early-career researchers from diverse fields to foster collaborative efforts. One primary objective of this project is to investigate the asymptotic behaviors of various interacting particle systems, such as local statistics, global fluctuations and large deviations. These findings will facilitate deriving asymptotic properties of symmetric polynomials, a task less accessible through traditional algebraic combinatorics methods. Additionally, new universal laws, such as the Tracy-Widom distribution, appear in both random matrix theory and intersecting particle systems. The scaling limits of interacting particle systems converge to two-dimensional universal limiting objects, from which we can recover random matrix eigenvalue statistics by taking one-dimensional slices. Another key aim is to employ tools from interacting particle systems to establish characterizations of random matrix statistics, particularly from the view of line ensembles. These characterizations provide novel pathways to understand convergence to random matrix statistics in many statistical physics models. Lastly, the PI aims to develop efficient particle-based derivative-free sampling algorithms. These algorithms will enable effective uncertainty quantification for models where differentiation is impractical. 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 · 2024-09

ABSTRACT Meniscus tears are one of the most common knee injuries and often fail to heal in adults. Current surgical treatments increase osteoarthritis (OA) risk, especially in patients with metabolic syndrome (including obesity, hyperglycemia, and dyslipidemia). While this is often attributed to mechanical overloading, metabolic syndrome is also associated with OA in non-weightbearing joints. Preclinical studies suggest elevated inflammatory signals from adipose tissue (e.g., adipokine dysregulation) mediate articular cartilage degeneration following meniscal injury. Obesity and OA are associated with aberrant microstructural remodeling and strain attenuation in the outer meniscus. Despite these findings, the mechano-metabolic mechanisms controlling meniscus cell function remain unresolved. To address these gaps in knowledge, this proposal will investigate the impact of metabolic syndrome on meniscus cell mechanoactivation. Our central hypothesis is that persistent adipokine dysregulation exacerbates degeneration by altering meniscus cell setpoints for mechano-responsivity and perturbing their response to homeostatic signals. To test this hypothesis, this proposal uses novel, multiscale experimental techniques to determine if metabolic syndrome impairs transmission of tensional cues in the meniscus. Specifically, Aim 1 will test if mechano-metabolic interactions alter meniscus cell contractile force generation and response to static and dynamic microenvironmental cues. Aim 2 will determine how metabolic memory arising from transient and sustained adipokine dysregulation influences meniscus cell mechanoactivation, phenotype, and multiscale tissue mechanical properties in response to homeostatic and pathological tensional cues. I hypothesize that adipokine dysregulation will impair meniscus cell contractile force generation and mechanoactivation, leading to loss of fibrous phenotype and aberrant matrix remodeling. This work will generate novel insight into how mechanotransductive and metabolic crosstalk regulates fibrous tissue homeostasis and direct regenerative strategies for meniscus repair in high-risk patients.

NSF Awards · FY 2024 · 2024-09

Silicon quantum dot devices hold significant promise for scalable quantum computing. However, tuning these devices into the desirable states for quantum applications is highly challenging, creating substantial barriers to entry. Traditionally, tuning has been a manual process that is time-consuming, heavily reliant on experimental intuition, and inherently unscalable. This situation underscores the need for automated tuning (autotuning) approaches. The development of autotuning algorithms has been impeded by the lack of experimental training data and the limitations of existing quantum dot simulators, which only capture the physics of already-tuned devices. To this end, this project aims to provide full-stack support for quantum dot device autotuning research by delivering new quantum dot device simulation infrastructures for cold start and exploring corresponding autotuning algorithms. This initiative will democratize autotuning research, offering researchers without access to experimental facilities both training data and a low-cost autotuning testbench. These advancements will promote the progress of science by facilitating broader access to quantum computing research and enhancing the efficiency and scalability of quantum dot device tuning. This project will provide training opportunities for the next-generation quantum computing workforce, and the research outcomes will be integrated into undergraduate and graduate education efforts. The proposed research will significantly advance our understanding of quantum device modeling and tuning, providing innovative tools, data, and methods that can shape the tuning process of quantum dot devices. Specifically, this project will develop the QDREAM (Quantum Dot Real-Time Emulation and Autotuning Model) framework. QDREAM consists of 1) device-physics-based cold start simulations that focus on combining a finite element electrostatic simulation with a constant interaction quantum dot model to simulate devices in a completely untuned regime; 2) an FPGA-based quantum dot device emulator that will take in real voltages and output a charge sensor signal in real-time; and 3) a series of autotuning algorithms targeting various stages of the device tune-up process from cold start. QDREAM will be validated using real quadruple quantum dot devices routinely fabricated and measured in our lab. These comprehensive advancements will serve as a foundational step towards realizing larger-scale, more advanced quantum-dot-based quantum computers. 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 · 2024-09

