Grants

NSF

Understanding how fluids interact with elastic or porous materials, such as blood flowing through arteries or water filtering through soil, is crucial for addressing practical challenges in medicine, environmental science, and engineering. This type of modeling, known as fluid-structure interaction (FSI) or fluid-poroelastic structure interaction (FPSI), involves complex physics and mathematics because the fluid and the structure influence each other in strongly coupled ways. Traditional domain decomposition approaches solve the fluid and structure parts separately, then iteratively exchange information, but this process can be computationally expensive, especially for large systems. This research aims to develop new and efficient numerical methods that can solve these coupled problems more accurately and with reduced computational cost, enhancing simulation capabilities across diverse applications from hemodynamics to subsurface flow. This project is on a rigorous development and analysis of numerical schemes for solving FSI and FPSI problems, using a unified, monolithic framework with Lagrange multipliers to enforce interface conditions. The core of the work includes: (1) formulating and analyzing a monolithic system to establish well-posedness, stability, and finite element error estimates; (2) deriving a Schur complement equation to decouple the subdomain problems and enable efficient computation of the Lagrange multipliers; (3) applying projection-based reduced order modeling (ROM) to the Schur system, stabilized by supremizer enrichment, to reduce computational cost; and (4) extending the framework to a novel three-dimensional fluid–two-dimensional plate interaction model. These advancements aim to significantly enhance the computational efficiency and robustness of simulations for strongly coupled multiphysics systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NHLBI - National Heart Lung and Blood Institute

PROJECT SUMMARY/ABSTRACT Mitral regurgitation (MR) is one of the most prevalent heart valve diseases. If left untreated, patients will experience left ventricle (LV) structural and functional alterations. These include chronic increases in wall stress and changes in cellular and extracellular matrix response that leads to progressive LV hypertrophy and fibrosis, leading to atrial fibrillation (AFib), heart failure, and death. The only effective, long-term treatment for MR remains valve repair or replacement. Minimally invasive mitral valve (MV) repair and percutaneous MV replacement are becoming stronger alternatives to open-chest, MV replacement surgery; however, they are not indicated for all patients, may result in MR recurrence, or have limited durability. Thus, there is a pressing need to develop a therapeutic pharmacological alternative to surgery. Furthermore, there is a need for MV-specific therapies that also address MR-mediated LV dysfunction. Serotonin 2B receptor (5-HT2B) signaling impacts both MV and LV remodeling; however, the interdependence between the mitral valve interstitial cell (MVIC) and cardiac fibroblast (CF) populations remains unknown. Given our ability to selectively remove 5-HT2B from MVICs and/or CFs, we possess the tools to decouple, for the first time, 5-HT2B-mediated MV dysfunction from LV remodeling both in murine models, as well as in human-derived MVICs and CFs. Additionally, our recent development of novel 5- HT2B antagonists that are unable to cross the blood-brain-barrier provides the first treatment option for targeting this pathway for human disease. These studies will result in clarification on the causal role of 5-HT2B in MV disease, while also examining the down-stream role of the receptor in MV-mediated LV dysfunction. We believe that due to the dual citizenship of the 5-HT2B receptor on the MVICs and CFs, which is unique to these cell types vs other valve and heart cells, this strategy can provide a ‘two-hit’ therapy for MV-LV disease, which encompasses nearly all patients with MR.

Deen Arts Foundation

Deen Arts Foundation is an active grantmaking foundation based in Plano, TX. Focus: arts. Contact the foundation directly for current funding opportunities.

NIAID - National Institute of Allergy and Infectious Diseases

PROJECT SUMMARY/ABSTRACT Type 1 diabetes (T1D) is an immune-mediated disease in which functional β cells are lost, leading to insulin dependence. HLA class II genotypes are the dominant genetic risk factor, suggesting a key role for CD4+ T cells. Islet-reactive T cells produce inflammatory cytokines and support formation and affinity maturation autoantibodies, the appearance of which accurately predicts disease risk. At-risk individuals develop additional specificities during progression. Therefore, epitope occurs and may be an indicator of impending disease onset. Our preliminary studies show that expanded numbers of CD4+ T cells that target self-antigens are present in individuals with established T1D. Specifically, our preliminary data enabled us to define an array of self-epitopes that are disease relevant and recognized in individuals with two of the highest risk HLA class II genotypes. These include newly discovered conventional and neoepitopes from GAD65 and other beta cell antigens. It is believed that self-reactive T cell responses evolve over time and that beta cell injury elicits neoepitope formation. However, these phenomena have not been directly studied, leaving a significant knowledge gap. Given their important role in orchestrating autoimmunity, understanding the CD4+ T cell responses is a topic of great importance. Indeed, the approval of teplizumab as a therapy to delay the progression of T1D increases the rationale for understanding and monitoring epitope spreading in at-risk individuals. Our work will test the hypothesis that in at-risk subjects there are pivotal shifts in the number, phenotype, and transcriptional programs of autoreactive CD4+ T cells and an expansion of distinct TCR sequences and that these changes reveal important pathways that drive disease progression. Our first aim will characterize longitudinal changes in the number and phenotype of autoreactive T cells in at-risk subjects by performing high dimensional flow cytometry analysis using a robust surface marker panel combined with second generation HLA class II tetramer reagents. Our second aim will utilize the 10X genomics platform to generate rich whole genome RNAseq data sets on antigen specific T cells sorted from IAA positive at-risk individuals. This will allow deep molecular profiling of autoreactive T cells to identify immune cell subsets that contribute to T1D progression and deep analysis of TCR sequences and their structural features, tracking their phenotype trajectories over time and the emergence of key T cell transcriptional states in at-risk subjects. In total, our proposed studies will advance our understanding of T1D, providing important new insights about the T cell specificities, phenotypes, and functional attributes that drive the development of T1D the immunologic changes and mechanisms that promote autoimmune progression.

