University Of Missouri Kansas City

NSF Awards · FY 2026 · 2026-10

Artificial Intelligence (AI) technologies are transforming daily life, but their rapid adoption has also introduced serious security and privacy challenges. Addressing these risks requires a workforce that can both advance AI innovation and safeguard its deployment. This project will help meet that need by strengthening undergraduate computing education through a curriculum-based research experience program that connects classroom learning with real world research experiences. The effort will integrate the latest AI security and privacy topics into existing computing courses while helping students build professional skills such as communication, teamwork, and leadership. By creating flexible learning modules that can be used across a range of undergraduate computing courses and institutions, the project will support workforce development and contribute to the secure, reliable, and responsible use of AI in society. The project will establish a curriculum-based undergraduate research experience program focused on AI security and privacy across partner institutions. The research team will design, implement, and evaluate flexible educational modules including labs, tutorials, assignments, and research activities in computer vision, speech and audio, and network systems. These modules will address vulnerabilities across the AI lifecycle and will be designed for seamless integration into undergraduate computing courses. The instructional materials will also be aligned with the NICE (National Initiative for Cybersecurity Education) Cybersecurity Workforce Framework to strengthen career-relevant competencies. In parallel, the research team will study educational approaches that embed research into coursework, including project-based and competition-based learning, and evaluate their effects on student engagement, success, technical growth, and professional skill development. The project will generate transferable resources and evidence-based practices that can be adopted more broadly in computing education and shared with academic and community audiences. 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 2026 · 2026-05

It is important to have a complete history of the type and number of eruptions at a volcano to prepare for potential future volcanic eruptions. Askja volcano is a popular tourist destination in Iceland that has produced small lava flows and large explosive eruptions. No one has studied Askja’s pre-historic explosive eruptions in detail. The likelihood and timing of future explosive eruptions at Askja is not well known. This study will use field work to confirm the order of eruptions at Askja. Rock and mineral chemistry will be used to look for connections between different rock types and the magmas from which they crystallized. Analyses will also help date older eruptive materials and identify how magma is stored beneath the volcano before eruption. A complete history of Askja’s eruptions will reveal patterns to identify future eruption scenarios. Askja sits next to two other recently active volcanoes covered by glacial ice. Results from Askja will lead to a better understanding of harder to reach volcanoes in Iceland and volcanoes in the US. This study will increase awareness of the hazards of active volcanoes and the risk to neighboring populations. Askja volcano in Iceland has produced multiple explosive rhyolitic eruptions and numerous basaltic fissure eruptions over the last 70 ka and has been experiencing uplift since 2021. The recent ca. 65 cm uplift (2021-ongoing) in Askja caldera makes it imperative to understand the past eruptive activity and magma storage conditions to prepare for a potential future eruption. The unstudied, high-silica eruption deposits and gabbro xenoliths provide the opportunity to investigate not only the eruptive frequency, but also the patterns and location of magma storage under Askja. This study aims to address questions: 1) at what depth do silicic and mafic magmas accumulate under Askja, and how common is magma recharge? 2) What are the most common eruption scenarios at Askja based on the last 70,000 years? and 3) How can Vatnajokull National Park better communicate with visitors at Askja about hazards? These questions will be addressed through field work; whole rock characterization; plagioclase, clinopyroxene and zircon mineral analyses; 40Ar/39Ar and U-Th geochronology, and visitor surveys in partnership with the Vatnajokull National Park. The breadth of approaches in this study aims to target key gaps from multiple directions to increase understanding of the Askja volcanic system, its hazards, and the populations at risk. 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 · 2026-04

Project Summary In mammalian cells, RNAs are predominantly located within cytoplasm and nucleus. A recent study, however, has reported that RNAs can be glycosylated, and such glycosylated RNAs (called glycoRNAs) are localized on out cell surface. The glycoRNAs are glycan-modified small non-coding RNAs. These RNAs are transcribed and maturated in nucleus and transported to cytoplasm for processing and then conjugated with glycan chains in endoplasmic reticulum. The conjugated molecules are then transported to cell membrane and anchored on cell membrane by binding to transmembrane RNA binding proteins. The cell surface glycoRNAs can serve as ligands or receptors to mediate cell-cell interaction, communication and infiltration and may also trigger cell signal transductions. Our recent works suggest that there were two forms of glycoRNAs, named glycoRNA-L and glycoRNA-S, robustly expressed in leukocytes, but not non-immune cells. GlycoRNA-L was migrated with ~11 kb RNA, whereas glycoRNA-S was migrated with ~0.6 kb RNAs. Using RNase removed the RNA frag- ments, the migration of both glycoRNA-L and glycoRNA-S was slightly faster, suggesting that the migration of glycoRNA-L and glycoRNA-S was determined by the glycan chains, but not RNA fragments. Further studies suggest that the glycan structures and functions of glycoRNA-L and glycoRNA-S may be distinguished. How- ever, the compositions and structures of glycan forms of glycoRNA-L and glycoRNA-S remain unknown. We hypothesize that the glycoforms of glycoRNA-L and glycoRNA-S from leukocytes are determinants of their functional significance. The goal of this proposal is to decode the compositions and structures of glycan forms of glycoRNA-L and glycoRNA-S from leukocytes. We will reach this goal by two approaches: 1) metabolic labeling combined with enzymatic digestion; 2) glycoRNA-L and glycoRNA-S purification and LC/MS analysis. Completion of the project will significantly advance our understanding of the role and mechanisms of glycoRNA- L and glycoRNA-S in the regulation of immune response and immune-related human diseases. The study will also provide a method for mapping the glycan structures of glycoRNAs from other cells such as cancer cells, which may provide insights for generating innovative diagnostic and therapeutic strategies.

