University Of Arizona

NIH Research Projects · FY 2026 · 2025-01

Summary Existing anti-fibrotic treatments for pulmonary fibrosis have not significantly improved survival. There is a critical need for new therapeutic approaches. Pulmonary fibrosis results from dysregulated lung repair and involves multiple cell types. The role of endothelial cells (EC) in lung fibrosis is poorly understood, even though lung fibrogenesis is associated with vascular remodeling, increased vessel permeability, hypoxia, partial loss of capillaries, focal increase in pathological angiogenesis and development of pulmonary hypertension. Our long- term goal is to develop clinically relevant approaches to correct EC dysfunctions, prevent loss of microvasculature, and slow down progression of lung fibrosis. Our preliminary data identify FOXF1 as a key transcription factor in pulmonary endothelial cell functions, down-regulation of which is indispensable for transition of normal lung EC into fibrosis-associated EC. We also demonstrate that FOXF1 transcriptionally activates R-Ras, a G protein from Ras family of GTPases, which is shown to be important for lumenization of newly formed microvessels and maintenance of EC barrier function in mouse models of muscle ischemia and cancers. Our central hypothesis is that lung EC-specific nanoparticle delivery of FOXF1 or R-Ras or transplantation of FOXF1+cKIT+ endothelial progenitor cells (EPCs) will improve lung microvascular integrity and inhibit the progression of pulmonary fibrosis. To test the hypothesis, we propose two specific aims: (1) to determine whether restoring microvascular integrity via nanoparticle gene therapy will inhibit lung fibrogenesis, (2) to define whether transplantation of FOXF1+cKIT+ EPCs will restore microvascular integrity and inhibit lung fibrosis. Altogether, nanoparticle gene therapy or cell transplantation with FOXF1+cKIT+ EPCs have translational potential in IPF and other pulmonary diseases associated with fibrosis.

NIH Research Projects · FY 2025 · 2024-12

ABSTRACT: Patients with wakefulness during the biological nigh frequently experience emotional dysregulation (e.g., negative affect, hopelessness) and cognitive dysregulation (e.g., impaired decision-making, impulsivity) that increase the likelihood of engaging in unhealthy behaviors. Consistent with this observation, meta-analyses indicate that sleep disruption triples suicide risk. Our group discovered that suicides are 3-4x more likely to occur between 2-4am than would be expected by chance. We have replicated this finding multiple times using both experimental and epidemiological data, demonstrating a relationship between nocturnal wakefulness and suicide ideation within individuals and across demographics, seasons, comorbidities, and depression status. This phenomenon may be explained by the “Mind After Midnight” hypothesis: Wakefulness during the biological night exposes the individual to enhanced negative affect, a reduced ability to make healthy decisions, and a level of disinhibition that enhances impulsivity. This occurs due to a confluence of factors related to the normal regulation of sleep, wakefulness, and circadian rhythms. If correct, this phenomenon would represent a transdiagnostic process applicable across the behavioral spectrum and partially explain why aberrant behaviors are more likely to occur at night or after sleep loss. Although we have ample cross-sectional data from the community, and laboratory-based feasibility data, our hypothesized model requires an experimental study to support mechanistically-informed treatments that reduce this modifiable suicide risk. The proposed experiment will be the first study of mood, neuropsychological function, and suicidality that probes both chronobiologic and homeostatic factors. This project will utilize an approach that can be used with subsequent neurophysiologic studies across a wide variety of conditions with similar features of impulse dysregulation, especially those occurring at night. To successfully execute this transdiagnostic, translational, and RDoC-responsive proposal, we will recruit n=90 adults with a history of suicide ideation in the past 6 months to complete a protocol that involves both in-lab and at-home components. This study includes a laboratory-based assessment (AIM 1) of whether suicide-associated cognitive processes (irrational and risky decision making, delay discounting) and affect (negative mood, hopelessness, suicide ideation) are greater at 2-4am, compared to other times of the day, within individuals. To examine the role of homeostatic sleep pressure on cognitive performance and dysregulated mood (AIM 2), we will examine individuals in two conditions at 2-4am: under high sleep pressure (kept awake until 2am) and low sleep pressure (allowed to sleep and awakened at 2am). To examine the role of circadian rhythms (AIM 3) in the model, we will capture ecologically-valid circadian (behavioral: amplitude, chronotype, regularity; and physiologic: melatonin) phenotyping data. The results from this experiment will advance the fields of circadian science and suicide prevention though an improved understanding of the physiologic mechanisms driving elevated suicide risk during the biological night.

NIH Research Projects · FY 2023 · 2024-12

Project Summary Project Summary: Bile acids (BAs) are synthesized from cholesterol. BA synthesis is tightly controlled to prevent incidence of diseases, such as cholestasis, gallstone disease, malabsorption, hypercholesterolemia, etc. BAs are important for nutrient absorption and also function as endocrine hormones to regulate metabolic homeostasis. BAs can activate farnesoid X receptor (FXR) and TGR5 to prevent non-alcoholic fatty liver disease (NAFLD), diabetes and obesity. NAFLD is one of the most common chronic liver diseases worldwide, and is often associated with obesity and diabetes. Forkhead box protein A3 (FOXA3) is a transcription factor. So far, the role of hepatic FOXA3 in BA metabolism is completely unknown. Using both gain- and loss-of-function approaches, we show that FOXA3 is regulated by FXR and may regulate BA metabolism and metabolic homeostasis. In this project, we plan to investigate the role of hepatic FOXA3 in feedback regulation of BA metabolism and the role of BA signaling in FOXA3-regulated metabolic homeostasis. We will use a number of genetically modified mice as well as gain-of-function approaches to accomplish our goals.