NHLBI - National Heart Lung and Blood Institute

PROJECT SUMMARY Cardiovascular disease and obesity are conditions that cause high morbidity in women, including women in rural areas; contextually tailored, evidence-based multilevel, multicomponent interventions that take social determinants of health into account are needed to prevent or improve risk factors for obesity and cardiovascular disease (e.g., dietary patterns, physical activity behaviors). The proposed project, Deep in the Heart, includes the following specific aims: 1) facilitate local community engagement and conduct formative research to inform tailoring for the intervention components as well as engagement and implementation strategies based upon data from bilingual focus groups with diverse residents and input gathered from a local Community-Clinical Advisory Board and a National Rural Advisory Board; 2) evaluate the Deep in the Heart intervention (experiential obesity and cardiovascular disease prevention group classes including aerobic exercise, strength training, and dietary skill-building facilitated by a Community Health Worker, with participant referral to resources based on social determinants of health survey; mobile health app for goal setting and self- monitoring; and a Community-Clinical Advisory Board refining and promoting a local Community-Clinical Resource Guide) in a community-engaged study in a diverse, medically underserved rural county in south Texas (>80% Hispanic); 3) conduct implementation and process evaluation guided by RE-AIM and the Consolidated Framework for Intervention Research; and 4) conduct cost-effectiveness analysis to inform resource allocation for future scalability. Deep in the Heart holds great potential to meaningfully reduce obesity and cardiovascular disease risk, improve rural women’s health equity, and provide an effective shorter-duration program, which will allow participation by individuals who may not enroll in a longer program due to scheduling, transportation, caretaking, or other constraints.

NHLBI - National Heart Lung and Blood Institute

Project Summary Bicuspid aortic valve (BAV) is the most common congenital heart defect, and it predisposes patients to complications such as aortic stenosis (AS, most common cause) and aortic aneurysm. BAV patients can develop highly divergent outcomes (e.g., rapid progressive aortic dilatation vs. no long-term complications) but the underlying mechanisms that determine the individual risk for complications are not well understood. There is growing evidence that BAV-based changes in aortic hemodynamics are drivers of aortic wall remodeling and subsequent aortic dilation. A number of studies by our group and others have shown that 4D flow MRI can measure altered aortic 3D hemodynamics in-vivo and has potential to provide better assessments of risk for aortic dilatation in BAV patients. However, current implementations of 4D flow MRI are hampered by long acquisition times (8-15 minutes) and cumbersome manual processing, such as eddy current corrections, noise masking, and 3D segmentations. The goal of this project is to develop an deep learning-based acquisition, image reconstruction, and analyses pipeline for efficient and highly accelerated aortic 4D flow MRI. The first aim of this proposal is development and validation of a highly accelerated 2-point velocity encoding 4D flow MRI with deep learning reconstruction. This will allow enable a 4D flow sequences with low scan times (<2 mins) without sacrificing image quality or hemodynamic accuracy. The second aim will be the development of a deep learning-based automated processing pipeline that will enable rapid processing of aortic hemodynamics and calculation of the wall shear stress dynamics and relative area changes. In the third aim, 20 BAV patients and 20 healthy controls will be recruited from the patient population at Northwestern, then imaged and analyzed using the new protocol. This will demonstrate the utility of using the highly optimized method for the acquisition and analysis of 4D flow MR in a clinical setting. Clinical collaborators will help guide the project to fulfil the ultimate goal of improving clinical imaging and analysis of these complex patients. And Siemen support will help with pulse sequence development and the direct integration of our deep learning network on the scanner, so that this project can be easily integrated in clinical workflows.

