# data[].attributes.title
Determining how the evolution of the coronavirus macrodomain contributes to its biochemical and virological functions

# data[].attributes.awardee_organization.name
University of Kansas Center for Research Inc

# data[].attributes.abstract
This project explores how macrodomain proteins have evolved to balance their different multiple biochemical activities. Macrodomains are ancient enzymes that bind to and remove ADP-ribose, an important post-translation modification that is critical in several cellular stress responses, including DNA damage, ER stress, and virus infection. These enzymes are conserved through all domains of life, including archaea, bacteria, eukaryotes, and viruses, indicating that they are critical for multiple cellular processes. However, the function of macrodomain enzymes in cell biology and microbiology are just now being uncovered. Furthermore, recent research indicates that macrodomains have evolved to properly balance their biochemical functions depending on if they are expressed from a virus, a bacteria, or from a eukaryotic cell. This project will evaluate how viral macrodomains have evolved to develop the ideal biochemical properties that allow them function in the context of a virus infection. This project also has strong educational and community outreach components. Most notably, students at all training levels will participate in this project and will learn how to evaluate the evolution of proteins through workshops in phylogenetics. This project will provide new insights into the fundamental biology of macrodomain enzymes and could lead to new insights into antiviral drug-development.    This project aims to define how the coronavirus macrodomain has evolved to best function in the context of a virus infection using the mouse coronavirus, murine hepatitis virus (MHV), as a model. The use of MHV, which is unable to infect humans, for creating macrodomain mutations eliminates the potential for gain-of-function research. Research over the last decade has demonstrated that the coronavirus macrodomain blocks innate immune responses, is critical for viral pathogenesis, and is a potential drug target. Furthermore, the macrodomain uses both its ADP-ribose binding and hydrolysis activities to promote virus replication, and they must be balanced for optimal replication. The PI will use recombinant proteins and a panel of recombinant viruses, developed using a bacterial artificial chromosome based reverse genetic system, to better understand how highly conserved amino acids and selective pressure induced mutations impact Mac1 biochemical activities, virus replication, and pathogenesis using well-established assays and model systems. Additionally, macrodomains from across the evolutionary spectrum will be expressed in the context of MHV infection to define the evolutionary limits of macrodomain divergence that is tolerated in MHV. This work will provide a deeper understanding of how macrodomains have evolved to counter various ADP-ribose dependent antiviral responses.    This project is jointly funded by the Genetic Mechanisms Program and the Division of Molecular and Cellular Biosciences.    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.

# data[].attributes.title
Collaborative Research: CUE-T: Broadening Participation in Computing via Active Learning Strategies in Multi-Institution Online Synchronous Learning Environments

# data[].attributes.awardee_organization.name
Georgia Southern University Research and Service Foundation, Inc

# data[].attributes.abstract
Due to the COVID pandemic, most U.S. Institutions of Higher Education (IHEs) transitioned in-person classes to online classes. Such a transition provides fertile ground for research into improving undergraduate STEM education in computing fields, specifically in broadening participation for underrepresented students and improving learning outcomes. There are ongoing challenges in attracting and retaining students to computing. This project intends to explore the impact of combining effective active learning approaches in computing courses in online synchronous learning environments (OSLEs) across multiple institutions with a Learning Assistant model. The proposed approach has the potential to improve student learning outcomes and retention rates in computing.    This project's primary goal is to explore the impact of integrating effective active learning approaches in computing OSLEs and sharing resources across multiple institutions on students' learning outcomes, engagement, and retention. The project team plans to use a mixed-methods experimental design to investigate four research questions focusing on conducting professional development, using active learning approaches on student learning outcomes and retention rates, and sharing courses across institutions. This project will be conducted at six institutions, including two Hispanic Serving Institutions, two Historically Black Universities, and two small universities. This proposed project has the potential to significantly pathways for computing in both academia and industry.    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.

