Ohio State University

NIH Research Projects · FY 2025 · 2024-09

Willi L. Tarver is an Assistant Professor in the Division of Cancer Prevention and Control, College of Medicine at The Ohio State University. Dr. Tarver is responding to PAR-21-295 to obtain the skills, knowledge and mentored research experience that are essential for a career as a research scientist focusing on cancer health informatics and health services research. His long-term goal is to build an independent program of research that utilizes health information technologies to improve cancer care and cancer health. The short-term goals for the award period include: 1) gaining formal training in psychometrics and practical experience with PatientReported Outcomes (PROs) and their assessment in the cancer context, 2) expanding knowledge and skills of Qualitative and Mixed Methods Research Approaches; 3) gaining formal training in health services research, with a focus on methodological approaches to improve cancer health; and 4) developing leadership skills training for research scientists, including training in manuscript writing and grantsmanship toward building a presence in his respective field. Some patients may experience a greater cancer burden and poorer health outcomes on account of various community health factors (CHF). PROs provide additional prognostic information that may lead to more patient-centered care, improved patient-provider communication, and better clinical outcomes such as survival. However, studies have shown that some cancer patients are less likely to complete PROs and more likely to report difficulty in understanding the wording of PRO questions. Furthermore, adequately assessing PROs in all populations may require the collection of data beyond standard clinical measures, such as CHF. This proposal is aimed at improving the assessment of patient-reported outcomes among all cancer patients. I will conduct qualitative interviews with cancer patients to understand the concerns and impediments to (e.g., computer literacy, security concerns, etc.) and facilitators of (e.g., education or other assistance) completing PROs and items capturing CHFs. I will also conduct qualitative interviews with cancer care providers to understand their impediments to and facilitators of the collection of PROs and information about CHFs, their information needs, and their preferences for assessing and using PROs and CHFs. The knowledge derived from the interviews of patients and providers will inform the development, refinement, and implementation of a PRO/CHF tool tailored to the needs and preferences of patients and their cancer care providers. The resulting PRO/CHF tool and delivery approach will undergo feasibility testing and will be adapted in a manner supportive of provider workflow. The research accomplished during this award period will lay the foundation for a randomized trial to test the effectiveness of equipping cancer care providers with PRO/CHF data on the provision of cancer care, clinical decision-making, and changes in medical treatment.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY The continuing emergence and rapid dissemination of antibiotic-resistant pathogens are becoming a major threat to public health. Infections caused by carbapenem-resistant Enterobacterales and carbapenem-resistant Acinetobacter, which are difficult to treat, were recognized as one of the urgent threats among patients in medical facilities. Serious infections caused by antibiotic-resistant pathogens are associated with higher rates of morbidity and mortality and contribute to significant economic costs. Cefiderocol, which received FDA approval in 2019, is a novel siderophore-conjugated cephalosporin with expanded activity against carbapenem-resistant Gram- negative pathogens including strains that produce serine carbapenemases and metallo-β-lactamases. Cefiderocol-nonsusceptible isolates were reported in surveillance studies but the resistance mechanisms are largely unknown on many occasions. Antimicrobial heteroresistance describes a phenomenon where subpopulations of genetically homogeneous bacteria exhibit a range of susceptibilities to a particular antibiotic. Heteroresistance has considerable clinical relevance because antibiotic treatment may select more resistant populations. It is considered an important factor contributing to unexplained antibiotic treatment failure. Heteroresistance has been reported in various bacterial species to many classes of antibiotics. However, there is a lack of thorough research studying cefiderocol heteroresistance, the underlying mechanisms, and its clinical relevance. The overall goal of the proposed project is to study preexisting cefiderocol resistance and heteroresistance without prior cefiderocol exposure and the evolution of cefiderocol resistance after cefiderocol exposure in vitro and in patients. In Aim 1, we will investigate preexisting cefiderocol resistance and heteroresistance mechanisms in clinically isolated carbapenem-resistant Gram-negative pathogens. In Aim 2, we will study in vitro and clinical evolution of cefiderocol resistance following cefiderocol exposure, and characterize isolates with reduced cefiderocol susceptibility.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Following a myocardial infarction, an intense inflammatory response occurs whose duration and magnitude are modulated by CD4+CD25+Foxp3+ regulatory T cells (Tregs) that express CD39, an ectonucleotidase that degrades proinflammatory ATP and ADP. Immune responses are central to cardiac healing, and Tregs exert critical modulatory functions. Levels of immune-suppressive ectonucleotidase CD39 on Tregs are genetically controlled in humans by specific single nucleotide polymorphisms. However, no studies have examined whether differences in Treg CD39 activity impact cardiac inflammation resolution and healing following myocardial infarction in humans. In alignment with NOT-ES-20-018 “Notice of Special interest: Promoting Fundamental and Applied Research in Inflammation Resolution,” our overall experimental goal is to elucidate the impact of genetic regulation of Treg CD39 expression on the resolution of cardiac inflammation following myocardial infarction. Our recent publication demonstrates that post-myocardial infarction healing in mice devoid of CD39 expression is dysfunctional, with increased fibrosis and worsening diastolic function. However, CD39 is expressed in several immune cells and endothelial cells; therefore, in this model, no conclusions can be drawn regarding which CD39- expressing cell subset is instrumental in regulating cardiac healing. Our critical data demonstrate that in humans, the genotype at the ENTPD1 promoter SNP rs3814159 associates with the level of expression of CD39 on Tregs. Given the evolving role of Tregs in modulating post-MI inflammation and healing, our central hypothesis is that genetic polymorphisms resulting in decreased Treg CD39 activity convey a pro-inflammatory phenotype that fails to resolve chronic inflammatory conditions. We will test this hypothesis by conducting functional genomic experiments using novel murine experimental model systems and clinical studies, examining isolated cells and patient biospecimens. The proposal consists of two Aims. In SA1, our investigative team will determine how CD39 activity on T regulatory cells impacts cardiac inflammation resolution and myocardial healing following myocardial infarction. This will be done using murine models of reduced and ablated expression of CD39 on Tregs. In SA2, we will determine the impact of differences in CD39 expression on the inflammatory response and resolution following myocardial infarction in humans. We have assembled a collaborative team with clinical and experimental cardiovascular disease, genetics, and biostatistics expertise. Completing the proposed aims will provide an understanding of the role of the genetically predetermined expression of CD39 on Tregs in cardiac inflammation and inflammatory resolution. Translation to clinical practice will be facilitated by identifying important biomarkers and novel targets, including CD39 and related pathways, for therapeutic intervention in myocardial infarction.