NIH Research Projects · FY 2026 · 2026-03

PROJECT SUMMARY/ABSTRACT Diabetes is one of the most pressing public health challenges in the U.S., with over 98 million adults – more than one in three – already living with pre-diabetes mellitus (pre-DM), placing them at heightened risk for type 2 diabetes and its severe complications. African Americans (AA) face a disproportionate burden, with DM rates nearly twice that of Whites (13% vs. 7.5%), obesity prevalence exceeding 60% and lower rates of fruit/vegetable intake and physical activity (PA). A critical component of national efforts to curb the diabetes epidemic is the Diabetes Prevention Program (DPP), a lifestyle intervention proven to reduce or delay DM onset by 58 to 71% through structured diet changes, increased exercise, and modest weight loss (5-7%) in a rigorously evaluated national trial. Despite the proven efficacy of the DPP, AA experience only half the weight loss of White participants – highlighting a critical gap in effectiveness that must be addressed. Our enhanced DPP model builds upon our promising pilot studies by integrating culturally tailored healthy food delivery, on- site physical activity, and linkages to existing food and PA community resources to extend support beyond class and the duration of this study. These enhancements are designed to overcome social determinants that impede clinically meaningful weight loss among underserved AA populations. To assess the impact of this enhanced model, we propose a cluster randomized controlled trial of 408 pre-DM AA participants recruited from churches in communities with the highest risks of DM. Participants will be assigned to either a standard, culturally tailored DPP (S-DPP) – which incorporates tailoring of language, culturally relevant foods, religiosity, and community norms and values – or a culturally tailored, enhanced DPP (E-DPP), which further addresses systematic barriers to food access, healthy eating, and physical activity over 12 months. We will: 1) examine the effects of E-DDP on percent weight loss (primary outcome) and secondary outcomes (food and nutrition insecurity, healthy eating, physical activity, DPP attendance, hbA1c, and blood pressure) at 6 and 12 months, 2) identify key mediators/moderators related to weight loss among AA participants at 6 and 12 months to determine modifiable facilitators and barriers, and 3) conduct a process evaluation to examine E-DPP acceptability, feasibility, and fidelity, cost-effectiveness, and the link between program delivery and outcomes to identify and improve essential intervention components. This study represents the first effort to integrate culturally tailored DPP adaptations with direct food and physical activity access supports, addressing systemic barriers in a way that could redefine national diabetes prevention efforts. By leveraging trusted church settings and addressing key barriers, this innovative model holds promise for national scalability and long-term sustainability. This approach has the potential to set a new standard for diabetes prevention in high-risk populations and inform future policy and practice at the national level.

NIH Research Projects · FY 2026 · 2026-03

Project Summary/Abstract Brain function depends on the precise assembly of neural circuits during development, but the gene-regulatory principles that govern how neuronal lineages integrate into functional circuits remain poorly understood. Using the Drosophila Ventral Nerve Cord (VNC) as a model, this project investigates how specific neuronal lineages assemble into circuits, focusing on the Jump Circuit—a key and conserved pathway for escape behavior. Aim 1 (K99) will explore how neuronal identity influences connectivity within the jump circuit. I hypothesize that segment-specific morphologies, regulated by neuronal identity, enable interactions between interneurons and the motor neuron controlling the jump response. I will employ genetic manipulation, expansion microscopy, and single-cell RNAseq data to link neuronal identities to their transcriptomes and connectivity patterns, ultimately determining if segmental identity genes regulate motor neuron connectivity. My collaborators Drs. Jefferis and Tillberg will help me develop the technical expertise to complete this aim. Aim 2 (K99) seeks to map the composition and function of the jump circuit. In collaboration with Dr. Azevedo, I will generate a complete synapse-resolution map of the jump circuit and analyze the role of neuronal activity in circuit formation and function. This aim will reveal whether early neurotransmission is crucial for proper circuit assembly and maturation. Aim 3 (R00) will investigate how epigenetic factors regulate neuronal identity during circuit formation. Drawing on insights from Aims 1 and 2, I will examine how epigenetic mechanisms control neuronal behavior during circuit assembly. Career Development Plan and Goals: To achieve my goal of becoming an independent scientist, I will execute this research mentored by Dr. Lacin, at the University of Missouri – Kansas City (UMKC), who is a leading expert in the field of neuronal development in the VNC. Furthermore, I have assembled a dedicated mentoring team, including Dr. Spletter as co- mentor. Dr. Lacin's expertise in developmental neurobiology, Dr. Tillberg's expertise in expansion microscopy, Dr. Jefferis' expertise with generating and analyzing single-cell RNAseq data, and Dr. Azevedo's focus on mapping neural circuits will provide a robust foundation for my research. With support from these experts, I will develop a deep understanding of neural circuit formation, microscopy techniques, and gene-regulatory mechanisms governing neural connectivity. The environment at UMKC, enriched by these collaborations, will enable me to transition to an independent research program.

NSF Awards · FY 2025 · 2025-10

This project's goal is to assess and improve the safety of real-world speaker recognition models against advanced adversarial attacks. These models are used by voice-controlled devices such as Amazon Echo, Apple Siri, and Google Home that are increasingly integrated into people's lives. However, these models are at risk of being fooled by attackers trying to create requests that imitate legitimate users' voices but issue unauthorized commands. For now, most known attacks are impractical because the adversary needs to be able to make numerous requests to the model before they can create examples that fool it. More effective attacks may exist, however, and the goal of this project is to learn more about them. In particular, it may be possible for attackers with minimal access to, and limited knowledge of, the speaker and the recognition model -- maybe only a single speech sample from the target speaker -- to develop methods for generating adversarial examples with high transferability that can effectively spoof speaker recognition models without requiring any additional queries. The research team will evaluate these vulnerabilities in current commercial voice-controlled systems and propose robust defense mechanisms to build more secure next-generation voice applications. To meet these goals, this project will focus on three core areas. First, the project leverages generative models to develop a Parrot Training attack that uses voice conversion techniques. By generating supplementary speech samples from a single speech instance of a target speaker, the system builds surrogate models that approximate black-box speaker recognition systems, increasing the effectiveness of adversarial example transfer. Second, this project evaluates the interplay between human perception and attack effectiveness by analyzing the perceptual quality of adversarial speech. This involves assessing how various state-of-the-art adversarial examples affect both transferability and human-perceived audio quality, with the goal of identifying optimal perturbation strategies. Finally, the project incorporates human perception into the development of defense mechanisms. It explores human-in-the-loop adversarial training techniques that are resilient against diverse adversarial examples while reducing computational costs compared to conventional Lp-norm-based training methods. This project will strengthen the security of voice-driven technologies by developing human-aware methods to generate and defend against adversarial attacks on speaker recognition 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.

