Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=5&sort=other_investigators
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=other_investigators", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1419&sort=other_investigators", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=6&sort=other_investigators", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=4&sort=other_investigators" }, "data": [ { "type": "Grant", "id": "14894", "attributes": { "award_id": "1R01AI178605-01A1", "title": "A NOVEL STRATEGY TO INHIBIT SARS-COV-2 INFECTION AND COVID-19", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [ { "id": 6115, "first_name": "DIPANWITA", "last_name": "Basu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-06-13", "end_date": "2029-04-30", "award_amount": 697983, "principal_investigator": { "id": 31583, "first_name": "PHILIPPE ANDRE", "last_name": "GALLAY", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 745, "ror": "", "name": "SCRIPPS RESEARCH INSTITUTE, THE", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "While the development of effective vaccines against CoV-2 is cause for optimism, vaccine hesitancy in developed countries and shortages in low-income countries are jeopardizing efforts to curb the pandemic. Out of the 6.4 billion people living in low-income countries, only 2% have access to vaccines. Consequently, the conditions are ripe for continued spike mutation and evolution to increasingly transmissible strains causing more severe illness. Some of these emerging strains may even challenge the protection of vaccines. In this application, we propose a novel therapeutic approach for the eradication of CoV-2. We developed a new strategy, which consists of hijacking the viral replication machinery to trigger the death of CoV-2-infected cells, while preserving uninfected cells. We propose to administer intranasally human ACE2 transgenic mice and Syrian hamsters a “tailored” RNA encoding the diphtheria toxin fragment A (DTA) called {CoV-2 Hijack DTA} that is only recognized and transcribed by the CoV-2 polymerase (Pol/RdRp) present in infected cells, triggering DTA expression and rapid death of infected cells. Since DTA cannot cross the cellular membrane, it cannot kill uninfected cells. Because RNA can be easily broken down in the body, it needs to be transported within a protective carrier. Noninvasive aerosol inhalation is a well-established method of drug delivery to the respiratory tract and represents an ideal route for nucleic-acid-based therapeutics as demonstrated in various clinical trials. We propose to design degradable polymer-lipid nanoparticles (LNPs) that can deliver RNAs by nebulization (inhalation) to the respiratory tract. We propose to synthesize hyperbranched poly-beta amino esters (hPBAEs) to enable nanoformulation by nebulizer of stable and concentrated polyplexes suitable for inhalation. This strategy should achieve uniform distribution of RNAs throughout lungs resulting in high levels of proteins of interest 24h post-inhalation of hPBAE polyplexes without local or systemic toxicity due to rapid degradation of hPBAE vectors. The safety and antiviral efficacy of nebulized {CoV-2 Hijack DTA} RNA LNPs stably protected by degradable hPBAEs will be analyzed. Our in vivo imaging IVIS Lumina S5 system permits a daily bioluminescence (NanoLuc-CoV-2) or fluorescence (mNeonGreen CoV-2) quantification of the {CoV-2 Hijack DTA} RNA LNPs-mediated killing of infected lungs in live animals. We will investigate the MoA causing the killing of CoV-2-infected cells by {CoV-2 Hijack DTA}. We will use complementary approaches to determine whether {CoV-2 Hijack DTA} triggers apoptosis, membrane permeability and/or chromosomal degradation leading to cell killing. By scRNA-Seq, we will analyze i) the specific killing of infected cells at high resolution on large numbers of cells exposed to {CoV-2 Hijack DTA}; ii) the global map of apoptotic DNA breakpoints such as DNA fragmentation; and iii) the phenotype of immunological target cells. We will examine whether {CoV-2 Hijack DTA} RNA LNPs counteract the deleterious inflammatory response, which occurs during CoV-2 infection including histopathological lesion development, interstitial pneumonia and cytokine cascade.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15296", "attributes": { "award_id": "1R25AI175011-01A1", "title": "Integrated Training Program in Vaccinology (ITP-Vax)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [ { "id": 31247, "first_name": "MADELYN", "last_name": "Reyes", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-08-15", "end_date": "2029-07-31", "award_amount": 352643, "principal_investigator": { "id": 31887, "first_name": "Sharon Mei", "last_name": "Tennant", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 793, "ror": "", "name": "UNIVERSITY OF MARYLAND BALTIMORE", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "Vaccination has had a profound impact on human health and has eradicated or almost eradicated once feared diseases such as smallpox and polio and substantially decreased morbidity and mortality due to pneumococcus, measles and pertussis amongst many others. The utility and cost effectiveness of vaccination has been shown multiple times