NSF Awards · FY 2024 · 2024-09

Scientists detect exoplanets by using spectrographs that measure tiny changes in the color of starlight caused by stars wobbling back and forth as planets orbit around them. In 1995 this method was used to detect the first exoplanet in orbit around a star like the Sun, a breakthrough recognized with the Nobel Prize in Physics in 2019. Finding even smaller exoplanets in the future, including those like Earth, requires careful calibration of the spectrographs that make these measurements. With funds from NSF’s Major Research Instrumentation program, this team will procure, install, and optimize a new “laser frequency comb” calibration source for two spectrographs at the 8.4-meter Large Binocular Telescope in Arizona. In addition, this project will contribute to training the next generation of scientists and engineers, and graduate students will lead key program elements while being mentored by senior members of the team in training and career development. High resolution spectroscopic measurements will play an essential role in exoplanet science. In addition to supporting transit surveys, the radial velocity (RV) method will also play a critical role in the characterization of planets discovered by future direct imaging missions. To accomplish these goals it is crtical that we continue to advance the sensitivity, resolution, and precision of extreme precision radial velocity (EPRV) spectrographs. This project will deliver a state-of-the-art Laser Frequency Comb (LFC) to the Large Binocular Telescope (LBT) and complete its optimized integration, enabling critical multi-year spectroscopic studies with the Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI) and iLocater spectrograph. With their precision high-resolution (R>190,000) capabilities spanning visible (PEPSI: 383-912nm) and near-infrared (iLocater: 970-1310nm) wavelengths on a dual 8.4m telescope, these instruments are optimized for EPRV studies of exoplanets and stellar astrophysics. Augmenting them with a dedicated LFC with its absolute wavelength calibration capabilities enables robust intercalibration between LBT instruments and expands short-term instrument performance to multi-year baselines. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Tensors, which naturally extend the concepts of vectors and matrices to multiple dimensions, have become ubiquitous due to the accessibility of numerous affordable and deployable sensors capable of collecting data on the same object or phenomenon from multiple perspectives. This proliferation is further accelerated by the powerful and flexible models that tensors can provide for representing multi-attribute data and multiway interactions, rendering tensors indispensable in modern data science across various fields of science and engineering. Among various applications, a fundamental task is to estimate tensors from highly incomplete measurements. This challenge emerges due to the exponential growth in the number of potential viewpoint combinations or multiway interactions, while our data collection capability increases only polynomially. Even if sufficient data could be collected, the amount of data may overwhelm the computational and storage resources of a single machine. Fortunately, in many practical applications, tensors often obey certain low-dimensional representations. This project will exploit these representations to address key challenges in modern data science across a spectrum of scenarios, spanning from centralized to distributed settings, while also accounting for the presence of maliciously perturbed measurements. By advancing the field of tensor analysis, this project has significant potential benefits across diverse areas such as signal processing, biomedical imaging, machine learning, and quantum information science. This project will develop a unified framework for exploiting low-dimensional structures for tensor recovery from incomplete measurements. To overcome computational challenges for large-scale tensors, this project will develop computationally and statistically efficient optimization methods that directly optimize over the low-dimensional structures (or factors in various tensor decomposition models). Our work will first study the stable embeddings of low-dimensional tensors from random yet structured linear measurements to determine the number of measurements needed for a stable recovery. This project will then leverage the stable embedding results to characterize the geometric landscape of the factorized nonconvex problems over the low-dimensional structures. The geometric landscape analysis will enable us to develop efficient local search algorithms with guaranteed convergence to the target tensors. In cases where privacy is a concern or the measurements overwhelm the computational and storage resources of a single machine, this project will enhance the algorithms with distributed optimization techniques that offer similar convergence and recovery guarantees, along with consensus guarantees. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Many individuals living with serious psychiatric disorders – including those that span the psychosis, autism, and anxiety spectrums – experience significant social dysfunction and disability secondary to mental illness. Unfortunately, social impairments are generally not addressed by psychiatric medications and psychosocial interventions for social dysfunction are often difficult to access or otherwise limited in their scope (i.e., intended for a discrete diagnostic group) or clinical benefit. Thus, novel therapeutics capable of addressing social dysfunction across diagnostic groups are needed but will rely on improved understanding of the neurobiological mechanisms that underlie these impairments. Notably, social cognition – and in particular, mentalizing (i.e., the ability to make inferences about the mental states of others) – plays an important role in functional outcomes among individuals with mental illness. Though mentalizing has known neural underpinning in the cerebral brain regions that comprise the mentalizing network (MN; i.e., medial prefrontal cortex, precuneus, temporoparietal junction), emerging data suggests that the posterior cerebellum (Crus II) plays a critical role in social cognitive processing that has not been examined among individuals with serious mental illness. More specifically, the posterior cerebellum may act as a forward controller with cerebral MN regions – which, given the accessibility of the cerebellum for neurostimulation relative to cerebral regions of the MN, may have critical implications for translational interventions. In this proposed project, we will develop a brain network model of dynamic interactions between key brain regions involved in mentalizing among a transdiagnostic sample of youth and young adults (14-30) selected specifically for prominent social dysfunction secondary to a psychiatric illness. By investigating network models in a sample of individuals during the phase of life in which the majority of mental illnesses emerge or escalate, we can minimize the influence of confounding factors related to more chronic illness or long-term use of psychiatric medications. Crucially, we will also examine the extent to which cerebellar activity and connectivity is associated with lab-based, validated measures of functional and social-cognitive performance to better understand neural factors that may be most impactful on critical functional outcomes. Findings from this study have notable potential to define a novel treatment target for a future translational clinical trial studying neuromodulation of cerebellar regions most strongly associated with devastating and difficult-to- treat social dysfunction.

