Arizona State University-Tempe Campus

NIH Research Projects · FY 2026 · 2026-06

PROJECT SUMMARY Tuberculosis (TB) and multidrug-resistant TB (MDR-TB) remain major global health threats, with over 10 million cases and 1.5 million deaths annually. MDR-TB presents a significant barrier to TB control, with nearly 20% of affected patients dying within a year of treatment initiation. Accurate and timely drug susceptibility testing (DST) is essential to guide therapy and prevent ineffective treatment, yet current DST methods are insufficient. Molecular resistance assays, though rapid, are limited by incomplete knowledge of TB resistance mechanisms, rendering them ineffective for detecting resistance to new, repurposed, or experimental pre-clinical TB drugs. In contrast, phenotypic DST remains the gold standard, as it directly measures bacterial growth in the presence of antibiotics. However, traditional phenotypic methods are slow, culture-based, and labor-intensive, delaying treatment decisions by weeks. The long-term goal is to advance a universal, simple, rapid phenotypic DST technology that can integrate processed raw samples and determine TB susceptibility or resistance to any new, repurposed, or clinical trial drug, thereby ensuring that the appropriate choice of drug treatment is determined and executed as early as possible in the time course of MDR-TB disease. To address this critical gap, we propose to develop Large Volume Scattering Imaging (LVSim) and rapid machine-learning-based TB phenotypic DST (LVSim-TBDST), a high-throughput, universal, label-free, and rapid phenotypic DST technology. LVSim- TBDST can determine TB drug susceptibility independent of genetic markers and detect heteroresistance at the therapeutic failure threshold. Our central hypothesis is that LVSim-TBDST can rapidly and accurately assess TB drug susceptibility using scattering-based optical imaging and advanced deep learning to analyze bacterial growth dynamics. This approach eliminates the need for molecular labels, genetic markers, or biochemical staining while significantly reducing time-to-result for phenotypic DST. By applying advanced imaging techniques and data-driven analysis, LVSim-TBDST has the potential to revolutionize universal TB drug susceptibility testing, particularly for new and repurposed drugs lacking molecular resistance assays. The project will 1) engineer next-generation LVSim2.0 optical sensing technology for microplate-based, high-throughput, label-free rapid phenotypic DST, 2) establish LVSim2.0 technology and develop the AI-driven image processing algorithms for rapid TB pDST with new TB drugs and for detecting 1% heteroresistant TB populations, and 3) develop a workflow for direct from mycobacterial clinical sample LVSim2.0 pDST TB testing. The project will be carried out by a productive multidisciplinary scientific team with over a decade of collaborative research experience and extensive expertise in 1) biosensors and engineering, 2) tuberculosis, clinical microbiology, and diagnostics, and 3) bioanalytical instrument development and production. The results will have a positive impact immediately because this technology universally performs TB phenotypic DST to promptly inform clinical decisions for effective treatment of MDR-TB patients.

NIH Research Projects · FY 2026 · 2026-06

ABSTRACT Fluorescently labeled antibodies have found extensive use as diagnostic tools due to their high affinities and specificities for their antigens as well as the high sensitivities associated with fluorescence-based assays. Despite this, most antibody-based diagnostic techniques require extensive experimental manipulations (e.g., multiple washing steps to remove unbound antibodies) and require costly and sophisticated equipment for detection. A new class of fluorescent antibodies that directly report on antigen binding through alterations in fluorescence properties that are readily detectable by eye could address this challenge. Not only would this eliminate the need for laborious experimental protocols but could also allow for rapid diagnostic analyses to be carried outside of laboratories. This possibility was explored almost 15 years ago when a coumarin-containing fluorescent non-canonical amino acid (fNCAA) was encoded within the binding site of a CD40L-binding antibody termed 5c8. The coumarin modified version of 5c8 exhibited an ~2-fold increase in fluorescence emission when bound to CD40L. More recently, structural studies of both wild type and coumarin-modified 5c8 revealed that, in both cases, a conformational change occurred far from the active site upon CD40L binding. This raised the intriguing possibility that moving the environmentally sensitive coumarin moiety from the combining site to this conformationally flexible region could elicit similar increases in fluorescence upon antigen binding without compromising affinity. In a recent set of preliminary studies, we have confirmed this hypothesis. If this approach is generalizable, fNCAAs could be used to convert essentially any antibody into a direct fluorescent sensor of its antigen without losses in affinity. Despite this promise, the generality of this approach has not been demonstrated; this is the focus of the proposed research. Here, we propose to build on our previous results in an effort to generate allosterically responsive fluorescent antibodies that directly report on the antigen binding event. Our efforts toward this goal will be carried out in two complementary aims: In Aim 1, we will seek to enhance the fluorescence properties of a previously identified, allosterically responsive fluorescent antibody by introducing tryptophan (Trp) residues in the vicinity of the fNCAA. Additionally, we will seek to identify new Fab variants with enhanced fluorescence properties through an extensive computational design campaign using the Rosetta software. In Aim 2, we will explore the generality of this approach by introducing coumarin-containing amino acids in other antibody scaffolds. As in Aim 1, these efforts will also be guided by a Rosetta-based design approach. Collectively, these efforts will pave the way for the development of a new paradigm of antibody-based diagnostics in which fluorescent antibodies not only directly sense their antigen targets but do so without the need of laborious experimental protocols or sophisticated instruments that facilitate detection.

NIH Research Projects · FY 2026 · 2026-06

SUMMARY Magnetic resonance imaging (MRI) is one of the most powerful imaging modalities, capable of providing detailed insights into specific metabolic pathways within tissues through magnetic resonance spectroscopy (MRS). The recent approval of ultrahigh-field 7 Tesla (7T) MRI systems holds great promise for enhancing the signal-to-noise ratio (SNR), enabling the detection of metabolites at lower concentrations, and allowing for a more comprehensive characterization of tissue biochemistry. Furthermore, the enhanced spatial resolution of 7T MRI improves the separation and identification of metabolite peaks, thereby enhancing diagnostic capabilities. In MRI and MRS, each nucleus requires a dedicated radiofrequency (RF) coil for signal induction and acquisition. The quality of the RF coil is a critical determinant of overall signal acquisition performance, particularly in multinuclear applications. However, accommodating multiple nuclei within the same imaging session presents significant technical challenges. Strong RF coupling among resonating structures, substantial signal loss due to additional electrical components required for frequency switching, and limited geometric space for multiple resonating RF circuits must be carefully addressed. Using multiple RF coils or a multi-tuned RF coil typically increases hardware complexity, introduces signal interference, and degrades image quality. Addressing these challenges is essential to fully leverage the advantages of 7T for multinuclear MRI and MRS applications, which have the potential to advance our understanding of tissue biochemistry and pathology beyond structural anatomic imaging. This project aims to overcome these challenges and limitations by developing a novel RF coil, AeroCoil, for multinuclear applications using a single RF coil structure. The AeroCoil will innovatively employ a pneumatic mechanism, termed AeroCap, for capacitive control to switch resonance frequencies. This approach strategically avoids electrical control, eliminating the need for conductive long wires, additional noise, signal loss, and electrical hazards. Aim 1 will focus on the development of a quadruple-tunable AeroCoil capable of switching resonance frequencies for proton (1H), phosphorus (31P), carbon (13C), and deuterium (2H). Aim 2 will demonstrate the automatic tuning and matching capabilities of AeroCoil, enabling dynamic adjustments to varying loading conditions in the quadruple-tunable AeroCoil to ensure optimized frequency and impedance conditions for each nucleus. Aim 3 will validate the clinical applicability of all-in-one multinuclear MRI and MRS for brain tumor imaging using the AeroCoil in vivo animal studies. The outcome of this project will establish a standardized RF coil design for multinuclear MRI and MRS applications at 7T, with potential clinical applicability.