DECD

Deep River Open Government Enhancements

NSF

Volatile cycles between Earth’s atmosphere, lithosphere, cryosphere and hydrosphere play a critical role in planet evolution. Carbon, oxygen and hydrogen are the dominant volatile elements, and Earth’s mantle is the largest reservoir of these elements. One of the most important volatiles on Earth is water. Water exerts key controls over the properties of magma, mantle convection, the composition of the Earth’s atmosphere, and the evolution of life. This project will investigate water in the mantle transition zone (410–660 km depth) and deeper. A small proportion of diamonds, carried to the surface by rare and rapid volcanic processes, encapsulate minerals during their growth. These minerals are among the deepest direct samples available of the Earth's mantle. The project will use a collection of diamonds hosting such minerals to determine the water concentrations of the mantle where the diamonds formed. The project will also expand a large interactive exhibit in the Minerals Hall of the American Museum of Natural History into a web-based version on a platform for children and youth, called OLogy, and hosted by the museum. The new web version will be tested in upper elementary and middle school classrooms. Water is one of the most important volatiles on Earth. This project will investigate water in the deep regions of the planet, such as the mantle transition zone (410–660 km) and the lower mantle (660–2900 km), by studying mineral inclusions in diamonds. A small proportion of diamonds, carried to the surface by kimberlite pipes, contain inclusions of minerals that were encapsulated by the diamond during its growth. The main goals of this project are: 1) to identify the flux of water transported by subducted slabs into the deep subcontinental mantle; 2) to estimate the water budget in the mantle transition zone and the transition zone–lower mantle boundary, and to assess water concentrations in deep mantle minerals such as majoritic garnet and ferropericlase; 3) to investigate whether water is responsible for major redox (reduction–oxidation) reactions in the deep mantle. The project will investigate majoritic garnet and ferropericlase inclusions in diamonds from ultra-deep sources, such as the Amazonian craton in Brazil. Specifically, the research will identify and characterize mineral inclusions in a set of diamonds from Juina, Brazil, using optical microscopy, Fourier Transform Infrared and Raman spectroscopy, as well as cutting-edge computed tomography. Some majoritic garnets will also be studied by synchrotron Mössbauer spectroscopy, and phases that are difficult to identify will be examined by synchrotron X-ray diffraction. Some of the majoritic garnet and ferropericlase inclusions will be used for water analysis. The largest inclusions and those covering a wide range of compositions will be selected for water analysis by nanoSIMS. While sufficient standards exist for the analysis of majoritic garnets, there are currently no standards for ferropericlase. Therefore, this project will also experimentally synthesize standards for water analysis in ferropericlase. Given the unique nature of the studied diamonds, there is strong potential for side projects arising from newly discovered and exposed mineral inclusions in Juina diamonds. 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.

NIA - National Institute on Aging

PROJECT SUMMARY/ABSTRACT Alzheimer’s disease (AD) affects one in eight Americans over 65 and is among the leading causes of death in the United States. Despite its prevalence, the accurate clinical diagnosis of AD remains challenging due to non-specific clinical tests and symptom overlap with other types of dementia. Except at top medical centers, the resulting misdiagnosis rates in excess of 15% relative to “gold-standard” neuropathologic analysis at autopsy negatively impact the efficacy of care, patient outcomes, and clinical trial efficiency. Although there are biomarkers that correlate with the neuropathology of AD, many are either invasive or largely inaccessible in routine clinical practice, such as PET imaging. One in-vivo marker that could be largely accessible is morphological metrics derived from non-invasive T1-weighted structural brain magnetic resonance imaging (MRI). These scans are already routinely acquired for individuals presenting with age-related cognitive decline, but integration barriers hamper the clinical accessibility of derived metrics. The fundamental goal of this project is to enable hospitals with limited access to AD biomarkers to achieve the diagnostic accuracy of top-performing institutions. We aim to improve the sensitivity and accessibility of structural MRI metrics by improving longitudinal, within-subject approaches that drive the morphometric analysis of MRI scans using a subject-specific reference image—a template—constructed from time points after rigid registration correcting for differential head positioning. We will build upon recent image-synthesis techniques and cutting- edge deep learning to develop anatomy-aware registration tools that generalize to medical imaging data across different MRI scanners and hospitals, without retraining or preprocessing. First, we will incorporate randomized, synthetic atrophy of AD-specific structures, ventricular expansion, and MRI distortions into a generative model. We will use this model to develop a deep neural network for rigid brain regis- tration that is robust to localized change and irrelevant intensity variations common in clinical imaging. Second, we will develop a deformable registration network that differentiates session-specific MRI distortions from disease effects. We will leverage AD-aware registration networks to construct individualized deformable templates across time to enhance the sensitivity of longitudinal morphometry, making it compatible with the clinical workflow. The project will result in deep-learning tools for longitudinal brain registration and template construction that are fast, accurate, and easy to use without machine-learning expertise or high-end computational resources. They will increase the power to detect disease effects with fewer subjects and dramatically reduced runtimes.