NSF Awards · FY 2024 · 2024-09

The ability to understand other people’s thoughts and feelings (commonly referred to as theory of mind) is related to narrative comprehension during the preschool years because children need to understand characters’ mental states to understand the meaning of a story. Little research has explored what predicts how these two skills develop together. This project examines two family-level factors, the home literacy environment and the mental state talk parents use when reading to children, that might explain how theory of mind and narrative comprehension co-develop during early childhood. Both skills are important for school readiness because theory of mind predicts socially competent interactions with peers, and narrative comprehension predicts later reading comprehension. Thus, understanding the predictors of theory of mind and narrative comprehension, and how they are reinforced by the same early environmental supports (such as parent-child talk about mental states), is key to developing approaches to promote these skills. The research plan for this project includes testing preschoolers at three time points, each six months apart, using longitudinal three-way cross-lag panel design. At the first time point, the research team gathers information on the home literacy environment (such as how frequently parents read to children and the mental state language parents use when reading to children). At each time point, the research team tests preschoolers’ theory of mind and narrative comprehension skills. The study includes additional assessments to control for the possibility that other variables (including socioeconomic status and children’s vocabulary size) contribute to the observed relations between the key variables of interest. The research plan includes recruitment of families that are diverse with respect to race, ethnicity, and socioeconomic status. The study design allows the research team to test a novel framework that highlights shared developmental antecedents of theory of mind and narrative comprehension skills. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The ability to process large sets of data on research computing (RC) platforms has led to remarkable advances in science and engineering and has become an indispensable tool for researchers, industry professionals, and students. The importance of RC platforms and tools (and in particular those involving AI technology) has been recognized by the highest levels of the United States government, as evident by the National AI Initiative Act of 2020, which calls for the creation of a National Artificial Intelligence Research Resource (NAIRR). Unfortunately, for many individuals, RC use and adoption is hindered by the complex way in which these resources are accessed. While web browsers and smart devices have become the dominant access mechanism for remote consumer and enterprise computing services, the adoption of such mechanisms has lagged for many RC service providers, creating an accessibility gap that impedes further adoption. Open OnDemand is a mature, National Science Foundation (NSF) funded, open-source platform that enables remote web access to RC services, thereby simplifying use of those resources and facilitating collaboration. RC clients can manage files and jobs, create and share apps, run GUI applications, and utilize a traditional terminal all through a web browser from anywhere on any device because it requires no specialized client software and has a simple interface that is easy to learn and use. The Open OnDemand community has begun to expose platform limitations and request additional features and capabilities, many of which will require significant collaborative development efforts to implement. Further adoption of this powerful platform, and the resultant scientific advances, can be accelerated via a variety of innovations: (1) Catalog, providing capabilities to conceptualize, create, modify, share, and publicize apps; (2) Classroom, focused on Open OnDemand in educational environments; (3) Customization, involving innovation in client interfaces and new technologies; and (4) Community, facilitating communications among the community. A cross-cutting aspect of the GOODLUCK project will pilot and deliver integrated sets of tools, documentation, and training materials, which researchers can select from to create an environment tailored to their research. Initial beneficiaries of these efforts include: (1) biochemists utilizing cryogenic electron microscopy (Cryo-EM) to identify the underlying mechanisms of viral action; (2) materials scientists designing new alloys from first principles; (3) art design students creating novel works via the use of generative artificial intelligence; and (4) aerospace engineers improving the performance of drones via computational fluid dynamics. In summary, the GOODLUCK effort will provide tools and processes that allow researchers to more easily and extensively utilize Open OnDemand, as well as to analyze and share their computational results, regardless of their access to RC resources or position in the research lifecycle. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

With the support of the Chemical Catalysis program in the Division of Chemistry, Professor Christine Thomas of The Ohio State University is studying the fundamental design of new, more sustainable, catalysts for carbon-element bond-forming reactions. Catalytic transformations provide an environmentally friendly method to convert widely available chemical feedstocks into value-added products for use in the pharmaceutical, consumer product, and commodity chemical industries. The project will explore fundamental aspects of catalyst design and establish new catalysts that are easily produced from naturally abundant and inexpensive precursors, particularly taking advantage of Earth-abundant metals such as iron and cobalt. This project will directly contribute to the rigorous training of graduate and undergraduate students in preparation for their careers as scientific researchers, with a particular focus on recruiting and retaining students from diverse backgrounds, including Black and LatinX students, U.S. military veterans, and students with disabilities. In efforts to increase the participation of underrepresented groups in chemistry, Professor Thomas serves as the faculty advisor to the student organization for women in chemistry at Ohio State (Females of Chemistry Uniting Scientists, FOCUS) and as Ohio State’s representative to the NOBCChE (National Organization for the Professional Advancement of Black Chemists and Chemical Engineers) Collaborative, helping to empower and provide opportunities for women and Black students. Professor Thomas and her team will also participate in several annual local outreach events geared towards K-12 students from Columbus City Schools. With the support of the Chemical Catalysis program in the Division of Chemistry, Professor Christine Thomas of The Ohio State University is studying the design of new multidentate ligand frameworks to ultimately promote carbon-element bond forming reactions using Earth-abundant first row transition metals (e.g. iron and cobalt). The project will establish more sustainable catalytic methods by leveraging unique multidentate ligand designs that promote the formation and cleavage of chemical bonds at first row transition metal centers. This project is centered on ligand design, and Prof. Thomas and her team will evaluate two different ligand types in this regard. A tridentate bis(phosphine) pincer ligand featuring a central π-accepting diamidophosphine, diamidophosphite, or triamidophosphine (PPXP) (X = CF3, OR, NR2) moiety will be coordinated to Co and Fe and the resulting metal compounds will be evaluated as precatalysts for the hydroboration, hydrogenation, and hydrosilylation of alkenes. Detailed mechanistic studies will be performed to establish the catalytic reaction mechanism and understand turnover limiting steps that can be the subject of catalyst improvement. The fundamental evaluation of different substituents on the central phosphorus atom of the ligand will allow structure/activity relationships to be established in the context of pincer ligands with π-accepting functionalities. In addition, this project will explore a non-innocent tetradentate (PNNP)2- ligand whose ligand backbone readily undergoes hydrogen atom transfer upon coordination to Co. The resulting enediamide ligand is redox non-innocent, allowing the resulting (PNNP)Co complex to access four different redox states while only cycling between two oxidation states. A series of cobalt-alkyl compounds will be synthesized and the strength and nature of cobalt-carbon bonds will be investigated as a function of metal/ligand redox state to gain insight into the tunability of cobalt-alkyl bonds, which are important intermediates in alkene hydrofunctionalization reactions. 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 Non-small cell lung cancer (NSCLC) is a highly aggressive disease with dismal prognosis associated with high rates of treatment resistance and disease recurrence. In the last decade, first line NSCLC treatment has been substantially reinforced with the introduction of immunotherapy targeting immune checkpoints such as programmed cell death 1 (PD-1) or its ligand PD-L1. PD-1/PD-L1 immune checkpoint blockade (ICB) shows very promising clinical profile, yet long-term disease control occurs in less than 25% of NSCLC patients. Understanding the mechanisms of treatment resistance is essential to address the dire need of introducing novel synergistic therapies to target refractory disease in immune-privileged NSCLC tumors. Experimental evidence shows that NSCLC tumors, belonging among the most hypoxic tumor types, display poor rates of immune cell infiltration and impaired T cell effector function within the hypoxic tumor regions. This suggests that low oxygen may contribute to the immune privilege and poor response to treatment in NSCLC. Interestingly, tumor hypoxia has been associated with anti-cancer treatment resistance for decades, yet its role in clinical management of NSCLC remains largely unexplored. Recent literature suggests that persistent antigenic stimulation of tumor- infiltrating CD8+ T cells within the hypoxic tumor microenvironment (TME) induces T cell exhaustion, a dysfunctional state characterized by progressive loss of T cell effector function. In the current K22 Transition Career Development Award application, we propose to investigate the role of tumor hypoxia as a modulator of immune privilege in murine NSCLC models. We have previously identified that mitochondrial inhibitor papaverine (PPV) and its experimental derivative SMV-32 can reversibly elevate partial oxygen pressure in murine NSCLC tumor models by up to 90%. Our preliminary data show that PPV or SMV-32-mediated TME reoxygenation prior to delivering PD-1 ICB led to significant enhancement of tumor growth delay in mouse syngeneic NSCLC tumor models, compared to PD-1 monotherapy. Repeated treatment with either drug alone did not affect tumor growth. We also show that hypoxia leads to enrichment of dysfunctional CD8+ T cell populations in vitro and in vivo and that reoxygenation promotes elevation of PD-1 ICB-responsive progenitor exhausted T cell population while decreasing terminally exhausted T cell population. The overall goal of the K22 proposal is to elucidate the TME- specific mechanisms of hypoxic immune privilege in NSCLC tumors and to gain advanced research experience and professional development required for transition into a successful independent investigator.