NSF Awards · FY 2025 · 2025-10

This ExLENT Explorations Tack project is a partnership to expand employment opportunities in the advanced manufacturing and construction sector. The partnership intends to grow a competitive workforce by engaging participants in hands-on learning experiences in state-of-the-art laboratories, along with internships at STEM employers.  The project is designed to extend support beyond the initial experiential learning activities. Participants receive financial, academic, and career focused assistance to participate in short-term training aimed at securing stable employment. These supports are a critical component of the overall strategy to strengthen workforce readiness. By training more people to work in this high-demand sector, this project supports economic growth at both the regional and national level. This project aims to explore how a short-term, high-support training and internship program can effectively prepare individuals without postsecondary degrees for family-sustaining careers in advanced manufacturing and construction. To achieve this, the team will implement and evaluate a two-month hybrid training and internship program that includes hands-on technical training, paid work experience, and wraparound support services. This project is expected to generate new insights into how support-intensive, community-based interventions can serve as effective, scalable alternatives to college and university-based degree pathways into STEM fields. Findings will be shared openly and disseminated to researchers, educators, workforce trainers, employers, and other stakeholders engaged in building the advanced manufacturing and construction workforce. The goal is to develop a replicable model that can be adapted to other regions and extended to additional high demand STEM sectors. By embedding research, targeted interventions, and evaluation throughout the project, the team seeks to produce actionable insights that can inform workforce development efforts nationwide. The NSF ExLENT Program supports inclusive experiential learning opportunities that provide cohorts of learners with the skills needed to succeed in emerging technology fields. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-09

RNA regulation plays a critical role in muscle development and function. Fine-tuning isoform expression ratios of sarcomere proteins enables muscles to acquire mature, fiber-type specific contractile properties and to adapt to physiological demand, although the regulatory mechanisms that direct fiber-type specific splicing are still not well understood. In diseases such as myotonic dystrophy, mis-regulation of RNA-binding proteins including CELF1 leads to altered isoform expression patterns and muscle malfunction. The development of new therapies will rely on a better understanding of how aberrant RNA regulation leads to muscle disease. Our work has helped establish Drosophila melanogaster, a tractable model organism with a powerful genetic toolbox, as a model to study conserved mechanisms of RNA-binding protein function in myogenesis. We have shown that the CELF1 homolog Bruno1 (Bru1) regulates fiber-type specific splice events in indirect flight muscle. Loss or gain of Bru1 disrupts cytoskeletal rearrangements during early stages of differentiation that are necessary for myofibrillogenesis and blocks a developmental transition in alternative splicing to mature sarcomere protein isoforms necessary for proper regulation of sarcomere growth and myosin activity. Bru1 as well as CELF homologs in vertebrates are themselves alternatively spliced, but little is known about their isoform-specific functions. Here we propose to elucidate the function of individual Bru1 isoforms during muscle development using a multi-pronged approach integrating genetic, molecular and biochemical techniques. Based on preliminary data demonstrating Bru1 isoform-specific phenotypes, we will expand our isoform-specific toolbox to monitor isoform localization dynamics and test which isoforms are required by manipulating developmental-stage dependent isoform expression. We will uncover Bru1 isoform-specific regulatory logic by analyzing transcriptome-wide splicing signatures in RNA-Seq complemented with Nanopore sequencing to assemble full-length transcripts. We will verify alternative regulatory events in loss and gain of function backgrounds with splicing reporters. We will demonstrate Bru1 protein isoform-specific binding affinity and motif preference using EMSA and eCLIP, and test domain-specific function with structure-function constructs. Successful completion of these aims will enable us to evaluate Bru1 isoform-specific function in alternative splicing and translation, and demonstrate how alternative splicing of CELF proteins fine-tunes regulatory capacity. Given the strong conservation in muscle structure and function between flies and vertebrates, our work has the potential to identify conserved and disease-relevant genetic principles governing RNA-binding protein function.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ ABSTRACT Biomineralization is an essential process controlling the structural development and pathological progression of several tissues and organisms. Depending on the degree of biomineralization, collagen fibers can be as compliant as tendons and ligaments (without minerals), as rigid as bones (with abundant minerals), or have a gradient rigidity as cartilage (with zonal-specific minerals), in the musculoskeletal system. On the other hand, ectopic biomineralization often results in severe diseases. For instance, calcification of vascular tissues may lead to thrombus formation or atherosclerotic lesions, while calcification of articular cartilage is a sign of osteoarthritis (OA) progression. Therefore, it is essential to understand the mechanisms of biomineralization and mimic the mineralization process in vitro to replicate the composition, structure, and properties of mineralized tissues. Osteochondral (OC) tissue has a multiphasic structure consisting mainly of articular cartilage and subchondral bone with zonal-dependent mineralization. Specifically, the intrafibrillar minerals (within collagen fibers) and extrafibrillar minerals (on the surface of collagen fibers) constitute 85.8 wt.%, 65.1 wt.%, and 0% of the dry weight of the subchondral bone, calcified cartilage layer, and cartilage layer, respectively. Due to this complex structure and poor intrinsic regeneration capability, OC repair is highly challenging. Tissue engineering approaches using multizonal scaffolds have been shown as effective alternatives for enhanced OC regeneration. The objective of this application is to develop and evaluate a zonal-specific mineralized scaffold optimal for OC regeneration by controlling the mineralization of collagen. The central hypothesis is that the progenitor cell- seeded multizonal scaffold mimicking the hierarchical microstructure and composition of native OC tissue with sustained local release of functional trace elements is a promising therapeutic option to improve OC regeneration. To test our hypothesis, the objective of this proposal will be achieved by three specific aims: (1) Design and fabricate individual zones with different compositions and fiber orientations by controlling biomimetic mineralization. (2) Seamlessly bond Characterize and individual zones into monolithic multizonal scaffolds. (3) Evaluation of in vitro osteochondral cell differentiation and in vivo osteochondral tissue formation within the progenitor cell-loaded multizonal scaffold. The innovation lies in (1) designing highly biomimetic five-zone scaffolds with zonal-dependent mineralization and fiber orientation. (2) for the first time, considering the intrafibrillar and extrafibrillar features in the subchondral bone zone. (3) achieving sustained local release of functional trace elements. (4) using chondroprogenitor cells and BMSCs harboring fluorescent reporters to virtualize zonal-specific osteochondral differentiation in situ. This application is partially designed to create an appropriate undergraduate training experience in biomaterials development and evaluation by advanced imaging technologies, particularly for the first class of Biomedical Engineering students in the university’s history.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY/ABSTRACT This proposal centers around a secondary analysis of available whole genome sequencing data from the Gabriella Miller Kid's First orofacial cleft cohorts. Non-syndromic orofacial clefts, such as cleft lip/palate, are among the most common human birth defects, yet our understanding of the significant genetic component underlying the risk of being born with this anomaly is far from complete. The proposed research plan involves a two-pronged targeted analysis to identify genetics variants that is unique in its approach. The first aim seeks to catalogue variants located within regulatory elements specifically active in the facial ectoderm, while the second aim investigates deep intronic variants in ectodermally expressed genes for their potential to disrupt correct mRNA splicing. The unique focus on ectodermal gene contributions is based on strong demonstrable biological data for this cell population being a major contributor to orofacial cleft risk. These analyses hold the promise of providing unique insight into the genetic architecture of non-syndromic cleft lip/palate.