NIH Research Projects · FY 2026 · 2024-12

Summary Mutations in genes that encode the proteins of the cardiac sarcomere are a primary cause of hypertrophic cardiomyopathy (HCM). HCM represents the most common genetic cardiac disorder and is characterized by a complex and progressive clinical course exhibiting broad phenotypic variability and, for patients carrying mutations in sarcomeric genes in particular, significant morbidity and mortality. Recent longitudinal studies have begun to define the natural history of HCM and revealed a “preclinical” stage in genotype-positive cohorts. Before the availability of genetic testing the majority of patients presented with significant symptoms and late stage cardiac remodeling, thus limiting their response to treatment. The ability to identify patients before the onset of irreversible HCM opens a therapeutic window whereby genotype- positive, phenotype-negative patients can be treated before the onset of pathogenic remodeling and thus perhaps change the natural history of this lifelong disorder. This goal will require the ability to precisely identify primary disease mechanisms at the level of the complex and dynamic cardiac sarcomere. An enduring clinical challenge in HCM remains the treatment of patients with diastolic dysfunction (impaired left ventricular relaxation) which manifests as shortness of breath, often with minimal exertion and is one of the most common manifestations in this otherwise diverse disorder, thus representing a significant unmet need. To date, our group has focused on mutations in the regulatory thin filament and developed a program that combines structural biophysics with in vitro experiment, in vivo animal models and an experimentally validated all-atom computational model of the cardiac thin filament (cTF). As the thin filament is the primary arbiter of cardiac relaxation at the molecular level we now propose to apply our integrated approach to first, in Aim 1, fully characterize (at the atomic level) three specific functional domains of the cTF linked to the regulation of relaxation, determine the mechanistic effects of known cTnT mutations on these domains and second, in Aim 2 use this information to design Fluorescence-based High Throughput Screens to identify, validate and test in vivo (via existing cTnT and MyHC– linked HCM mice) novel small molecule modulators of diastolic performance. Successful completion of these studies will not only provide new knowledge regarding thin filament function and regulation, it will also provide a proof of principal approach to the targeting of the cardiac thin filament that can be applied to other sarcomeric disorders.

NSF Awards · FY 2024 · 2024-12

This is a collaborative project examining how large-scale population history of ancient peoples corresponds to changing political-religious institutions of prehistoric Indigenous societies. Archaeological reconstructions of past population numbers rely on changes in the number of houses in a particular time period and archaeologists understand that community solidarity and institutional power was often expressed by monumental construction, specifically earthen platform mounds. Currently, the time periods used by archaeologists to constrain events such as village construction and mound building in one region have uncertainties ranging from several decades to a century. This uncertainty is broader than human timescales of years to decades in which hypotheses for institutions are framed. This is a persistent problem for archaeologists who are interested in addressing major problems associated with the origin and evolution of human institutions and political change. This project revises the timeline for population history and monumental construction by systematically redating wood and charcoal recovered from archaeological sites nearly one hundred years ago. New techniques for tree-ring dating and radiocarbon calibration enable much high-precisions than ever before, approaching annual precision in favorable cases. The scientific outcome of this project is new high-precision radiocarbon and tree-ring data, and statistical models for the pace of population change and the history of institutional development in the study area. Another objective of this project is to provide independent temporal data to direct descendants that empower their own historical narratives. Therefore, an important broader impact of the study is the inclusion of descendant communities in the research. This is accomplished by including knowledgeable descendant collaborators in project planning and creating an undergraduate research opportunity for students in STEM or humanities majors. Participants have the opportunity to assist in the research and explore an independent project compatible with their interests and career goals. 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 · 2024-12

The broader impact of this I-Corps project is based on the development of a software tool used for verification strategies in systems engineering. This project introduces a software tool designed to optimize verification strategies within complex systems such as satellites, automobiles, and autonomous vehicles. This innovation is able to enhance efficiency and reduce costs by automating the evaluation and optimization of complex verification processes. The technology aims to elevate the reliability and performance of systems through a refined approach, thereby reducing the likelihood of errors. The scalability and adaptability of the technology make it well-suited to handle the increasing complexity of modern systems, with machine learning algorithms enabling it to evolve and improve over time. In addition to offering a competitive edge in the global market through the development of higher quality systems, the application also promotes sustainable engineering practices by minimizing waste and re-work. By enhancing the verification processes within systems engineering, this technology offers more reliable, efficient, and innovative system development. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The technology merges graph theory, data science, and machine learning to tackle the complexities of verification strategies in systems engineering. This research and development advances knowledge by applying theoretical concepts to practical challenges, enhancing the efficiency, reliability, and manageability of verification processes. The technology also advances the understanding of how computational techniques can augment human cognition and decision-making in the face of complex system dependencies. 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 · 2024-12

The broader impact/commercial potential of this I-Corps project is the development of an imaging biomarker technology for assessment of brain damage after stroke. Currently, stroke is a leading cause of disability and death worldwide with approximately 15 million new cases annually. Motor deficits occur in approximately 80% of stroke patients, and stroke survivors have a 200% increased risk of developing dementia. However, there is an unmet need for a stroke assessment tool for preclinical and clinical research as well as for clinicians evaluating stroke patients. The proposed technology is a noninvasive method for assessing post-stroke damage in the brain utilizing imaging. This stoke assessment technology may be used for both clinical diagnosis and therapy progress assessment in stroke patients, which may improve research and patients’ outcomes. This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of molecular imaging probes to identify fatty acid metabolism and protease activity in the brain to assess stroke damage and track healing. Following an ischemic stroke, myeloid cells in the infarcted region must clear a large volume of lipid debris due to the abundance of myelin within the brain. However, lipid processing mechanisms within these cells become overwhelmed, resulting in the formation of foam cells. Foam cells are dysfunctional, neurotoxic, and drive a chronic inflammatory response that contributes to secondary neurodegeneration in the weeks and months following stroke. Tracking foam cell formation and clearance would greatly facilitate the development of effective treatments. In addition, recent research has identified increased fatty acid metabolism and protease activity as hallmark features of foam cells in the brain after stroke. Molecular imaging probes have been developed to identify fatty acid metabolism and protease activity in the brain after stroke. These imaging biomarkers may be used to assess stroke damage and track recovery in preclinical and clinical research, as well as for clinicians evaluating stroke patients. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2024-12