NIH Research Projects · FY 2025 · 2024-09

Abstract People with advanced cancer experience a greater frequency and severity of physical and psychological symptoms, ranking sleep difficulties, worry-anxiety, depression, and fatigue as four of the most common and distressing symptoms. These symptoms form a symptom cluster, contribute to functional impairment and poorer quality of life, and are undertreated, especially in rural communities. There is strong evidence for biobehavioral interventions to improve these symptoms. However, cognitive-behavioral (CBT) and acceptance and commitment therapies (ACT) are often too time and energy intensive (e.g., 12-20 sessions) and not tailored for people with advanced cancer. Preliminary Results. In response to specific needs of people with advanced cancer, we completed a pilot randomized, controlled trial of a brief, integrated CBT-ACT intervention utilizing the most effective components of these treatments. Finding Our Center Under Stress (FOCUS) is a four-module mHealth intervention that teaches patients how to control symptoms, when possible, while continuing to live meaningfully despite these symptoms. FOCUS participants demonstrated statistically and clinically significant improvements on insomnia severity (d=-0.98), worry (d=-0.86), depression (d=-0.77), fatigue interference (d=-0.59), self-report and physiologic sleep efficiency (effect size d=0.92), sleep latency (d=-0.66), and psychological distress (d =-0.78). The proposed project, guided by the biobehavioral theoretical model, will build on the success of our pilot trial and complete a larger effectiveness trial of FOCUS compared to a telemedicine-mHealth information control on this symptom cluster; evaluate dose-response, particularly among rural patients; and explore biobehavioral mediators of symptom changes. Our primary goal for this study is to improve this symptom cluster, functional status despite symptoms, and quality of life for people with advanced cancer from underserved rural communities. Innovative features include our population (50% rural and Appalachian), symptom cluster focus, telemedicine-mHealth delivery, tailoring for people with advanced cancer, and use of a biobehavioral approach. Aim 1. Evaluate the effectiveness of FOCUS on a symptom cluster (sleep-anxiety-depression-fatigue), Aim 2. Determine the impact of FOCUS dose on symptom severity and interference and examine usage by patient geographic location and gender. Exploratory Aim 3: Examine biobehavioral mediators of treatment effects. Design and Method: This is a prospective, triple blinded (patient, research assistant, statistician), single-site, randomized trial of FOCUS vs information control. We will recruit 120 participants with advanced lung, prostate, breast cancer, myeloma, and melanoma. The trial will take place at The Ohio State University James Comprehensive Cancer Center. All participants will complete assessments at baseline, 6 and 12 weeks, and 6 and 12 months. We hypothesize that FOCUS participants who use the app more frequently will demonstrate improvements on the symptom cluster longitudinally compared to the control group via psychological, inflammatory, and endocrine mediators.