NIH Research Projects · FY 2026 · 2026-06

Project Summary/Abstract The increasing use of Glucagon-Like Peptide-1 Receptor Agonists (GLP-1 RAs) among older adults highlights the urgent need to investigate their potential impact on skeletal muscle health, as emerging concerns suggest they may accelerate muscle loss and worsen sarcopenia—the age-related decline in muscle mass and function. Current evidence linking GLP-1 RAs to muscle loss is largely based on extrapolated data from studies in younger individuals, which often measure lean body mass rather than directly assessing muscle mass. This critical knowledge gap leaves older adults, who are already at a higher risk for sarcopenia, particularly vulnerable to potential muscle-related complications from GLP-1 RA therapy. This project will evaluate the effects of GLP-1 RA pharmacotherapy on muscle health in older patients before and six months after treatment. Specifically, we will measure muscle mass and investigate the underlying processes that regulate muscle mass (i.e., muscle protein synthesis and breakdown) using stable isotope tracer methodologies. Additionally, we will assess changes in muscle fiber types, mitochondrial function, and overall muscle quality/functional capacity. Single muscle fibers will be isolated from collected muscle samples to determine fiber type distribution. Mitochondrial function will be assessed using mitochondrial respiration assays in isolated mitochondria, while muscle quality will be evaluated based on strength measurements from dynamometry, adjusted for muscle mass. While concerns exist about GLP-1 RA pharmacotherapy and potential muscle loss, emerging evidence suggests it may have beneficial effects on muscle quantity and quality in older adults. This project will generate foundational data essential for understanding its specific impact on muscle health in this population. The findings will help fill a critical knowledge gap and provide key data for larger, hypothesis-driven clinical trials, ultimately advancing our understanding of the complex relationship between GLP-1 RA pharmacotherapy and muscle health in older adults.

NIH Research Projects · FY 2026 · 2026-06

Project Summary/Abstract This proposal addresses the significant public health concern of destructive interparental conflict (IPC), which is strongly associated with a range of adverse outcomes for children, including mental health disorders, substance use, academic challenges, risky behaviors, and suicidality. These effects are particularly pronounced in the context of parental separation and divorce, which impacts over half of U.S. children by age 15. Family courts frequently interact with families experiencing high levels of IPC, making them critical settings for implementing interventions aimed at reducing these negative outcomes. However, most parenting programs mandated or referred by family courts are not evidence-based, leaving a critical gap in effective support for families experiencing high IPC. This pilot study aims to address this gap by evaluating the feasibility, acceptability, and preliminary impact of intervention components designed to mitigate the effects of IPC on children’s mental health. Using the Multiphase Optimization Strategy (MOST) framework, we will pilot a highly efficient experimental trial design (N = 96) to gather preliminary data on five candidate intervention components: high- versus low-intensity delivery of IPC reduction approaches, inclusion of constructive IPC skills, inclusion of IPC resolution skills, inclusion of skills for repairing parent-child relationships after IPC events, and high- versus low-intensity home practice support. These components were selected based on empirical support for their potential to reduce child mental health problems. The findings from this pilot study will inform the design of a future fully powered trial to identify the most effective and scalable combination of components that can be delivered within the practical constraints of family courts. In Aim 1, we will assess the feasibility of recruitment, randomization, and trial procedures, and the acceptability of intervention components among parents and family courts. Quantitative and qualitative feedback will guide refinements to the components and trial design. In Aim 2, we will explore the components’ preliminary impact on children’s mental health using validated measures and explore hypothesized mechanisms of action, including quality of parents’ home practice and children’s emotional security. These findings will help refine the intervention’s conceptual model. In Aim 3, we will identify potential implementation barriers and facilitators by conducting qualitative interviews with judges and court administrators from three family courts of varying resources and sizes. Using the Consolidated Framework for Implementation Research (CFIR) and the Expert Recommendations for Implementing Change (ERIC), we will develop an Implementation Research Logic Model (IRLM) to guide scale-up planning for the fully powered trial. This pilot study will lay the foundation for a scalable and effective intervention addressing IPC, leveraging family courts as a key implementation context. The future fully powered trial will advance the development of effective, evidence-based parenting programs that improve children’s mental health outcomes in the aftermath of parental separation/divorce.

NIH Research Projects · FY 2026 · 2026-06

PROJECT SUMMARY/ABSTRACT Nearly 1 in 4 emerging adults engage in simultaneous cannabis and alcohol use, and rates of emerging adult simultaneous use continue to rise despite known deleterious consequences. While research on simultaneous use has gained popularity, extant data lack the ability to understand the complex acute process through which simultaneous use events commence in daily life, particularly what occurs before, during, and after alcohol and cannabis are combined within a given use episode. Outlining the immediate antecedents to cannabis use while drinking (or alcohol use while using cannabis) would afford important information on early-episode markers to spur the need/optimal timing of a just-in-time intervention. Similarly, outlining the immediate and long-term outcomes of initiating simultaneous use during a given episode would afford important information on mechanisms of just-in-time interventions that may be effective to target if/when simultaneous use does occur in daily life. Therefore, the current study will recruit N=300 emerging adults who report regular simultaneous alcohol and cannabis use for an ecological momentary assessment study encompassing two 28-day bursts of EMA at baseline and 1 year follow-up. Participants will complete event-contingent alcohol and cannabis initiation reports to indicate the beginning of use events and when simultaneous use occurs. Participants will also complete a variety of prompts throughout the day and acute follow-ups after alcohol/cannabis initiation reports are triggered. First, we will characterize simultaneous use events that are most related to acute negative consequences, based upon ordering/timing of alcohol and cannabis and quantity of each substance occurring before and after first simultaneous use is initiated. We will also test whether certain patterns of simultaneous use from the first burst of EMA predicts a change in AUD/CUD symptoms and psychosocial functioning one year later. Second, we will test whether subjective effects and contextual influences at the beginning of a drinking/cannabis use episode predict within-session initiation of cannabis use while drinking (or alcohol use while using cannabis). Third, we will test whether simultaneous use-induced changes in subjective effects and contextual influences predict continued versus ceased use of alcohol and cannabis thereafter. Data collected will present novel, important next steps in the etiological understanding of simultaneous cannabis and alcohol use, and will offer insights into optimal timing, markers of risk, and targetable mechanisms for just-in- time adaptive interventions. The proposed study has the potential of pioneering high-quality understanding of how, when, and why simultaneous cannabis and alcohol use events occur in emerging adults, an important yet unanswered question with direct implications for prevention.