NSF Awards · FY 2025 · 2025-06

This project focuses on advancing the field of robotic visual perception by addressing critical limitations in current artificial intelligence systems, particularly their inability to generalize effectively to novel environments and human-centered interactions. These limitations are in stark contrast to human perception, which supports a comprehensive human understanding of social activities and efficiently establishes visual learning of novel scenes with limited prior knowledge. Therefore, this project calls for a paradigm shift via transforming machinery perception into embodied recognition to achieve performance guarantees in real-world applications. This is achieved by the proposed human-like visual understanding and efficient learning methods. These advances are expected to foster interdisciplinary applications, including enhanced human-robot collaboration, and benefit areas like disaster response, security, and healthcare. The outcomes will also contribute to education by integrating findings into curricula and engaging diverse student groups, thus promoting inclusivity and STEM education. The research seeks to establish algorithmic foundations for human-embodied visual understanding, mirroring that of human recognition. To accomplish this objective, this project proposes two thrusts: human-centered visual understanding and human-like visual learning. Through these two thrusts, the project will develop novel frameworks for understanding human behaviors and interactions and creating robust learning mechanisms from sparse data. These include: (1) a unified, end-to-end cross-modal framework for instance-level human parsing; (2) a multi-modal large-scale dataset dedicated to human non-verbal communication; and (3) a label-efficient learning strategy inspired by human cognition, enabling systems to recognize complex patterns from limited annotations. The project will incorporate cutting-edge techniques such as multimodal learning and memory-augmented neural networks, with the aim of achieving significant improvements in human semantic understanding and application adaptability. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-05

With the support of the Chemical Catalysis program in the Division of Chemistry, Professors Daniel Weix and Shannon Stahl of the University of Wisconsin-Madison, Professor Mohammad Rafiee of the University of Missouri-Kansas City, and Professor Robert Paton of Colorado State University are studying new approaches to catalysis and electrochemistry for the synthesis of biaryl molecules useful in polymers and agriculture. Building upon their recent advances, this team will continue to develop analytical and computational tools that will be used to illuminate fundamental principles that are important for success of these catalytic reactions. The lessons learned will enable lower-cost, higher-efficiency synthesis of important molecules using electricity in place of metal reductants. The research team will also work to train the next generation of chemists via several established programs and to educate the broader chemistry community about organic electrochemistry via courses and lectures. This project focuses on electrochemistry-driven and nickel-catalyzed reductive biaryl synthesis from a variety of aryl electrophiles. The research team will use a combination of stoichiometric organonickel studies, theory, and electroanalytical techniques to understand how each step in the biaryl synthesis (oxidative addition, transmetalation, reduction, and reductive elimination) is influenced by catalyst identity, conditions, and applied potential. This understanding will be used to make electrochemical biaryl synthesis suitable for commercial scale-up by conducting additional studies to improve catalyst turnover number, turnover frequency, and selectivity, including the development of cross-selective reactions. More broadly, these studies will contribute to an improved understanding of nickel catalysis and electrosynthesis; the resulting reactions will be lower-cost, more efficient alternatives to the state-of-the-art biaryl syntheses, which may utilize less selective oxidation reactions, more expensive precious metal catalysts, and/or more reactive aryl nucleophiles. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-05