NSF Awards · FY 2024 · 2024-09

A major goal of modern probability is to understand the macroscopic behavior of large random systems. This project studies a class of random growth models taking place in different geometric settings and will develop new tools effective for these structures; the aim is to understand the behavior of these systems and the impact of the underlying geometry on this behavior. These systems, for example, might be used to model the growth of cancer along a wall or a cylinder. The extensive algebraic structure underlying integrable or exactly solvable models without boundary has been successfully used to study a variety of probabilistic questions for these models. Many of these models are expected to exhibit universality, meaning that the behavior studied should occur in a wide variety of other models. However, once non-trivial boundary conditions are imposed, our understanding is incomplete. The proposal aims to develop a better understanding of the algebraic structures involved once boundary conditions are imposed and to use this structure to attack probabilistic problems. In particular, the work aims to find new hidden symmetries for these models and to establish asymptotic results via new exact formulas for models with boundary. Undergraduate students will participate in the research, continuing the awardee's record of student mentorship, and the work will be disseminated at seminars and conferences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The Generation-4 NSF Engineering Research Center titled “Transformation of American Rubber through Domestic Innovation for Supply Security: TARDISS” will lead fundamental research towards US natural rubber biomanufacturing. Currently the single commercial source of natural rubber is the tropical rubber tree (Hevea brasiliensis), with production areas all outside of the United States. TARDISS will use a systems engineering approach to integrate engineering with biology, biotechnology, agriculture, and other disciplines optimizing alternative plants to produce entirely new natural rubber materials at scale. The TARDISS team will collaborate with communities, farmers, processors and rubber manufacturers to enable biomanufacturing-based natural rubber production optimized to large parts of the US, with a focus on marginal agricultural lands. TARDISS will enable a circular biomanufacturing economy that respects natural systems, including pollinator services by the new domestic crops, water recycling and re-use, additional CO2 capture, and an estimated 2 million jobs tied to US soil. Engineering workforce development will provide training in this new U.S. area, also include those with untapped potential that are currently underutilized in the workforce. The outcomes will be a sustainable domestic rubber industry and a new, young workforce converging engineering and agriculture trained through a new American Rubber Academy. The “U.S. Sunlight to Materials” vision motivating the systems engineering approach of TARDISS is encapsulated by two hypotheses: #1: The U.S. can replace imported natural rubber (NR) with rubber from domestic crops, utilizing marginal agricultural lands, hydroponic systems, and new extraction methods; and #2: The U.S. can replace imported goods with products made with home-grown natural rubber. TARDISS will integrate engineering with biology and other science disciplines via the following three research thrusts: 1: BioEngineering will converge engineering, biochemistry, enzyme chemistry, and molecular biology to fundamentally understand how plants naturally produce rubber. Natural variety will be combined with genetic approaches to tailor hydroponic dandelion to produce new NR variants and transfer the knowledge to the guayule and mountain gum plant species. 2: Crop Engineering will converge plant and agricultural engineering to develop and disseminate new “smart” crop production practices for all three crops. 3: Latex/Rubber Engineering will converge engineering, materials/polymer science and engineering, chemistry, and physics to invent extraction methods to produce consistent high-performance latex and rubber and new processing methods for products. Furthermore, TARDISS will invent enabling technologies in field and hydroponic systems, industrial scale latex and rubber extraction methods, and novel processes-for-products and bring these to communities. A seamless integration of scalable biology, engineering, and science, while co-developing economically scalable pathways with domestic stakeholders, will be critical for success in Convergent Research. The outcomes will be a sustainable domestic rubber industry and a new, young workforce converging agriculture and engineering trained through a new American Rubber Academy in collaboration with the Rubber Division of the American Chemical Society. The TARDISS Innovation Ecosystem will bring together American business leaders and entrepreneurs, researchers, students, national labs, and communities, and features novel programs such as the Piranha Pit to encourage innovation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Our long-term objective is to understand the expression and function of monocyte/macrophage Fcγ receptors with a goal of improving antibody-based therapies for diseases such as chronic lymphocytic leukemia (CLL). We and others have demonstrated that CD20 antibodies improve outcome of CLL patients receiving both chemoimmunotherapy and recently treatment with a second generation BTK inhibitor acalabrutinib. Monocytes / macrophages play a critical role in antibody-mediated depletion of tumor cells, but they are in a suppressed state within CLL. In particular, macrophages in CLL patients are unusually large in size and play a major role in supporting the survival and proliferation of CLL cells. These macrophages have been called nurse-like cells (NLCs). We have found that activating the intracellular receptor NOD2 in monocytes / NLCs substantially reduces expression of negative regulators such as the inositol phosphatase SHIP1 and the inhibitory receptor CD31. Conversely, we saw upregulation of the activating FcγRI and the associated γ-chain. This led to significant increases in FcγR-mediated cytokine production, including those that activate NK cells. Along with such cytokines, there was upregulation of NK cell activating surface ligands in monocytes / NLCs treated with NOD2 agonists. Indeed, co-culturing of treated monocytes with NK cells enhanced NK-cell maturation and cytotoxicity. Collectively, these results suggest that NOD2 agonists may be an effective adjuvant for the treatment of CLL. Importantly, the NOD2 agonist MTP-PE (mifamurtide/ MePACT) has been the subject of past and current clinical trials for osteosarcoma and was approved by the European Medicine Association (EMA) in combination with intensive chemotherapy for osteosarcoma as an immune adjuvant. Overall, mifamurtide has an acceptable safety profile as well, justifying it as an alternative strategy for clinical development. Based on the above observations, we hypothesize that NOD2 agonists will activate monocytes / NLCs and will also indirectly or directly activate NK cells. To test the predictions of this hypothesis we propose the following three Aims: 1) Interrogate the mechanisms of influence of NOD2 stimulation on monocytes / NLCs and functional outcomes; 2) Examine the mechanisms of influence of NOD2 stimulation on NK cells, including contact- dependent/independent requirements, NK-cell maturation and cytotoxic ability; and 3) Validate the central hypothesis in vivo that NOD2 activation can lead to phenotypic and functional changes in monocytes / NLCs, as well as in NK cells, leading to stronger antitumor activity. At the completion of these studies, we will have established an entirely novel mechanism of activation of monocytes and NK cells in CLL, thus enhancing the efficacy of monoclonal antibody-based therapies.

NIH Research Projects · FY 2025 · 2024-09

Abstract Recently, high-throughput spatial omics technologies have made it possible to simultaneously measure close- to-cell-level gene or protein expressions and spatial locations of these cells within a tissue or organ. These new technologies have provided an unprecedented opportunity to investigate tissue architecture and cell-cell communications. Although multiple computational tools for spatial omics data analysis have recently become available, a rigorous statistical framework for designing spatial omics experiments is still missing in the literature. Researchers need to determine various experimental design parameters, such as the sequencing depth and the number and sizes of Field-Of-View (FoV), in planning a spatial omics experiment. These choices affect whether key goals of spatial omics experiments can be achieved, e.g., identification of tissue architecture and cell-cell communications. In this proposal, we aim to develop a rigorous power analysis framework for spatial omics experiments across various experimental designs and profiling technologies. The assembled team has strong and complementary expertise in development of statistical frameworks for power analysis and design of high throughput sequencing studies, statistical modeling of spatial omics and scRNA-seq data, technology development in spatial omics, spatial statistics, bioinformatics tool development, pulmonary science, and lung fibrosis and relevant age-related mechanisms. We will achieve the proposed goal by implementing three specific aims. In Aim 1, we will develop a rigorous power analysis framework for multi-sample and longitudinal sequencing-based spatial transcriptomics experiments (e.g., 10X Genomics Visium). In Aim 2, we will develop a statistical power analysis framework for imaging-based spatial transcriptomics and proteomics experiments (e.g., seqFISH+, MERFISH, CODEX) in single- and multi-sample and longitudinal settings. In Aim 3, we will develop an interactive web interface for power analysis of spatial omics experiments and utilize and validate it for designing spatial omics experiments for lung cells. The proposed power analysis framework will be developed and evaluated using simulation data, spatial omics data in the public domain, and in-house spatial omics datasets from collaborators. The to-be-developed statistical framework in this project, along with the open-source software implementing this framework, will provide essential tools for the optimal design of future spatial omics experiments.