NIH Research Projects · FY 2026 · 2026-06

Project Summary Among the possible sensorimotor consequences of stroke, impaired control of posture and gait is a major cause of chronic disability, significantly impacting the quality of life of 7 million stroke survivors in the US. Mounting evidence supports the critical role of the human ankle joint in posture and gait control, serving as the first line of defense against external disturbances at the interface between the lower body and the physical world—a mechanism known as the ankle strategy. However, little is known about how stroke affects ankle mechanics during upright posture control and gait. Previous studies characterizing ankle mechanics following stroke have been conducted in overly restrictive settings, often involving a seated position, limiting analysis to a single degree-of-freedom of the ankle in the sagittal plane, and primarily focusing on the paretic ankle. Furthermore, it remains unclear which specific alterations in ankle mechanics contribute to impaired posture and gait control. This lack of comprehensive knowledge prevents clinicians from effectively utilizing current findings to develop rehabilitative strategies. This project aims to address these knowledge gaps with two primary objectives. First, we will characterize ankle mechanics during lower-extremity function. The characterization will encompass both paretic and non-paretic ankles across different planes of motion (specifically, sagittal and frontal planes) during upright posture control and walking (Aim 1). Next, we will conduct a pilot study to evaluate the relationships between various aspects of the characterized ankle mechanics and performance metrics associated with posture control and gait functions (Aim 2). Additionally, we will assess the predictive capacity of robotic characterization outcomes for impaired posture and gait functions in stroke survivors, comparing them to conventional, yet subjective, clinical measures of ankle impairments. This research, involving 20 chronic stroke survivors and 20 age-matched unimpaired individuals, will validate the effectiveness of the proposed robotic approach and provide a foundation for future studies exploring the link between altered ankle mechanics and impaired posture and gait functions in stroke survivors. The contribution of this research is clinically significant because the objective and refined characterization of 2D ankle mechanics bilaterally during upright posture control and gait—unachievable with subjective clinical assess- ments or simple robotic evaluations—will provide clinicians with richer insights into a patient’s particular ankle impairments. Furthermore, understanding the relationship between detailed ankle mechanics and functional per- formance of posture and gait will enable clinicians to identify specific and clinically relevant aspects of altered ankle mechanics and prescribe targeted interventions, such as exercise training programs (e.g., side- and direction- specific stretching or strengthening exercises) and pharmacological treatments (e.g., Botulinum toxin injection targeting specific muscles). Successful completion of this research will not only enhance lower-extremity func- tion in stroke survivors but also yield secondary benefits, such as reduced fatigue during motor tasks, increased independence in daily activities, and lower healthcare costs, ultimately improving their quality of life.

NIH Research Projects · FY 2026 · 2026-06

Project Summary/Abstract National estimates suggest more than five million children in the United States have experienced parental incarceration. Rates of parental incarceration have increased dramatically over the past four decades. Children with an incarcerated parent (CIP) are seven times more likely to have a diagnosed substance use disorder due to multiple stressors, including separation from parents, exposure to traumatic events, parental substance use, and poverty. Caregivers of CIP experience high levels of stress, and many have their own history of trauma and adverse childhood experiences (ACEs). These experiences can impede their use of effective parenting strategies, which have been shown to prevent substance use and associated behavioral health problems among children in a range of stressful circumstances. Evidence-based parenting programs (EBPPs) have been shown to prevent adolescent substance use by enhancing positive parenting in other populations experiencing stress and major life transitions. However, no EBPP has been designed to address the unique circumstances of caregivers who bear the day-to-day responsibility for raising CIP. Moreover, most EBPPs were developed without focusing on scalability, resulting in limited dissemination or public health impact. Over the past 3 years, we have worked with a community-based Steering Committee (SC) to develop a conceptual model of contextually specific risk and protective mechanisms, adapt candidate components from existing parenting programs, and pilot the components with CIP caregivers. Qualitative data from caregivers and providers suggest high acceptability for program components, but challenges related to feasibility. The proposed R34 includes a partnership across three states, each with a high rate of incarceration and variability by race/ethnicity (i.e., Arizona, Florida, and Texas). In Aim 1, we will leverage our existing community partnerships and form a Design Workgroup to refine the program in ways that promote adaptability and potential adoption by agencies serving families affected by incarceration. In Aim 2, we will conduct a pilot trial using a randomized waitlist-controlled design (n=48) Caregivers and their CIP (aged 9-15 years) will provide assessment data at baseline (T1), 3 months (T2), and 6 months (T3). Caregivers will be randomized to participate in the intervention after T1 (Cohort 1) or after T2 (Cohort 2). Study aims focus on recruitment (Aim 2a), data collection for CIP and caregiver assessment batteries (Aim 2b), and implementation batteries (Aim 2c) in preparation for a future multisite Hybrid Type 2 Effectiveness Implementation trial. Moreover, results will provide important information for addressing the implementation gap for EBPPs more broadly.

NIH Research Projects · FY 2026 · 2026-05

Staphylococcus aureus is the most common cause of lung infections in the US cystic fibrosis (CF) population, with nearly half (48.3%) of persons with CF testing positive for S. aureus in 2023. Testing for CF lung infections heavily relies upon the collection of sputum, but as CF care improves through the use of highly effective cystic fibrosis transmembrane conductance regulator therapy, the production of sputum has declined, though the risk of lung infections persists. Therefore, novel methods for diagnosing lung infections without sputum are urgently needed. Our goal is to develop highly sensitive and specific, non-invasive breath tests for the detection of S. aureus and other lung infections. The overall objective of this proposal is to develop biomarkers for S. aureus lung infections through the secondary analysis of breath volatilomics data and clinical metadata collected for the IMproving P. Aeruginosa deteCTion using Breath (IMPACT-Breath) clinical study. We hypothesize that breath biomarkers can detect S. aureus lung infections and discriminate them from other mono-infections and co-infections with > 80% accuracy. We will test this hypothesis via three Specific Aims: Aim 1: Identify biomarkers that differentiate breath samples from pwCF who are Staphylococcus aureus positive vs. negative. Using machine learning algorithms, we will build classification models that discriminate breath samples from subjects with new or chronic S. aureus infections (Sa+) vs. S. aureus negative (Sa-). Aim 2: Identify breath biomarkers that differentiate S. aureus vs. P. aeruginosa lung infections. P. aeruginosa is the second most common lung pathogen in the US CF population and in the IMPACT-Breath study cohort. Using the P. aeruginosa infection status from the IMPACT-Breath study, we will build classification models that discriminate breath samples from subjects infected with S. aureus vs. P. aeruginosa (Sa+ vs. Pa+). Aim 3: Identify breath biomarkers that differentiate S. aureus mono-infections from S. aureus-P. aeruginosa co-infections. Using IMPACT-Breath data, we will build classification models that discriminate breath samples from subjects with S. aureus mono-infections vs. S. aureus–P. aeruginosa co-infections (Sa+ vs. Sa+Pa+). The expected outcomes of this project are putative breath biomarkers for detecting S. aureus lung infections and estimates of their sensitivity and specificity, which will provide us with the necessary preliminary data to design a prospective clinical study to validate S. aureus biomarkers in the breath of pwCF.