Project Summary: Heart disease is the leading cause of mortality and is often preceded by pathological cardiac hypertrophy due to chronic hypertension and sustained increases in cardiac afterload. While initially an adaptive response to maintain cardiac output and systemic blood supply, pathological cardiac hypertrophy eventually leads to a decompensated state of heart failure (HF). The initial adaptive aspect of hypertrophic growth requires increases in protein synthesis, which must be balanced by adequate protein folding, and degradation of misfolded, potentially toxic proteins. Without this balance, cardiac myocytes cannot maintain protein homeostasis, or proteostasis, which threatens functional cellular integrity and viability. The endoplasmic reticulum (ER) is a central node in proteostasis, with ~40% of proteins trafficked through this organelle, underscoring the importance of ER proteostasis in the heart. An important feature of ER proteostasis is recognition and degradation of terminally misfolded proteins through ER associated degradation (ERAD). While ERAD canonically recognizes misfolded ER proteins, we have recently identified the first and only described non-ER substrate for ERAD, serum/glucocorticoid regulated kinase 1 (SGK1), a pro-growth, cytosolic (non-ER) kinase. Intriguingly, SGK1 is not misfolded, yet is targeted to the cytosolic face of the ER for proteasome- mediated degradation via ERAD and requires the ER E3 ubiquitin ligase, HRD1. Further, we have found that SGK1 degradation by ERAD is impaired in human hypertrophic heart failure and in a mouse model of pressure overload-induced heart failure. SGK1 promotes growth in cancer cells, and our work and others’ have demonstrated relevance for SGK1 in cardiac pathology, but none have investigated whether SGK1 is required for the development of pathological cardiac hypertrophy and if this is mediated by impairing its degradation at the ER via ERAD. Our hypothesis is that the cytosolic kinase, SGK1, drives pathological cardiac hypertrophy in the pressure-overloaded heart and that inhibiting SGK1 ubiquitylation at the ER slows its degradation by proteasomes, which increases SGK1 levels and enhances its pro-hypertrophic effects in the heart. We will address this hypothesis using primary cultured cardiac myocytes and mice subjected to pressure overload in the following specific aims: (1) Determine the effects of depleting endogenous SGK1 on cardiac myocyte hypertrophy; and (2) Examine the effects on cardiac myocyte hypertrophy of ectopically expressed wild type SGK1, or a degradation resistant mutant form of SGK1 that cannot be ubiquitylated but retains ER localization. Pursuit of these aims will determine whether SGK1 is a promising target in mitigating pathological cardiac hypertrophy and whether SGK1 degradation by non-canonical ERAD is an important mechanistic aspect of cardiac pathophysiology that can be modulated therapeutically.

NIH Research Projects · FY 2026 · 2024-11

Abstract Human papillomaviruses (HPVs) contribute to 5% of global cancer cases, with HPV-associated oropharyngeal cancers now surpassing cervical cancers in the United States, representing an epidemic. Notably, HPV16 is the leading cause of oropharyngeal cancers. Following infection, HPV maintains its genome in basal epithelial cells, exploiting cellular processes for replication via oncogene expression, while the balance between transformation and productive infection remains a crucial inquiry. To study the HPV16 lifecycle and address the role of HPV16 in oropharyngeal cancer, we generate primary tonsil-derived epithelial cells that maintain the HPV16 genome. For unclear reasons, it is technically challenging to generate these cell lines, creating a bottleneck for reproducible research in this area. To address this, we will develop molecular tools using primary epithelial cells from tonsillectomies, a physiologically relevant model for HPV16-driven oropharyngeal cancer. Aim 1 will develop a complementation assay to enhance the recovery of cells with episomal viral DNA. Furthermore, different HPV16 variants may exhibit varying oncogenic properties and replicative capacities in cell culture. In Aim 2, we will quantify lifecycle stages and tumorigenicity across HPV16 variant genomes using primary tonsillar epithelial cells. Despite technical hurdles, studying HPV16 in the lab is vital for understanding the viral role in the development of oropharyngeal cancer. Developing novel methods to select infected cells and discern variant-specific phenotypes promises to advance HPV research, aligning with the NIH mission and fitting the scope of an R03 proposal. Future research will use these tools to ask biological questions, compare and contrast viral types (e.g., HPV16 vs HPV18), study HPV16 variants further, and aid in understanding the role of HPV16 in oropharyngeal cancers.

NIH Research Projects · FY 2025 · 2024-11

Calorie restriction (CR), without malnutrition, is the most robust non-genetic intervention to promote longevity through metabolic improvements that delay aging in mice, rats, and primates. Most research aimed at understanding the mechanism by which CR slows aging has focused on insulin and its downstream signaling cascades. We have shown that glucagon, the counter-regulatory hormone to insulin, is essential for CR induced improvements in lifespan, improved metabolic function, and the activation of healthspan and lifespan associated nutrient sensing proteins. This suggests that glucagon is essential for CR to extend both healthspan and lifespan. Although the role of glucagon receptor signaling in aging has not been heavily investigated, the rigor of this work is supported by known effects of glucagon on downstream messengers that extend healthspan. Glucagon increases liver AMP Kinase (AMPK) activity, cyclic AMP (cAMP), and fibroblast growth factor 21 (FGF21), which promote healthy aging. Glucagon limits the protein kinase mechanistic target of rapamycin (mTOR) and IGF-1 bioavailability, which accelerate aging. Highlighting the significance of this proposal, Glucagon receptor agonists are entering the market for the treatment of diabetes and obesity and could be repurposed to promote healthy aging. To understand the potential impact of these agonists, we propose 2 aims using samples collected from CALERIE™ trial participants, to establish a key role of glucagon in CR improved aging. The studies proposed in this R21 create a unique opportunity to study glucagon physiology under long-term calorie restriction in healthy non-obese humans. Aim 1: Using samples collected from participants of the CALERIE™ trial at baseline, 12, and 24 months, we will measure fasted serum glucagon, GLP-1, and FGF21 concentrations, hormones that modulate aging and healthspan. We will assess glucagon sensitivity by calculating the glucagon-alanine index, an established biochemical marker of glucagon sensitivity in humans. Hypotheses: Serum glucagon and the glucagon-alanine index will be decreased, while serum FGF21 will be increased in calorie-restricted people, indicative of improved hepatic glucagon sensitivity. Serum GLP-1 will not be affected by calorie restriction. Aim 2: Assess the relationships of glucagon, the glucagon-alanine index, GLP-1, and FGF21 with markers of lipid homeostasis, glucose homeostasis, IGF-1 and the IGF binding proteins, and measures of whole-body energy homeostasis in CALERIE™ trial participants. Hypothesis: A decrease in fasted serum glucagon, the glucagon-alanine index, and increased FGF21 will be correlated with improved lipid homeostasis (decreased serum cholesterol and triglycerides), improved insulin sensitivity, decreased IGF-1: IGFBP1 ratio (indicative of decreased IGF-1 bioavailability), decreased body lipid, and increased whole-body energy expenditure and lipid oxidation, independent of serum GLP-1 levels.