Summary We propose to create a comprehensive training program that encompasses research training in science related to kidney, benign urology, and benign hematology across the lifespan entitled the Philadelphia Program for Mentored Research Training in Kidney, Urologic, and Hematologic Diseases (PERFORM-KUH). Leveraging the physical proximity and the history of interinstitutional and interdisciplinary training and collaboration, PERFORMKUH is uniquely positioned to build/enhance a biomedical research training program that integrates well-established training programs at the University of Pennsylvania (Penn) and the Children’s Hospital of Philadelphia (CHOP), and pre- and post-doctoral programs at Drexel, Jefferson, and Temple (with affiliated Fox Chase Cancer Center) Universities. The primary goal of this program is to develop skilled investigators trained to conduct impactful research in clinical, translational, or basic science in KUH, and capable of further developing careers as independent researchers. PERFORM-KUH will replace three longstanding T32 training programs located at Penn/CHOP, in hematopoiesis, kidney disease, and renal epidemiology, add training in pediatric and adult urology research, and importantly, integrate with three partner institutions in Philadelphia. This program assembles one hundred and six talented faculty trainers from five institutions, sixteen graduate programs, and thirty-eight departments, to create a premiere integrated research training program for KUH trainees in the Philadelphia region. PERFORM-KUH is designed to support eight predoctoral and twelve postdoctoral trainees per year. This request is justified by the historical demand by high-quality applicants for training slots in our standing T32s, accommodated by the size and quality of the PERFORM-KUH faculty, large and outstanding trainee pools, strong institutional and departmental commitments, and collaborative training environment. The PI/PD with focus area advisors and site PIs are well supported by the Steering Committee of the Administrative Core consisting of a Recruitment and Admissions committee, Mentorship Oversight subcommittee, and an External Evaluation Board. Research mentorship is provided by scientifically diverse trainers of all academic ranks with research interests that encompass virtually all areas of KUH. The Training Program will leverage innovative PERFORM-KUH cores, including its Professional Development Core (PDC), and its Networking Core (NWC) that integrate pipeline programs to attract undergraduate, medical, and high school students from underrepresented backgrounds. The DEI director is dedicated to minority recruitment and retention efforts in PERFORM-KUH research training. The academic elements of the Program include laboratory work, skills training, seminars, mentoring and career counseling, presentation, manuscript and grant writing, and peer mentoring in collaboration with PDC and NWC. It will offer an integrated core curriculum that includes the completion of a formal master’s degree program for MD research fellows. Facilitated by a professional Evaluation Director, PERFORM-KUH will be evaluated using systematically collected and formally analyzed data. Project Summary/Abstract

NSF Awards · FY 2024 · 2024-09

This project aims to serve the national interest by closing the academic completion gap for Latina/o STEM students through the implementation of a "Circle of Champions." The Circle of Champions framework seeks to organize individuals around students, actively supporting them throughout their academic journeys. Under this approach, students nominate parents, other family members, friends, former high school teachers, professors, and similar individuals as their champions. With a Circle of Champions around each student, the project tracks their journey, informs champions of progress, and facilitates their learning on how to provide support effectively. The goal is to leverage students' assets and community wealth into traditional forms of social, cultural, and academic capital. This project employs a cultural assets approach to student learning combined with an intentional focus on harnessing the considerable resources students possess within their families, communities, and themselves. By addressing this oversight, the project will set the stage for an equity-oriented approach to supporting student success. This project seeks to accomplish four goals: 1) advance the understanding of converting social capital into academic capital; 2) investigate conditions under which the Circle of Champions model can be optimized to impact student success in STEM; 3) narrow or close the equity gap in STEM at Gavilan College; and 4) develop a replicable model for other Hispanic Serving Institutions. Project activities aimed at achieving these goals include supporting the Circle of Champions model for all Gavilan College students enrolled in STEM courses, expanding and developing an AI assistant platform, studying the effectiveness of research and program evaluation to fully understand variables influencing success, and disseminating findings. The researchers aim to explore existing assets in the lives of Latina/o students, particularly their social capital, and how these assets can contribute to academic success. To investigate the impact of social networks on students' lives, the project utilizes Community Cultural Wealth (CCW) and Funds of Knowledge (FK) models as guiding frameworks and employs a mixed method of analysis, including qualitative analysis of user opinions, quantitative analysis of user activity using machine learning, and quantitative assessment of student academic outcomes. The NSF IUSE: Innovation in Two-Year College STEM Education (ITYC) Program seeks to accelerate the impact of and advance knowledge about emerging and evidence-based practices in undergraduate STEM education at two-year colleges. This project is partially funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and build capacity at HSIs. 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 2024 · 2024-09