# data[].attributes.title
S-STEM: Bothell Engineering and Technology Scholars

# data[].attributes.abstract
The UW Bothell Engineering and Technology Scholars project will contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need at the University of Washington Bothell. UW Bothell is a Minority Serving Institution, and its student body is one of the most diverse in the state where 38% of incoming first-year students are first generation and 28% are eligible for federal Pell Grants. Over its six-year duration, this Track 2 S-STEM project will fund scholarships to 60 unique full-time students who are pursuing bachelor's degrees in Engineering and Technology (E&T), including computer and software systems, computer engineering, mechanical engineering, electrical engineering, data visualization, mathematics, and physics.  Project activities include dedicated math and science courses and cohort-based programming that provides academic success workshops, networking and career development opportunities, and faculty mentoring. Faculty mentors will learn about proven best practices and support each other through a faculty learning community. This project investigates which of several evidence-based strategies are the most effective in supporting and training low-income students specifically interested in E&T degrees through their journey from first year through graduation. In addition to measuring traditional elements of student success such as pass, persistence, and graduation rates, the project tracks students' sense of purpose, academic and social belonging, career readiness, and overall well-being. Faculty will deepen their understanding of the complex student experiences and use this knowledge to help address institutional barriers for all students entering UW Bothell in the post-pandemic era.      The overall goal of this project is to increase STEM degree completion of academically talented, low-income undergraduates with demonstrated financial need.  This project seeks to increase the percentage of students who complete an E&T major by providing coaching, dedicated academic support, and re-designed prerequisite courses; increase the number of students obtaining an E&T major by providing faculty mentoring, networking, and career development opportunities that promote a sense of belonging and a sense of purpose; and enhance faculty and staff ability to best support student populations by creating an ongoing faculty learning community.  Currently, only 30% of incoming students who want to pursue E&T degrees graduate with an E&T degree, and the diversity of the incoming class is starkly different from the graduating class. National and institutional research indicates that the loss of UW Bothell students in E&T fields can be attributed to four primary barriers: financial burdens, early academic struggles, a lack of sense of belonging and purpose, and complex institutional systems. Research has shown that providing financial support, academic support through dedicated coursework and academic seminars, mentoring, cohort experiences, and/or career development opportunities can help bridge these barriers. The project will provide additional support to faculty mentors to help students overcome these barriers and provide faculty opportunities to learn about and address institutional barriers. Most research studies only examine one or two of these components. This project seeks to understand which combination of programing, academic support, pedagogical approaches, and faculty mentoring have the greatest impact for low-income students by implementing an extensive assessment plan. The assessment plan utilizes both formative and summative evaluation methods that include student and faculty mentor surveys, student focus groups, and monitoring of institutional data to explore our research questions: (1) How are academic supports affecting students' academic skills and metrics of success? (2) How are mentorship and professional development activities affecting students' sense of belonging, purpose, and commitment to pursuing a STEM degree? (3) What is the relative importance of various program elements for retaining students in STEM? (4) How is the faculty mentor learning community affecting faculty perceptions of student experience and assets? (5) To what extent is the program providing responsive program supports and how can the program supports be improved?  Results of the project will be published in journal articles and presented at conferences.  Project information will also be available on a public website.  This project is funded by NSF's Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of low-income academically talented students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future STEM workers, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income 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.

# data[].attributes.title
RUI: BMAT: Evaluating Ionizable Amphiphilic Janus Dendrimers as Delivery Agents for Nucleic Acids

# data[].attributes.abstract
NON-TECHNICAL SUMMARY:    Methods to alter gene expression have the potential to transform modern medicine. These tools directly modify genetic information or change how much or how little a specific gene is expressed. Many of these approaches use molecules called nucleic acids to treat disease, but for these therapies to be successful, small particles or vesicles must encapsulate and carry these nucleic acids to desired cell types. Various biomaterials such as lipids, polymers, and dendrimers have been used to construct these carrier systems. A relevant example of such a system is the COVID-19 vaccine, a lipid-based nanoparticle that delivers messenger RNA (mRNA) to elicit an immune response. Understanding how these biomaterials influence the physical properties of the resulting particles and how they affect interactions within the body is critical to designing effective materials for delivery of nucleic acid therapeutics. This work aims to characterize vesicles made from a new type of molecule called ionizable amphiphilic Janus dendrimers (IAJDs). Janus dendrimers are structures with two different chemical characteristics on each side. The proposed studies will establish how differences in IAJD properties affect vesicle characteristics like size and shape, how these vesicles interact with common biological proteins like those found in the blood stream, and how these vesicles enter and release nucleic acids in cells. More broadly, this project will provide meaningful hands-on research experiences for undergraduate students via summer research opportunities and development of a mini-course based undergraduate research experience (mini-CURE) in biophysical chemistry. Undergraduates will also be encouraged to explore their scientific interests and participate in the broader scientific community via participation in a STEM-focused student club on campus.     TECHNICAL SUMMARY:    Effective use of nucleic acid therapeutics relies on delivery agents that enhance nucleic acid circulation times, shield from nucleases, and aid in intracellular delivery. In particular, the success of RNA therapeutics, including messenger RNA (mRNA) and small interfering RNA (siRNA), can be attributed to innovations surrounding the ionizable lipid component of the lipid nanoparticle (LNP); however, challenges associated with immunotoxicity, laborious syntheses, and extrahepatic delivery continue to limit the scope of these delivery vehicles, suggesting a need for new ionizable amphiphilic molecules. Recently, ionizable amphiphilic Janus dendrimers (IAJDs) have emerged as tools to encapsulate and deliver mRNA in vivo via a one-component dendrimersome nanoparticle (DNP) delivery system. Initial publications exploring mRNA delivery using DNPs suggest that IAJD structure dictates in vivo localization as well as activity; however, fundamental and mechanistic questions remain. The major goal of this work is to characterize DNPs prepared from IAJDs in the presence and absence of nucleic acid therapeutics (mRNA and siRNA) and understand how these DNPs interact with and within biological systems. Specifically, this work will (1) elucidate how IAJD structure dictates the physical characteristics of DNPs including size, shape, morphology, and nucleic acid encapsulation, (2) determine how these differences influence interactions of DNPs with serum proteins, thus impacting cytotoxicity and immunogenicity, and (3) evaluate mechanisms for cellular internalization and functional delivery of mRNA and siRNA. These studies will establish structure-function relationships to explain how DNPs encapsulating nucleic acids exert their therapeutic effects. This project will provide meaningful hands-on research experiences for undergraduate students via summer research opportunities and development of a mini-course based undergraduate research experience (mini-CURE) in biophysical chemistry. Undergraduates will also be encouraged to explore their scientific interests and participate in the broader scientific community via participation in a STEM-focused student club on campus.    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.