and most recently during the COVID-19 pandemic. SARS-CoV-2 has had a devastating effect on humankind causing significant morbidity and mortality as well as major disruptions to the economy, education, the supply chain and mental health. However, the extremely rapid development and deployment of multiple COVID-19 vaccines has allowed society to return to a semblance of normality. These vaccines were developed because of the large amount of money invested by governments to de-risk development and the many dedicated vaccinologists (laboratory personnel, clinical trialists, nurses, regulatory affairs specialists, statisticians etc. in academia, government and industry) who were committed to working on a common goal. Additionally, novel vaccine platforms had been in development for many years so the knowledge about how these platforms could be harnessed for COVID-19 was already present. In order to be ready for the next pandemic, we need to ensure that there are sufficient individuals entering and staying in the field of vaccinology so that they can develop new platforms, evaluate and dissect immune responses, perform clinical trials and have a broad understanding of the entire vaccine development process. The overarching goal of the Integrated Training Program in Vaccinology (ITP-Vax) is to encourage more trainees to join the field of vaccinology, particularly under-represented minorities (URM), and to enable our existing outstanding early-career vaccinologists to excel in mentorship and to become fully independent. To achieve this goal, we propose the following aims: Aim 1) To provide training in mentorship to early-career investigators and assist them on their path to independence in vaccinology, and Aim 2) To provide comprehensive training in vaccinology to post-baccalaureate or Master’s level students who are intending to apply for a PhD or medical school in the next 1-2 years and who seek a career in vaccinology. We will also actively engage and recruit URM’s for ITP-Vax so that we can ultimately improve diversity in vaccinology.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15304", "attributes": { "award_id": "1R01LM014156-01A1", "title": "Optimizing mRNA sequences with deep neural networks", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Library of Medicine (NLM)" ], "program_reference_codes": [], "program_officials": [ { "id": 31895, "first_name": "Catherine Mary", "last_name": "Farrell", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-08-26", "end_date": "2028-07-31", "award_amount": 351000, "principal_investigator": { "id": 31896, "first_name": "Xiaobo", "last_name": "Zhou", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 788, "ror": "", "name": "UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "The COVID-19 pandemic has presented new challenges to individuals world-wide. Since the first reports of infections in the US more than 90 million individuals have become infected and more than 1 million have died. SARS-CoV-2 genome has various open reading frames (ORFs) encoding 16 non-structural proteins (NSPs), 4 structural proteins and several accessory proteins. The genome of RNA virus can easily generate mutations as virus spreads. The constant emergence of new mutations in SARS-CoV-2 is the major challenge for the ongoing development of antiviral drug and broad neutralizing antibodies. The two mRNA vaccines from Pfizer/BioNTech and Moderna are moderate effective, 45 to 75 percent at protecting people from in preventing infection from the delta variant, and both of them have received emergency use authorization. More seriously, the omicron variant was first detected in southern Africa and quickly expanded to the whole world. According to a recent study, traditional dosing regimens of COVID-19 vaccines available in the US do not produce antibodies capable of recognizing and neutralizing the Omicron variant. The global data shows the coronavirus pandemic is far from over. Thus, more variants are expectable and some of them may escape the immune response produced after vaccination. How to keep the efficacy of existing mRNA vaccines on variants is challenging us. Aside from SARS- CoV-2, mRNA medicines against cancer and other infectious disease, such as Ebola, Zika virus, and influenza, are advancing through clinical trials. The goal of this project is to develop an integrated deep learning model to optimize 5'UTR, codon usage, and 3'UTR at same time that enables users to design the optimal mRNA sequence to enhance protein expression level, thus to improve the efficacy of mRNA medicines. mRNA medicines hold great promise for the treatment of a wide variety of disease, extending from prophylactics to therapeutics for infectious diseases, cancer, and genetic disease. mRNA medicines have several beneficial features: safety, efficacy, production, and speed. Multiple factors are involved to regulate the stability and efficiency of mRNA, including 5' untranslated region (UTR), 3' UTR, codon et al, and several in silico approaches have being developed to optimize these factors respectively However, as these factors always function together during the translation of mRNA, and individual optimization is insufficient. Thus, a novel integrated deep learning model for these factors is needed to comprehensively enhance the stability and efficiency of mRNA medicine. In silico optimization of mRNA vaccine provides a fast methodology to investigate all possible integration of the ORF, 5' UTR and 3'UTR and identify the optimal mRNA vaccine. The interdisciplinary team proposed to develop the following aims: (1) developing deep learning models for 5' UTR, codon, and 3' UTR respectively, and integrated model for systemic optimization of 5' UTR, codon, and 3' UTR; and (2) experimentally validate the integrated models by designing the 5'UTR, codon, and 3'UTR sequence for representative.