NSF Awards · FY 2024 · 2024-09

Bilevel optimization is a powerful paradigm used to solve modern problems in signal processing and machine learning, such as multi-task learning, sequential decision making, robust adversarial training, and hyperparameter fine-tuning. More recently, the online bilevel optimization framework has been proposed to handle practical applications where environments and datasets change over time. These online problems are challenging because streaming data require fast decisions on-the-fly, and only limited information about the objectives can be sampled due to their rapid variations. In general, online bilevel optimization is largely unexplored, calling for a systematic in-depth investigation. The primary goal of this project is to comprehensively study online bilevel optimization, aiming to (i) speed up online bilevel algorithms, improve their scalability, and ensure their performance, and (ii) explore two real-world applications to further leverage the advantages of online bilevel optimization in solving practical problems. The proposed program will focus on the following research innovations to significantly broaden timely applications of online bilevel optimization in real-world problems: (i) algorithmic and analytical foundation for online bilevel optimization; (ii) a novel approach for online robust adversarial training via the lens of online compositional bilevel optimization; (iii) accelerated online multi-agent meta-learning design via online nonconvex bilevel optimization; and (iv) extensive experiments to validate the proposed approaches and algorithms. This project will also provide exciting training and research opportunities through topic courses, tutorial presentations, undergraduate research programs, and K-12 programs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This three-year project, Collaborative Research: e4usa + FIRST: Scaling Collective Impact Through Pre-College Robotics Curricula, is housed at the Ohio State University and Arizona State University. The world is rapidly transforming due to technological advancements making the ability to innovate educationally crucial for fostering the next generation of engineers and scientists. This project aims to bridge the gap in pre-college engineering education by developing robust, universally accessible robotics lessons capable of being used as either a stand-alone resource or a complementary resource for existing engineering programs. Partnerships with Engineering for Us All (e4usa) and For Inspiration and Recognition of Science and Technology (FIRST) will leverage and ensure that the resulting engineering curricula will be more accessible to students across diverse urban, suburban, and rural communities. The linkage with industry professionals brings a benefit for teachers and students to promote STEM career opportunities, and possibly strengthen STEM literacy within a more general population. This project has the potential to advance the knowledge and understanding of the feasibility, methodology, and scalability of two successful blended programs to create a new program that is both curricular and co-curricular. The democratization of access to cutting-edge robotics education supports a diverse, well-equipped future workforce to maintain competitive advantages in science and technology. This three-year project, Collaborative Research: e4usa + FIRST: Scaling Collective Impact Through Pre-College Robotics Curricula, is housed at the Ohio State University and Arizona State University. The project will iteratively develop robotics lessons, teacher guides, and artificial intelligence driven teacher support to achieve nationwide implementation. The project scaffolds engagement with teachers across the nation, building on an initial cohort of 12 high schools. Participating teachers will serve as co-creators and collaborators, with continuous feedback mechanisms to evaluate teachers’ implementation of lessons, impact on student engagement, and scalability of resources. A key strategy is building and securing alliances with academic, non-profit, and industry leaders to foster broad participation. Project activities feature a kick-off workshop, multiple development sprints, summer professional development, an academic year community of practice, mentorship, university and industry partnerships, and scalability and sustainability initiatives. Partnerships among academic institutions, non-profit organizations, industry leaders, and state organizations will allow the project to establish a robust model for integrating robotics into pre-college engineering education, leverage collective resources, and catalyze actions to broaden participation in STEM fields. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-08

PROJECT SUMMARY Two issues related to adolescent vaccination have recently come to the forefront of public health in the United States (US): coronavirus disease 2019 (COVID-19) vaccination and general vaccine hesitancy (i.e., a delay or refusal of any vaccination despite availability). These issues are especially important for adolescents in rural areas, as these areas experience several vaccine-related disparities. A necessary starting point in this novel line of research is to gain an in-depth understanding of these health outcomes via two types of epidemiological data. First, we need to quantify COVID-19 vaccine coverage and the prevalence of general vaccine hesitancy in rural areas. Second, we need to identify multi-level factors associated with each outcome in rural areas. In producing these epidemiological data, it is critical to do so in a way that accounts for the heterogeneity of rural areas. However, a key and recurring limitation of past vaccine-related research is that rural areas have been aggregated into a single, homogeneous group. This approach obscures the heterogeneity of rural areas and can actually create “hidden” disparities between different types of rural areas. Rural-Urban Continuum Codes (RUCCs) are a measurement approach that avoids this limitation and examines rurality in a nuanced manner by classifying each US county into one of nine categories that span the continuum of urbanicity/rurality. Our long-term goal is to understand how rurality affects COVID-19 vaccine coverage and general vaccine hesitancy and then apply this understanding to improve these outcomes in rural areas. The proposed study will take the first step toward achieving this goal by generating the epidemiological data described above. We will analyze existing data from the 2022-2023 National Immunization Survey-Teen (NIS-Teen) on both COVID-19 vaccine coverage among a large national sample of adolescents (estimated n=40,650) and general vaccine hesitancy among their parents. In doing so, we will use RUCC categories to examine rurality during analyses. Specifically, the proposed study will determine how rurality affects COVID-19 vaccine coverage among adolescents (Aim 1), multi-level factors associated with COVID-19 vaccine coverage (Aim 2), general vaccine hesitancy among parents (Aim 3), and multi-level factors associated with general vaccine hesitancy among parents (Aim 4). Each aim will address a unique research question and together will provide the most comprehensive data to date on rurality, COVID-19 vaccine coverage, and general vaccine hesitancy. Findings will provide highly novel data that impact future interventions to increase COVID-19 vaccine coverage and decrease general vaccine hesitancy in rural areas (e.g., results will identify priority rural areas for interventions to target and highlight strategies that interventions can use to improve these health outcomes).

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY Malaria is a devastating disease that impacts millions of people on an annual basis. While several species of Plasmodium parasites cause malaria in humans, P. falciparum is responsible for the highest rates of complications and mortality. Malaria elimination efforts are continually challenged by the emergence and spread of resistant P. falciparum strains to frontline chemotherapies. New treatments targeting alternative molecular targets in the parasite are therefore urgently needed. An ideal antimalarial drug should exhibit prophylactic, curative and transmission blocking properties. However, few clinically approved drugs fit this profile due to a two-fold problem: 1) many genes that are essential in mosquito or liver stage parasites are dispensable in symptomatic blood stages, making it hard to identify a drug target that is relevant throughout the parasite life cycle; 2) the field has historically suffered from a dearth of robust genetic tools to investigate basic parasite biology, a prerequisite for uncovering novel therapeutic approaches. In response to these challenges, we propose using new and improved genetic methods to expand the druggable parasite proteome across all stages of infection. We will focus our efforts on the parasite mitochondrion, a promising source of drug targets since it is essential in all parasite life stages and is highly divergent from its human counterpart. This organelle’s potential as an antimalarial target has already been validated by atovaquone, the only mitochondrial inhibitor in clinical use. Notably, atovaquone belongs to the very small group of drugs that are active against both symptomatic and transmission stages of infection. The mitochondrion contains nearly 10% of the total parasite proteome, the majority of which has no known function. Identifying essential processes within the mitochondrion can pave the way for the development of new drugs that not only prevent or treat malaria but also block transmission.