Today's artificial intelligence (AI) systems are powerful but often operate as opaque "black boxes," making decisions without clear explanations. This lack of transparency limits trust in AI, particularly in critical domains such as healthcare, finance, and autonomous systems, where understanding the reasoning behind decisions is essential. At the same time, decades of research have produced mature, well-established, and theoretically proven algorithms. This project introduces Algorithm-Informed Neural Networks (AINNs), a new approach that integrates these proven algorithmic principles into the design of neural networks. By embedding logical steps into AI architectures, AINNs enhance explainability, reliability, and efficiency, making AI systems more interpretable and reducing their dependence on large datasets. This advance is particularly beneficial in fields where data is scarce or sensitive, such as medical diagnostics or regulatory decision-making. By addressing these challenges, the project contributes to the development of trustworthy, transparent, and efficient AI technologies that can drive scientific progress and benefit society. To achieve these goals, the project is structured around two key research tasks. First, it focuses on algorithm-mapped neural models, which construct neural networks by systematically integrating well-established algorithmic logic. Instead of relying solely on training data, these models leverage predefined logical rules — ranging from pseudocode to flowcharts — to ensure reliability and trustworthiness in AI decision-making. This approach reduces training data requirements while improving generalization and interpretability. Second, the research develops latent behavior analysis of neural blocks, a novel debugging tool that enables AI systems to be systematically inspected for correctness. By analyzing the execution patterns of neural subnetworks, this method detects input-specific anomalies and traces them back to logical inconsistencies, facilitating targeted debugging and improving model robustness. The project will evaluate AINNs across diverse tasks, from algorithmic reasoning to perception-based applications, using key metrics such as data efficiency, error localization accuracy, and generalization performance. Expected outcomes include AI systems with greater transparency, lower data dependency, and enhanced reliability, making them more effective in real-world applications. The project will publicly release datasets, models, and tools to promote broader adoption of algorithm-informed AI across multiple domains. 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 · 2024-10

Wireless data traffic continues to grow at an exponential pace, demanding more and more bandwidth. Networks of the future will need to exploit frequencies above 100 gigahertz, which are much higher than what is typically employed today. These high frequencies need to propagate as narrow directional beams, rather than the wide- angle broadcasts currently used by base stations and cell towers. Using beams offers a number of important advantages, but also poses some significant challenges. One key challenge surrounds the question of how to adapt if the beam is blocked by an intervening obstruction between the transmitter and receiver, such as a person walking through the beam path. This research program explores a novel solution to this problem which relies on the generation of beams that follow a curved trajectory. Such beams can be generated in situations where the size of the transmitter is sufficiently large, with the appropriate engineering of the properties of the generated signal at all points across the emitting aperture. The use of such exotic beams in wireless communications is unprecedented, so many open questions must be explored in order to validate the feasibility. This work will open a new realm of possibilities for the implementation of local area networks operating at ultra-high frequencies. This project also includes a significant effort to broaden participation by under-represented groups, at the high school, undergraduate, and graduate levels. This research lays the foundations for the use of self-accelerating beams in mobile wireless local area networks (LANs) operating in the near-field regime. Since conventional link analysis cannot be applied in the near field of a transmitter, fundamental electromagnetic calculations are used to establish heuristic models for link budgets that can be employed to estimate the performance of such links, including a characterization of the effect of receiver aperture and of the near-field to far-field transition for various types of self-accelerating beams. Two different strategies are explored to create electrically reconfigurable metasurfaces that can be used to generate and manipulate such beams, which could be integrated into a transmitting base station for agile adaptation to transient blockage events. In addition, issues facing the control plane will also be explored, including the development of strategies for link discovery using beams with curved trajectories, and the implications of the asymmetry of the channel resulting from the fact that the receiver is in the near field of the transmitter but not vice versa. 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 2024 · 2024-09

Project Summary The goal of this study is to understand the timing and patterns of treatment seeking after rape. Rape survivors have high, varied, and long-term health needs after rape, and research is contradictory as to when and what kind of healthcare services rape survivors may over- or under-utilize. Screening programs are often implemented with the intent of improving access to care or directed referrals to care. Yet, outside of the Veterans Health Administration, screening programs have little evidence of effectiveness. By recruiting a large, diverse sample of mostly marginalized, mostly women rape survivors and following them for years, we will be able to observe naturalistic screening practices and treatment seeking across a variety of treatment needs and contexts. Thus, the data collected in this study will be a new foundation for understanding the features of screening programs and nature of treatment-seeking after rape.

NIH Research Projects · FY 2024 · 2024-09

Project Summary / Abstract The proposal requests funding for the purchase an modern animal cage and rack washer system with bottle washing carts with rotary spray and universal basket rack for cages, as well as a cloud-based environmental monitoring system for UMKC’s Laboratory Animal Research Core facility. The former is to provide the Laboratory Animal Research Core facility with an advanced, environmental-friendly, high performing and high-throughput system that will assist in and improve facility operations. As part of the high performing and high-throughput system capacity of the system two bottle washing carts with rotary spray and two universal basket rack for cages are being requested to facilitate higher staff and facility efficiency and reduce down-time of the system. The proposed modern equipment will aid in the consistency and accuracy of animal care through improved environmental sustainability and automation of animal facility operation. The latter is to provide the Laboratory Animal Research Core facility with a cloud storage and web-based system to replace the current system that is limited to a local server and can only be accessed in the office of the core director and not elsewhere in the core facility or the institution. Further, it will enable core staff to monitor environmental conditions from any computer improving both efficiency of operations and increased responsiveness to animal care needs and users, as well as enable core staff to more effectively and quickly communicate with the university’s Central Facilities Management team to control more readily environmental conditions. The modern equipment will enable detection, measurement, monitoring, recording, and reporting environmental extrinsic factors to allow experiments reproducibly conducted under similar environmental conditions and animal care, husbandry settings. The novel and modern equipment will take advantage of existing resources while allowing core staff to detect, monitor, quantify, record, analyze in real-time and report these factors and allow for the longitudinal assessment of environmental factors, a capability that currently does not exist for the core and that a routine upgrade would not be able to accomplish. The proposed systems will serve a diverse and increasing community of NIH-funded researchers at UMKC meeting the current increased and future needs for biomedical research, as well as modernize training in health-related research. The proposed equipment will accelerate research progress and enhance the rigor, quality and breadth of research results and generate data of the highest impact possible. Overall, these advancements will allow NIH-funded UMKC investigators active in biomedical research conduct research on diseases that affect significant and increasing portions of the U.S. population including minorities affected by disparities in health care delivery, to determine the underlying causes of human disease, help design future therapeutics and improve health care.