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14985", "attributes": { "award_id": "5K99DK133502-02", "title": "Mechanisms of mitochondrial-ER communication during dietary and thermal induced stress", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)" ], "program_reference_codes": [], "program_officials": [ { "id": 20615, "first_name": "MAREN R", "last_name": "LAUGHLIN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-07-01", "end_date": "2025-06-30", "award_amount": 90000, "principal_investigator": { "id": 27594, "first_name": "Pedro Antonio", "last_name": "Latorre Muro", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 997, "ror": "", "name": "DANA-FARBER CANCER INST", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "Obesity is a pandemic affecting 40% of the population that increases the risk of serious metabolic diseases including type 2 diabetes and severe forms of SARS-CoV2 infection. Obesity reduces insulin sensitivity and dysregulates glucose homeostasis sustaining high blood glucose levels and the development of type 2 diabetes. Activation of brown adipocytes (BAs) is a promising approach to treat obesity and associated diseases. Brown adipocytes rely on an extensive network of mitochondria that increases energy expenditure and maintains glucose homeostasis through glucose, amino acid, and fatty acid oxidation. During fat-induced stress, mitochondrial-endoplasmic reticulum (ER) communication sustains cellular function in BAs. However, the mechanisms by which mitochondrial-ER communication shapes cellular adaptation during obesity are poorly understood. Therefore, studying these pathways will provide new therapeutical approaches to target obesity. The main goal of this application is to study the mechanisms of mitochondrial-ER communication that ensure mitochondrial function and cellular homeostasis during diet-induced stress. We have described that in BAs mitochondrial-ER communication promotes thermogenesis during cold stimulation through the ER-resident kinase PERK. To follow up this work, in Aim 1, the effects of long-term high fat diet (HFD) will be studied in UCP1-Cre PERK-/- mice exposed to different dietary and bioenergetic conditions. Our preliminary information suggests that PERK may be signaling to the chaperone PPID to control mitochondrial protein import. In Aim 2, structural approaches using Cryogenic Electron Microscopy (CryoEM) will be used to explore the molecular interactions that control and maintain mitochondrial functions in BAs including mitochondrial protein import, focusing on PPID-dependent pathway, and cellular respiration during dietary and thermal stress. Finally, in Aim 3 the role of PPID in physiology and cellular functions will be studied in mice exposed to diet and thermal stress. While Aims 1 and part of 2 will be completed during the training stage, part of Aim 2 and the entire Aim 3 will be conducted during the independent phase of the award. The extensive training in different fields proposed in this application including physiology and cellular and structural biology will provide the tools to become an independent researcher and study the mechanisms of inter- organalle communication that regulate mitochondrial biogenesis and cellular metabolism. This training will be received in the vibrant scientific communities of Dana-Farber Cancer Institute and Harvard Medical School. This environment will expose me to the collaborations and discussions necessary for career development and future opportunities. Dr. Puigserver mentorship will be supportive to establish those connections and actively guide me in talk and manuscript preparation, student mentorship, experimental design, and career development. Together, the research and career development plans proposed in this application will strengthen my skills and competitiveness to become an independent researcher at a major institution.