NIH Research Projects · FY 2026 · 2026-05

Drug overdose is the leading cause of accidental death in the United States (US), and reducing drug overdose deaths requires intervening across all levels of the Social-Ecological Model. Many studies have examined overdose risk factors at the individual, community, and policy levels, but fewer studies have examined overdose risk and protective factors at the household or family level. Prior research indicates that unmarried status and “living alone” are associated with overdose mortality, yet it is unclear which other household characteristics are associated with risk of overdose fatality, or how factors at community levels may moderate these associations. In addition to their influence on health, social support, and substance use behaviors, household and family members can play a key role in reducing overdose deaths by providing emergency response in case of an opioid overdose. Household/family members are often the first to witness an overdose that occurs at home, uniquely positioned to respond in time to prevent fatality. Participating in overdose education and naloxone distribution (OEND) programs is one critical way in which family and household members can develop knowledge and skills in overdose response. OEND programs are evidence-based interventions with well-documented effectiveness in reducing opioid-related mortality, yet studies suggest that Hispanics at risk of overdosing are less likely to report receiving take-home naloxone or training, and Hispanic family members are also underrepresented in OEND programs. Most OEND programs are not culturally adapted or targeted for family members, despite substantial evidence supporting the enhanced efficacy of culturally adapted interventions. Therefore, this mixed methods, community-engaged study proposes to fill gaps in the literature on the role of family/household members in reducing opioid overdose deaths, using the following aims: Aim 1. Identify family/household-level risk and protective factors for overdose-related outcomes and elucidate how these household characteristics interact with individual and community characteristics. Aim 2. (a) Culturally adapt an OEND program for adult family members of Hispanics at high risk for opioid overdose and (b) assess the adapted program's feasibility, acceptability, and preliminary effectiveness in improving adult family members' knowledge of, and attitudes toward, opioid overdose response. Consistent with these aims, the objective of this K01 proposal is to enable the candidate to gain expertise in, and fill gaps in the literature on, the role of family/household members in overdose prevention. The proposed mentoring from renowned scholars at Arizona State University, as well as coursework in data analysis, clinical trials, cultural adaptation, and intervention evaluation methodologies, will enable the candidate to develop an independent research career centered on reducing drug overdose deaths, especially in populations at disproportionate risk.

NIH Research Projects · FY 2026 · 2026-05

Summary Objective: This study aims to determine whether micro- and nanoplastics (MNPs) accumulate in the human brain, evaluate their relationship with Alzheimer’s disease (AD) pathology, and explore whether environmental disadvantage, measured by the Area Deprivation Index (ADI), is related to variation in cerebral MNP burden. Rationale: MNPs are widespread environmental pollutants with emerging evidence of human tissue accumulation and potential neurotoxicity. Preliminary data show detectable MNPs in the brains of individuals with AD and progressive supranuclear palsy. Social disadvantage may increase exposure to environmental risks, potentially elevating MNP burden and susceptibility to neurodegeneration. Aims: 1. Quantify MNPs in the olfactory bulb (OB) and middle temporal gyrus (MTG) of 140 postmortem human brains (70 with AD pathology, 70 without AD pathology) using five complementary detection methods. 2. Assess associations between cerebral MNP burden and AD pathology, adjusting for age, sex, APOE genotype, postmortem interval (PMI), and other covariates. 3. (Exploratory) Examine the relationship between ADI and cerebral MNP burden, investigating whether MNP burden varies by level of socioeconomic disadvantage. Innovation: This study employs state-of-the-art environmental toxicology methods rarely applied to human brain tissue, integrated with high-resolution neuropathology and life-course social determinants data. It represents the largest and most methodologically rigorous study of cerebral MNPs to date, and the first to directly examine their links to AD and environmental disadvantage. Significance: Findings could identify a novel, modifiable environmental contributor to AD, inform targeted public health interventions, and advance our understanding of how plastic pollution and social disadvantage may shape brain disease. Impact: By bridging environmental science, neuropathology, and social epidemiology, this study could redefine how we think about environmental risks in neurodegeneration. Demonstrating a link between MNP accumulation, AD pathology, and social disadvantage would establish a new line of inquiry with major implications for public health, regulation, and disease prevention.

NIH Research Projects · FY 2026 · 2026-05

SUMMARY Cell therapies are a promising alternative therapy for the treatment of type 1 diabetes, and stem cell-derived insulin secreting beta cells (sBC) have demonstrated the feasibility of restoring insulin independence in clinical models. However, this strategy has limited long-term application due to the requirement of ineffective and toxic immunosuppressive drug regimens and immune rejection, which currently limits the applicable patient pool to high-risk patients. The leading commercial entities clinically testing stem cell-derived islet replacement products are pursuing macroencapsulated cell delivery methods to overcome this critical hurdle to translation. Macroencapsulation devices can blunt immune responses to the graft and confer the safety benefit of cell delivery in a single, retrievable device. However, functional clinical success of these devices has not been demonstrated to date due in part to inevitable antigen shedding resulting in indirect antigen recognition, which results in immune destruction of encapsulated cells. Thus, synergistic immunomodulatory approaches are necessary to fully immunoprotect encapsulated cell grafts, and achieve immunological tolerance in the absence of immune suppression. The fetal-maternal interface is a robust model of immune tolerance toward allogeneic tissue, where placental trophoblasts maintain tolerance by two main approaches: (1) presenting an inert surface to maternal immune cells, a strategy akin to cell encapsulation which blocks direct antigen recognition; and (2) through secretion of tolerogenic factors which induce tolerance toward fetal antigens that escape the placenta. Our preliminary data demonstrates that a macroencapsulated tolerogenic trophoblast cell therapy can evade rejection and delay rejection of bystander macroencapsulated cell grafts in a challenging xenotransplant model. In this proposal, we aim to (1) validate our preliminary studies using translatable cell sources of sBC and trophoblasts, and (2) elucidate the immunological mechanisms of trophoblast cell therapy-induced tolerance in xeno and humanized allogeneic transplantation models. This will be addressed in three Specific Aims: (1) Identify immune mechanisms of trophoblast cell therapy-induced transplant site-dependent graft tolerance, (2) Optimize and characterize tolerogenic cell therapy dose impact on tolerance induction, and (3) Untangle the contributions of antigen-specific and non-specific mechanisms of trophoblast cell therapy tolerance induction. In this work, we expect to identify the immunological mechanisms by which tolerogenic trophoblast cell therapies delay or prevent immune rejection.

NIH Research Projects · FY 2026 · 2026-05

Project Abstract Alcohol use and a variety of other attitudinal, behavioral, and cognitive variables are reliable predictors of sexually aggressive behavior (SAB). However, studies using longitudinal designs have not typically examined within-person risk factors for SAB that are unconfounded by between-person variability, even though within- person risk (and protective) factors that covary with SAB perpetration are likely to be the most effective prevention/intervention targets. Although a small number of daily diary or ecological momentary assessment (EMA) studies have disaggregated within- from between-person risk for SAB, very low base rates of SAB (~5- 8% past year) create significant challenges for this approach. The current study will address these challenges and gaps in the literature by disaggregating between- from within-person risk factors for SAB using a longitudinal burst design, and by looking at non-contact SAB as well as contact SAB. Collecting data across multiple EMA bursts (e.g., every 6 months) will increase our power to detect effects at the daily level, as will the use of our newly developed measure of non-contact SAB that has a higher base rate (~40% past year) and correlates reliably with contact SAB. At the daily level, we will examine the effects of alcohol consumption and drinking context on SAB, as well as the potential mediation of these relations by sexual arousal and key protective factors: Protective Behavioral Strategies (PBS) for SAB, risky sexual behavior, and heavy episodic drinking (HED). The PBS findings may have important implications for prevention and early intervention as PBS for HED have been identified as an important target of effective prevention/early intervention approaches. We also will examine partner type (new vs. existing), cannabis use, and sexual judgement and decision- making (JDM) as potential moderators. Moreover, we will compare the magnitude of the mediated and moderated effects for non-contact and contact SAB. The focus on day-level moderators and mediators will identify important contexts for (i.e., sex with a new partner, co-use of alcohol and cannabis) and targets of `in- the-moment' interventions (i.e., sexual arousal, PBS). Finally, at the burst level, we will determine whether noncontact SAB prospectively predicts contact SAB, while controlling for prior contact SAB, which could greatly inform theory and prevention efforts. We will accomplish these goals by recruiting a sample of 300 male college students (ages 18-20) to complete traditional survey measures and 28 days of daily assessments (EMA) bi-annually (4 total surveys and EMA bursts). Multilevel models will disaggregate between- and within- person effects and examine main effects and moderated and mediated effects at the daily level. The ultimate goal of this work is to inform the development and refinement of prevention programs designed to reduce SAB. MPIs Corbin and Treat recently completed a study examining the efficacy of a computer-delivered prevention program combining cognitive retraining and normative feedback (NIAAA R34 AA027713) and are therefore well positioned to translate the daily-level findings to ecological momentary intervention efforts.