NIH Research Projects · FY 2025 · 2024-08

Project Summary The proposed research is designed to illuminate how semantic organization emerges in the course of development, and how it contributes to the fundamentally human ability to comprehend language. The proposed research will be guided by two general hypotheses. The first hypothesis is that comprehension may fundamentally rely on semantic organization – an organized network of words. The second hypothesis is that semantic organization emerges from exposure to statistical regularities in language input and from the developing ability to extract these regularities. To test these hypotheses, we will conduct three studies with 4-9- year-old children, and adults. The proposed project has the following Specific Aims. Specific Aim 1 is to conduct a cross-sectional training study (Study 1), presenting 4- to 9-year-old children and adults with controlled, varied exposure to sentences containing novel words that are rich in regularities, and testing how the amount of exposure and the ability to form semantic links affect subsequent comprehension. Specific Aim 2 is to recruit 4-year-old children and use a longitudinal design to examine how exposure to language and maturation of ability to form semantic links affect the development of semantic organization (Study 2). Specific Aim 3 is to use a longitudinal design (with the same sample as Study 2) to examine whether the development of semantic organization drives improvements in language comprehension. The proposed project will advance our understanding of a critical component of typical cognitive and language development and inform theoretically-based enrichment programs for atypical language development.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY/ABSTRACT Aphasia is commonly operationalized as a linguistic impairment affecting expressive or receptive language. People with aphasia (PWA) often experience profound emotional disturbances to a greater extent than post-stroke adults without aphasia given the direct relationship between emotional well-being and the capacity to engage in human interaction. PWA have been reported to develop ‘linguistic anxiety’, or stress when using language, due to the preoccupation with communication breakdown opportunities. Acute stress can be adaptive and inform our bodies of when to avoid or escape danger. However, persistent episodes of stress (i.e., chronic stress) can have adverse effects on physical and mental health. Chronic stress may also lead to harmful changes in the body’s neurological function, which may, in turn, interfere with language rehabilitative outcomes. Given the direct relationship between chronic stress, well-being, and rehabilitation, there is a critical need to better understand sources of stress related to communication in PWA to inform clinical practice and interventions. In line with NIDCD’s mission, the study plans to explore perceptions of stress concerning communication in PWA to enhance long-term outcomes and promote communicative participation. This will be achieved by conducting a mixed methods research paradigm to explore sources and self-management strategies of chronic stress in PWA. PWA will complete patient-reported outcome measures (PROMs) and semi-structured interview prompts related to sources of stress that may impact communication participation. To our knowledge, this project will be the first to directly examine the lived experiences of PWA through a mixed methods research paradigm to identify candidate sources of chronic stress in relation to communication (Aim 1a). Next, we will collect PROMs and interview prompts to elucidate the self-management strategies used to reduce perceptions of stress during communication attempts. While self-management strategies can be adaptive, we suspect PWA will endorse recruiting maladaptive strategies, such as avoidance or excessive rehearsal, that may suppress acute stress but facilitate long-term stress toward the feared situation (Aim 2a). Finally, we will collect longitudinal stress and coping data via ecological momentary assessments (EMAs), or repeated real-time data sampling, for the first time in PWA. Data collected via EMAs are suspected to provide a better insight into the variation of stress and coping perceptions from day to day. (Aim 1b and 2b). Potential moderating variables (i.e., socioeconomic status, physical immobility) will be accounted for in the proposed project. The findings of this study will provide critical information to inform future interventions that address chronic stress as it impedes communicative participation. The fellowship training plan will take place at a large, research-intensive university under the direction of a strong, systematically selected mentorship team. Training will include formularized courses, independent studies, workshops, and conferences to enhance background in the neurophysiology of chronic stress, analytics, research ethics, and scientific dissemination.

NIH Research Projects · FY 2025 · 2024-08

ABSTRACT Tuberculosis (TB), caused by Mycobacterium tuberculosis (M.tb), reaches the lung alveoli where it is in contact with the alveolar mucosa. This mucosal surface is lined by alveolar epithelial cells (ATs) and composed of a monolayer formed by surfactant lipids and a hypophase, called alveolar lining fluid (or ALF), containing soluble innate components and enzymes. M.tb is exposed to ALF for an undetermined period of time before and during its engulfment by host cells, primarily alveolar macrophages (AMs) but also ATs, providing a shield for M.tb and portal for dissemination. M.tb infection drives inflammation, which eventually attracts neutrophils, monocytes, eosinophils and other innate cells entering the alveoli from the periphery. Following primary infection and dissemination, tissue granulomas begin to develop. This proposal is in response to the specific RFA, “Analyzing Early Events in TB and TB/HIV Infection for Interventional Targets”. These earliest interactions, i.e., how the lung environment, specifically ALF and alveolar host cells interact with M.tb, are poorly understood, yet critical to impacting eradication or progression of M.tb infection. Our research program is focused on these earliest events for M.tb in the alveoli. Our data support the finding that M.tb’s interaction with ALF from HIV-infected individuals (as well as elderly individuals), fundamentally remodels the bacterial surface and its metabolism thereby affecting host cell entry, trafficking and host response, culminating in enhanced host susceptibility to infection. Thus, our central hypothesis is that the first interactions of M.tb with soluble human ALF components shape its cell surface and metabolic status, impacting its subsequent interactions with AMs and ATs, the two major resident alveolar cell populations, and leading to control or spread of M.tb infection. To address our hypothesis, we will systematically integrate our unique in vitro and in vivo models starting with single cell interactions and moving to an innovative lung-on-chip infection model with time-lapse imaging to reveal the dynamics of host- M.tb interactions at the air-liquid interface with spatiotemporal resolution, and an in vivo experimental approach to assess early dynamic interactions in the alveoli using the rhesus macaque (RM) model. We will also delineate the effects of HIV infection on alveolar composition & function, addressing how HIV’s effects drive M.tb faster replication and dissemination within the alveoli. The specific aims are to: 1) Determine how M.tb exposure to people living with HIV ALF (HIV-ALF) vs. control ALF generates early-stage M.tb metabolic adaptations that lead to host cell immune dysregulation; 2) Determine how the combined effect of exposure of alveolar cells and M.tb to HIV-ALF (vs. control ALF) causes dysfunctional alveolar immunity that accelerates M.tb growth and dissemination using a lung-on-chip (LoC) model; and 3) Determine how infection of BAL-acquired AMs by HIV or control ALF-exposed M.tb instilled in the airways alters the alveolar cellular immune response using the NHP model. Results from this proposal will move science forward by guiding the scientific community on the development of effective immune-based early interventions, specifically for people living with HIV.