NSF Awards · FY 2024 · 2024-10

This project aims to serve the national interest by establishing best practices in supporting a neurodivergent engineering workforce during their postsecondary education and early training. The project team plans to recruit and coach students with Autism Spectrum Disorder (ASD) on pre-employment and professional skills, such as communication, team dynamics, and creative problem solving. The team also plans to provide training and support to internship hiring and supervising managers in engineering internships to help them understand the assets of engineering interns with ASD, along with ways to support them. This project aims to measure the effectiveness and document the process of providing specialized career preparation for autistic engineering students. The team intends to measure and document strategies for supporting hiring and supervising managers to accommodate autistic employees. A greater understanding of both learning processes—that of the student with ASD and that of the prospective employer—will lead to improved practices in pre-vocational habilitation and cultivation of engineering identity, self-efficacy, and self-advocacy for engineering students with ASD. Research methods include pre- and post-surveying and qualitative interviewing of students and employers. The NSF IUSE: EDU Program supports research and development of projects to improve the effectiveness of STEM education for all students. Through the Engaged Student learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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

This project investigates recently discovered monumental hydraulic features at an important archaeological site. Through excavations and a series of analyses (e.g., soil and faunal), the project examines how a group of people that lacked political centralization or marked social hierarchies built large and complex hydraulic features such as reservoirs, embankments and possible canals. The project examines larger questions regarding human collaboration and expands knowledge of earlier societies’ organizational and building capacities. The research also expands the current understanding of monumentality and the emergence of complex societies. This study promotes international collaborations, provides training opportunities for graduate students, includes local people into the knowledge-building process, and contributes to public information through talks and museum exhibits. The study aims to establish: (1) when these monumental hydraulic features were constructed, (2) whether they were contemporaneous with other monumental constructions at the site; and (3) the functions these features served (e.g., ritual and aquaculture). To fulfill these aims the study excavates multiple areas at the site (e.g., an embankment, a lagoon shore, an artificial island and a monumental structure) and analyzes soil samples recovered from these as well as previous excavations. The study cores artificial reservoirs and the local lagoon to collect and analyze soil, shell and fish bone samples. 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

Plant phenology – the timing of plant life-cycle events, such as leaf growth, flowering, and fruiting – plays a fundamental role in shaping terrestrial ecosystems. The timing of plant phenology not only affects the fitness of individual plants, it also impacts the fitness and behaviors of organisms dependent on plants, which in terrestrial ecosystems includes nearly all animals, either directly or indirectly. Thus, changes in plant phenology can trigger dramatic, and sometimes devastating, consequences for ecosystems and human economic interests and health. Plant phenological data are therefore indispensable for understanding ecosystem function, detecting ecosystem changes, and predicting the impacts of ongoing climate and land use changes. Given the importance of plant phenology, continuing local, regional and national data collection efforts have generated large volumes of phenological data. However, these data are surprisingly heterogeneous, difficult to integrate, and thus remain largely inaccessible for broader research. At the same time, community science and specimen digitization infrastructure have produced massive, rapidly expanding collections of herbarium specimens and in situ plant photographs, which contain a wealth of virtually untapped historical and contemporary phenological information. This project will use machine learning approaches to extract phenological data from plant photographs and digitized specimens. These data will then be integrated with phenological monitoring resources to create an open access, global plant phenology database – Phenobase. During this project, one postdoctoral researcher and several graduate and undergraduate students will be trained in programming and data science skills. The goal of this project is to support community needs for generating and delivering high-precision, harmonized and semantically integrated plant phenological data at unprecedented taxonomic, geographic, and temporal scales, along with new tools to help scientists and the public engage with these data. To achieve this goal, this project will develop a global, standardized knowledge base by integrating different phenology observation networks around the world; expand this knowledge base by using computer vision (CV) techniques to generate new, high-quality phenological data from the rapidly growing collection of community-submitted plant photographs on iNaturalist and Budburst; add critical historical data by using similar CV techniques on herbarium specimens available through iDigBio and GBIF; develop tools for data query, access, and visualization delivered via the Web and as software packages; and foster compelling, community-driven use cases showcasing the use of Phenobase for new research and for public good. These approaches will not only meet current growth in imaging, but scale to meet continuing, exponential growth into the future. By weaving together phenologically relevant outputs from monitoring projects from around the globe, including the efforts of millions of community scientists, Phenobase will support and empower phenological research that is currently impossible. Results derived from this project can be found at http://plantphenology.org/. 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

