University Of Texas At Austin

NSF Awards · FY 2024 · 2024-09

The NSF Center for the Creation of Abiotic Replicating Materials and Assemblies (CARMA) is supported by the Centers for Chemical Innovation (CCI) Program of the Division of Chemistry. One hallmark of terrestrial life is that it is both driven by sequence-specific replication and subject to self-sustaining Darwinian evolution. CARMA will demonstrate an entirely new chemistry-based system of molecular building blocks comprised of non-biological components, but still capable of self-replication and evolution. Establishment of these molecular replicating systems will have numerous societal benefits, including materials that can self-heal in a self-sustaining manner, repairing themselves akin to how a body heals wounds or become stronger with stress, as do muscles. Activities within this Center will include a public facing website to transfer all technology developed to the broader community, and week-long annual workshops that diversify graduate experiences. CARMA will integrate high school students into university laboratories, and expand an outreach program that sparks scientific excitement in K-6 age children and their families within the Spanish speaking community (“Supper and Science”). Sequence defined chemical chains or polymers and their hybridization will be demonstrated using a set of four chemical “pairs” that have physicochemical properties which both mimic the Watson:Crick isosteres, while simultaneously being very different. CARMA will build upon previously demonstrated TORC (Tunable, Orthogonal, Reversible, Covalent) bonding pairs which associate via dynamic covalent bonding rather than hydrogen bonding. Four classes of reactions are embodied by the TORC pairs: thiol conjugate additions, boronic acid/diol condensations, metal chelation, and amine/carbonyl condensations. Sequence-specific hybridization and subsequent dissociation of polymers containing TORC pairs will be investigated by balancing between the kinetics of association/dissociation and the valency of individual pairs. Distinct combinations of molecular design properties—including different backbone chemistries (e.g., phospho-ribose, peptide, peptoid, urethane), spacing between the TORC pairs, and the number and identity of specific TORC pairs—will enable dynamic and tunable sequence-specific hybridization. Modeling will play a critical role in judiciously guiding and informing synthetic efforts, including the structural characteristics (rigidity) of short sequence motifs across different backbone chemistries, the type of linkages to append the TORC pairs to the backbones, and optimization of regiochemistry. CARMA will explore how TORC bonds and architecture influence the hybridization and ultimate copolymer replication, thereby unlocking strategies for improving the precision of selection and evolution. This will begin with probing the hybridization of ‘perfect’ complementary oligomers to block copolymer templates, followed by examining the impact of dispersity in duplex assembly. CARMA’s investigations will enable critical understanding of the necessary limits on block size and proper TORC pairs to achieve hybridization selection that will set the stage for multiple cycles of hybridization and replication in the future. 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

How new species are formed is a grand challenge across biology. Particular combinations of genes from different populations may not interact favorably during hybridization, creating unhealthy offspring due to genetic incompatibilities. The specific genes involved in this process are seldom identified, but genes involved in mitochondrial function are prime candidates and the focus of recent research. This project will investigate how different combinations of mitochondrial and nuclear genes create reproductive barriers in hybridizing swordtail fish (Xiphophorus), a model system for genetic incompatibilities. Genomic tools will be used to identify which specific combinations of nuclear and mitochondrial genes influence overall hybrid health. Specific aspects of mitochondrial function such as respiratory efficiency will also be investigated as a mechanistic basis for hybrid incompatibilities. Genetic incompatibilities will also be investigated in different environments and developmental stages because incompatibilities may only manifest in certain conditions. This work includes generating hybrids in the laboratory by targeted crossing experiments and examining natural populations with ongoing hybridization. These activities will be used to recruit students from diverse backgrounds to STEM research, especially in the opportunity-rich field of bioinformatics. Freshmen will be explicitly targeted though the development of a new program called “Power in the Powerhouses” as part of the University of Texas at Austin’s highly successful Freshman Research Initiative to recruit and train the next generation of STEM researchers. Coevolution between nuclear and cytoplasmic genomes can create coadapted genomes within a population that may be disrupted during hybridization, creating reproductive isolation and acting as a common mechanism of speciation. Under this hypothesis, selection during introgressive hybridization should act to maintain coadapted cytonuclear genotypes. To test this hypothesis, genome-wide patterns of ancestry will be generated from three naturally hybridizing pairs and three lab-generated hybrid pairs of swordtail fish species (genus Xiphophorus). Selection should especially favor matched ancestry between mitochondrial genomes and the subset of nuclear-encoded genes that interact with mitochondrial-encoded gene products. Mitonuclear incompatibilities will be identified through statistical associations between nuclear alleles and mitotypes in natural and lab-bred hybrids. Lethal mitonuclear incompatibilities have already been identified using this approach in one pair of hybridizing Xiphophorus. Mitochondrial- and nuclear-interacting genes should also show concordant clines in ancestry with geography. Compromised energetic phenotypes as well as reduced organismal fitness should result from incompatible combinations of mitochondrial and nuclear genes, likely in an environmentally-dependent context. Therefore, in addition to standard metrics of organismal health, whole-organism metabolic rates and mitochondrial DNA copy number will be assessed in parental Xiphophorus species and their hybrids in response to thermal and hypoxic stressors. Multiple respiratory phenotypes in isolated mitochondria will also be investigated, including those dependent on mitonuclear interactions. Phenotypes will be assessed in adults and embryos, as lethal mitonuclear incompatibilities can prevent embryos from developing. 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 · 2024-08

Project Summary/Abstract Ethanol is the most common teratogen and the leading cause of mental retardation. Fetal alcohol exposure can cause numerous birth defects, most commonly effecting the nervous system. Fetal Alcohol Spectrum Disorder describes the full range of potential ethanol-induced birth defects and has been estimated to have a prevalence of 10 in 1000 births. The timing and concentration of fetal alcohol exposure are important determinants of FASD phenotypes. There also appears to be genetic susceptibility to FASD, yet we know little about the nature of these susceptibility loci and the mechanisms by which they modify the teratogenicity of ethanol. The zebrafish embryo is particularly useful to identify and characterize loci that may underlie the neural defects associated with FASD. In Aim 1, we characterize the effect of ROS on ethanol teratogenesis. In Aim 2, we determine how mTORC1 signaling, downstream of ROS, modulates ethanol teratogenesis. In Aim 3, we characterize risk and resilience factors modulating ethanol teratogenicity. Because of the conservation of gene function between zebrafish and humans, the results from our studies will provide key insights into the genetic loci that interact with ethanol to cause FASD.