NIH Research Projects · FY 2024 · 2024-08

Project Summary This project focuses on whether the COVID-19 pandemic has put the well-established Hispanic infant health advantage in peril. The U.S. Hispanic population has been one of the hardest hit by the COVID-19 pandemic with some of the highest rates of hospitalization, death, and illness, due in large part to overrepresentation in frontline occupations. The adult mortality impact on the Hispanic American population has been stark—Hispanic life expectancy experienced the largest decline across all racial/ethnic groups, with the exception of non-Hispanic American Indian and Alaska Native populations. The impact on infant health, however, is not yet known. We leverage U.S. Natality data (2015-2022) to first determine whether Hispanic perinatal outcomes have been impacted by the COVID-19 pandemic, for the overall population and disaggregating by three critical sources of heterogeneity in the Hispanic population—nativity, region-of-origin, and maternal education level. Second, given pronounced temporal and geographic variation in the pandemic’s progression, we determine whether impacts vary at the county-level and by county-level disease burden. Third, we assess whether either county poverty level and/or Hispanic concentration moderates the identified impacts. Determining if, for whom, and in what context, the Hispanic birth advantage has been impacted by the pandemic is critical for determining where to focus resources, not just at birth, but also at other stages of child development. Establishing these patterns is a fundamental piece of a full accounting of the extent of the pandemic’s toll on our country, particularly how it altered the health of such hard-hit U.S. sub-populations as Hispanic Americans.

NSF Awards · FY 2024 · 2024-08

Globally important carbon (C) stores in northern (boreal) peatlands are vulnerable to changes in altered precipitation and runoff patterns, groundwater inputs, and changes in the extent of frozen ground in high latitudes (called ‘permafrost’, or the ‘cryosphere’). These changes can affect the extent of boreal wetlands as well as their ability to sequester and transform C and other nutrients. In 2005, the Alaska Peatland Experiment (APEX) was created to examine the role of changing soil climate and vegetation on peatland C cycling. Over the past fifteen years, core data has been collected on soil moisture and temperature, plant composition and amount, and the fluxes of important atmospheric gases emitted (as methane and carbon dioxide) from water table treatments that simulate floods and droughts. A key result from this group's prior investigations was that C emissions from this experimental site appeared to be high, regardless of water table position, revealing that interactions among changes in plant species composition in response to the treatments were strongly controlling the ability of this ecosystem to retain C. This is a five-year renewal of a Long-Term Research in Environmental Biology (LTREB) project, DEB-1354370. The study is examining the interactions among changes in hydrology, plant species composition and changes in climate (particularly flooding and drought) in controlling C storage in this peatland complex; this work is necessary for understanding the consequences of an altered climate for C cycle processes. Undergraduates, graduate students and post-doctoral researchers will all be trained and in field and laboratory techniques. Results from the research will also be incorporated into new high school curricula for use in the Fostering Science summer camp. The current view of peatland carbon cycling is that the majority of soil carbon mineralization occurs in the relatively shallow aerated peat layer above the water table (acrotelm), and that deeper peat carbon occurring in anoxic layers (catotelm) undergoes minimal decomposition. As such, the position of the water table (and the associated thickness of the acrotelm) is used as a predictor of overall decomposition rates and long-term peat accumulation rates. However, findings from this team's fifteen-year manipulation of water table position in an Alaskan fen (Alaska Peatland Experiment, APEX) challenge this view, and in particular suggest that carbon mineralization in saturated peat is faster than previously expected, leading to high fluxes of anaerobic CO2 production. Prior analyses indicated no significant effect of water table position on ecosystem respiration, but it is possible that this result was due at least partially to changes in vegetation that have occurred both under lower (drier) and higher (wetter) water table positions. The initial experimental design could not disentangle the effects of changes in vegetation from hydrology on peat redox and C fluxes. As such, understanding the interactive effects of altered hydrology and vegetation on anaerobic decomposition processes, and how this governs the turnover of deep soil C pools in peatlands, was the prime objective of the first phase of LTREB funding. Results during that initial LTREB funding period showed that sedge and Equisetum (horsetail) rhizospheres indeed had oxidizing effects on peat and dissolved organic matter. However, persistent flooding over this period of research has presented key gaps in mechanistic understanding of controls on trace gas production in this system, and revealed that plant community structure and the dominance of algae likely have unique controls on soil redox processes and C fluxes. Flooding history also exerted strong control over the relative activity of algae vs. heterotrophic microorganisms, depending on changes in C substrates from different plants. Exactly how changes in plant community interact with altered water tables in governing the supply of electron donors and acceptors, and how this controls anaerobic metabolism in low- and high-water table years, are key questions this collaborative team will examine in the next five years. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

As society’s problems continue to become increasingly more complex, engineers need new skills to tackle these problems head-on. One approach to arming engineers with this skillset is through interdisciplinary engineering education. This method is different from traditional single disciplinary engineering education and helps foster broader thinking and creative insights. For the US to maintain its competitive edge in the global workforce, engineers must learn to work effectively in cross-functional teams. To address this need, universities are offering interdisciplinary programs that allow students to expand the boundaries of their education in ways that match their career goals and industry needs for creative problem solvers. Understanding student career choice can help universities better tailor programs to meet student needs. This project contributes to the NSF’s goal of broadening participation by exploring new ways in which multi- and interdisciplinary engineering programs affect students’ career goals and choices during their education. The research team will explore factors that guide students’ academic and career pursuits and determine the student perceived value in engaging with interdisciplinary learning and experiences during their undergraduate education. The results can be used to improve the way we train engineers to solve the complicated and multidimensional issues of the 21st century. The project will use a qualitative research design to build on the knowledge of how engagement in multi- and interdisciplinary programs impact engineering students’ career choices. The research team will conduct interviews with students in both multi-disciplinary and single disciplinary engineering programs at a large public university. Interviews will be framed using social cognitive career theory and will explore how learning experiences, personal characteristics, and environmental influences impact students’ decision-making process for career selection, as well as outcome expectations and their confidence in their ability to succeed on that path. Researchers will employ inductive and deductive thematic analysis techniques in combination with narrative analysis to elevate the experiences and perspectives of diverse engineering students. The results of this research will generate knowledge about how multi- and interdisciplinary programs influence students’ career choices and decisions to persist in an engineering career. These findings on interdisciplinary engineering education will help educators design programs to support tomorrow’s industry needs and adapt to evolving career paths. As a director of an interdisciplinary engineering program, the PI is well-positioned to make significant positive impact on the nearly two hundred students who are enrolled annually in an integrated business and engineering program at a large public university. The advisory board will support the research team in interpreting findings and tailoring dissemination to other leaders of similar programs in the US. The project also supports NSF’s significant investment in research initiation grants in the last decade by using a collaborative autoethnographic study of this project to explore the mechanisms by which research mentoring relationships succeed. The findings of the collaborative autoethnographic study will expand the knowledge of how structured mentorship of engineering faculty can build research capacity in engineering education. This will have useful implications for NSF research initiation programs such as the Research Initiation in Engineering Formation (RIEF) and Building Capacity in STEM Education Research (BCSER) programs and will also offer the potential to improve other peer-to-peer or hierarchical mentor training initiatives. 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.