NIH Research Projects · FY 2025 · 2024-09

The US not only has the highest rate of maternal mortality in the developed world but is the only country in which this rate is rising. While affecting only 1-4% of pregnancies, cardiovascular disease (CVD) accounts for ~30% of maternal deaths and yet there no is evidence about how best to stratify risk or deliver care to this high-risk population. While cardio-obstetrics (COB) clinics have emerged, with encouragement and support from the AHA and ACOG, these have been implemented very heterogeneously. In collaboration with a large network of COB clinics, we have identified 5 structural components of care that have been variably deployed, and for which further evidence is needed to define whether any of these independently improves outcomes. Along with 33 partner sites, we propose the first-ever, US-based, prospective evaluation of 1000 consecutive pregnant women with CVD to identify clinical, patient-reported, and structural characteristics of care associated with adverse pregnancy outcomes (APO), maternal adverse cardiac outcomes (MACE), neonatal adverse clinical events (NACE) and quality of life (QoL). Our study will address the exceedingly high prevalence of adverse outcomes pregnant women with CVD by: 1) Identifying patient characteristics at the time of prenatal care initiation and throughout pregnancy associated with APOs, NACE and MACE; and 2) By adjusting for these factors, define the independent association of alternative structures of care, with outcomes, so that more effective COB practices can be developed and disseminated to reduce maternal mortality and morbidity and improve neonatal outcomes. We will prospectively collect detailed patient-level variables, and the first ever serial assessment of quality-of-life data, from initial COB clinic presentation throughout pregnancy, delivery, and 1 year after delivery. This will be the first national, multisite, prospective study of pregnant women with CVD ever conducted in the US and to address our country's rising maternal morbidity and mortality. Moreover, given the lack of evidence-based observational insight into what practices improve outcomes in which patients, this work will be foundational for future clinical trials. To accelerate the translation of our findings to clinical practice, we have actively engaged dissemination partners to join us in the design, analysis, and interpretation of our findings to accelerate their efforts to improve maternal care.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY/ABSTRACT Successful treatment and management of oral mucosal lesions depend on a definitive, accurate, and timely diagnosis. Oral squamous cell carcinoma (OSCC) is very aggressive and tends to be diagnosed at late stages, leading to poor prognosis. Most OSCCs are preceded by oral potentially malignant disorders (OPMDs), which are a heterogeneous group of clinical oral lesions associated with a statistically increased risk of malignant transformation. The existing histopathological diagnosis for OPMD is subjective and unable to predict malignant transformation risk for individual OPMD cases, leading to challenges in precancerous oral lesion management. To fill the important medical gap in OPMD risk assessment, we propose an innovative Fourier Transform Infrared (FTIR) based multimodal imaging diagnostic platform, which integrates three complementary modalities: FTIR imaging for biochemical pattern recognition, histological imaging for morphological feature identification, and spatial transcriptomics for gene expression profiling. We will also employ cutting-edge machine learning (ML) and deep learning (DL) techniques for feature extraction and predictive model development. The central hypothesis of this proposal is that the integration of FTIR imaging with histological imaging and spatial transcriptomics techniques aided by ML/DL provides quantitative, objective, and accurate risk assessment for individual OPMDs. To test the hypothesis, we propose the following three specific aims: 1) Develop ML/DL models using the FTIR imaging technique for OPMD risk stratification, 2) Augment FTIR imaging with histological imaging to improve diagnostic efficiency and accuracy, 3) Apply spatial transcriptomics to profile gene expression and enhance biological interpretability of the OPMD diagnostic platform. The multimodal imaging-based diagnostic system can be easily integrated into the existing clinical diagnostic workflow for precise OPMD diagnosis, which together with effective OPMD management can lead to significantly improved patient outcomes and alleviate the global burden of oral cancer.

NIH Research Projects · FY 2024 · 2024-09

Project Summary / Abstract Pattern formation, the spatial organization of cells of different types, is central to the development and function of metazoans. Pattern formation also occurs in microbial communities such as biofilms and colonies. For example, pattern formation is manifested by localization of different cell types to different regions of a microbial community. Formation of these patterns requires communication between individual cells, and so the first organisms to communicate were likely microorganisms within communities. From this perspective, the most ancient and fundamental mechanisms of communication on earth evolved, and still exist, in simple microorganisms. Here we propose that in the model genetic organism, Saccharomyces cerevisiae, this communication involves secreted metabolites that serve as cell-cell signals. A variety of evidence suggests that this type of communication is important in healthy and diseased human tissues. Yeast colonies are ideal for investigating pattern formation and the cell-cell signals that underlie these patterns. Two advantages of this organism are its facile genetics and the depth of knowledge we have regarding this particular species. Yeast colonies contain a thick layer of meiotic cells at the top of the colony supported by an underlying layer of feeder cells. Feeder cells are so named because they provide metabolites to the upper colony layer. A sharp boundary forms between these two layers. The focus of the proposed research is the mechanism of differential partitioning-- a change in the relative allocation of the colony, the ratio of meiotic cells: feeder cells, in response to environment (food, temperature, etc.). We propose that communities adapt to their environment by differential partitioning. Our specific aims are to determine: 1) the role of signaling pathways and their target transcription factors in regulating differential partitioning in response to environmental cues, 2) the role of secreted metabolites as a type of cell-cell communication that controls this partitioning. To achieve these aims, we will utilize several approaches. First, we will use flow cytometry to distinguish different colony subpopulations, corresponding to different cell fates, and how environmental cues and genetic mutations drive the relative allocation of these subpopulation. Second, we will determine the temporal/spatial expression of genes within colonies using fluorescent-tagged proteins and colony sectioning. Third, we will identify and characterize metabolites serving as cell-cell signals that control colony organization. The proposed research has potential connections to broader biological topics that are difficult to study in other organisms. These include biofilm pattern formation, which contributes to the pathogenicity of some yeast species, the effects of environment on development, and the role of secreted metabolites in regulating multicellular functions.