Non-native species invasions are causing worldwide ecosystem degradation and economic loss, with average global economic costs exceeding 27 billion dollars per year over the past five decades. More urgently, both the number of non-native species and their impacts are projected to increase over the coming decades. For example, approximately an additional 1,500 non-native species are likely to establish in North America by 2050. Furthermore, the economic costs of biological invasions are predicted to increase threefold per decade. Government agencies, conservation organizations, and private citizens have spent significant resources to mitigate the impacts of species invasions, but the outcomes are far from satisfactory. One main reason is that we still do not have a holistic and predictive understanding of species invasion across scales. This project will compile an open-access, cross-scale database of species invasion centered around the datasets collected by the National Ecological Observatory Network (NEON). This database will be analyzed using advanced statistical methods to test theory on the relative roles propagule pressure, abiotic variables, and biotic variables on invasions for multiple taxonomic groups (plants, birds, and beetles) across spatial scales. Model results will be disseminated by building an online interactive application that can dynamically present and forecast risks of invaders at all NEON sites. This application will be updated automatically with new data to provide real-time management recommendations. One postdoctoral researcher and two undergraduate students will be trained in macrosystem biology, statistical, and data science skills during the project. The goal of this project is to test the relative importance of propagule pressure, abiotic variables (e.g., climate, land-use history), and biotic variables (e.g., species interactions) in driving species invasions across spatial scales in the context of community assembly. To achieve this goal, this project will improve the ability of phylogenetic generalized linear mixed model (PGLMM) to work with large datasets and then apply it to the integrated database of species invasions based on NEON to investigate patterns and mechanisms of biological invasions of different taxonomic groups across spatial scales. This project will address the following questions: 1) Do functional traits of non-native species interact with abiotic variables to determine their distributions? 2) Do biotic interactions between non-native and native species in the recipient communities affect the distribution of non-native species? 3) What is the relative importance of propagule pressure, abiotic variables, and biotic variables in determining the distribution of non-native species from local to continental scales? This project is jointly funded by the Division of Environmental Biology/Macrosystem Biology and NEON Enabled Science program and the Established Program to Stimulate Competitive Research (EPSCoR). 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

The overarching objective for this project is to realize novel optical and electronic devices using unprecedented spatial control of interlayer exciton (IX) flow and quantum tunneling in two-dimensional (2D) semiconductor heterostructures. An IX is a bound object consisting of an electron and hole that are spatially localized to different layers. Over the past decade, there has been significant interest in controlling IXs for future optical and quantum device applications. The project will develop unprecedented spatial control of IXs for potential applications to high speed and low power consumption optoelectronic devices. Based on the increasing need of computing power and the associated energy demands, the development of novel information processing devices that harness quantum effects at higher temperatures is critical. In addition, this project will train graduate, undergraduate and high school students in the area of nanoscale semiconductor devices which have the potential for revolutionary advancements in quantum information systems. The education and outreach activities focus on promoting the STEM fields by directly recruiting, providing research opportunities and career mentorship for high school students and UA undergraduates working with the University of Arizona’s Arizona Science, Engineering, and Mathematics Scholars Program, and KEYS program. The proposed project to spatially control IXs is at the state-of-the-art of 2D material device design, fabrication, and applications. The ability to trap IXs at the nanoscale was only recently developed by the PIs’ groups. Building on these recent developments, we will fabricate and optically investigate bilayer semiconducting transition metal dichalcogenide heterostructures with nano-patterned graphene top gates to generate custom potential-energy landscapes to realize unprecedented spatial control of IX flow and tunneling. Very recently, our team has reported evidence of high temperature IX superfluidity, motivating new devices that utilize this quantum phase. The project has two specific research aims: 1) demonstrate spatial control of valley-polarized IX flow, 2) demonstrate IX tunneling across a potential barrier and the equivalent of the Josephson effect in IX superfluid structures. Controlling of IXs will include both the demonstration of a valley-polarization based IX transistor as well as a valley-based filter that makes use of the valley Hall effect. IX currents will enable applications in low energy consumption valleytronic material devices. We will demonstrate the first ever 2D semiconductor based IX tunneling devices based on two IX traps separated by a tunneling barrier. The final goal of this research is to demonstrate Josephson-like IX oscillations which have potential applications in quantum technology devices such as on chip interferometers and gyroscopes. 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

We are on the verge of the development of the next generation of wireless networks, variously referred to as 6G, Next G, or Future G. Over the past decades, mobile networks have become part of the country’s critical infrastructure, and it is vital for the United States (U.S.) to maintain technological leadership in this area. This industry-university research center, WISPER, forms a partnership between industry and academia in the research and innovation that will drive Next G. WISPER stands for Wireless Innovation towards Secure, Pervasive, Efficient and Resilient Next G Networks, reflecting a consensus that the next generation of networks needs to be secure by design, efficient and sustainable in the use of resources, and resilient to both failures and attacks. Our goals with WISPER include: (1) to grow the U.S. competitiveness and innovation capacity with Next G wireless technologies; (2) to deliver breakthrough pre-competitive research for enabling secure, pervasive, efficient, and resilient Next G; (3) to contribute to the emerging North American vision for the Next G, currently coordinated by the Next G Alliance; (4) to guide research and development efforts on Next G; and (5) to train a workforce prepared to tackle complex Next G challenges. Researchers from Virginia Tech, the University of Arizona, and George Mason University will work together with a large array of industry members to develop this technology under the four major themes of: open software and interfaces; artificial intelligence-native network operation; spectrum innovation; and security. The University of Arizona will capitalize on its extensive partnerships and collaborative projects with the wireless industry, as well as experience in managing industry/academic centers. WISPER aims to impact the 6G development and pre-standardization activities by leveraging its strong alignment with key 6G stakeholders. Furthermore, WISPER will respond to the urgent need for a skilled Next G workforce. The WISPER leadership has extensive experience recruiting students in computing; to this end, we will leverage the Commonwealth Cyber Initiative (CCI) consortium, and dozens of community colleges. Developing our solutions on open-source platforms, such as Open RAN, will increase the accessibility of advanced Next G techniques, methods, tools, and platforms by professionals, trainees, and students. 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