NSF

Single cell photosynthetic organisms, the phytoplankton, generate roughly 50% of the oxygen produced each year on the planet and are the base of the marine food web on which life in the ocean depends. Flow cytometry is the most accurate method for counting and identifying phytoplankton populations in the ocean. The DeepCyte submersible flow cytometer represents a significant advancement in flow cytometry instrumentation and is characterized by high sensitivity, low power consumption, compact size, and low maintenance. DeepCyte is designed detect the smallest phytoplankton populations (0.5-10 µm) while suspended underwater from an autonomous buoy platform. This size range encompasses the most abundant phytoplankton populations found in both open ocean and coastal environments from the tropics to the poles. In this project, the DeepCyte instrument and buoy platform will be iterated to a final design by repackaging the instrument components into a smaller volume to facilitate easier deployment of the instrument and buoy package. Automated calibration and alignment routines will be developed to improve measurement quality while deployed autonomously. Finally, previously developed automated flow cytometry data analysis and visualization software will be implemented on the instrument to generate a real-time data feed for broadcast to research vessels and to shore. Fully processed data will be available through public repositories and presented on a publicly accessible data portal. This project also offers educational opportunities: undergraduate students will assist in development and analysis throughout the project. The work included in this project will transition the DeepCyte from a functional lab prototype to a useable and useful marine instrument that will provide an unprecedented view of phytoplankton community dynamics within marine environments. The breakthrough technology that allows DeepCyte to collect stable measurements during a long deployment on autonomous platforms is an immersed primary optic combined with Virtual Core flow cytometry technology that operates without the need for clean fluids. The excitation and collection optics are immersed in an open bath and protrude into a flow of the external sample fluid, sidestepping the usual clogging and maintenance issues associated with the small orifices present in all flow cytometers. The current DeepCyte prototype is robust, compact, and energy-efficient, consuming only 25 watts during full operation. Power is fed to the submersed instrument from a surface buoy that can generate 100 watts of solar power, perform instrument control and analysis through a small PC, and can transmit data back to ship or shore via satellite modem. Instrument development will be divided into two phases. The current DeepCyte prototype will be refined to a final V1 design by first simplifying and then miniaturizing the acquisition electronics, adding fluidic components for injection of an internal bead standard, and then repackaging the instrument into a smaller volume for easier deployments. Software will be developed for auto-alignment of the instrument and a modified version of previously developed real-time data analysis and visualization tools will be integrated. Testing of these instrument enhancements will occur in the University of Washington’s test tank facility and through two three-day research cruises in the Strait of Juan de Fuca. In the final test of the DeepCyte, the instrument and buoy will be operated in a quasi-Lagrangian deployment off the coast of Washington to demonstrate full untethered multi-day deployment of the instrument system. 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.

OD - NIH Office of the Director

Abstract Deep-tissue imaging remains a fundamental challenge in biomedical optics due to light scattering, limiting high- resolution optical imaging to depths of approximately 1 mm, also referred to as the optical diffusion limit due to the use of ballistic or quasi-ballistic photons. Photoacoustic tomography (PAT) uniquely circumvents this limitation by using deep penetrating diffuse light to excite photoacoustic waves, which are then detected ultrasonically, leveraging the low scattering of sound in biological tissues to provide high spatial resolution. This proposal aims to push the imaging depth of PAT from the current limit to 6 cm while providing high spatial resolution. Achieving this ambition requires fundamental improvements across the entire imaging chain, from optical excitation to ultrasonic detection and image reconstruction. We propose the following advancements: (1) optimizing SNR by scanning laser pulses with a higher repetition rate to satisfy both ANSI safety limits and incorporating ultrasonic excitation for accurate acoustic speed-of- sound imaging and de-aberration, (2) enhancing ultrasonic detection by maximizing the detection solid angle and packing density (i.e., fill factor) while providing spatial Nyquist sampling with coded masking, (3) refining joint reconstruction augmented by ultrasonic excitation to de-aberrate acoustic blurring and tailoring motion correction to mitigate motion artifacts over extended acquisition times, and (4) performing in vivo imaging of human breasts to validate the proposed technology using contrast-enhanced MRI as the gold standard owing to its shared ability with PAT to image blood vessels. The team has achieved multiple milestones in PAT, including the first in vivo functional PAT, the first 3D pho- toacoustic microscopy with cellular resolution, and the most widely adopted PAT reconstruction method. These foundational contributions have established PAT as the leading high-resolution optical imaging technique in terms of deep-tissue penetration. Despite its success, further technical breakthroughs are required to address the challenges of providing even greater penetration. This proposal introduces a synergistic approach by optimizing laser delivery, ultrasonic detection, acoustic de- aberration, and advanced reconstruction algorithms to achieve a quantum leap in PAT. The proposed innovations will significantly enhance PAT’s diagnostic potential in biomedicine, particularly in breast cancer detection, where deep-tissue visualization is critical for early detection and treatment monitoring. The impact of this research extends to a broad range of biomedical applications. In summary, by systematically improving PAT from excitation to detection and reconstruction, this work will es- tablish the next-generation PAT, capable of transforming clinical imaging. The proposed research aligns with the long-term goal of developing PAT into a widely accessible, non-invasive imaging tool that provides greater imaging depths with high resolution.

NSF

This project addresses the critical need to approximate complex statistical models in the era of big data. The investigator aims to develop a comprehensive understanding of when simpler approximations can be effectively used, and to provide rigorous guarantees for their accuracy. The core challenge lies in the trade-off between model complexity (which is often necessary to capture the nuances of large datasets) and computational feasibility. While complex models offer rich descriptions, their computational demands can be prohibitive. The investigator proposes to explore whether simpler, approximated models can retain the essential features of their complex counterparts while significantly reducing computation time. Graduate students will be involved in this research. The research will concretely examine the validity of naive mean-field variational inference in several key areas where complex models are prevalent, which include (i) High-Dimensional Bayesian Regression (linear and logistic), (ii) Latent Dirichlet Allocation (LDA), (iii) Mixed Membership Models, and (iv) Exponential Random Graph Models (ERGMs). For each of these examples, the investigator plans to develop tailored inference methods, and provide rigorous, quantified bounds on the errors introduced by these approximations. This will offer a clear understanding of the trade-off between simplicity and accuracy. The overarching goal is to equip researchers using naive mean-field based variational inference with concrete guidelines on when and under what circumstances such methods can be reliably applied, and when they might fall short. This will advance the principled application of approximate inference techniques in the context of big data analytics, contributing to more efficient and reliable scientific discovery. 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.