NIH Research Projects · FY 2024 · 2024-08

PROJECT SUMMARY Family caregivers of people with dementia have to decide between tube feeding and hand feeding when persistent eating problems arise. This decision can be difficult for Chinese-American dementia caregivers, due to the interplay of culture, potential absence of a patient’s advance directive, poor understanding of dementia, and lack of knowledge on the risks and benefits of tube feeding. There is a high prevalence of tube feeding among Chinese older adults with advanced dementia; however, tube feeding does not have health benefits for older adults with advanced dementia, and may in fact be related to increased risk and discomfort. Shared decision-making is a process by which patients, family members, and healthcare providers work together to create care plans that balance clinical evidence and patient preferences and values with risks and expected outcomes. Current clinical discussions on feeding tubes rarely meet this standard. Limited research has been conducted to improve decision quality regarding feeding options among Chinese-American dementia caregivers. This pathway to Independence Award (K99/R00) will give Dr. Pei the training, mentoring, and skills necessary to conduct intervention research to improve decision-making about feeding options for dementia patients in Chinese American communities. The goal of this study is to develop and pilot test a culturally adapted decision aid intervention to support Chinese American dementia caregivers in decision making about feeding options. To become an independent investigator in improving end-of-life decision making, Dr. Pei will receive training and mentoring in four areas: (1) deepening the knowledge of end-of-life decision-making, (2) gaining additional training in qualitative methods research, (3) developing proficiency in clinical trial design and (4) enhancing professional developmental skills in grant writing, research team management, and leadership. In the K99 phase, the candidate proposes two aims. Aim 1: Conduct individual interviews with family caregivers and healthcare professionals to inform the adaptation of an existing intervention; Aim 2: Develop, refine, and acceptability test the culturally adapted decision aid. In the R00 phase, the candidate aims to refine and evaluate the efficacy of the decision aid in a pilot randomized controlled trial among 60 Chinese American dementia caregivers (Aim 3). By the end of the R00 award, Dr. Pei will complete the transition from observational and explanatory research to behavioral intervention work and submit an R01 proposal. Her strong mentoring team, well-established collaboration with community organizations in New York City, and ideal environment of research support and resources at New York University will help Dr. Pei become a successful independent investigator in improving end-of-life decision making for older adults with dementia.

NIH Research Projects · FY 2025 · 2024-08

Project Summary/Abstract: Manganese (Mn) is an essential micronutrient, but in excess, it is neurotoxic. Humans who are over-exposed to Mn environmentally or occupationally develop cognitive and motor deficits. Under conditions of over-exposure, Mn builds up in the basal ganglia of the brain, which primarily contains dopaminergic or GABAergic neurons. However, the exact neural targets and mechanisms of Mn toxicity are poorly understood. A question that remains unanswered is whether Mn targets dopaminergic or GABAergic neurons of the basal ganglia to induce motor disease. In the proposed work, we use the critical Mn efflux transporter protein SLC30A10 as a tool to address this question. Homozygous loss-of-function mutations of SLC30A10 causes childhood dystonia and adult-onset parkinsonism. We previously showed that loss of SLC30A10 in the brain leads to elevated Mn levels in the basal ganglia in early-life, lifelong motor deficits, and impaired evoked dopamine release. Previous studies also revealed that selective loss of SLC30A10 in dopaminergic neurons leads to motor deficits in early-life that persist into adulthood. These findings show that activity of SLC30A10 in dopaminergic neurons is required to protect against Mn toxicity and suggest that Mn targets dopaminergic neurons of the basal ganglia. To definitively identify the neuronal targets and mechanisms of Mn toxicity, we will use dopaminergic- or GABAergic-specific Slc30a10 knockin mice. These mouse models allow us to selectively increase Slc30a10 expression in specific neurons and attenuate increased Mn levels after exposure. In the proposed work, we will use behavioral and neurochemical approaches to test the hypothesis that dopaminergic neurons are the primary target of Mn. Knockin and control mice will receive an oral Mn treatment or vehicle treatment starting from birth, and we will perform behavioral assays at various timepoints from PND28-180. Proposed experiments also include metal analyses and assaying for changes in evoked dopamine and GABA release by in- vivo microdialysis. Results from early-life behavioral assays with the dopaminergic-specific Slc30a10 knockin strain have shown that knockin mice are protected from early-life Mn-induced motor deficits after Mn exposure, compared to control littermates that develop motor deficits. These novel findings corroborate the hypothesis that Mn primarily targets dopaminergic neurons of the basal ganglia to induce motor disease. This proposed study will therefore provide valuable insight into the prevention of Mn-induced disease and inform future studies towards developing treatments.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY In recent years, adenosine has been identified as an important therapeutic target due to its observed immunosuppressive effects in the tumor microenvironment. By agonism to adenosine receptors, adenosine is a broad suppressor of immune function, decreased cytotoxic activity of T cells and NK cells, and increased differentiation of T cells to T regulatory cells. In the tumor microenvironment adenosine are elevated due to the overwhelming release of adenosine triphosphate and nicotinamide adenine dinucleotide, both of which are degraded to adenosine in the extracellular environment during cancer-associated stress conditions. Structurally similar 5’methylthioadenosine, and adenosine’s extracellular degradation product inosine are also observed to stimulate adenosine receptors. Independent of immunomodulatory mechanisms, tumor- expressed adenosine receptors have been observed to contribute to growth, metastasis, and proliferation of cancer cells. This effect is less defined compared to the immunosuppressive activities, but has significance in both solid tumors and post-chemotherapy or radiation models where adenosine and inosine are often greatly elevated due to surrounding dead or dying cells. Individual cancer cell lines commonly delete the gene encoding methylthioadenosine phosphorylase, responsible for depleting 5’methylthioadenosine, and are separately observed to modulate the expression of enzymes responsible for producing or degrading adenosine, or expression of adenosine receptors. The varied and redundant pathways resulting in adenosine receptor stimulation limits the effectiveness of single receptor agonists or enzymatic inhibitors. For this reason, in Aim 1 I will engineer a stable, high affinity human methylthioadenosine phosphorylase which substantially degrades both adenosine and 5’methylthioadenosine. Engineering an enzyme with favorable kinetic parameters, selectivity, and stability will allow for therapeutic characterization. In Aim 2, I will evaluate the in vitro efficacy of the enzyme and immune-independent mechanism with human cancer cell lines. Finally, in Aim 3 I will perform in vivo analysis of therapeutic potential. Following toxicology and pharmacologic studies, I will define the therapeutic effect on a the CT26 colon carcinoma syngeneic murine cancer model. I will use CD4 and CD8 T cell depletion and tumor immunophenotyping to gain insight into the immunomodulatory mechanism, specifically the balance of effector versus regulatory lymphocytes.