NIH Research Projects · FY 2026 · 2026-05

Project Summary/Abstract Many biological analytes of interest to both clinical oncologists and cancer researchers are unstable when the unfixed biospecimens in which they reside are exposed to thawed conditions. For example, American Society of Clinical Oncology / College of American Pathologists guidelines state that the post-excision-up-to-fixation exposure time span for tissues collected for clinical HER2 testing in breast cancer must be less than 1 hour. For blood plasma/serum and many types of tissue specimens that are to be frozen, the proper cold storage temperature is well below the common laboratory freezer temperature of -20 °C. For this and many other reasons, every year improprieties and inconsistencies in pre-analytical sample handling and storage generate unacceptably large numbers of costly false leads in biomedical research. Unsurprisingly, experts in the field agree that this problem must be minimized immediately. Currently there are few tools and not so much as one widely accepted approach by which to implement evidence-based tracking of biospecimen exposure to thawed conditions. In practice, it is actually quite rare for biomedical researchers to employ any evidence-based QA/QC tools at all—which suggests that easy-to-use, individual aliquot-level thawed-state indicators could have a major impact on improving biospecimen quality tracking and therefore actual biospecimen quality. In 2022, the PI’s lab was awarded an R21 grant through the NCI’s IMAT program to pursue development of the kinetically unique, autocatalytic, color-changing permanganate/oxalate reaction in melting point-depressed aqueous solvents as simple (i.e., user friendly), inexpensive, visual trackers of biospecimen exposure to inappropriately warm conditions, including temperature thresholds as low as -18 °C, -37 °C and -67 °C. The chemistry for 14 targeted time-temperature indicators (TTIs) has been successfully developed. Under this proposed project, the PI’s lab seeks to maximize the color intensity of the TTIs (advanced development) and to develop and validate user-friendly, self-contained, customer-activatable physical devices that will ultimately translate the unique chemistry that underpins the TTIs into market-ready products that provide aliquot-level color-changing indicators of biospecimen exposure to thawed or inappropriately warm conditions that make it essentially impossible for anyone handling the specimens to ignore their integrity status. This will be accomplished under two Specific Aims: Specific Aim 1: Leverage our recently developed, AI-enabled chemical kinetics simulations to develop and validate permanganate/oxalate reaction-based TTIs with maxed-out, 5x color intensity that run for as little as 5 minutes to as long as 2.5 hrs at 25 °C—and that have melting points of 0 °C, -18 °C, -37 °C, or -67 °C. Specific Aim 2: Develop and performance-test several physical device designs that will provide self-contained, aliquot-level, user-activatable, color-changing TTI devices that anyone can use to track the exposure of biospecimens to thawed / inappropriately warm conditions.

NIH Research Projects · FY 2026 · 2026-05

Project Summary/Abstract Under the auspices of R24 grant AG073138 (in response to RFA-AG-21-003), we have developed a highly innovative model of Alzheimer’s disease (AD) and related dementias (ADRD) based on intracortical injections of an AAV carrying an aggregation-prone isoform of human tau containing two mutations (AAV-2xTau) into the entorhinal cortex (ERC) of adult macaques. During this funded application, we have comprehensively characterized this model at multiple levels of resolution across several time points (6 weeks, 3 months, and 6 months), including local patterns of tau biochemical progression (from normal tau to neurofibrillary tangle formation, including multiple hyperphosphorylated pre-tangle intermediate species). We identified a window of cell loss in the medial temporal lobe, with little to no cell loss up to 3 months, but extensive thioflavin S expression with neuronal loss by 6 months post-treatment, providing a known therapeutic window for future experiments. We associated these changes with markers of inflammation with microglial infiltration occurring early and astrogliosis occurring later in the preclinical disease process. Critically, we observed a time-dependent permissive templating of pathology across the ERC connectome, which by 6 months includes both hippocampal and neocortical propagation of misfolded proteins in a pattern resembling what is seen in AD. We have also seen changes in both CSF and blood biomarkers that identified tau isoforms, neurofilament light chain changes, inflammatory markers, as well as reductions in brain-derived neurotrophic factors just as seen in human AD. Finally, we observed widespread neuroimaging changes on MRI and PET changes following gene delivery of AAV-2xTau. The theme of this new application is to further assess gene delivery of AAV-2xTau but now in aged monkeys (>22 years old), which models individuals with AD and other tauopathies more accurately. Since the R24 grant is not renewable, we have been told by NIA leadership we should continue this program using an RO1 mechanism. We will compare the data collected in the aged monkeys to adult monkeys that were identically treated and from whom brain sections, as well as serum and CSF samples, remain available. Thus concomitant analyses from adult and aged animals can take place without confound. Additionally, we will assess AAV-double mutant tau treated adult and aged monkeys using powerful quantitative neuroanatomical techniques examining early cellular and synaptic events reflecting the initial progression of tau-based neuropathology, including cellular events reflecting disruption of the cytoskeleton, spine loss across the dendritic tree, and detailed analyses of affected synapses/connections.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY Overdose deaths remain a significant public health problem in the US. Arizona overdose mortality data show seasonal variation with significant surge in overdose deaths in the summer months. Despite increasing concerns about the health impacts of environmental heat, there has been a limited understanding of how extreme heat conditions interact with drug-related risks and associated psychosocial vulnerabilities. Given rapidly increasing frequency of extreme heat events in the US and globally due to climate change, there is an urgent need to generate actionable data on the intersection of environmental heat and dug use-related risks to develop effective policies and harm reduction interventions. The overarching goal of the proposed multi-PI R01 study (NOT-ES-22-006: Notice of Special Interest: Climate Change and Health) is to investigate the association between environmental heat and drug overdose- related risks among persons who use drugs in Phoenix, Arizona, America’s hottest metropolitan area. Our multidisciplinary team includes researchers from ASU College of Health Solutions, Urban Climate Research Center, and School of Social Work, along with the key community partners including the City of Phoenix Office of Public Health, Arizona's Medicaid agency (AHCCCS), and Southwest Recovery Alliance, a grassroots harm reduction organization. The proposed study builds on a mixed-methods approach and innovative integration of a) big data analytics of Arizona Medicaid and hospital discharge data on drug-related emergency department visits and death certificate data on overdose deaths (2017-2025), along with high-precision climate data, b) in-depth, qualitative interviews with persons who use drugs (N=80), and c) key stakeholder focus groups (N=30) to provide a comprehensive and multi-faceted assessment of heat-related risks and impacts on people who use drugs in Metro Phoenix, Arizona. Specific aims are: Aim 1: Leverage big data analytics to identify the specific urban heat characteristics, person-level and housing factors, and mediating effects of service use that impact fatal and non-fatal drug-related overdose and hospital events in the Phoenix metro area. Aim 2: Through in-depth, qualitative interviews (N=80), characterize how individuals who use drugs perceive, experience, and navigate heat-related risks in the context of their daily drug use practices, access to services, and other structural and social vulnerabilities. Aim 3: Identify priority intervention and policy response strategies to address the heat-related risks for persons who use drugs through focus groups with key stakeholders (N=30), including public health practitioners, treatment providers, harm reduction coordinators, and other service providers and policymakers. The study is highly significant because it will provide actionable data on the intersection of environmental heat and drug-related risks to help identify key needs and potential solutions in the context of climate change.