NCI - National Cancer Institute

ABSTRACT Molecular markers have transformed the diagnosis, prognosis, and treatment of human cancers. However, ac- cess to molecular testing is uneven and often delayed because of the complex laboratory infrastructure required to obtain molecular data from surgical cancer specimens. These and other multifaceted barriers result in <10% of patients receiving molecularly targeted therapies that improve patient survival. Rapid, point-of-care molecular screening would transform the treatment of human cancers by identifying patients at the earliest possible point in their cancer care, ensuring easy access to molecular testing and allowing for immediate delivery of molecu- larly targeted surgical and medical treatment. There exists a critical need for innovative and scalable methods for molecular cancer screening. Stimulated Raman Histology (SRH) is an emerging and innovative optical imag- ing method that produces fast, high-resolution, label-free microscopy images of fresh surgical specimens at the patient’s bedside. We recently demonstrated that SRH combined with artificial intelligence (AI) models can accu- rately detect tumor infiltration and predict the key molecular markers in brain tumors within two minutes of tumor biopsy (Nature Medicine 2023, Nature 2024). However, earlier SRH-AI models are limited in that they require extensive data annotations, lack clinical context, and cannot adapt to other organs or cancer types. Address- ing these limitations through advanced AI methods is an essential step towards developing scalable SRH-based molecular cancer screening methods. Here, we aim to develop DeepSRH, an integrated, point-of-care, SRH- based screening system for rapid and accurate molecular marker prediction using deep neural networks. Driven by our preliminary data and motivated by recent work on vision-language AI models, we hypothesize that large- scale, self-supervised foundation model training on a diverse SRH dataset plus efficient model fine-tuning can produce SRH-AI models for accurate molecular marker prediction. The central objective of this proposal is to vali- date DeepSRH across cancer types (brain, lung, prostate) for AI-based molecular cancer screening and real-time clinical decision support. Firstly (Aim 1), we aim will develop a self-supervised learning strategy, called Slide Pre- trained Transformers (SPT), for DeepSRH foundation model training. Next (Aim 2), we will optimize DeepSRH foundation models for molecular marker prediction through efficient and multimodal fine-tuning methods. Lastly (Aim 3), we will test fine-tuned DeepSRH performance in a multi-center, multi-organ cohort of cancer patients. Using College of Pathology and DECIDE-AI guidelines, our milestone is a balanced diagnostic accuracy of ≥95% with a calculated target sample size of 424 total patients. The expected contribution is an autonomous SRH-based molecular cancer screening workflow. This proposal aims to bridge the gap between rapid optical imaging and real-time molecular screening by strategically addressing multiple challenges using state-of-the-art AI techniques. Translating SRH using advanced AI could revolutionize access to molecular testing in today’s precision medicine landscape. We aim to create a new standard for the accessibility of molecular diagnosis in human cancers.

Interior Department

The natural resource trustee agencies for the Louisiana and Open Ocean Trustee Implementation Groups (the TIGs) have prepared the Draft Joint Restoration Plan and Environmental Assessment #1: Wetlands, Coastal, and Nearshore Habitats, Federally Managed Lands, Fish and Water Column Invertebrates, Submerged Aquatic Vegetation, Sea Turtles, and Birds Restoration of the Chandeleur Islands (Draft RP/EA). The Draft RP/EA analyzes projects to partially restore resources injured in the Deepwater Horizon (DWH) oil spill. The Draft RP/EA evaluates a reasonable range of six action alternatives under the Oil Pollution Act (OPA), including criteria set forth in the OPA natural resource damage assessment (NRDA) regulations, and the National Environmental Policy Act (NEPA). A No Action alternative is also analyzed. The total cost to implement the TIGs' two preferred alternatives is approximately $360,000,000. The TIGs are proposing to allocate approximately $247,000,000 in DWH NRDA funds to implement the preferred alternatives and the State of Louisiana is actively pursuing additional funding sources. The TIGs invite comments on the Draft RP/EA.

DEPT OF DEFENSE.DEPT OF THE ARMY.US ARMY CORPS OF ENGINEERS.ENGINEER DIVISION SOUTH ATLANTIC.ENDIST MOBILE.W074 ENDIST MOBILE

Deer Island Ecosystem Restoration, Phase 1 Deer Island, MS (Harrison County)