People’s body movements can reveal a lot about students’ mathematical reasoning. Examples such as using one’s whole body to explore properties of geometric shapes and raising eyebrows during mathematical insight illustrate ways people’s movements are closely linked to how they think. Despite the value of these nonverbal indicators of students’ learning experiences, this body-mind connection remains understudied. In this project various data sources are gathered from learners playing a video game designed to improve mathematical reasoning through movement and speech. While learning, students occasionally use their bodies to express mathematical insights and trouble spots. These events are important enough that they can influence students’ learning and attitudes toward mathematics, but subtle enough that teachers may miss them in the buzzing dynamics of the classroom. AI will help the research team select when to interview students about these rare but significant moments in their learning, combining the speed and pattern recognition of computers with the depth and insight of humans' natural conversation. This approach creates a rich dataset for analysis and to develop design principles that support mathematics learning through movement. The findings will advance a deeper understanding of how people learn using nonverbal and verbal thought processes and ways to better support these thought processes. The broader impacts include improving mathematics learning for everyone, especially for those who rely on nonverbal thought processes that might be overlooked using current learning designs. In this project, investigators target two common and critical moments in mathematics learning: 1) forming mathematical insights, and 2) encountering trouble spots that indicate a student is struggling to adapt their understanding to new information. Findings from the five phases of research provide the investigators with detailed findings that can be leveraged to develop new theories and improve classroom learning. In Phase 1 of the project, initial data are collected (including movement, speech and interaction) as students play a mathematics learning game that encourages them to use their bodies. Phase 2 involves creating automated AI detectors, driven by scientific hypotheses, that can recognize students' insights and trouble spots in real-time. In Phase 3, additional data collected with the detectors from phase 2 alert trained interviewers to critical events during student learning, prompting data-driven interviews that gather evidence on cognitive, metacognitive, and affective processes. Phase 4 uses learning analytics and data from these AI detection-driven interviews to build a theoretical model explaining the interplay of cognition, metacognition, affect, and embodiment. Finally, Phase 5 generates practical design principles for classroom instruction and embodied learning technologies, informed by the resultant model and empirical findings. The broader impacts include improving mathematics learning for everyone, especially for those who rely on nonverbal thought processes that might be overlooked using current learning designs. 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 2024 · 2024-09