NSF Awards · FY 2024 · 2024-08

This partnership development project deepens an existing partnership between the researcher and leadership of an elementary school in central Texas that serves predominantly Black and Latine students. The project focuses on engaging community members, teachers, and learners at the school in conversation about how mathematics teaching and learning might be improved. This partnering is important because the relationship between schools and communities is often marked by one-way communication and decision-making without dialogue. By promoting dialogue, all members of this partnership can learn more about the mathematical storylines embedded into the community—that is, the stories that community members, teachers, and learners share about their personal relationship to mathematics teaching and learning. Approaching mathematics education in this way also provides a space for addressing myths about mathematics such as math is free of culture, history, or specific points of view. In the context of this school and the students it serves, the storylines that are uncovered can be a strong cornerstone for developing mathematical practices that support learning by connecting to students' culture, history and community experiences. Finally, by understanding more deeply the mathematical storylines of community members, teachers, and learners, the researcher and leadership team can co-design a research program about mathematics teaching and learning that is anchored in the school communities' concerns, interests and talents. The question guiding this partnership development project is: In what ways can the research and school leadership teams be in dialogue with the community to enhance the professional development of teachers and experiences of learners in elementary mathematics? To answer this question, the research team will engage in the following activities: 1) Listen to and document the stories of resistance, perseverance, and inequities shared by community members, learners, and teachers regarding mathematics teaching and learning; 2) Analyze and compare mathematical storylines within community dialogues. 3) Develop a collaborative plan of action leading to the development of a research project responsive to the DRK-12 solicitation. The project's findings will add to our understanding of how to (re)create educational spaces that serve, rather than marginalize, communities. Developing a partnership means a deep commitment to the community; consequently, feedback and continued dialogue must be a key component to evaluating the project's success. As such, newsletters, video-updates, member checking, community presentations, and other forms of sharing in the decision-making processes will be used. Across the project, an advisory board of experts in bilingual education, students' learning of mathematics, and community-school partnerships will foster accountability by offering meaningful feedback regarding the extent to which the partnership's processes and objectives are being fulfilled. Lessons learned and reflections can provide a conceptual framework for developing powerful community partnerships through dialogue with school communities and provide district policymakers and school leadership with tools and strategies for creating more bidirectional relationships with community members.

NSF Awards · FY 2024 · 2024-08

It is generally understood that most language learning happens implicitly; that is, that learners acquire language incidentally as a by-product of language use, as opposed to intentional, explicit studying. Although it is also understood that learners must pay attention to grammatical forms to acquire them, there is considerable debate about the role of explicit learning in language acquisition. In particular, research has not yet established to what degree learners need to have conscious awareness of grammatical rules in order to acquire them. This project therefore aims to explore how learners go about learning a new language, focusing specifically on the roles of attention and awareness, and the relationship between these two and how they influence the learning process. It explores how beginner learners of a second language process and learn the word order rule known as subject-verb inversion (e.g., in English, "The dog ran into the house" vs. "Into the house ran the dog") – a structure that remains challenging for beginners despite its emphasis in instruction. The goal is to understand how attention and awareness affect the acquisition of inversion, as this will help us understand the role of these factors in language learning more generally. In doing so, this study will also inform teaching practices, for example, by suggesting methods that would be effective for teaching a variety of languages with computer-assisted learning programs. Moreover, this study provides the opportunity to involve undergraduate students in psycholinguistic research. In order to explore the links between attention and awareness, participants complete a training in which they are taught to comprehend simple sentences in a second language, including sentences with and without inversion. Participants are divided into three groups: one group receives an explanation about inversion; the second group is asked to actively look for patterns in the sentences they read; and the third group is only asked to read the sentences and try to understand them. While the participants complete this training, their eye movements are recorded. These data are used to determine the parts of the sentence that participants pay attention to. After the training, they are asked to complete tasks that assess 1) to what extent they are aware of the grammatical rule, and 2) how well they have learned the rule. It is expected that learners’ processing and acquisition of the rule is directly related to the amount of attention given to it, but not their awareness of it. In other words, for this form to be acquired, learners must perceive the changes in the sentence, and it is not sufficient for them to know the rule. 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 · 2024-08

Modern machine learning models often need to make predictions with an enormous amount of choices. For example, on the internet, search engines need to predict the most relevant candidate for a given query from billions of potential candidates. There are similar prediction problems that are ubiquitous in many search, retrieval and recommendation systems in our daily lives. It is challenging for a machine learning algorithm to deal with a large output space in both the training and inference phases, as any linear scan through all candidates is computationally prohibitive. This project aims to develop a family of scalable and reliable algorithms to tackle the problem of predicting in a large output space. To develop an end-to-end solution, we will tackle the problem of designing novel architectures, and accompanying training and inference procedures that jointly optimize inference speed and prediction accuracy. These efforts will eventually produce a comprehensive toolkit for learning with large output spaces, thus enabling its application in both practical systems and future research activities. The project will also support students and train them in conducting research activities in collaboration with application domains. Existing approaches for dealing with a large output space split the prediction task into two separate components: a neural network encoder and an approximate nearest neighbor search module. The neural network encoder encodes queries and items into a latent space, while the nearest neighbor search module finds the closest vectors in the database for a given query vector. This two-stage approach simplifies the development of each module, but this splitting of components is not focused on end-to-end prediction performance, and thus compromises accuracy and efficiency. The core challenging technical direction of this project is to create algorithms that allow the two components to be aware of each other and thus develop an end-to-end model and training algorithm to handle very large output space. This research direction will be addressed through the development of a novel end-to-end neural network architecture that contains both encoders and trainable search modules. The end-to-end training process will enable direct optimization for precision and efficiency in a single step, instead of requiring two separate steps. 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 · 2024-08

Self-assembly and structural ordering of particles during the slurry drying process are ubiquitous, intricate, and functionally critical. This process significantly influences important applications such as genotyping, biosensing, 3D printing, and the production of thin films for various purposes. Monitoring, understanding, and predicting the multiscale structural dynamics under different drying conditions poses a major challenge in studying particulate and multiphase processes, which involve fundamental phenomena like wetting, evaporation, surface tension, and multiphase flow. This project aims to develop a comprehensive fundamental understanding of the dynamic structural evolution in slurries and to create a predictive machine learning model for guiding the optimization of the drying process. This knowledge and methodology will offer new insights into the dynamics of particle self-assembly, aiding in the design of drying processes to control the microstructure of particulate systems to achieve desired mechanical and electrical properties. The collaboration between University of Texas at Austin and University of Wisconsin-Madison presents unique opportunities for recruiting under-represented students and for engaging with the science-technology-entrepreneurship training programs. This award aims to develop a comprehensive fundamental understanding of the dynamic drying process of a particle-laden slurry. The mechanistic insights will be integrated into a predictive machine learning model to guide the optimization of the drying process for various composite systems. The following research tasks will be conducted. (i) Establishing the correlation between the drying condition and multi-scale structure ordering. (ii) Imaging and predicting the spatiotemporal evolution of the microstructure. (iii) Model-guided optimization of the mechanical and electrical properties of particulate composites. Specifically, 3D in-situ imaging will be applied to model slurry systems consists of thousands of oxide particles with controlled morphology suspended in a liquid solvent with controlled viscosity. A computing module will be developed to identify, recognize, and track all of them in the 4D imaging data (space and time), which will then serve as inputs for the graph-based machine learning effort. Overall, the project will reveal how the system’s non-equilibrium behaviors would affect its final structural ordering and, thus, its mechanical and electrical properties. 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 · 2024-08