NINDS - National Institute of Neurological Disorders and Stroke

ABSTRACT A complete understanding of the underlying mechanisms of pain chronification – how temporary acute pain becomes a permanent problem – remains elusive. Pain chronification mechanisms have been explored in the peripheral nervous system and the spinal cord, but the supraspinal mechanisms of chronification are understudied. fMRI is a powerful tool that can detect subtle changes in brain function, including changes in network-level connectivity while at cognitive rest. The Default Mode Network (DMN) is a network that subserves internally directed cognition, deactivating in response to externally directed attentional needs. The DMN has repeatedly been found to have abnormal within-network connectivity in patients with chronic pain. Interestingly, increased intra-DMN connectivity is associated with pain rumination, a psychological symptom of chronic pain similar to the rumination characteristic of Major Depressive Disorder (MDD), a common comorbidity of chronic pain. Abnormal DMN connectivity has been found in patients with MDD, and in people at high risk of developing MDD, suggesting that abnormalities in this network’s connectivity may precede psychological dysfunction. From this, we believe that abnormal DMN connectivity may also precede chronic pain, beginning before acute pain chronifies. We hypothesize that the change in DMN connectivity may be a supraspinal mechanism of pain chronification. This proposal aims to characterize DMN connectivity in a rat model of peripheral nerve injury, examining the rats longitudinally as neuropathic pain progresses. This proposal extends ongoing clinical work seeking connectivity biomarkers predictive of pain chronification in acute musculoskeletal trauma. Additionally, this proposal will explore a potential mechanism of connectivity change: localized neuroinflammation. Multiple brain regions become inflamed after peripheral neuropathic injury, including the prefrontal cortex, hippocampus, and brainstem. It is, therefore, likely that other nodes of the DMN may also experience localized inflammation. This proposal will characterize cytokine and chemokine expression in multiple DMN nodes after peripheral nerve injury to examine the natural inflammatory processes that may occur. Additionally, this proposal will test if microglial silencing in the DMN using site-specific minocycline administration can reverse changes in DMN connectivity and both evoked and spontaneous pain behaviors. Collectively, these results will provide foundational data on the significance of inflammatory processes in the DMN, and of intra-DMN connectivity more broadly, to the propagation of pain after peripheral nerve injury, justifying future longitudinal clinical studies and providing new targets for the prevention of pain chronification.

NSF

NON-TECHNICAL SUMMARY The electric storage capacity of Li-ion battery technology is limited, leading to issues such as cell phones that cannot retain enough charge for a full day and electric vehicles that cannot travel for more than 300 miles before they need to be plugged in. Graphite, currently used as a lithium reservoir in Li-ion batteries, has limited storage capacity rate capabilities. Lithium is stored inside the atomic structure of graphite, which minimizes the formation of lithium metal filaments, or dendrites, that can cause the battery to short-circuit. However, if charging is done too quickly, there is insufficient time for the lithium ions to be transported into graphite, resulting in lithium accumulation on the surface of the graphite, raising safety concerns. In principle, if lithium and other alkali metals such as sodium could be directly electrodeposited onto the surface of a suitable substrate without the formation of dendrites, both the storage capacity and charging rate could improve significantly. The advantage of sodium is that it is much more earth abundant than lithium, which would significantly reduce costs. By taking advantage of analogies between electrochemical and physical vapor deposition, this research is developing transformative electrodeposition methods to enforce the evolution of atomically flat surfaces that prevent dendrite formation. This knowledge is being used to guide models that inform the design of the next generation of alkali metal batteries. The project involves a range of activities to increase the number of students involved in science and will introduce the next generation of materials scientists and engineers to the varied skills needed to maintain U.S. agility in battery technology. These efforts are contributing to and leveraging investments by the State of Arizona through its New Economy Initiative, which seeks to address local workforce needs and foster growth of industries through establishing the state-funded science and technology center on Advanced Materials, Processes and Energy Devices. TECHNICAL SUMMARY The electrochemical deposition of virtually all metals can result in the evolution of dendrites, where growth occurs at the tip of a protrusion involving tip-splitting phenomenon. Growth of a protrusion can also occur from its base, by an extrusion process at high enough homologous temperature, as a result of compressive stresses that evolve during electrodeposition. This type of growth is called a whisker. The ambient temperature electrodeposition of both Li and Na often results in the development of dendrites and whiskers, which is the major issue in developing practical metal batteries, since this can lead to short circuiting of the batteries. The key issue this project addresses is the identification of electrochemical parameters that result in two-dimensional and atomically flat electrochemical growth of Li and Na without the development of dendrites or whiskers. This project focuses on applying concepts derived from manipulating the kinetics of thin-film growth modes in physical vapor deposition to obtain atomically flat overlayers for film-substrate systems that conventionally result in three-dimensional Volmer-Webber growth. One of the approaches used is called Defect Mediated Growth and involves the use of potential pulsing routines and specific additives in the electrolyte referred to as mediator metals. The other approach, called Surfactant Mediated Growth, involves an additive that floats on the surface of the depositing Li or Na and facilitates an interlayer exchange process promoting the development of flat electrodeposited films. Physical vapor deposition is used to identify the surfactants subsequently used in electrochemical deposition-dissolution cycling of Li and Na to obtain dendrite-free films. Kinetic models of physical vapor deposition verify the role of the surfactants in the experiments and mechanism for formation of atomically flat overlayers. The surfactant-based approach also addresses pitting during the dissolution process and how preferential deposition inside a pit can be achieved without the occurrence of dendrites. 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.