NIH Research Projects · FY 2026 · 2026-01

PROJECT SUMMARY/ABSTRACT Many evidence-based preventative interventions have been developed to prevent substance use, physical and mental illness, and promote positive educational and social outcomes among adolescents. Among these, caregiver-mediated interventions boast strong effects that are mediated by effective parenting skills. However, the impact of these interventions is severely limited by low rates of home practice of intervention skills among caregivers. To address this research-to-practice gap, researchers have been investigating barriers and facilitators of caregiver engagement, focusing in large part on intervention attendance. Strategies for increasing caregivers' home practice of skills remain underexamined. Yet, caregiver home practice is a key component of theorized intervention effectiveness and has been found to impact parenting behaviors and subsequent child outcomes over and above that of attendance. Therefore, the next important step in supporting parenting behavior change is to develop implementation support strategies for evidence-based interventions that target caregiver home practice specifically. This K01 Mentored Research Scientist Development Award will develop and pilot a digital behavior change intervention for use as an adjunct to an evidence-based preventative intervention. The digital behavior change intervention aims to increase caregivers' home practice of intervention skills. Informed by the theory of planned behavior, habit formation principles, and relapse prevention theory, the intervention will leverage mobile health technologies (mHealth) to circumvent and problem solve common barriers to home practice including home practice intention, frequency of practice, home practice competence, and maintenance of intervention skills. The intervention will be developed as a smartphone application (i.e., “app”) with components informed by a qualitative assessment of barriers to caregiver home practice and refined through direct stakeholder input on design requirements to optimize acceptability and feasibility. The intervention will be piloted with 48 caregiver participants as an adjunct to Bridges, an evidence-based intervention for adolescent substance use prevention and mental health promotion. Findings from this project have the potential to improve caregiver home practice, intervention engagement broadly, and ultimately boost effectiveness and public health impact of numerous caregiver- mediated interventions. In response to NOSI NOT-OD-23-031, this administrative supplement seeks the support of personnel to support the continuation of proposed project activities (e.g., participant recruitment, qualitative and quantitative data collection, pilot trial of the digital behavior change intervention) within the original timeline. No changes have been made to the aims, goals, or scope of the work proposed in the funded K01 application.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Early life exposures play a significant role in shaping health and disease susceptibility. Yet, our understanding of the developmental programming of adult stem cells that maintain tissue homeostasis is limited. Mature adult intestinal stem cells (ISCs) sustain continuous life-long adaptations to diet and the intestinal microbial milieu to preserve tissue stability and prevent sequelae leading to diseases such as inflammatory bowel disease (IBD) or sporadic cancer. ISC’s developmental trajectory is influenced early in life by a maternal environment that provides extrinsic patterning cues and nutrients to influence cell, tissue, and system maturation. Despite the fundamental nature of these developmental phases, we do not understand how durable programmable molecular mechanisms are established or how adverse maternal environmental exposure is maintained in a stable and homeostatic manner within ISCs. There is a critical need to establish how the environment contributes to intestinal homeostasis and long-term disease risk. Using genetically engineered mouse and organoid models, this project aims to distinguish ISC developmental programming and determine both early intrinsic adaptations and extrinsic environmental interactions that promote establishment of a stable pre- pathological ISC ground state. Our central hypothesis is that offspring exposure to an obesogenic maternal environment during pre- and postnatal development establishes a maladaptive pre-pathological ground state ab initio. In Aim1 we will characterize the extent of altered ISC changes in offspring exposed to maternal pro- obesity high-fat Western diet (HFD) during pre- and postnatal phases of maternal dependence, and test the duration that these features exist as offspring age. We will further challenge offspring with the reintroduction of the HFD and test for pathological states. In Aim2, we will investigate how lipid metabolism drives ISC- programming by testing for necessity of lipid regulators, Ppar-d and Ppar-a, and for sufficiency with increased PPAR-d activity. In Aim3, we will explore the role that external signaling from the immune system contributes to developmental programming and later risk of disease. We will test the necessity of pro-inflammatory cytokine IL-17 and the influence in tumorigenesis and inflammatory states. In summary, these efforts will enhance our understanding of how developmental programming in early life leads to health and disease disparities as we age.

NIH Research Projects · FY 2025 · 2025-09

More than 1 in 10 mid-life (age 35-64) Americans have mobility impairing disabilities, this is especially so for women who have higher prevalence than men. Mid-life is a critical window for women to enhance healthy aging, by improving health and reducing cardiometabolic (CM) risk. The higher prevalence of daily stress encountered by mid-life women with mobility impairment has been linked to emotional health and CM disease risk factors, such as excess abdominal fat that can lead to premature mortality. This is especially so for women with mobility impairment (WMI) who have higher prevalence of mobility impairment, excess body fat, higher risk for cardiometabolic risk than men, and are typically not eligible for most interventions that involve vigorous PA. Our work combines two forms of low intensity PA meditative movement, Tai Chi and Qigong (TCQ), in a mind-body practice described in our model, Biobehavioral Model of Effects of TCQ on Body Composition. TCQ can be completed in a seated position and has been tested in non-impaired populations, consistently showing improvements in body composition, as well as stress related factors and associated dynamics (neurophysiological and hormonal) associated with abdominal fat in women. Our own preliminary study using TCQ with WMI provides evidence of reduced abdominal fat. Reduced stress in response to TCQ is directly observed as changes in heart rate variability and cortisol, reductions in reported emotional distress, and behavioral indicators of emotional eating and sleep quality. These all contribute to excess abdominal fat (measured as waist circumference WC) and strongly associated with cardiometabolic risk. Our team brings singular expertise in the proposed TCQ intervention to be implemented, measures, and engaging with WMI. Building on our extensive experience working with our partners, we propose to recruit a nationally representative, diverse sample (final N=196) of WMI (age 35-64) who have a waist circumference >83 cm (benchmark of cardiometabolic risk). We will randomize women to a 12-week, online, on-demand TQG intervention or health education video (HEV) control, with assessments at baseline (T1), immediately post- intervention (12 weeks; T2), and at a 24-week follow-up (T3) to determine the efficacy and sustained effects of the TCQ intervention. We hypothesize that TCQ participants will experience (T2) and sustain (T3) significant improvements in WC, heart rate variability (increased high frequency power) and salivary diurnal cortisol (decreased area under the curve) (primary outcomes). We also expect that TCQ participants will experience (T2) and sustain (T3) improvements in self-reported perceived stress and emotion regulation, depressive symptoms and anxiety, emotional eating and sleep quality (secondary). Last we will explore a model of biobehavioral mechanisms by which TCQ may reduce abdominal fat via physiological and behavioral pathways. If efficacious, TCQ could have high impact improving accessible strategies to reduce stress responses and abdominal fat as well as reducing CM risk and improving healthy aging among WMI.