NON-TECHNICAL SUMMARY: Enzymes are important molecules in biology. Enzymes are catalysts that convert substrates to products and are essential for driving processes that allow cells to function and respond rapidly to environmental conditions. There are a wide variety of enzymes in Nature corresponding to the diverse array of chemical reactions that a cell must execute for proper physiological function. It has been found that enzymes can exert forces when they convert substrates, and in this project, these forces will be harnessed to drive the motion of cell-sized capsules in response to substrates. The capsules will be made from biocompatible polymers, so they can be used to deliver drugs and communicate with cells by secreting bioactive compounds. Microfluidics will be used to assemble biocompatible capsules of defined chemistry, size, and composition. It has been found that asymmetry – either in the chemistry or the geometry of the capsule, or both – is required for robust motion. Asymmetry can be systematically built into the capsules using capsule chemistry and microfluidic design. A wide variety of enzymes will be tested to understand how the mechanism of action of each enzyme relates to its ability to support the propulsion of capsules. Capsules of tailored asymmetry with two faces – Janus capsules – will be used to understand how geometrical asymmetry can drive capsule motion via enzyme turnover. Systems in which capsules can communicate by secreting substrates to activate the motion of nearby enzyme-laden capsules or real biological cells will be developed, and furthermore, the motion of capsules in gradients of substrate will be measured. The project will train two graduate research assistants and two undergraduates, and the investigators will communicate their ideas to the broader research community through demonstration lectures to middle school and high school students and faculty. TECHNICAL SUMMARY: Enzymes are a diverse set of molecules that catalyze a host of biochemical reactions throughout biology. Enzymes are known exert forces during enzymatic turnover, and previously catalase and urease were used to drive the motion of biocompatible cell-sized capsules. Based on the hypothesis that propulsion is due to osmotic influx at the catalytic binding site (osmophoresis), a wide array of enzymes will be tested to relate fundamental features of enzyme activity (reaction rates, Michaelis constants, and reaction schemes) to capsule propulsion. Of particular interest are cleaving enzymes, such as amylase and nucleases, which are hypothesized to generate augmented osmotic forces and hence avid propulsion. Furthermore, higher order cell behavior, such as chemotaxis and multicellular organization, will be recapitulated with enzyme-functionalized microcapsules. The microcapsules are made by microfluidics using biocompatible polymers (poly-lactic-co-glycolic acid), allowing the control the size, composition, porosity and asymmetry of the capsules. Asymmetry in capsules chemistry and geometry has been demonstrated to enhance capsule motion. The aims of this project will be to measure the motility of single capsules across a range of enzyme-substrate systems and measure the dynamics of motion of asymmetric (Janus) capsules; to quantify the directional motion of capsules in gradients of substrates, analogous to the chemotactic motion of cells; and to determine the ensemble motion of capsules, both with different volume fractions of active particles, as well as mixtures of active and passive particles, to understand how motility can be used to separate and organize multi-particle assemblies. Another goal is to build communication systems in which one capsule can secrete a substrate and drive the motion of a neighboring capsule. Finally, we will understand how motile, synthetic capsules can communicate chemically and physically with biological cells. The capsules can be thought of as synthetic cells (protocells) inspired by and designed to mimic biology. Since the capsules are biocompatible, a host of applications, such as targeted drug delivery and tissue assembly, can be envisioned in which these motile protocells can interface with real biological cells and tissues. 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 · 2024-09

PROJECT SUMMARY Visual decision-making in the brain is thought to depend on two behaviorally distinguishable computational components: one that converts uncertain visual inputs into a decision variable, and a second that applies a rule to the decision variable to commit to a choice. Our long-term goal is to understand the neural mechanisms that implement these computational components of high-order visual processing, which represent key building blocks of cognition. Here we propose to examine where and how visual decision rules are implemented in the brain. We build on three primary innovations: 1) a novel theoretical framework predicting that normative decision rules tend not to be static, as prescribed in many commonly used decision models, but rather dynamic with flexible adjustments both within and across decisions; 2) a novel task design that allows us to control the decision variable and measure decision commitment directly for each decision; and 3) measurements and manipulations of neural activity at multiple cortical and subcortical components of a key oculomotor pathway to assess their relative contributions to implementing and updating flexible decision rules. We have three Specific Aims. Aim 1 is to characterize flexible decision rule use by monkeys. Aim 2 is to identify correlative relationships between neural activity in the oculomotor pathway and decision rules on single trials. We targe the frontal eye field and lateral intraparietal area of the cortex; the substantia nigra pars reticulata, which is a major output structure of the oculomotor basal ganglia; and the superior colliculus, which receives input from the other three regions. Aim 3 is to identify causal relationships between neural activity in these brain regions and decision rules on single trials. Results from the proposed project will provide new, theoretically motivated, and empirically grounded insights into circuit mechanisms that control a major building block of deliberative information processing in the brain: the rules that govern when and how to end the deliberations and commit to an action. These results will help to provide a solid foundation for investigating cognitive impairments associated with dysfunction of the cortico-basal ganglia pathway.