Large ground-based astronomical telescopes deliver blurry images due to perturbations introduced by Earth's atmosphere. To recover sharp images, these distortions must be optically corrected in real time by an adaptive optics (AO) system. The control system that performs this task must operate thousands of optical sensors and correction elements at kHz speed to finely match the fast-changing incoming aberrations. This project develops a free and open-source software (FOSS) package to perform the adaptive optics computations with the required compute speed. Its modular design allows for flexibility and customization for multiple applications, including imaging life-bearing planets orbiting nearby stars, which requires exquisite image quality with large telescopes. To achieve their full diffraction-limited angular resolution, large ground-based astronomical telescopes must overcome the blurring of images induced by atmospheric turbulence. Sharp images can be recovered by Adaptive Optics (AO), using optical sensor(s) to measure optical aberrations and deformable mirror(s) to compensate for them. The correction must be done at high speed (kHz) to keep up with fast-changing atmospheric turbulence. A key application is imaging planets around nearby stars to search for life outside our solar system. Adaptive Optics also finds uses in medical imaging and laser beam propagation in air. This project develops a free and open-source software (FOSS) package for high-performance, low-latency computing pipelines with stringent real-time requirements for astronomical adaptive optics (AO). The Compute and Control for Adaptive Optics (CACAO) is an AO real-time computing toolkit, developed with a mindset of high performance and high modularity. CACAO's performance will be improved as well as its ease-of-use to broaden its adoption and enable the next generation of AO instruments on large astronomical telescopes. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Astronomical Sciences in the Mathematics and Physical Sciences Directorate. 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

The Colorado River is facing its worst mega-drought in a millennium and is no longer able to meet the demands of the 40 million people in the United States who rely on it. As a result, cities throughout the U.S. Southwest are reconsidering both their dependence on imported water and the reliability and management of their existing 20th century water systems. In many cities in this region, the built, natural, and social systems conflict with advancing water conservation and sustainability. Faced with the pressures of climate change, population growth, and aging infrastructure, one possible strategy presents itself: reinventing community water management to thrive using only local water sources through a Net Zero Urban Water (NZUW) approach. NZUW is a holistic water planning approach that explicitly accounts for natural and human needs. This proposal focuses on Tucson, Arizona, where a net zero water ordinance is currently under development by the city and county and ambitious urban greening and tree canopy goals are key components of recently adopted city and county climate action plans. With increasing temperatures and urban heat island impacts, new water demands are emerging as cities move to expand their urban landscape to provide cooling benefits. Our community-identified research need explores how Southwest cities achieve NZUW balances while expanding urban greening and the associated socio-environmental co-benefits. To conduct this research, our project fills local natural systems data gaps (Objective 1) and local social systems data gaps (Objective 2) to create an integrated NZUW evaluative tool (Objective 3) for urban greening goals. Local natural system data gaps will be met through a combination of in-situ data collection focused on quantifying vegetation water use and evapotranspiration via monitoring and discrete sampling (e.g., soil samples) across a set of Tucson urban landscape typologies. In Stage 1, these typologies and in-situ sites will be identified, and monitoring plans will be solidified with grant collaborators. Objective 2 will address social system data gaps through a series of workshops on public preference and key informant interviews with resource managers. In Stage 1, a work plan for the workshops and interviews will be co-created with civic partners and stakeholders. Finally, in Stage 1 a method will be solidified to use remote sensing data (NDVI, LiDAR, Orthophoto) and artificial intelligence to scale in-situ monitoring data across the city and county as inputs into the NZUW urban greening evaluative tool produced in Stage 2. 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

This National Science Foundation Innovations in Graduate Education (IGE) Track 2 award to the University of Arizona will help to increase the success of STEM graduate students through the creation, expansion, and assessment of the Graduate Communities for Academic Fellowship and Efficacy (Grad CAFE) program. Grad CAFE is a strengths-based, holistic, intersectional, interdisciplinary multi-tiered mentoring community that has the potential to transform how graduate scholars in STEM and beyond are supported by addressing challenges in mental health and well-being among graduate students, and recruitment, retention and completion among STEM graduate students. Unlike most mentoring programs, Grad CAFE creates a peer mentoring community within a multi-tiered mentoring program. Additionally, Grad CAFE creates a space for all students to come together and build community. Finally, Grad CAFE is a multi-year program that students can join in their first or second year, complete their comprehensive exams and return as a community leader and provide near-peer mentoring for newer students while building their teaching, facilitation, curriculum, and leadership skills. Grad CAFE will provide a blueprint for creating and scaling up from a small cohort to over 200 students in the fifth year without significantly increasing the time commitment for faculty and staff, providing an easily replicated model for other institutions to follow. Grad CAFE seeks to identify evidence-based best practices for holistic, community-based support for supporting graduate students in STEM. The theoretical framework of Grad Cafe is based on factors impacting student persistence at institutions like the University of Arizona. Grad CAFE is a multi-tiered mentoring program that spans the entire UArizona STEM ecosystem. The project seeks to identify, through formative and summative assessments, how Grad CAFE impacts STEM graduate students through several measures: 1) a greater sense of capacity, 2) improved sense of self-efficacy, 3) greater sense of interest, 4) greater sense of community, 5) increased satisfaction, 6) higher retention rates, and 7) higher completion rates as compared to non-participants. The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Abstract Vaccination is a highly effective public health intervention that saves millions of lives per year, yet declination rates for are increasing in the US for a variety of reasons ranging from safety concerns to religious and philosophical objection. In the wake of declining vaccination rates associated with the COVID-19 pandemic, the Chiricahua Community Health Centers, Inc. (CCHCI) in rural southeast Arizona initiated an innovative project to enhance vaccination through placement of an immunization specialist in dental clinics affiliated with the federally qualified health center (FQHC) system. The literature suggests that there are multiple salient and modifiable points to promote vaccine uptake within a multilevel approach that engages adults, adolescents, providers, families and communities. To enhance vaccine coverage through novel strategies, we propose the following specific aims: 1) Identify barriers and facilitators to vaccine uptake for specific vaccine types and populations in rural and border regions through engagement of individuals, communities, providers, and public health officials; 2) Determine the sustainability of the CCHCI FQHC dental clinic immunization program and scalability of the intervention to dental clinics at the Mariposa Community Health Center (MCHC) FQHC clinics in Santa Cruz County; and 3) Implement and evaluate a multilevel intervention to enhance vaccination uptake in populations unlikely to access FQHC care via an Underserved Population Study Team deployed through the MHU. Our approach will integrate socioecological and health beliefs model framing to understand the roles of socioeconomic factors, trust in health systems and public health authorities, and perceptions of vaccine efficacy and risk. We propose implementation of the dental clinic immunization program at the MCHC and support for the continuation of the program at CCCHCI. We also propose that staff from both CCHCI and MCHC work with the study investigators to author an implementation guide, rooted in Normalization Process Theory and a Dynamic Sustainability Framework, to participate in rigorously evaluating adaptability, effectiveness, and sustainability of this approach in FQHCs. We will develop, pilot, and assess a multilevel intervention strategy aimed at improving vaccination rates within populations that face barriers to healthcare access, particularly those residing in rural and hard-to-reach areas or individuals who do not typically utilize FQHCs. We will leverage the UA College of Public Health Primary Prevention Mobile Health Unit (MHU) program as a strategic platform for delivering vaccinations, utilizing community events as key touchpoints for outreach. At the community level, our focus will be on fostering a supportive environment that promotes vaccination through education, awareness campaigns, and collaboration with local community leaders. Simultaneously, at the individual level, the MHU team will provide personalized education, addressing specific concerns and providing tailored information to encourage vaccine uptake.