NIH Research Projects · FY 2025 · 2024-09

Biomolecular condensates are dynamic, membrane-less organelles formed within cells, and both host cells and viruses encode proteins that can assemble into these structures, facilitating essential cellular processes and viral replication. My laboratory uses model positive-sense, single-stranded RNA viruses (+ssRNA) like Pea enation mosaic virus 2 (PEMV2) and Turnip crinkle virus (TCV) to better understand virus-host interactions that take place in biomolecular condensates. Over the next five years, our objectives encompass several key aspects. Initially, we will investigate the specific mechanisms through which viral condensates, particularly focusing on p26 from PEMV2, disrupt cellular translation. Additionally, we will utilize nanopore sequencing to explore their potential role in interfering with fibrillarin-mediated 2'-O-methylation of ribosomal RNAs. We will use transcriptome-wide methodologies (e.g., TRAP-seq) to comprehensively investigate the impact of viral condensates on the translatome during infection and test the hypothesis that viral condensates promote translational repression of antiviral transcripts while enhancing translation of pro-viral transcripts. Using a similar approach, we will investigate whether viral condensates function as a molecular switch, repressing the translation of viral transcripts to favor late stages of the virus replication cycle, such as packaging and release. Next, we will shift our efforts to understanding how nuclear condensates formed by the coat protein (CP) of TCV inhibit RNA interference (RNAi), potentially via the sequestration of siRNA precursors. We will also investigate whether CP condensates interfere with the epigenetic regulation of siRNAs to alter their stability and host gene expression. Our research program's overarching vision is to employ model systems to understand better how viral biomolecular condensates disrupt cellular homeostasis, ultimately promoting virus fitness. This research addresses a critical knowledge gap by investigating the impact of viral condensates on host cell function, an area that has received limited attention compared to the extensive research on their effects on virus replication. Our research will also yield novel virus-host interactions with potential applicability across RNA virus families, potentially serving as a foundation for developing innovative therapeutics.

NSF Awards · FY 2024 · 2024-09

The 9th Annual Meeting of Society of Industrial and Applied Mathematicians Central States Section (SIAM-CCS) will be held at the University of Missouri-Kansas City during October 5-6, 2024. The SIAM-CSS Annual Meeting provides an opportunity for researchers to facilitate knowledge transfer, networking, and exchange of novel ideas in applied mathematics, numerical analysis, scientific computing, and related fields. Moreover, the conference provides valuable opportunities for career development, particularly for early career mathematicians, postdocs, and graduate students. The SIAM-CSS annual conference series is an important forum for applied and computational mathematicians from central states (Arkansas, Colorado, Iowa, Kansas, Mississippi, Missouri, Nebraska, and Oklahoma) and beyond. In addition to plenary lectures by distinguished applied mathematicians, the annual meeting hosts mini symposiums in several active areas of applied mathematics and related fields. The scientific focus of the annual meeting will encompass a broad range of topics within applied mathematics and computational science. While the exact themes and emphasis may vary depending on the specific interests of the mini-symposiums organizers and participants, common areas of focus include Numerical Analysis, Partial Differential Equations, Optimization, Scientific Computing, and interdisciplinary applications. The conference website is https://sse.umkc.edu/siam-2024/. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Project Summary My immediate career goals are 1) to obtain a tenure track position as a principal investigator and 2) to improve our understanding of the structure and function of β-hairpin antimicrobial peptides to help combat antibiotic resistant pathogens. My previous expertise, along with the career development laid out in this proposal, will allow me to complete the proposed research strategy and achieve these two immediate goals. New strategies and methods for antibiotic discovery are critically needed. Macrocyclic peptides are a promising class of antibiotic because they can target sites refractory to small molecule inhibition; however, their large size limits their ability to bypass membranes and access intracellular targets. Macrocyclic cationic antimicrobial peptides (CAMPs) are capable of penetrating bacterial membranes, but often have associated toxicity, making them more difficult to use clinically. A small class of CAMPs with cyclic β-hairpin structure (β- AMPs) access intracellular targets through bacterial membrane disruption and have a wide range of associated toxicity. Unfortunately, the rarity of this class prevents our understanding of how their amino acid sequence dictates their antibacterial potency and mammalian cell toxicity. I have helped developed a new synthetic macrocyclic peptide screening technique which has identified thousands of synthetic β-AMPs, expanding sequence information and allowing us to begin analyzing how their amino acid sequence impacts their antibacterial potency, cell membrane specificity, and ultimately their therapeutic potential. During Phase I of this proposal, I plan to biochemically analyze a newly acquired dataset of putative β- AMPs with diverse antibacterial potency and mammalian cell toxicity and use this data to train a machine learning algorithm to identify sequence features promoting antibacterial specificity. The in vivo activity of lead peptides will then be examined using the Galleria mellonella infection model. During Phase II, I will examine how β-AMPs interact with and permeate cell membranes composed of different lipids using strains with genetically modified lipopolysaccharide, in vitro liposome disruption assays, and ultraviolet photodissociation mass spectrometry. This will help us understand how β-AMPs overcome traditional methods of CAMP resistance and have an ability to selectively target bacterial cell membranes. Lastly, through modification of our screening technique, I have generated predictive data for how over 7,000 mutational variants of one promising natural β-AMP's amino acid sequence impacts its antimicrobial activity. I plan to evaluate the accuracy of these predictions through biochemical evaluation of 48 of the 7,000 variants. Differences in the toxicity and membrane specificity of this group will also be evaluated and compared to the native sequence to better understand how certain residues impact therapeutic potential.