# data[].attributes.title
Collaborative Research: III: Small: Towards A Computational Foundation of Post-Pandemic Network Science of Team

# data[].attributes.funder_divisions[]
Computer and Information Science and Engineering (CISE)

# data[].attributes.abstract
Teams appear in almost any organization such as universities, corporations, and governments. The importance of teams is even more evident with the work practice has been evolving to a new hybrid mode – a combination of work in office and from home which inevitably changes how people collaborate as a team. Consequently, it presents new challenges to team collaborations, in that it increases difficulty of communications, stifles innovation, and affects collaboration. Despite an organization as well as an individual’s profound dependency on teams and the rapid changing landscape of team-enabled operations, computational models, algorithms and tools to optimize the team collaboration are lacking and lagging. To name a few, how to model the multi-channel, multi-platform team collaboration data? How to foresee the rising or the falling of a team at an early stage? How to form a high-performing team as well as to enhance the performance of an existing team?    This project develops data mining models, algorithms and tools to optimize team collaboration facing novel challenges in a new hybrid working environment. It consists of three mutually complementary and synergistic research tasks. The first task models the raw team collaboration data to provide a worldview representation of how complex tasks are conducted by teams in multiple channels and platforms. The second task builds multi-task, multi-target predictive models to forecast the performance of a given team. The third task develops algorithms and tools to optimize teams. Specially, it develops data-driven approaches to form and enhance teams. Based on that, it develops reinforcement learning based methods to proactively optimize teams and game-theoretic methods to interactively optimize teams by incorporating user feedback. This project helps improve team efficacy, and optimize human resource allocation, thereby mitigating the challenges that the post-pandemic age has posed to the workforce. The project team actively seeks to engage under-represented students. The research outcome of this project is disseminated through publications, tutorials and open-source software.    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.

# data[].attributes.title
Collaborative Research: III: Small: Towards A Computational Foundation of Teams Network Science

# data[].attributes.funder_divisions[]
Computer and Information Science and Engineering (CISE)

# data[].attributes.awardee_organization.name
University of Illinois at Urbana-Champaign

# data[].attributes.abstract
Teams appear in almost any organization such as universities, corporations, and governments. The importance of teams is even more evident with the work practice has been evolving to a new hybrid mode – a combination of work in office and from home which inevitably changes how people collaborate as a team. Consequently, it presents new challenges to team collaborations, in that it increases difficulty of communications, stifles innovation, and affects collaboration. Despite an organization as well as an individual’s profound dependency on teams and the rapid changing landscape of team-enabled operations, computational models, algorithms and tools to optimize the team collaboration are lacking and lagging. To name a few, how to model the multi-channel, multi-platform team collaboration data? How to foresee the rising or the falling of a team at an early stage? How to form a high-performing team as well as to enhance the performance of an existing team?    This project develops data mining models, algorithms and tools to optimize team collaboration facing novel challenges in a new hybrid working environment. It consists of three mutually complementary and synergistic research tasks. The first task models the raw team collaboration data to provide a worldview representation of how complex tasks are conducted by teams in multiple channels and platforms. The second task builds multi-task, multi-target predictive models to forecast the performance of a given team. The third task develops algorithms and tools to optimize teams. Specially, it develops data-driven approaches to form and enhance teams. Based on that, it develops reinforcement learning based methods to proactively optimize teams and game-theoretic methods to interactively optimize teams by incorporating user feedback. This project helps improve team efficacy, and optimize human resource allocation, thereby mitigating the challenges that the post-pandemic age has posed to the workforce. The project team actively seeks to engage under-represented students. The research outcome of this project is disseminated through publications, tutorials and open-source software.    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.