NIH Research Projects · FY 2025 · 2024-09

Project Abstract: For 25 years the Arizona Prevention Research Center (AzPRC) has served as a pivotal platform for collaborative research, training, capacity building, and translation to address health disparities. The overall goal of the Arizona Prevention Research Center (AzPRC) is to use innovative community-engaged approaches to expand knowledge, tools, strategies, and resources to achieve greater adoption, implementation, and wide scale use of EBIs to reduce health inequities. The AzPRC and our partners are committed to championing community health worker effectiveness in Arizona and beyond. Community health workers (CHWs), inclusive of promotoras de salud in Latine and community health representatives in American Indian (AI) communities, are frontline public health workers with a deep understanding and trust within the communities they serve. Given extensive experience and ties to CHWs, the AzPRC is well-positioned to address social isolation and loneliness (SIL) through promoting intergenerational connections (IGC). The AzPRC will conduct a core research project to understand the implementation, translation, and dissemination of CHW supported, evidence-based strategies to reduce SIL through intergenerational connection. The "Together Across Generations" core research project will address knowledge gaps surrounding SIL, particularly among rural border Latine and AI populations, who face severe health inequities in the state and nation. This project is guided by the Practical, Robust, Implementation, and Sustainability Model and The Transcreation Framework for Community-engaged Behavioral Interventions to Reduce Health Disparities. Collaborating with community-based organizations, local health departments, and Tribal nations, the first phase of the study will assess current social connectedness services and implement evidence-based intergenerational programs. Mixed methods data from organizations, CHWs, and 120 participants age >55 will be collected in four rural, border and Tribal sites to examine contextual factors, identify barriers and facilitators, and contribute to the evidence- base on the cost-effectiveness of these programs. Workshops to support CHW self-care and promote the sustainability of the workforce will be integrated. Implementation findings will be translated and disseminated throughout Arizona in the second phase of the project, achieved through partnerships with statewide, local and Tribal entities that promote equitable public health practices. Dissemination goals, including increases in IGC programming and improved surveillance of SIL throughout Arizona, will be evaluated through data from county health departments, federally qualified health centers, and Tribal health organizations. The impact of IGC services statewide will also be examined with propensity score matching from over 11,000 older adults who respond to the Arizona Behavioral Risk Factor Surveillance System, with SIL and IGC assessments to be added. The AzPRC will take leadership in the PRC Network to promote evidenced based practices, national SIL programming and surveillance, and in promoting the health of the CHW workforce.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ ABSTRACT The goal of this 3-year Special Interest Project is to perform intervention implementation costing and cost- effectiveness analyses (CEA) (cost-benefit, -utility, and -effectiveness) of the evidence-based Managing Epilepsy Well self-management program, MINDSET, in community and clinical settings, using retrospective and prospective data. Through goal-based patient-provider-driven Action Planning MINDSET (Management Information Decision Support Epilepsy Tool) has demonstrated impact in increasing patient epilepsy self- management (ESM) behaviors and validity in providing recommendations for linkage to salient MEW programs (PACES, UPLIFT, HOBSCOTCH) and assessment and feedback on patient social determinants of health. This proposal supports the 2012 IOM report for “development, evaluation, replication, and expanded use of ESM and educational programs, including MEW Network programs to improve quality of life for PWE” and multiple Health People 2030 targets to improve health and well-being in people with disabilities, improve mental health, and increase access to comprehensive, high-quality health care services. The CEA will be performed as recommended by the task force of experts organized by the U.S. Public Health Service and the International Society for Pharmacoeconomics and Outcomes Research. This proposal addresses the broader challenges around understanding financial preparedness and the value associated with interventions to enable the dissemination and implementation of evidence-based epilepsy self-management programs in clinical and community settings. As the MEW-EBP evidence base matures there is a need to guide healthcare providers (HCPs) and decision-makers on the economic feasibility of adopting, implementing, and maintaining these programs that includes guidance on coding and billing practices to offset implementation costs. This study aims to:1.) Assess MINDSET intervention implementation costs in community (EFCST, EFTx) and clinical health care (Kelsey Seybold, Harris Health, UTHealth, Banner, Barrow) settings using retrospective and prospective data (Year 1) to facilitate financial preparedness for new organizations wanting to implement MINDSET. 2.) Assess MINDSET cost-effectiveness in the community (EFCST, EFTx) and clinical healthcare (Banner, Barrow) settings using retrospective and prospective data (Years 2-3) to establish the value associated with the intervention. 3.) Collaborate with other MEW Network members (Years 1-3). 4.) Contribute to the annual evaluation report of site-specific activities and network-wide collaboration and disseminate findings (Years 1-3).