NIH Research Projects · FY 2025 · 2025-09

Hispanic/Latino older adults are 1.5 times more likely to develop Alzheimer’s disease (AD) than White non-Hispanic older adults, yet they are diagnosed substantially later in the disease process, missing the early-stage window in which emerging therapies are most effective. Furthermore, they are excluded from AD clinical trials at nearly twice the rate of White non-Hispanic participants, often for being considered as too progressed. Although these disparities exist for a number of reasons, a contributing factor is that existing tests that are feasible for use in primary care to screening patients for the early signs of AD show worse diagnostic accuracy for Hispanics/Latinos, even when using normative data and controlling for differences in education. Thus, there is an urgent need for more universal screening tools, especially in preclinical stages of AD. The long-term goal of this research is to develop convenient methods for assessing and screening patients for AD risk across varying demographics. To meet this goal, an objective behavioral test has been newly developed that is associated with cognition and measures daily functioning, and has been shown to be sensitive and specific to AD staging. The brevity and simplicity of the test make it an ideal assessment to be paired with emerging blood tests for screening and monitoring in primary care. The central hypothesis is that the novel test (herein, bean game) proposed here will not vary significantly between Hispanic/Latino and White non-Hispanic adults within the current AT(N) framework of AD, and may be more acceptable, appropriate, and preferable than traditional cognitive tests. The overall objective of this R01 application is to leverage the existing MindCrowd electronic cohort to test this hypothesis. MindCrowd was developed to improve accessibility and inclusion in AD research, and collects lifestyle, health, cognitive, genetic, and medical history data via the internet to study AD risk. The latest MindCrowd cohort has an average monthly recruitment rate of 901 Hispanic/Latino adults over age 40. Consistent with the general U.S. population, 19.5% of the current MindCrowd cohort over age 40 identifies as Hispanic/Latinos, with countries of origin similar to the general Hispanic/Latino population, providing sufficient samples sizes for pursuing the proposed aims. In addition, the research proposed in this R01 application is innovative and rigorous because it utilizes an affordable version of the novel test that can be self-administered in-home and that is offered in English and Spanish, opening up alternative applications outside of primary care. Thus, the proposed research is significant because it offers a more universally applicable alternative to existing assessments used in AD care and research, which will lead to a clearer and more accurate understanding about AD.

NIH Research Projects · FY 2025 · 2025-09

Primary goal of this project is to significantly elevate the positive predictive value (PPV) and sensitivity of exercise stress electrocardiography (ESE) in assessing obstructive coronary artery disease (CAD), defined as > 50% stenosis in at least one major coronary vessel identified by invasive coronary angiography (ICA), across pretest cardiac risk spectrum using an expert-AI collaborative approach. We leverage a large, harmonized ESE dataset correlated with ICA of a broad range of patients from three major cardiac care sites in USA (via Mayo Clinic Integrated Stress Center (MISC)) to develop an automated CAD likelihood determination technique from ESE with uniform performance across age, sex, race, socio-economic status (SES) and CAD co-morbidities. This will benefit a key synergistic ongoing effort in wearable electrocardiography (ECG) CAD risk monitoring by this team via Arizona New Economy Initiative’s (NEI) for a healthy US workforce. Despite lower prevalence, women are marginally less likely to die from cardiovascular diseases than men and are likely to have poorer prognosis. ICA, after initial coronary computed tomography angiography (CCTA) triage, is the gold standard for CAD diagnosis, however, it is expensive and cannot be used frequently on individuals with high SES deprivation index. On the other hand, CAD risk estimation with clinician review of low-cost non-invasive ESE show poor PPV in men (77%) and even poorer in women (47%) in population with nearly similar prevalence across sex (0.36 in men vs. 0.33 in women). An accurate unbiased automated CAD risk determination method from ESE can potentially pave the way for continuous CAD risk assessment through mobile monitoring using wearable ECG for a broad range of clinical and general population. The ASU-Mayo research team have developed CAESER (Computer Aided Exercise Stress ECG Reader), that can automatically analyze ESE and provide likelihood of CAD. CAESER adopts precision cardiology approach, where baseline ST depression is captured by a personalized digital twin, which is integrated to continuous CAD risk assessment through a transformer based deep learning architecture. The first aim is to evaluate the performance of CAESER as compared to ICA evidence of CAD across large scale symptomatic patient population. CAESER will be tested on 40,000 ICA correlated ESE cases from the MISC repository as well as independent secondary dataset from Physionet. The second aim is to evaluate the variance in performance of CAESER across gender, race and SES. The performance of CAESER developed in AIM 1 will be evaluated for variance across sex, race and area deprivation index (ADI) using metrics such as precision, sensitivity, specificity, area under the curve of ROC. Using a multi-variate logistic regression model, the variance of CAESER performance metrics with respect to the ADI percentile of patients will be evaluated for statistically significant correlation. CASER can provide low- cost continuous CAD risk monitoring to underserved population of USA including American Indians whose CAD risk is over 20% the national average.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY This project aims to develop new scalable nD cellular and unicellular organism imaging and analysis approaches to study the ‘rules of life.’ We propose to develop a novel multimodal imaging platform, blending fluorescence super-resolution and tomographic polarized light imaging. Paired with the proposed platform, we will provide an open-source suite of computational imaging tools to recover the dielectric tensor in multiple scattering samples using GPU acceleration. As part of these tools, we address optimal pattern generation, correct for phase drift, test against rigorous simulations, and integrate recent advancement in deep learning denoisers. We will benchmark the platform’s performance on two cellular motility projects. In the first project (Aim 2), we will quantify both 3D hydrodynamic flow fields surrounding motile bacteria using tomographic polarized light imaging and molecular cell fate markers using fluorescence. We then aim to demonstrate two unique measurements by quantifying the flow field and cell fate of motile bacteria near or at surfaces and near the edge of a swarming bacteria colony. In the second project (Aim 3), we will quantify for the first time the local 3D viscoelastic properties and applied forces for eukaryotic cells placed into collagen matrices. We will validate our measurements using known atomic force microscopy and standard 2D traction force measurements before attempting to generate self-calibrated 3D traction force microscopy data by quantifying the local viscoelastic environment surrounding the motile cells. Across all three aims, we intend to demonstrate a multimodal imaging platform that is easily adaptable and addresses critical needs as the community moves towards probing biology at the fastest rates possible.