Applications such as air purification, carbon capture, molecular sensing, gas separations, and catalysis often use porous materials capable of gas sorption. Temperature is a crucial factor governing the gas adsorption (i.e., gas uptake) and desorption (i.e., gas release) processes, so precise thermal control of the adsorbent material can significantly improve sorption performance. However, most porous adsorbent materials are not good thermal conductors, making it challenging to heat them evenly and quickly to a specific temperature. To address this limitation, this project will incorporate porous gas adsorbing materials inside high thermal conductivity, three-dimensional (3D) micro-structured substrates such as silicon. This arrangement can provide reliable thermal control by leveraging the excellent thermal properties of the substrate and the high surface interaction area with the adsorbent material to facilitate heat distribution. This approach will lead to significant improvements in the design of components and devices that use gaseous adsorbents. Moreover, it will advance the current state-of-the-art technologies for gas sensing, gas storage, and separating complex gaseous mixtures. The project outcomes have the potential to address some of society's biggest challenges today, such as climate change. Integrating this research with educational activities will provide high-quality training opportunities for students and engineering professionals, enabling them to tackle real-world interdisciplinary engineering problems collaboratively. The goal of this research is to develop 3D architectures in which a porous gas adsorbent material is embedded inside a macro-structured substrate of high thermal conductivity. This arrangement is expected to significantly improve thermal control and, thus, control gas sorption performance. The research objectives include developing methodologies for the incorporation and characterization of adsorbent materials inside high-thermal conductivity substrates, which will advance our understanding of the relationships between the adsorbents’ properties and their interfacial interactions with the substrate. The effects of the amount and the distribution of the adsorbent inside the macro-structure and the micron-sized features of the substrate on the thermal behavior and sorption will be determined. Finally, the applicability of the developed 3D architectures will be demonstrated for gas sensing, gas storage, and separations. The educational objectives are aimed at engineering industry professionals and graduate and undergraduate students. Activities will include the development of courses and educational resources on sorption and the design of sorbent devices and their applications. The activities will facilitate faculty and student interactions with industry via an industrial advisory board and training and professional development activities 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 · 2024-08

A classical problem, with many applications in the sciences, engineering and the arts, is to determine the symmetries of an object. The branch of mathematics that studies such questions is called representation theory. In this field, symmetries are studied in part by packaging them together as abstract structures with appropriate algebraic properties, such as groups or Lie algebras. Vertex Operator Algebras (VOAs) are a generalization of Lie algebras. VOAs are tightly connected to theoretical physics in what is known as Conformal Field Theory, and, also, to the geometry of surfaces, like spheres or donut-like objects. An important way to study VOAs and their relationship to geometry is via what is known as Chiral Homology. This can be seen as a recipe that takes a VOA and a surface as ingredients and produces a collection of spaces that encode information about the symmetries of the VOA and the complexity of the surface they depend on. However, a variety of fundamental questions about the spaces produced through this recipe are still unresolved. In this project the PI will answer some of these questions. In particular, the PI will describe how Chiral Homology behaves when the surface it depends on is appropriately deformed, and provide a geometric realization of Chiral Homology. The project will also provide research training opportunities for students. In more technical terms, spaces of conformal blocks associated with projective curves--the algebraic analogue of surfaces--and Lie algebras have been a central object of study in algebraic geometry. In fact, these spaces can be identified with generalized theta functions on the moduli space of principal bundles, and they also define vector bundles on moduli spaces of stable curves. One can consider natural generalizations of these spaces: replacing Lie algebras with VOAs; considering the derived notion of conformal blocks, called Chiral Homology; and allowing the projective curve to admit worse than nodal singularities. The PI and her coauthors have shown that conformal blocks from regular VOAs satisfy factorization and sewing. These properties explicitly control the behavior of conformal blocks under nodal degeneration of the curve they depend on and have been the main tools to explicitly compute the dimensions of these spaces through the Verlinde formula. The In this project, the Pi will show that Chiral Homology from regular VOAs satisfies factorization and sewing. Furthermore, the PI will provide a geometric realization of Chiral Homology and extend this notion to curves with worse singularities. 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 · 2024-08

This Faculty Early Career Development Program (CAREER) award funds research that deals with development of methods used to evaluate the safety and integrity of existing concrete structures. After decades of infrastructure expansion, we find ourselves responsible for an increasing inventory of aging and deteriorating concrete structures nearing the end of their service life and in need of structural assessment. Managing this growing inventory of deteriorating concrete structures poses a significant challenge for the civil engineering community. In this context, this research project will answer the following fundamental question: How can simultaneously occurring deterioration mechanisms, which were not accounted for during the design phase, be effectively considered in the assessment of reinforced concrete structures? The combined effects of corrosion of steel reinforcement, alkali-silica reaction, and freeze-thaw cycles on the integrity of concrete structures will be investigated. These deterioration mechanisms, although extensively studied individually, lack comprehensive understanding when it comes to their interactions, coupling phenomena, and overall impact at the structural level. The research effort is integrated with the education and outreach plan that intends to promote excellence in structural engineering. Furthermore, hands-on activities in undergraduate classes and interactive demonstrations at recruitment events aim to increase student engagement and foster a deeper understanding of structural engineering principles. The overarching goal of this research is to provide a robust framework for the systematic assessment of concrete structures. To achieve this goal, the following specific research objectives were formulated (1) Identify, characterize, and validate at the material level the synergistic effects between the deterioration mechanisms affecting the performance of RC members, (2) Create and validate a numerical method for structural-level characterization that integrates the material-level findings, (3) Develop a holistic structural assessment method and a systematic procedure for model validation and calibration to help ensure accuracy and reliability across different existing modeling approaches. The research objectives will be accomplished through a seamless integration of experimental and analytical phases strategically designed to address all three core research objectives of the project. The approach taken in this project is distinct in two ways: (1) it emphasizes the integration between material-level and structural-level responses, providing insights into overall behavior and enabling informed societal risk and hazard mitigation assessments, and (2) it specifically investigates the structural-level implications of the coupling of deterioration mechanisms. This project will allow the PI to advance knowledge in the field of structural assessment of reinforced concrete structures, and establish her long-term career in developing advanced modeling techniques. 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 · 2024-08