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY: Episodic memory declines during healthy aging and is an early symptom of Alzheimer’s disease (AD). However, the nature of memory changes that occur during the prolonged preclinical course of AD are poorly understood and ill defined. The concept of an asymptomatic, preclinical stage has gained importance in AD research due to the recognition that AD pathological processes begin years before appearance of pronounced memory deficits. Consequently, individuals at this stage often perform normally on standard neuropsychological tests designed to detect more overt memory and cognitive impairments. We propose a single, highly powered study to identify the memory processes that are most sensitive to this asymptomatic stage of AD pathologic change. The proposed study combines a continuous report item-location associative memory task with advanced behavioral (Aim 1) and neural (Aim 2) modelling to estimate subtle changes in memory precision that are independent of more traditional measures of retrieval success. The behavioral analyses in Aim 1 will allow us to test the prediction that subtle changes in memory precision can reliably differentiate between healthy aging and preclinical AD. Plasma biomarkers of amyloid, tau, and neurodegeneration will be used to classify cognitively unimpaired older adults into healthy (biomarker negative) and preclinical (biomarker positive) subgroups. This will allow us to validate and compare the predictive efficacy of memory precision against more traditional measures of retrieval success and ‘gold-standard’ standardized memory assessments. For Aim 2, we will use high-resolution functional magnetic resonance imaging (fMRI) to examine the neural computations that enable individuals to encode and retrieve precise memories. Critically, our approach will allow us to focus on how AD risk status affects local computations in hippocampal subfields as well as functional connectivity between larger cortico-hippocampal memory networks. The expected outcome of the proposed research is a novel behavioral assay that is sensitive to the earliest stages of AD pathologic change, when early detection and intervention have the highest likelihood of success. Moreover, the fMRI data collected as part of Aim 2 will provide novel mechanistic insights into the types of neural computations that enable older individuals to encode precise, high-fidelity memories. Finally, the insights gained from this project can inform future large-scale longitudinal studies aimed at clarifying the effects of healthy and pathological aging processes on episodic memory.

NIH Research Projects · FY 2024 · 2024-09

Project Abstract Osteoarthritis (OA) is the most common musculoskeletal disorder, presenting a large societal burden and affecting over 300 million worldwide. Knee pain in patients with knee OA is a leading contributor to physical disability and a major reason for hospital visits. Prior studies that have examined the determinants of knee pain have not considered the complexity of knee pain reporting systematically (e.g., localized, regional or diffuse knee pain). Moreover, the existing approaches focus on accurate prediction of knee pain and have limitation on the interpretability. There is, therefore, a critical need to address this crucial void by developing the computational tools with accurate prediction and interpretable properties. The overall goal of this research is to is to build computational tools to accurately predict different incident frequent knee pain spatial patterns and interpret the association between these knee pain patterns and the structural abnormalities (i.e., Bone Marrow Lesions (BML)) detected on Magnetic Resonance Imaging (MRI). The central hypothesis is that early in the disease course, abnormalities of structural features on knee MRI will be determinants of specific knee pain spatial patterns. This study is innovative in that it focuses on incident knee pain, examining knee pain spatial patterns early in the disease course, and taking into account different definitions of knee pain. This study is also innovative in that the study team will leverage excellent prediction performance of deep learning and interpretable properties of statistical approaches to predict and understand different knee pain spatial patterns. The specific aims are 1) To adapt a Transformer-based deep learning approach for predicting the incident localized, regional, or diffuse knee pain from MRIs in the Osteoarthritis Initiative (OAI), and 2) to develop a novel interpretable statistical framework for characterizing the relationship between BMLs on MRIs and incident localized, regional, or diffuse knee pain.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Follicular lymphoma (FL) is the most common indolent non-Hodgkin lymphoma (NHL) subtype with a highly variable clinical course. While asymptomatic and low-tumor burden patients can initially be managed by observation, symptomatic patients and patients with high-tumor burden disease are typically managed at diagnosis with immunochemotherapy (IC). We have shown that IC-treated FL patients who achieve event- free (i.e., no disease progression or re-treatment) status at 24 months after diagnosis (EFS24) have a subsequent life expectancy of the background age and sex-matched general population (thus doing well on standard of care), while those who fail to achieve EFS24 have aggressive disease with poor outcomes and represent a patient population with an unmet need. However, there is limited ability to identify this patient population at diagnosis. Building off our prior genome-wide biomarker discovery efforts, we have developed and internally validated a digital gene expression signature in formalin-fixed, paraffin-embedded tissue (FFPET) biopsies that predicts early clinical failure (defined as failing to achieve EFS24) in IC-treated FL using the NanoString nCounter platform, which we call FL24Cx (for FL EFS24 status classifier). We propose to use the UH2/UH3 mechanism to refine and validate our gene expression assay for use in routinely collected FFPET using a proven, clinical grade technology with which we have extensive experience. The goals of the UH2/UH3 proposal are to 1) analytically validate FL24Cx (UH2 Phase) and 2) clinically validate FL24Cx (UH3 Phase). In the UH2 Phase, we will challenge our preliminary tissue-based assay and algorithm, evaluate its analytical performance, and adjust as needed to optimize its prognostic power. Using our extensive test development experience, we will migrate the resulting locked assay to a clinical grade platform with rapid turnaround time. We will follow the federal guidelines for laboratory developed tests in a CAP-CLIA certified laboratory, so that the resulting test will be suitable for use in clinical trials and the clinic. In the UH3 Phase, we will rigorously validate FL24Cx in IC-treated FL patients. This will be conducted in both the geographically and racially/ethnically diverse Lymphoma Epidemiology of Outcomes (LEO) observational cohort study (NCT02736357) and in the large Southwest Oncology Group (SWOG) phase III clinical trial S0016 (NCT00006721). We will also evaluate FL24Cx in two additional NCTN clinical trials in FL. Furthermore, we will evaluate FL24Cx performance in subgroups defined on initial treatment approach, age, race/ethnicity, and other clinical factors as well as incorporate use of FL24Cx in the context of clinical models, further enhancing clinical utility. This application is highly responsive to PAR-20-313 (Assay Validation for High Quality Markers for NCI-supported Clinical Trials) and at the completion of this study, we will have rigorously validated FL24Cx to identify patients at high risk of early clinical failure, which is a missing clinical tool to rapidly conduct informative trials and effectively manage FL patients in the clinic.