NIAID - National Institute of Allergy and Infectious Diseases

During suppressive antiretroviral therapy (ART), HIV-1 persists in long-lived resting memory CD4+ T cells of children and young adults with perinatal HIV-1 as both intact and defective proviral genomes. The intact, replication-competent proviruses contribute to the latent reservoir and are a lifelong barrier to cure. In perinatal HIV-1, the reservoir is established early and shaped by unique immunologic factors. A growing body of evidence suggests that while defective proviruses cannot contribute to rebound in the absence of ART, these proviruses are transcriptionally and translationally active, potentially leading to adverse immune effects. However, the frequency, composition, and potential immunologic effects of defective proviruses across pediatric age groups remain poorly understood. In this proposal, we aim to characterize the defective proviral reservoir in children and young adults living with perinatal HIV-1 by determining the abundance and sequences of proviruses that are maintained for years despite ART and assessing their ability to produce viral mRNA and proteins. This project leverages well-characterized, bio-banked peripheral blood mononuclear cell (PBMC) and plasma specimens from pediatric HIV-1 cohorts to systematically characterize the landscape of defective proviruses in perinatal infection from infancy through adolescence. Our hypothesis is that in longstanding treated perinatal HIV-1, defective proviruses are transcriptionally and translationally active and drive persistent residual HIV-1 viremia during ART, promoting immune activation and exhaustion despite replication incompetence. Defective proviruses may also serve to produce decoy viral proteins that elicit autologous neutralizing antibodies, thereby reducing the efficacy of autologous neutralization of the latent reservoir. We propose three specific aims. In Aim 1, we will quantify and characterize intact and defective proviruses across pediatric age groups using near full-length single genome sequencing. In Aim 2, we will assess the transcriptional activity of defective proviruses following ex vivo stimulation in co-culture for HIV-1 mRNA analyses and their correlation with immunologic and clinical measures, including markers of immune activation and exhaustion. We will then compare it to sequences from low level plasma viremia to determine whether defectives are the source. In Aim 3, we will perform the quantitative viral outgrowth assay (QVOA) with the ultrasensitive p24 Simoa assay to identify if high- and low-level p24 producing wells are harboring intact or defective proviruses. We will then determine whether env-pseudotyped virus derived from intact or defective proviral sequences can be neutralized with autologous plasma IgG. By integrating molecular virology and immunology profiling in a pediatric context, this study will generate novel insights into the role of defective proviruses in HIV-1 persistence in children. Our findings will inform the design of age-specific cure strategies and contribute to the broader goal of ART-free remission in children with perinatal HIV-1 towards a life free of co-morbidities.

Air Force -- Research Lab

Defense Production Act Title III Expansion of Domestic Production Capability and Capacity

DARPA - Defense Sciences Office

Defense Sciences Office (DSO) Office-wide BAA

Washington Headquarters Services

Defense Security Cooperation University - Research Grants

NINDS - National Institute of Neurological Disorders and Stroke

Project Summary Temporal lobe epilepsy (TLE) is the most common type of epilepsy in adults and is associated with cognitive deficits that can prevent individuals from working and living independently. Yet, because the mechanisms leading to cognitive disability from TLE are still poorly understood, there are currently no effective treatments. In hippocampus, a brain structure critical for memory, pyramidal neurons fire at specific locations in space, creating a cognitive map of the environment. We have recently discovered that TLE model mice have a strong reduction in precision, reliability, and day-to-day stability of spatial representations in the hippocampus. Yet the mechanisms that lead to place cell imprecision and instability in hippocampal CA1 region remain poorly understood. Discovering these mechanisms could help with future discoveries of better treatments of cognitive difficulties in epilepsy. Recent work indicates that behavioral time-scale plasticity (BTSP) is a robust mechanism for single-trial generation of place-specific firing (place fields) after occurrence of single plateau potentials in CA1. BTSP may be the main mechanism for generation and remapping of place field maps. Yet, it is not understood whether BTSP is abnormal in TLE. Furthermore, our group has recently discovered that BTSP also occurs during the performance of non-spatial cognitive tasks, suggesting that dysfunctional BTSP could be a general mechanism driving cognitive dysfunction in TLE. We hypothesize that dysfunctional BTSP likely plays a dual role in the generation of imprecise and unstable place field maps. First, we hypothesize that plateau potentials will be less effective in generating robust place-related firing in TLE, resulting in imprecise place fields. Second, we hypothesize that the paroxysmal depolarizing shifts that are the intracellular correlates of epileptic spikes will aberrantly and repeatedly induce a weakened BTSP, resulting in repeated remapping of imprecise place fields. In Aim 1, using two-photon holographic optogenetics, we will test whether BTSP is more difficult to induce and results in less precise place fields in the pilocarpine model of epilepsy. In Aim 2 we will determine whether interictal spikes can induce a weakened form of BTSP resulting in rapid remapping of imprecise place fields. In Aim 3, we will determine if non-spatial BTSP during performance of a working memory task is also impacted in TLE. These experiments will allow us to focus in on a specific plasticity mechanism that can then be targeted in future experiments to improve cognition in TLE.

NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases

PROJECT SUMMARY Intestinal iron absorption is the major mechanism of iron delivery in mammals. Cellular or systemic iron deficiency can lead to dysregulation of metabolic pathways and anemic disorders. However, excess iron such as in hemochromatosis can lead to tissue injury and cell death. Therefore, systemic and cellular iron levels are tightly regulated. Due to the reactive nature of iron, iron is stored in ferritin, a protein capable of binding up to 4500 iron atoms. In conditions of high iron demand or deficiency, ferritin is degraded, releasing iron for cellular and systemic utilization. Ferritin is a critical protein that controls cellular iron, intestinal iron absorption, and oxidative metabolic pathways. Moreover, ferritin is essential in nutritional immunity, sequestering iron from microbial pathogens that require it for growth. Notably, in germ-free (GF) or antibiotic treated (Abx) mice, we observed a significant decrease of ferritin expression both locally in the intestine and in peripheral tissues. These findings indicate a dynamic regulatory role of host cells in modulating their iron storage pathways in response to commensal bacteria. We demonstrated that ferritin levels were restored in germ-free (GF) or antibiotic treated (Abx) mice upon treatment with microbial metabolites. This data suggests a metabolic exchange between commensals and epithelial cells that drives the ferritin response. Specifically, a synthetic community composed of 11 gram-negative and gram-positive commensals successfully restored intestinal ferritin expression in germ- free mice. Despite assessing several canonical mechanisms of ferritin regulation, including mRNA levels, autophagic degradation of ferritin (ferritinophagy), and hypoxic pathways, no changes were observed. We found altered activity of iron regulatory proteins (IRPs) in germ-free mice compared to wild type. IRPs are RNA binding proteins that regulate ferritin translation. I hypothesize microbial metabolites suppress mRNA binding activity of IRPs leading to an increase in host ferritin expression. However, studying microbial and intestinal epithelial cell interactions in vitro presents challenges due to the anoxic conditions required to grow anaerobes. Our ongoing work aims to elucidate the precise mechanism of microbial regulation of host ferritin levels and identify microbes and metabolites capable of inducing ferritin expression. I will test this hypothesis through two aims. Aim 1 will identify microbe(s) and their metabolites capable of inducing ferritin expression. This will be done using an asymmetric co-culture system that allows us to culture anaerobic bacteria adjacent to primary intestinal epithelial cells in an environment mimicking the intestine. Aim 2 will determine the cellular mechanism of microbial regulation of host ferritin. I will utilize conditional knockout mice for IRPs to determine if ferritin translation is regulated by microbes. Understanding the mechanism of microbial integration into host ferritin regulation is crucial for defining precise mechanisms by which microbiota regulate intestinal iron absorption, iron related disorders and in microbial pathogenesis.

NIAID - National Institute of Allergy and Infectious Diseases

SUMMARY Regulatory T cells (Tregs) actively suppress effector T cells that not only cause autoimmune diseases but also mount anti-tumor immune response. A diverse repertoire of T cell antigen receptors (TCRs) is conferred upon Tregs during their selection and development. We previously demonstrated that Treg repertoire diversity is essential for immune regulatory function. However, Treg repertoire is not static, but rather undergoes dynamic changes, involving continuous new Treg generation, incorporation, and likely turnover of aged Tregs. This raises questions about the nature of Treg repertoire dynamics, sustainability, and immunological roles. Despite the substantial advancements in Treg research, the answers to these questions remain largely speculative due to technical challenges in tracking and controlling specific Treg repertoire without introducing adverse effects. To address this critical knowledge gap, we developed novel mouse genetic tools. Rag1CreER knock-in mice were engineered to perform timestamp tracing of thymic T cells. In the presence of a Rosa reporter, such as RosaLSL-tdTomato (LSL, loxP-Stop-loxP), tamoxifen treatment labeled newly derived thymic T cells, allowing us to investigate the dynamics of thymic Treg generation, egression, and incorporation into the peripheral Treg repertoire in lymphoid and non-lymphoid organs at various stages of life. When integrated with advanced analytical platforms, this will enable us to resolve the developmental heterogeneity of Treg repertoire. We also developed Foxp3LSL mice to seamlessly switch Treg fate in an inducible manner via its master regulator Foxp3. When combined with CreER lines, such as Rag1CreER or available Cd4CreER, these Foxp3LSL mice, upon tamoxifen treatment, would restore normal Foxp3 regulation in precursor cells or Treg cells, depending on the timing of CreER expression. In preliminary experiments, we demonstrated the reliability and feasibility of these methods and unveiled unexpected findings of the activity of Tregs with a finite repertoire. In this study, based on preliminary results, we propose that existing Tregs undergo “exhaustion-like” deterioration over time or upon immune challenges. Consequently, continuous new Treg generation is required to maintain Treg repertoire integrity. To test this hypothesis, we will first rigorously define the exhaustion-like nature of Tregs with a finite repertoire in non-competitive conditions with or without immune challenges. We will then use these innovative genetic tools to determine the causal role of continuous thymic Treg generation. Finally, we will test the hypothesis that excessive stimulation via TCR signaling drives the exhaustion-like activity of Tregs in lineage stability and Foxp3-dependent gene regulation. Overall, we will utilize innovative approaches to define Treg deterioration in the resting state over time or after immune challenges, addressing a long-standing question in the field. Successful completion of our study would lead to a significant conceptual advancement and potential novel strategies to improve Treg-based treatment of cancer and autoimmune diseases.