A liveness property states that, under certain assumptions about its input, a system eventually responds with a desired output. Liveness properties are crucial for the correctness of systems. If a system has a liveness error, it may suddenly become unavailable, resulting in loss of critical services or data. It may also be vulnerable to attack by malicious parties that wish to disrupt critical infrastructure. Nonetheless, after decades of research, logically proving the liveness of practical systems remains a challenge that is typically beyond the capability or time constraints of practicing engineers. The goal of this project is to address the fundamental problems that make liveness proofs difficult, create techniques and tools that are accessible to engineers, and allow proof at the scale and complexity of systems encountered in industry. The project's novelty is a new form of liveness proof that is conceptually simple enough to be applied by engineers and provides automated deduction methods that are sufficiently stable and reliable to be applied in industry at scale. The project's impacts are in enabling more rapid design exploration and iteration while preserving design correctness, contributing to industrial competitiveness, and establishing partnerships between academia and industry. The project will provide benefits to industry, defense and consumers by enabling the design of more trustworthy systems, with potential benefits for privacy, security and life safety. Technically, the project will explore a method based on the novel concept of "Relational Rankings". This approach satisfies two key criteria: (1) unlike liveness-to-safety proof approaches based on numerical rankings, it keeps the proof obligations within the range of effectively propositional reasoning (EPR), allowing reliable and scalable automated proof search, and (2) unlike dynamic liveness-to-safety proof approaches based on finite projections, it requires the engineer to reason only about the system state, and not the state of an opaque automated construction. Anticipated advances include: (1) Developing a system for proving liveness by Relational Rankings, based on EPR, and implementing it within the Ivy verification framework, (2) Developing automated techniques to aid liveness proofs, including synthesis of relational rankings and associated invariants and automated diagnosis of proof failures, and (3) Industrial case studies to evaluate the scalability of the approach and its accessibility to engineers, and provide benchmarks for future research. 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 · 2024-08

Project Summary Syphilis is a sexually and vertically transmitted disease caused by Treponema pallidum subspecies pallidum (TPA). While adult syphilis is often asymptomatic and self-resolving, congenital syphilis – fetal infection during pregnancy – can cause birth defects and neonatal death. Since 2017, syphilis has climbed 170% in reproductive age women and 203% among newborns. Syphilis is treatable with penicillin, but timely maternal and newborn diagnosis remains a complex social and scientific problem. Polymerase chain reaction (PCR) can detect TPA in newborns and in adult chancres from initial (primary syphilis) and sores from subsequent flu-like (secondary syphilis) stages. But poverty, abusive relations, and information gap often prevent women from seeking timely care while high cost, long turnaround time and lack of knowledge diminishes clinical uptake. Pregnant patients often present in asymptomatic latent (late) syphilis stage when PCR has low sensitivity in peripheral blood, saliva, and urine. Meanwhile, studies have not looked at specimens, such as vaginal fluids, interfacing the uterine environment, which we hypothesize, are more likely to contain elevated TPA and correlated microbiome biomarkers for development of novel maternal diagnostics. Immunoassays also have poor sensitivity and specificity and require physical exam and treatment data. New molecular tests that make diagnosis easier, faster, more reliable, and accessible are urgently needed to fight the syphilis epidemic and prevent congenital infections. Our goal is to address this need using a triad approach where in Aim 1 we will develop a point-of-care nucleic acid test (POC NAT) and automate it on microfluidic rapid and autonomous analytical devices (microRAAD) with colorimetric readout. Without complex instruments, this POC NAT will allow rapid detection of congenital syphilis in neonatal peripheral blood and would be reconfigurable for adult swab self-testing. By using engineered DNA polymerases for amplification of multiple genes (sensitive) with sequence decoding strand exchange probes that will logically calculate an integrated colorimetric signal (specific) on a lateral flow dipstick (practical), our test should be more sensitive, more specific, faster, and more easily adapted to POC use than anything currently available. To ensure wide reach and uptake of this diagnostic, we will perform early end user assessment of feasibility, acceptability, usability, and implementation preferences (Aim 3). Finally, to enable new maternal syphilis diagnostics, we will evaluate TPA detectability and microbiome perturbation in maternal vaginal self- swabs (Aim 2). Our Aims are highly achievable because we have a history of collaboration, in-depth expertise, validated assay and device technologies, and public health nexus with sexual healthcare. The resulting data would facilitate future clinical validation and translation into practice via Early Translational Research Awards and industry partnerships for manufacturing. Taken together, by making syphilis diagnosis easier, more accurate, and accessible, this research will make a significant impact on congenital syphilis prevention. Moreover, this robust approach to fast and accurate pathogen detection can be readily diversified to a wider array of pathogens.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY/ ABSTRACT Auditory deprivation during childhood has serious consequences on all aspects of development. Otitis media (OM) is a highly prevalent condition in young children. It is principally important to examine the relationship between OM, hearing loss, and listening development to understand the functional sequelae of OM. Currently, it is difficult to ascertain the link between early childhood OM and developmental alterations in perception and listening because the available evidence is limited and is based on cross-sectional studies. The overarching goal of this project is to understand the residual effects of early childhood OM on functional listening development. In Aim 1, we will examine the effects of OM on the development of spatial listening skills after the OM is resolved. We will also examine the effect of resolved OM on the development of energetic and informational masking. In Aim 2, we will measure the sensitivity to frequency modulation and temporal gap detection to track the residual developmental effects of OM on basic auditory perceptual skills. In Aim 3, we will profile listening and communication abilities, and model listening development to define its trajectory following resolved OM in relationship to several predictors (e.g., OM history, hearing, cognition, etc.) using machine learning. In our approach, we will follow young children individually, with responses recorded longitudinally on experimental measures, and routinely document the middle ear status. The proposed work combines laboratory-based and real-world measures and carefully considers auditory, cognitive, language/literacy, and other factors for measuring functional listening skills comprehensively. Since listening is critical for language and learning in the classroom, the outcomes of this proposal are essential to understand the residual effects of OM on childhood development. This will improve our scientific and clinical knowledge about the developmental effects of OM, influencing the fields of audiology, pediatrics, speech-language pathology, otolaryngology, neuroscience, and early intervention.