NIH Research Projects · FY 2025 · 2024-09

Project Abstract The mammalian genome is organized into various regions at different scales as one mechanism to regulate gene expression and mediate cellular identity. One type of well-characterized region is the lamina-associated domain (LAD), which contains areas of chromatin that directly interact with the nuclear lamina (NL) at the nuclear periphery. Found across all chromosomes, LADs dynamically interact with the NL to release or attach genes and regulatory elements in accordance with cell-type and differentiation state-specific gene expression programs. Patients with mutations in LMNA, encoding the A and C type lamins in the NL, develop a heterogenous group of diseases, known as laminopathies. Laminopathies preferentially affect striated muscle, and patients often develop dilated cardiomyopathy (DCM), which can be fatal. Evidence from mouse models and human genetic studies of laminopathies have suggested a potential role for the Linker of Nucleoskeleton and Cytoskeleton (LINC) complex in mediating the disease phenotype. Abrogation of the LINC complex in a laminopathy mouse model resulted in a phenotypic rescue. Additionally, characterization of LMNA mutations in various cell types demonstrated a disruption to chromatin-lamina interactions in a cardiomyocyte-specific manner. This suggests a mechanism where the nuclear lamina and LINC complex are each playing a role in the pathogenesis of laminopathy phenotypes, and potentially affecting genome organization. However, while a LINC-LMNA-gene positioning axis has been previously suggested, the mechanism of how this may occur remains elusive. Using a combination of population-based genomics analyses, single-cell microscopy, and cellular functional assays, I will test the hypothesis that cytoskeletal-nuclear interactions in lamin variant cardiomyocytes destabilize LADs and contribute to abnormal cellular function. I aim to define the role of the LINC complex in mediating chromatin organization in LMNA mutant cardiomyocytes and will determine if disruption of LINC complex components can preserve the changes to genome organization observed. In addition, I aim to determine how cardiomyocyte function is affected by disruption of the LINC complex in the presence and absence of LMNA mutations. These studies will provide mechanistic insights into how the nuclear lamina and LINC complex are contributing to both LAD organization and cardiomyocyte function, which will begin to provide novel understanding of the molecular basis of laminopathy phenotypes.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract: Cytokinesis is fundamental to life, and the septins form cytoskeletal scaffolds or diffusion barriers of distinct architectures to impact diverse cellular functions including cytokinesis, cell migration, ciliogenesis, dendritic spine morphogenesis, spermiogenesis, and bacterial infection. Defects in cytokinesis or septins cause lethality or serious diseases including cancer, infertility, hereditary neuropathy, and neurodegenerative diseases such as Alzheimer's and Parkinson's. Thus, understanding cytokinesis and the septin cytoskeleton is critically important not only for basic science but also for public health. In this application, we will address the core issues regarding cytokinesis including the architecture and constriction mechanism of the actomyosin ring (AMR) as well as the mechanism of vesicle fusion at the division site. We will also address the key questions in the septin field including how a high-order structure such as the septin ring or hourglass is assembled and then remodeled into a distinct architecture for a distinct function. These questions will be addressed chiefly using the budding yeast model due to the stereotyped behaviors of cellular and molecular events involved in cytokinesis and septin architecture and remodeling during its cell cycle. Some of the key questions such as the architecture of the AMR, especially the organization of distinct myosin-II isoforms in the contractile ring, will also be investigated in fission yeast and mammalian cells to illustrate the mechanistic conservation and divergence during evolution. All questions will be addressed using an integrative approach that combines precise genetic editing, cell synchronization, AlphaFold2-based structural predictions, biochemical analysis, and cutting-edge imaging technologies including super-resolution microscopy, platinum-replica EM, and cryo-FIB-SEM/cryo-ET. We have made major contributions to the understanding of cytokinesis and the septin cytoskeleton. The proposed project is based on rigorous published and unpublished data, which sets the stage for testing specific hypotheses and exploring new directions. The completion of this project is expected to generate deep architectural and mechanistic insights into cytokinesis and septin assembly and remodeling.

NSF Awards · FY 2024 · 2024-09

Dental wear is a common but poorly understood process that progresses over the lifespan of an individual. In time, dental wear leads to dental senescence and significant dental costs. This study investigates the progression of dental wear over the course of fifty years of simulated chewing. The study employs complementing methodologies to measure changes in chewing function, and in tooth’s shape, structure, and elemental composition. The data captures the onset and development of dental senescence, advancing an understanding of dental wear to benefit the fields of biological anthropology, oral biology, and dentistry. This project provides STEM training opportunities to a postdoctoral scientist and undergraduate students. The project engages elementary school students through the production of dental anatomy learning kits that promote knowledge and good oral health. This project investigates the impact of longitudinal dental wear in humans at four distinct scales: (1) dental function; (2) occlusal topography; (3) dental microstructure; and (4) elemental composition. The study utilizes extracted third molars, and an Artificial Resynthesis Technology (ART VII) chewing simulator, capable of replicating a year of human chewing cycles in a single day. This unique equipment allows for a direct assessment of changes associated with longitudinal dental wear in human teeth without using in vivo or comparative approaches. Unworn occluding pairs of third molars are positioned in the ART VII, where they chew foods with different material properties over a simulated 50-year period. At five-year intervals, changes in dental function are evaluated by quantifying: (1) chewing efficiency; (2) occlusal topography; (3) dental microstructure; and (4) enamel elemental composition. 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.