# data[].attributes.title
Investigating the Uptake of Research-Based Instructional Strategies: A Post-COVID Update

# data[].attributes.abstract
This project aims to serve the national interest by mapping national patterns in the use of research-based instructional practices in post-secondary chemistry, mathematics, and physics courses five years after the disruptions due to the COVID-19 pandemic. In the Spring of 2019, a survey was sent to roughly 18,000 instructors of first-year mathematics, chemistry, and physics courses at nearly 1000 post-secondary institutions. That survey provided a comprehensive view of introductory science courses and instructors across the United States, with responses from nearly 4000 faculty from 660 U.S. colleges and universities. However, just one year later colleges and universities across the nation quickly shifted to online, emergency remote teaching in response to the COVID pandemic. The scale of instructional change during this time was both unprecedented and ubiquitous, with nearly every instructor teaching in the spring of 2020 required to try something new, and many needing to continue experimenting and revising their courses for the following semesters. This project will repeat the 2019 survey in order to characterize any lasting impact of the COVID pandemic on undergraduate science education and understand what this new instructional landscape may mean for change agents working to improve undergraduate science education through the uptake of research-based instructional practices.    The goals of this project are to 1) understand the impact of the COVID pandemic on undergraduate science education as well as provide a current description of undergraduate science instruction, and 2) in consideration of any shifts following the COVID disruption to higher education, revise and update the research-based insights and recommendations for supporting and achieving instructional change in undergraduate STEM. To do so, the roughly 18,000 instructors will be re-surveyed. Some of the survey analyses will be conducted on the new responses alone, including multilevel modeling of the impact of malleable factors on instructors’ adoption of research-based instructional practices. Other analyses will incorporate the prior results for pre-post analysis to capture changes in the practices of both individuals and the disciplines in the aggregate. Where changes are observed, additional statistical tests and modeling will be used to identify the impact of emergency response teaching strategies on those shifts. These findings will be used by change agents (e.g., professional development organizations, instructional coaches) to better support undergraduate instructors in implementing research-based instructional strategies and by administrators (e.g., department chairs, course coordinators) in making resource allocations and policy decisions. These results will update the foundational knowledge base needed to support widespread pedagogical shifts toward the use of research-based instructional practices in post-secondary STEM education, impacting undergraduate students across the country. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Institutional and Community Transformation track, the program supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities.    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.

# data[].attributes.title
HBCU-UP RAPID: HBCU Leadership Crisis on STEM Broadening Participation and Research Capacity Building - Impact and Implications

# data[].attributes.abstract
The Historically Black Colleges and Universities - Undergraduate Program (HBCU-UP) supports RAPID projects when there is an urgency concerning the availability of, or access to, data, facilities, or specialized equipment, including quick-response research on natural or anthropogenic disasters and similar unanticipated events, such as the COVID-19 pandemic. During and after the COVID-19 pandemic, several higher education institutions experienced changes in the president and chancellor positions. For Historically Black Colleges and Universities (HBCUs), in 2022 alone, there were 23 leadership changes announced, and in 2023, 41 changes were announced, almost double within one year. Essentially, one in four HBCUs experienced a resignation or termination at the highest administrative level. These leadership changes have been an added challenge to the ongoing recovery efforts of many HBCUs that were also disproportionately impacted by the global pandemic. HBCUs are critical for science, technology, engineering, and mathematics (STEM) education and workforce development and for their contributions to STEM research. HBCUs are critical players in helping the nation stay competitive globally and are a national asset, considering the large numbers of diverse students earning degrees in STEM from HBCUs. Unfortunately, excessive executive leadership turnover could negatively impact those efforts.    This research study will explore the institutional impact of turnover at the President/Chancellor and executive cabinet levels at HBCUs. By using pilot data collected at one of the largest annual convenings of HBCU executives related to the impact and implications of HBCU leadership turnover, our proposed convening to collect rich qualitative data, and their feedback on the pilot survey results, will dynamically and strategically gain insight on this unprecedented challenge. This project will contribute to better understanding the impacts of leadership turnover and create recommendations for best practices. Ultimately, the results from this study are intended to increase stability at HBCUs experiencing leadership transitions so HBCUs can continue to play their important role in broadening participation in STEM, undertaking important STEM research, and providing excellent STEM educational 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.