NIH Research Projects · FY 2025 · 2024-08

ABSTRACT Melanoma is the fifth most common cancer in the US with almost 100,000 cases estimated for 2023. Late-stage disease has a five-year survival of just 30%, resulting in almost 8,000 deaths in the US alone. When detected early, melanoma has a survival rate of 99%; however, a widely adopted screening tool for melanoma currently does not exist. The current standard of care in skin cancer detection relies on a clinical visual assessment of moles, followed by an invasive biopsy of suspicious lesions. The low accuracy of this approach (84% sensitivity and 3-16% specificity) leads to missed melanomas and high rates of “unnecessary biopsies”, biopsies of benign moles. An average of 25 biopsies are required for each melanoma found, resulting in 3 million biopsies of benign moles each year. For this reason, the US Preventative Services Task Force does not recommend routine visual screening for skin cancer in adults, citing the potential harm of the high rate of unnecessary biopsies. Non-invasive genetic or spectroscopic tests that are currently available have either sensitivities that are too low (below 98%) or specificities that are too low (below visual assessment). We hypothesize that limited applicability of these approaches stems from the limited availability of melanoma biomarkers. Studies have shown that a combination genetic markers and histological analysis offer an excellent combination for specific and sensitive diagnosis; however, no minimally-invasive technology exists to provide samples for this purpose. We propose a “laser microbiopsy” as a technique to harvest microliter-sized tissues, using a ring-shaped infrared laser such that the center of the annulus can be removed with minimal damage by a pulse of light. Because laser tissue removal is essentially instantaneous (within microseconds) and the biopsy size is on the scale of hundreds of micrometers, the procedure is potentially much less harmful than traditional punch biopsies. Importantly, our preliminary work shows that the laser microbiopsy penetrates through the epidermis and to the melanocytes, where melanoma originates. To further develop this approach, we will refine and characterize the performance of the laser microbiopsy hardware (Aim 1) and validate viability of extracted micro-biopsies for molecular analysis (Aim 2). We envision our approach providing pain-free tissue for offline pathology and molecular analysis of melanoma as well as a possible surgical guidance tool for real-time assessment of tumor margins. In addition, harvested tissues could be used for primary tissue cultures or flow cytometry. Once this proof-of-principle (R61) project is complete, we anticipate transitioning the laser microbiopsy from a developmental phase to test feasibility for melanoma diagnosis in an R33 application.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY Spina bifida (SB) is a viable type of neural tube defect (NTD), the second most prevalent birth defect in humans. The genetic and environmental factors combinatorically contribute to the etiology of SB. Neuromesodermal progenitors (NMPs) are the precursors of spinal neural tubes (SNT), yet how genetic modification and teratogen affect NMP-mediated SNT formation is largely unknown. Model organisms have been widely used to study the effects of genetic and environmental factors on SB. Still, they have limitations in fully recapitulating human NTDs due to their different genetic backgrounds and subsequent drug sensitivity. Significant progress on in vitro 3D SNT organoids has been made, yet they did not fully recapitulate the in vivo spatiotemporal microenvironment to study the gene-environment interaction. Here, we will investigate the complex interplay between the genetic predisposition and teratogen in NMP-mediated human SNT formation using human induced pluripotent stem cells (hiPSCs) that recreate three-dimensional (3D) SNT organoids to fill the current scientific gaps. We will further develop a bioengineered Spinal Neural Tube-on-a-chip (SNT Chip) model to recapitulate the spatiotemporal microenvironment by controlling microfluidic modules to fulfill the technical gaps. Our preliminary study supported that GPR161 has a strong genetic association with human and mouse SB and NMPs are involved in GPR161-mediated SNT formation in mice. We will utilize GPR161 KO iPSCs-induced 3D SNT organoids as a human-relevant SB model to investigate how GPR161 genetic modification and its interaction with teratogens (Vismodegib and Valproic acid) affect NMP-mediated human SNT formation in both the static 3D human SNT organoids and an SNT-Chip. This will verify how the spatiotemporal modulations with biomechanical cues regulate the human SNT formation and the subsequent cellular and molecular profiles of human SNTs compared to the static 3D organoid cultures. We anticipate enhancing the scientific knowledge of gene- environmental interactions on human SNT formation and advancing the in vitro modeling of a human SNT system with in vivo-relevant microenvironmental milieu.

NSF Awards · FY 2024 · 2024-08

An award is made to the University of Texas at Austin (UT Austin) to explore the emerging field of glycosylated RNAs (glycoRNAs) by developing novel tools to sequence, visualize, and analyze these unique molecules in various organisms, including humans, plants, yeast, and bacteria. GlycoRNAs represent a new class of biomolecules that combine the properties of RNA and glycans, potentially playing critical roles in diverse biological processes such as gene regulation, cellular communication, and immune responses. The significance of this project lies in its potential to uncover fundamental biological mechanisms and advance our understanding of RNA biology and glycobiology. By developing innovative methods and establishing a comprehensive open-access database, this research aims to provide invaluable resources that will accelerate scientific discovery in this emerging field and foster interdisciplinary collaboration among scientists. Importantly, the project will create new opportunities to integrate research with the education of the next generation of scientists. This work enhances the scientific community's ability to study glycoRNAs, ultimately benefiting society at large through advancements in biotechnology, medicine, and education. The project aims to develop advanced methods for the enrichment, sequencing, and spatial imaging of glycoRNAs across various species, addressing key technological challenges. Aim 1 involves creating an unbiased enrichment method for glycoRNAs using glycan-specific ligands and Thermostable Group II Intron Reverse Transcriptase RNA sequencing (TGIRT-seq). This method will accurately identify glycoRNA sequences, leveraging TGIRT-seq's capability to handle highly structured RNAs and pinpoint glycosylation sites at nucleotide resolution. Phenylboronic acid-based affinity ligands will be developed to enrich glycoRNAs from native RNA samples without biases from metabolic labeling. Enriched glycoRNAs will be sequenced using next-generation sequencing (NGS), creating libraries with minimal bias and high efficiency. Deep learning will predict glycosylation sites, with sequences and the analysis pipeline shared through an open-access database. Aim 2 focuses on advanced spatial imaging techniques to visualize glycoRNAs at single-cell and tissue levels. DNA aptamer-based probes for glycan binding, RNA in situ hybridization, and proximity ligation will be integrated to enable multiplex imaging of multiple glycoRNAs simultaneously. Computational image segmentation methods will infer cellular origins of glycoRNAs from tissue images, with spatial distribution data incorporated into the open-access database. Aim 3 will demonstrate the developed methods' applicability in diverse model organisms, including plants, yeast, and bacteria, establishing glycoRNA profiles and visualizing glycoRNAs. Cross-species comparative analyses will investigate conserved glycoRNA motifs and families, integrating sequencing and imaging data into the open-access database, facilitating comparative studies and expanding its utility. 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 · 2024-08