NIH Research Projects · FY 2024 · 2024-08

Inactivation of the VHL tumor suppressor protein (pVHL) is frequently observed in clear cell Renal Cell Carcinoma (RCC). The mutated pVHL does not bind and degrade the regulatory α-subunits of the hypoxia- inducible factor (HIF-1/2/3α) under normoxia causing overexpression of HIF-dependent pro-angiogenic factors such as VEGF, EPO, PDGF, etc. As a result, RCCs are highly vascular in nature. Extensive studies have established that the inhibition of the HIF pathway is sufficient to suppress tumor growth by the VHL‒/‒ RCC cells, offering an attractive target to treat this disease. We have shown that pure honokiol inhibits the HIF pathway and hypoxia-mediated expression of pro-angiogenic genes in a number of cancer cell lines. Honokiol also inhibits constitutively active HIF pathway and expression of pro-angiogenic genes in VHL‒/‒ RCC4 cells under normoxia. Further, we have determined the mechanism of action of honokiol using chromatin immunoprecipitation experiments. These finding have allowed us to synthesize a new class of boron based HIF inhibitors with improved efficacy and anti-angiogenic properties under in vitro conditions. In this project we propose two specific aims: (i) determine the structure-activity-relationship (SAR) of honokiol analogs on the inhibition of the HIF pathway and (ii) determine the efficacy of selected honokiol analogs in a xenograft RCC mouse model. At the completion of this project, our expectation is that we will have evaluated the potential therapeutic efficacy of honokiol analogs as a treatment strategy for RCC. In addition to primary positive impact of our findings, potential outcomes may benefit treatment of other systemic problems associated with VHL mutations, e.g. hemangioblastomas of retina and CNS. Finally, activation of the HIF pathway plays critical roles in the development of many different cancer types at multiple stages. Evaluation of honokiol analogs as inhibitors of the HIF pathway is expected to provide an important tool to further define the contribution of this pathway in cancer development and resistance. Relevance to Public Health: RCC is an important disease with ≈60,000 new cases predicted each year with >13,000 deaths. The clear cell carcinoma are the most common form of RCC and making up nearly 70% of cases. Unfortunately, cure for RCC is only available to those with limited stage disease which can be surgically resected, as to date systemic therapies cannot eradicate the cancer if it has spread distantly. In advanced stages, systemic therapies are given to stabilize the disease. No conventional cytotoxic chemotherapy agents have demonstrated significant activity in this disease as monotherapy or combinations. Anti-VEGF therapies have been largely ineffective, possibly due to contribution of other pro-angiogenic factors, such as EPO, PDGF, etc. in RCC. Thus, there remains an unmet medical need to develop more effective treatments for RCC. The proposed research will evaluate honokiol and its analogs as inhibitors of the HIF pathway and more effective therapeutic agent for the treatment of RCC.

NIH Research Projects · FY 2026 · 2024-08

Project Summary The term “Cleft lip with or without cleft palate (CL/P)” encompasses a variety of clinical presentations that collectively represent one of the most common human birth defects. For each patient, the impact can also be significant. The severity of a patient’s clinical presentation is the major determinant of the duration and frequency of significant surgical intervention and long-term clinical care. Considerable progress has been made over the last few decades to determine the genes responsible for syndromic forms of CL/P. However, the low penetrance and variability in presentation pose challenges when counseling families about recurrence risks, as it is currently impossible to predict whether a child will be born with CL/P or how severe the presentation might be regardless of whether a genetic predisposition is known. This new proposal builds on important new observations and exciting preliminary data on established mouse models of CL/P to begin to dissect the factors that influence the cleft penetrance and severity in embryos that are genetically predisposed to CL/P. Specifically, this project will address the role of maternal diet (specifically vitamin A) as a modifier of genetic susceptibility, severity of presentation and in utero correction prior to birth, as well as investigate the basis for the left bias in unilateral cleft presentations. Although vitamin A and its derivatives have long been implicated as a risk factor in CL/P, this project will exploit a novel mouse mutant background that overcomes the limitations of prior animal model studies such as the need for excessive, non-physiologic levels of vitamin A and unnatural routes of administration. Furthermore, we test the impact on two distinct underlying genetic susceptibilities. The successful demonstration of modifying roles for these factors could ultimately have a significant impact on patient counselling and potentially open up the possibility of developing simple and effective interventional and preventative maternal dietary interventions such as personalized dietary supplementation for mothers carrying CL/P risk alleles, or crop biofortification approaches for whole populations where dietary deficiencies and genetic risk factors are known. Such approaches could have a profound impact on the incidence of NS-CL/P, much like the successes seen for maternal folic acid supplementation for reducing the risk of neural tube defects.

NIH Research Projects · FY 2024 · 2024-08

Project Summary This project will use model RNA plant viruses to elucidate the mechanisms used by viruses to target nucleoli and regulate chromatin dynamics and host gene expression. Specifically, we will investigate how the p26 protein from Pea enation mosaic virus 2 (PEMV2) modulates host chromatin and gene expression by undergoing liquid-liquid phase separation (LLPS) and partitioning into the nucleolus. We will perform both Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and RNA sequencing (RNA-seq) analyses during infection with wild-type or PEMV2-mutant viruses. These experiments will allow us to determine the extent to which p26 and PEMV2 influence chromatin accessibility and gene expression. The overarching objective of this study is to ascertain whether p26 and PEMV2 repress antiviral genes by inducing chromatin compaction while concurrently enhancing the expression of pro-viral genes by relaxing the surrounding chromatin. Next, we will utilize 2'-O-methylation sequencing (2OMe-seq) to determine whether p26 disrupts the function of fibrillarin in the nucleolus to alter the methylation patterns of small nuclear RNAs (snRNAs). Since disruption of snRNA methylation impacts pre-mRNA splicing, we will investigate whether p26 alters alternative splicing pathways to alter host protein expression and/or function. In addition to the research objectives outlined above, this project places a strong emphasis on training undergraduate researchers to conduct experiments and analyze data using safe and accessible plant virus systems. To further enhance the impact of this work on the undergraduate student body, the research findings will be directly incorporated into the undergraduate bioinformatics course at the University of Missouri-Kansas City (UMKC). This way, >20 students/year will be exposed to hands-on bioinformatics techniques and gain valuable skills in analyzing real-world data. Overall, this study will provide a comprehensive understanding of how nucleoli shape virus-host interactions and provide meaningful research experiences for underrepresented students at UMKC.