# data[].attributes.title
Endoplasmic Reticulum (ER)-phagy in Influenza Infection

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.awardee_organization.name
UNIVERSITY OF VERMONT & ST AGRIC COLLEGE

# data[].attributes.abstract
Influenza infection in susceptible patients results in a higher viral load, cytokine storm, tissue damage, lung function decline, and mortality. It is well known that interferons control influenza burden and inflammatory responses. However, mechanistic understandings of IFN-mediated regulation of influenza burden in the lung epithelial cells is unclear. We have identified a novel association between Endoplasmic Reticulum (ER)-specific-autophagy response, termed ER- phagy, as regulators of the influenza burden in lung epithelial cells. Characterizing the epithelial ER-Phagy-IFN axis in influenza infection will be the focus of the current application. Unraveling this axis in lung epithelial cells provides much-needed mechanistic insights into controlling viral burden and mitigating virus-induced lung injury. Our preliminary data suggest that levels of ER- phagy receptors in lung epithelial cells regulate viral burden in an IFNβ dependent manner. Based on these novel data, we hypothesize that lung epithelial cells upregulate IFNβ- and IRE1- dependent ER-phagy to diminish viral burden. We will test this hypothesis in the following specific aims: In specific aim 1, we will determine that specific ER-phagy receptors are required to decrease influenza burden in epithelial cells and subsequent lung injury. Aim 2 will use epithelial-specific knockouts of IFNAR1 receptor and recombinant interferons to determine that the type-I IFNs regulate ER-phagy activity post-IAV infection to control IAV burden and lung injury. These studies will determine that the ER-Phagy-IFN axis acts as a first line of defense in the primary site of influenza infection (epithelial cells) to decrease the IAV burden and subsequent lung injury.

# data[].attributes.title
SARS-CoV-2 initiation and acceleration of AD pathology in the setting of endogenous and exogenous risk factors

# data[].attributes.abstract
The uncertain e,ology of Alzheimer’s disease poses signiﬁcant obstacles to the development of both therapeu,c and preven,on strategies. At the root of this quandary is the fact that familial disease accounts for a very small frac,on of cases, with the vast majority remaining gene,cally sporadic. The most widely known risk factor, the ApoE4 allele of the gene coding for apolipoprotein E, has been iden,ﬁed, but mechanis,c ,es to disease development are s,ll emerging. Neuroinﬂamma,on has long been suspected as a contribu,ng factor, and regular exercise documented as a mi,ga,ng factor, with theories to explain their eﬀects being posed, but again with liGle mechanis,c proof. A picture of a very complex process of ini,a,on and progression of Alzheimers disease and related demen,as (AD/RD) including Pick’s disease, fronto-temporal demen,a (FTD) and other tauopathies, is slowly emerging. A key factor in the e,ology of AD/RD that repeatedly crops up is viral infec,on. COVID-19 has brought new aGen,on to this factor, with the observa,on that a frac,on of those infected experience “brain-fog”, a catch-all term that includes cogni,ve dysfunc,on, memory dysfunc,on and mental fa,gue, marked by impaired ability to perform mental tasks compared to before the infec,on. Several factors however, complicate an understanding of the eﬀect of COVID-19 on AD/RD and cons%tute the driving ques%ons for this proposal: These include (1) What are the rela,ve contribu,ons of gene,c risk factors and COVID-19 on ini,a,on and progression of AD/RD? (2) What are the eﬀects of SARS-CoV-2 variants: ex,nct strains e.g. Wuhan, alpha, delta vs. current strains e.g. omicron and its lineage, and their sequen,al infec,on on AD/RD ini,a,on and progression? (3) What are the eﬀects of prior infec,ons with other highly prevalent viruses e.g. HSV-1 on the ini,a,on and progression of AD/RD by SARS-CoV-2? Successful comple,on of this work will probe the rela,onship between COVID-19 and neurodegenera,on, while yielding deep mechanis,c insights into the role of SARS-CoV-2 in combina,on with HSV-1 in triggering/accelera,ng an AD phenotype and focus a search for therapeu,c targets to counteract AD ini,a,on/accelera,on/progression.

# data[].attributes.keywords[]
National Institute of Neurological Disorders and Stroke