Project Summary Children who grow up in low-income homes are at risk for worse physical and cognitive health for their entire lives, a phenomenon known as the “long arm of childhood”. But, understanding and intervening on this process is enormously difficult, as the effects of childhood environments can take decades to become visible in adult morbidity and mortality. What researchers need is a “wormhole”, i.e., a passage through time that connects childhood and adulthood. In the proposed research, we will examine the utility of DNA-methylation (DNAm) as a “molecular wormhole” for investigating how material and social conditions of childhood are linked with physical and cognitive health across the lifespan. We have exciting preliminary research that supports our key hypothesis that methylation profile scores (MPSs) can allow researchers to “see” – in real time – the impact of children’s social environments on their lifelong risk for poor cognitive and physical health. However, there remain yawning gaps in knowledge about the utility (and limitations) of MPSs for studying the life course. First, MPSs have yet to be integrated into experimental, longitudinal designs capable of testing causal hypotheses about the impact of childhood environments on development. Building on the Baby’s First Years Study (BFY; est. N=850), we will, for the first time, integrate MPSs into a randomized controlled trial testing whether unconditional cash transfers to low-income mothers for the first ~6 years of the child’s life cause changes in the child’s methylome in early childhood. Next, we will examine whether MPSs show potential for change early in the life course and whether this change is associated with longitudinal development of cognitive and physical health across childhood in the BFY (ages 4 and 6), Texas Twin Project (TTP, N=1404, ages 8-20), and Future of Families and Child Well-Being Study (FFCWS, N = 2,020, ages 9 and 15). Second, previous studies testing DNAm as a molecular wormhole have only traveled one way, by applying MPSs developed in studies of adult health in child samples. We will travel forward through the wormhole, by developing MPSs that index the socioeconomic conditions of childhood (comparing children in BFY low vs. high-cash groups, and in low vs. high SES families in TTP and FFCWS), and testing their associations with longitudinal development of cognitive and physical health in early childhood to adolescence and in older adulthood (Health and Retirement Study, N = 4,018). Finally, in order to derive candidate biological mechanisms of action, research must augment summary MPS measures with informatic approaches that identify biological pathways. We will delineate overlapping and diverging biological pathways implicated in genomic markers identified in analyses of socioeconomic contexts and cash gifts in childhood and markers identified in published adult studies of health. This application is poised to make rapid scientific progress as all measures, including biological specimens, are either already available or already being collected as part of separately funded projects.

NSF Awards · FY 2024 · 2024-08

This grant supports student participation at the Thirty-Fifth Annual International Solid Freeform Fabrication (SFF) Symposium, scheduled for 11-14 August 2024, in Austin, Texas. The SFF Symposium serves as a venue for the exchange of knowledge in the realms of additive, freeform, and hybrid manufacturing. Last year, the event drew participants from over 100 universities, with 70% representing domestic institutions. Notably, student attendees constituted approximately 45% of the 700+ total participants. The 2024 symposium will emphasize new developments in eco-friendly manufacturing processes and the integration of artificial intelligence in additive manufacturing. Additionally, a special session on biomedical applications of additive manufacturing will be featured to enhance interdisciplinary research and collaborations within the field. This year's symposium also features the introduction of a mentoring program, designed to match each student with a mentor from industry, national labs, or academia based on their career goals and interests. This initiative aims to provide personalized guidance and enhance career development opportunities for participants. To foster accessibility and encourage diverse student attendance, the travel award will help cover conference registration fees, accommodations, and travel expenses for qualified students. This initiative aims to lower barriers to entry and ensure a broad representation of ideas. Outreach for student support applications will include: (1) direct emails to authors of accepted abstracts, (2) targeted communications to past SFF attendees, (3) announcements on the SFF website, and (4) social media campaigns on platforms like LinkedIn. The selection process, conducted by the conference committee, will prioritize students from U.S. institutions who are actively contributing to the conference through presentations, posters, or participation in competitions. Special consideration is given to students attending for the first time, as part of a commitment to broadening participation and engaging new members of the community. Student awardees will also benefit from exclusive networking opportunities, including a luncheon panel that discusses current research trends and potential career paths in additive manufacturing. This award aims to equip emerging leaders with a comprehensive global outlook, exposure to innovative ideas, and insight into future industry challenges. 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 · 2024-08

PROJECT SUMMARY/ABSTRACT Spatial neuroscience has uncovered a great deal about how animals—primarily rodents—form allocentric (world-centered) spatial maps of the world. Rodents explore by moving their bodies through the world. In contrast, primates explore the world visually, and recent work suggests this could dramatically impact their formation of allocentric maps. The current project investigates the brain systems that allow humans to form allocentric maps of 3D spaces from afar, without physically visiting the locations being represented. This work will use fMRI to detect map-like representations of viewed locations in a 3-dimensional “scene space” and to compare these to map-like representations of visited locations in a virtual “navigable space”. This work is divided into 2 aims, the first optimized for experimental power and the second optimized for ecological validity. Aim 1 is to identify map-like representations of scene space and understand their relationship to cognitive maps of navigable space. Representational similarity analysis (RSA) will be used to quantify map-like allocentric representations of locations in scene space. Experiment 1a will identify brain regions that support viewpoint-independent (allocentric) maps of viewed locations in scene space. Experiment 1b will use an analogous procedure to identify brain regions that support viewpoint-independent maps of navigable space and relate them to viewpoint-independent maps of scene space. Aim 2 is to identify representations of scene space and navigable space using dynamic, ecologically relevant tasks. This aim will leverage voxelwise encoding models to detect map-like neural representations of viewed and visited locations while participants actively explore their environments. Experiment 2a will look for maps of scene-space by scanning participants while they view the virtual courtyard from different viewpoints and actively searching for a hidden target item. Experiment 2b will look for maps of navigable space by scanning participants while they freely navigate through the virtual environment searching for hidden rewards. This research will take place in the ideal training environment for the applicant. The sponsorship team's expertise in the field of spatial navigation, advanced fMRI analysis and designs, and the computational modeling of freely- navigating participants data are critical to the applicant's training goals. Further training is available through coursework in machine learning and data science, computing resources, and a diverse set of relevant lab meetings and seminars. This work addresses a critical gap in the literature between the fields of vision science and spatial neuroscience. Understanding the role of the visual system in forming spatial maps in sighted individuals could inform interventions aimed at mitigating navigational and other challenges faced by those with low vision or other differences in sensory processing.