NIH Research Projects · FY 2025 · 2025-09

Glyco-MAP: a high-throughput multiplexed platform for Glycosylated Mucin Antibody Profiling with glycoengineered cell lines expressing well-defined homogeneous glycostructures Abstract Early detection is critical to making inroads in the fight against cancer. Tumor antigens elicit tumor associated autoantibodies (TAAb) during early cancer development that can serve as markers for cancer early detection. However, the potential of TAAbs has not been fully realized because previous TAAb studies rely almost exclusively on proteins that lack post-translational modifications, partly due to the lack of appropriate technologies. Mucins are a class of heavily O-glycosylated proteins, whose expression and glycosylation are dysregulated in cancer, making them an excellent target for cancer biomarkers. We propose using mucins as model tumor antigens for the development of a high-through platform assaying TAAbs against glycosylated proteins, namely Glycosylated Mucin Antibody Profiling (Glyco-MAP). The complexity of mucin type O- glycosylation has historically posed challenges in dissecting different forms of endogenous glycosylated mucins. To this end, we will rely on a set of O-glycoengineered cell lines with homogeneous O-glycosylation capacities to express glycoproteins with defined O-glycan structures relevant to cancer. To screen many different glycoproteins in many samples we will use a new method, called Multiplexed In Solution Protein Arrays (MISPA), which combines immunoassays with next-generation sequencing (NGS) to simultaneously quantify hundreds of antibody-antigen interactions. MISPA can work with antigens from any protein expression system if they possess a HaloTag; however, so far it has been used predominately with in vitro expressed unmodified proteins. Glyco- MAP will combine glycoengineered cell lines and MISPA for systematic glycosylated mucin antibody profiling. HaloTagged human mucins will be expressed in O-glycoengineered HEK293 cell lines and covalently “barcoded” with unique DNA sequences. Barcoded mucins and TAAb from patients' sera will be subsequently immunoprecipitated. Individual sample indexing with unique DNA sequences added to protein barcodes, allows for the processing of many samples in parallel. Quantification of DNA barcodes on precipitated antigens and sample indexes using NGS provides a quantitative metric proportional to TAAb concentrations in each sample. Glyco-MAP enables the testing of TAAb abundance against many glycosylated mucins in thousands of patient samples with a single NGS run. We will analyze almost 1 million IgG and IgM antibodies in 400 patients with 2 major epithelial cancers and 400 cancer-free healthy controls against 40 mucins or glycoproteins with a mucin- like domain with 14 distinct glycoforms with cancer relevance. Our proposed study is a close collaboration between experts on proteomics technologies (Dr. Qiu) and glycobiology (Dr. Clausen). This profiling may find new early cancer biomarkers. Understanding the interaction dynamics of glycosylated proteins and how they change in disease is essential for elucidating cellular biology and disease mechanisms. Our study on TAAbs against glycosylated mucins serves as an exemplary application for studying general biological interactions dependent on glycans and unraveling the intricate interactions between the host and microorganisms.

NIH Research Projects · FY 2025 · 2025-09

The ability to retrieve biomarkers like heart and respiratory rates without disrupting a user's typical sleep environment can revolutionize sleep medicine, smart healthcare, independent living, and sleep health monitoring of cancer patients. Sleep health is closely tied to cancer risk, cancer prognosis, and health-related quality of life of cancer survivors. This need has driven an ever-growing interest in wireless remote sensing of biomarkers using WiFi signals or radars to monitor cardio-respiratory signals and thereby assess sleep quality, timing and duration. However, these technologies typically use a small number of antennas, limiting their spatial resolution. As a result, their performance can drastically deteriorate when a user moves, changes orientation, or when multiple people are present. This leaves wearable sensors as the main available non- intrusive privacy-preserving technology for sleep monitoring, but they require frequent user intervention and charging. To address these shortcomings, we will develop a smart wireless environment using multi-band reconfigurable intelligent surfaces (RISs). These surfaces are low cost, low power, and can arbitrarily redirect wireless signals. They are projected to play critical roles in next-generation wireless communication networks, ensuring widespread deployment. Hence, the proposed system aligns synergistically with the rollout of future wireless communication systems. By utilizing microwave RISs, we will retrieve users' low- resolution RF reflectivity maps by developing a comprehensive physics-based model for RIS-based computational imaging. This RF image is then interpreted using a novel multi-modal learning algorithm to detect and track regions of interest (e.g., the torso). A high-resolution wideband millimeter RIS is then used to focus on the user’s torso to retrieve breathing and heart rate with high spatial resolution. We will design and experimentally verify the novel hardware and processing algorithms required to implement such a smart wireless integrated monitoring (SWIM) system. We will demonstrate how multiple low-cost sensors in the form of multiband, high-resolution intelligent surfaces and off-the-shelf radars can collaborate and robustly retrieve critical cardiorespiratory biomarkers used to measure sleep without disrupting their daily routines. RELEVANCE (See instructions): The ability to monitor sleep by measuring breathing and heart rate using a smart system that uses wireless waves from the walls of the rooms can revolutionize sleep monitoring in people with cancer. Poor sleep may lead to cancer, and cancer treatment outcomes may be influenced by sleep including quality of life in survivors. We will build and test a smart wireless system called SWIM to monitor sleep easily. Such an approach will enable future sleep research for cancer prevention and treatment.

NIH Research Projects · FY 2025 · 2025-09

Glycosaminoglycans (GAG) are a family of large, linear, sulfated polysaccharides produced in mammals and other organisms. GAGs play diverse roles in tissue development/growth, inflammation, blood coagulation, viral infection, and amyloid plaque formation. As a result, GAGs have been used as biomarkers for many diseases. They are also the most widely used anticoagulant. Because of their biological activities, interest in structure- activity relationships of GAGs has always been high. However, due to their size, complexity, and heterogeneity, the analysis of GAG structures using conventional ensemble techniques is challenging. There is currently no method to sequence these important polysaccharides. We have been exploring single-molecule techniques for determining GAG structures for several years. Although work from us and other groups demonstrate that solid- state and protein nanopores can obtain some structural information on GAG polysaccharides, full sequencing of GAG by nanopore has not been realized because of a lack of translocation speed control. In this proposal, we want to develop a new single-molecule GAG sequencing method using fluorophore-labeled lysosomal GAG degradation enzymes. Our idea is inspired by fluorescence-based single molecule sequencing techniques for other biopolymers. These techniques utilize processive enzymes whose action on the polymer produces fluo- rescent signals that can be used to infer the sequence. We think lysosomal GAG degradation enzymes are perfect for this method. In particular, these enzymes processively degrade GAG from the non-reducing end (NRE) and each enzyme recognizes a specific feature of the NRE. As a result, the degradation of GAG proceeds through a set of enzymatic steps determined by the GAG sequence. This means the GAG sequence can be determined by the order in which enzymes bind the polymer. In this proposal, we want to develop such a se- quencing method by producing a set of lysosomal GAG degradation enzymes each with a unique fluorescent signature for identification. These enzymes will be used to degrade immobilized GAG chains while the unique fluorescence of each enzyme can be used to determine these enzymes’ binding order. This information can then be used to infer the GAG sequence. Because such a method requires no homogeneous samples, can sequence longer GAG polymers, and can provide high-resolution information, we think its realization will be a dramatic improvement over existing techniques. In particular, we want to complete the following two aims: 1) Design and produce fluorophore-labeled GAG degradation enzymes and use TIRFM to characterize the fluorescent signa- ture these enzymes produce when binding the correct immobilized substrates. 2) We will prepare a library of structurally defined GAG ligands and use the data obtained from aim 1 to determine their structures using these fluorophores labeled enzymes. Completing these aims will provide the crucial foundation for developing a gen- eral method for sequencing GAGs.