NIH Research Projects · FY 2024 · 2024-08

Project Summary Cystinuria is a rare disease characterized by chronic, recurrent lithiasis (stone formation) in the urinary tract due to accumulation of high concentrations of cystine in the urine. This accumulation results from impaired reabsorption of the amino acid cysteine and its poorly-soluble, oxidized form, cystine, from the kidney back into systemic circulation. Current therapeutic strategies involve lowering the effective cystine concentration or increasing its solubility in the urine, but patient compliance is low due to treatment burden and unfavorable side effect profiles. Chronic kidney disease is common and surgical intervention is a necessary and recurrent event in the lives of these patients. For these reasons, the disease burden due to cystinuria represents an unmet clinical need. In short, both the disease and its narrow range of treatment options exact a heavy toll on cystinuria patients, resulting in greatly diminished quality-of-life. Therefore, there is an urgent need to provide safe, effective therapies that not only prevent or slow the growth of cystine kidney stones, but also carry a low treatment burden and thus promote adherence to therapy. Human enzyme therapy represents an attractive, tractable means of combatting metabolic disorders that manifest as metabolite imbalances in the systemic circulation or in tissue compartments that are addressable through manipulation of the systemic circulation. In principle, cystinuria fits this treatment modality, as cysteine and cystine (cyst(e)ine) derived from the blood are filtered into the urine where they concentrate due to defective reabsorption mechanisms, leading to lithiasis. Lowering circulating levels of cyst(e)ine to concentrations that will normalize urine metabolite levels but not affect cyst(e)ine homeostasis should prevent or reduce the rate of stone formation, even in the context of impaired reabsorption of these amino acids. Therapeutic enzyme- mediated normalization of amino acid levels has been clinically validated for other diseases. This project seeks to determine if a human enzyme therapeutic that degrades cyst(e)ine can prevent or slow lithiasis and mitigate associated kidney pathology in the Slc3a1 knockout mouse model, a translationally-relevant model of human cystinuria. Changes in stone volume and multiplicity will be assessed by computed tomography and values will be compared to controls and baseline values as appropriate. Importantly, the long-term safety of this approach will also be evaluated by chronically dosing human cyst(e)inase in mice and undertaking a rigorous health assessment of treated animals, including body weight and behavioral measurements, blood- based measures of physiological function, and metabolomics.

NIH Research Projects · FY 2025 · 2024-08

Project Summary Individuals with lower limb amputations are at higher risk of falling compared to able-bodied and other clinical populations and are more likely to sustain life-altering injuries. The higher fall risk is primarily due to the loss of the muscles crossing the ankle, which are critical to maintaining balance control. Prosthetic devices are designed to provide appropriate stiffness for needed stability and support. While research has shown the optimal stiffness to maintain balance varies across ambulatory activities (e.g., straight walking versus turning), most clinically prescribed prosthetic devices are passive and only provide a fixed stiffness level. The one commercially available, powered prosthetic ankle-foot has not been shown to restore balance control. Thus, a prosthetic device that actively adjusts ankle stiffness across different ambulatory activities is critically needed to advance the field and improve balance control for those with lower-limb amputations. The goal of this project is to determine if automatic stiffness modulation can improve the balance control of individuals with lower limb amputation as they perform typical ambulatory activities of daily living. By matching the ankle stiffness to the task requirements, we believe we will significantly improve balance control and decrease fall risk for those with lower-limb amputations. In the proposed work, we will utilize an open source, lightweight, state-of-the-art hardware system (Open-Source Ankle) that includes novel hardware, actuation, sensing, computation, and control software and pursue three specific aims. In Aim 1, we will perform a human subject experiment to determine the influence of prosthetic ankle stiffness on balance control during a wide range of ambulatory activities that will provide the basis for our activity detection and stiffness modulation algorithms. In Aim 2, we will implement our activity detection and phase-varying stiffness modulation algorithms into the Open-Source Ankle. We will use machine learning techniques to predict different ambulatory activities and validate the ability of the Open-Source Ankle, fit with a commonly prescribed low-profile prosthetic foot, to modulate the stiffness profile throughout the stance phase of the different ambulatory activities. The outcome of this aim will be a semi-active prosthetic ankle-foot system with activity-dependent, phase-varying, and user-specific mechanical stiffness profiles. In Aim 3, we will perform a second human subject experiment to determine if automatic stiffness modulation improves balance control in real-world environments. The outcomes of this research will provide insight into the relationships between stiffness and balance and if a semi-active prosthetic system with automatic activity-dependent, phase-varying, and user-specific stiffness modulation improves balance control for those with below-knee amputations. This addresses a critical need in service member, veteran, and civilian populations with lower-limb amputations to reduce their fall risk and injury incidence, which will ultimately improve their functional mobility, overall health, and quality of life.

NSF Awards · FY 2024 · 2024-08

Metastasis is a complex series of cell migration events that involve multiple interactions with other cells, tissues, and blood and lymphatic vessels - causing the mechanisms to be unclear and treatments to be ineffective. Elucidating this complex cascade is impossible with current cell culture-based systems and cost prohibitive with animal models. Multi-tissue on-a-chip platforms (MTCPs) that possess integrated blood and lymphatics within a primary tissue (e.g. breast) and a secondary site (e.g. skin) while also replicating the biomechanical properties of these tissues would have tremendous value for uncovering cell migratory patterns of cancer metastasis, and ultimately impact drug development, personalized medicine, disease etiology, and toxicology. This project’s objective is to create a MTCP Breast-Skin platform with blood and lymphatic vasculature integrated within each tissue and connected seamlessly across tissues. The Breast-Skin platform will be utilized to determine the role of tissue properties, immune cells, and vessel flow dynamics in tumor cell metastasis. This work is a high-risk, high-reward endeavor, providing an invaluable tool for dissecting the metastatic process which will generate functional signaling and therapeutic targets for treatment of a wide array of aggressive and metastatic diseases. The project will enable the PI to provide unique tiered teaching and mentoring opportunities in which graduate and undergraduate students will expand their understanding of microfluidics fabrication and serve as role models for elementary school students through a newly created tissue instructional module for an existing outreach program at The University of Texas at Austin Longhorn Engineering Summer Camp. Metastatic cancer spread is a highly complex series of events involving multiple tissues, organs, and cellular interactions. Several clinical phenomena have been correlated with metastasis and poor patient outcomes, but their underlying mechanisms remain difficult to determine. Three such phenomena are of interest because of their significant clinical presentations in breast cancer: 1) lymphovascular space invasion (LVSI) – tumor clusters (emboli) within blood and lymphatic vasculature in the primary tumor, 2) dermal lymphatic invasion (DLI) – tumor emboli within the lymphatic vessels of the nearby skin tissue, and 3) skin metastasis. Existing in vitro systems lack the multi-tissue and lymphovascular complexity needed to model these events. In vivo models, while available, are not amenable to mechanistic studies or pharmacological screening because of the sheer number of animals required for such experiments. Therefore, there is a critical need for experimental models that can faithfully capture relevant metastatic phenomena. This need will be addressed by developing a multi-tissue on-a-chip Breast-Skin platform with functional blood and lymphatic vessels that are seamlessly connected to study the spatial and temporal process of LVSI, DLI, and skin metastasis. The central hypothesis is that the cross-talk between the extracellular matrix (ECM), macrophages, and vessel microenvironment provides synergistic cues to drive LVSI and DLI. This hypothesis will be tested in the Breast-Skin platform with the following project objectives: 1) Develop and validate the first Breast-Skin in vitro platform for modeling LVSI and DLI in breast cancer, 2) Determine the role of ECM features and macrophages in LVSI and DLI formation, and 3) Define the contribution of vessel fluid dynamics to LVSI and DLI formation. The project represents a significant breakthrough in the development of a unique Breast-Skin platform to study the spatial and temporal process of LVSI, DLI, and skin metastasis for the first time in a high-throughput and controllable manner. 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.