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15096", "attributes": { "award_id": "2403380", "title": "Collaborative Research: SHF: Medium: SCIOPT: Toward Certifiable Compression-Aware SciML Systems", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Software & Hardware Foundation" ], "program_reference_codes": [], "program_officials": [ { "id": 2785, "first_name": "Almadena", "last_name": "Chtchelkanova", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-10-01", "end_date": null, "award_amount": 272992, "principal_investigator": { "id": 31636, "first_name": "Martin", "last_name": "Burtscher", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 204, "ror": "", "name": "Texas State University - San Marcos", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "The future of science-enabled discoveries critically relies on the speed of high-performance simulations conducted at large scales and high resolutions. Unfortunately, lacking such performance and scale, current approaches cannot keep up with the backlog of problems in areas of paramount societal consequence, such as climate science and the spread of pandemics. A principal reason for these shortfalls is the rising cost of moving huge amounts of simulation data between supercomputer memories and processors – a cost that increasingly dwarfs the time spent in actual computations. Thus, developing techniques to reduce the volume of data exchanged without sacrificing accuracy is key to future progress in computation-enabled research. Such data reduction is even more important in the emerging area of Scientific Machine Learning (SciML), where simulations are assisted by artificial intelligence (AI) based surrogate models, an area where the data exchange needs are often much higher. The investigators’ expertise in scientific machine learning, data compression, compilers, and program correctness will be central in our collaboration to help SciOPT achieve its goal of fast and reliable AI-assisted scientific simulations. The impact of this project will be to establish new technologies that reduce data volume without sacrificing accuracy in both high-performance computing and the emerging area of SciML. These technologies, in turn, translate directly into societal benefits such as improved healthcare and safer environments. The project will broaden participation in this area through undergraduate research plans that reach out to students from groups underrepresented in computing.<br/><br/>This research project, entitled SciOPT, will principally rely on data compression to reduce the amount of data moved: simulation data will be compressed before transmission and decoded upon reception before applying computations. The investigators will also pursue the potentially even more impactful approach of compressing the data and applying computations directly on the compressed data. SciOPT will evaluate both of these approaches in the context of challenging SciML applications that are currently bottlenecked by data exchanges. To ensure higher degrees of automation and productivity, SciOPT will develop efficient compiler-based methods to manage compressed data layout and locality. Moreover, it will automatically generate high-speed compression algorithms that are tailored to the data. To ensure the veracity of the computational results produced by these compressed-data simulations, SciOPT will include rigorous correctness-checking methods at multiple stages to guard the overall simulation workflows.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15160", "attributes": { "award_id": "2413049", "title": "Collaborative Research: SaTC: EDU: A Socially-Distant Cloud-Based Hardware Security Educational Platform", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Directorate for STEM Education (EDU)", "IUSE" ], "program_reference_codes": [], "program_officials": [ { "id": 31735, "first_name": "ChunSheng", "last_name": "Xin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-08-15", "end_date": null, "award_amount": 213100, "principal_investigator": { "id": 31737, "first_name": "Aydin", "last_name": "Aysu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 245, "ror": "https://ror.org/04tj63d06", "name": "North Carolina State University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "The main goal of this project is to develop and deliver remote experiments utilizing cloud-based resources aimed at educating a broad audience of students and practitioners in hardware security. In the post-COVID era, it is imperative to develop online education platforms for remote training of both students and the workforce in the field of Hardware Security. Recent advances in this field and FPGA-based cloud servers have enabled an opportunity to move related experiments to an online format that only requires a standard computer and internet connection by the students. Teaching “hardware” security in a socially distanced format poses significant challenges. Essential experiments for teaching key concepts in hardware security necessitate multiple evaluation boards and physical equipment such as voltage supplies, oscilloscopes, multimeters, and function generators. To adapt these experiments for an online platform, the project will explore innovative methods to execute or emulate them using the cloud ecosystem. This project addresses a critical gap by developing a fully online hardware security training module accessible to students and professionals worldwide. <br/><br/>This project proposes various comprehensive experiments testing different notions in hardware security. The framework will be designed for both undergraduate and graduate students in the electrical engineering, computer engineering, and computer science departments, leveraging courses developed by the PIs in their respective institutions. The proposed infrastructure includes preparing detailed experiments for instructors with walkthrough documents and organizing student assignments for independent completion. This setup supports not only teaching but also facilitates independent research upon assignment completion. Supplemented with video instructions, these experiments will constitute a comprehensive training module, equipping participants with the necessary skills and knowledge to address complex challenges in this emerging domain, thereby instilling preparedness and confidence. <br/><br/>This award is co-funded by the NSF Improving Undergraduate STEM Education (IUSE: EDU) Program. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. This project is further supported by the Secure and Trustworthy Cyberspace (SaTC) program, which funds proposals that address cybersecurity and privacy, and in this case, cybersecurity education. The SaTC program aligns with the Federal Cybersecurity Research and Development Strategic Plan and the National Privacy Research Strategy to protect and preserve the growing social and economic benefits of cyber systems while ensuring security and privacy.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15223", "attributes": { "award_id": "1R01AG087296-01", "title": "Alzheimer's Special Care Units in Nursing Homes: Racial and Ethnic Disparities, Resident Outcomes, and State Policies", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute on Aging (NIA)" ], "program_reference_codes": [], "program_officials": [ { "id": 27518, "first_name": "THERESA YOUNGJOO", "last_name": "Kim", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": "2028-05-31", "award_amount": 424184, "principal_investigator": { "id": 27405, "first_name": "Huiwen", "last_name": "Xu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 265, "ror": "https://ror.org/03czfpz43", "name": "Emory University", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true }, "abstract": "Alzheimer's special care units (SCUs) are a promising care model for nursing home residents with Alzheimer's Disease & Related Dementias (ADRD). SCUs provide higher quality care and improve outcomes for residents with ADRD. Our preliminary analysis further found that, in facilities with an SCU, the disparities in 3-month hospitalization rates and pressure ulcers between Hispanic and White residents were eliminated or greatly reduced. Despite the benefits of SCUs, racial and ethnic minority residents are less likely to access SCUs than White residents, suggesting that lack of SCU access may be a mechanistic pathway responsible for disparities in outcomes. Currently, SCUs are available in only 14% of nursing homes and access varies substantially across states. State Medicaid policies and SCU regulations can incentivize or disincentivize nursing homes to develop SCUs. By analyzing national Medicare claims and resident assessment data, as well as unique Ohio surveys of SCUs and resident and family satisfaction with care, we propose to understand the extent to which racial and ethnic differences in SCU access contribute to disparities in outcomes, and the associations of current state policies and regulations with SCU availability. The specific aims are: Aim 1) To examine disparities in access to Alzheimer's SCUs among Black and Hispanic residents with ADRD; Aim 2) To understand SCU access as a pathway to disparities in health outcomes among Black and Hispanic residents with ADRD; and Aim 3) To investigate which state policies are associated with increased availability of SCUs. The primary analyses will study the 819,415 newly-admitted long-stay residents with ADRD in 15,305 nursing homes from 2011 to 2019. The decomposition method will uncover factors that explain disparities in SCU access among Black and Hispanic residents, and mediation analyses will assess how differences in SCU access contribute to racial and ethnic disparities in health outcomes. Dominance analyses will evaluate the contribution of specific SCU characteristics (physical environment, staffing, and physician involvement) to health outcomes and resident and family satisfaction, as well as reduced racial and ethnic disparities. We will also analyze 2020- 2024 data to examine whether our findings hold during and after the COVID-19 pandemic. Hierarchical Generalized Linear Mixed Models and Difference-in-Differences method will explore which state policies (e.g., supplementary payments for SCU care, Medicaid payment-to-cost ratios, regulations about staffing or training) are associated with SCU availability. Understanding the role of SCU access in racial and ethnic disparities in ADRD-related outcomes can inform policymakers as they seek to mitigate disparities in nursing home care.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14886", "attributes": { "award_id": "1R01NS136806-01", "title": "Cerebral Energy Metabolism in ME/CFS with and without PASC", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Neurological Disorders and Stroke (NINDS)" ], "program_reference_codes": [], "program_officials": [ { "id": 10999, "first_name": "Vicky R", "last_name": "Whittemore", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-07-01", "end_date": "2029-06-30", "award_amount": 670721, "principal_investigator": { "id": 23743, "first_name": "Xiang", "last_name": "Xu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 625, "ror": "https://ror.org/04a9tmd77", "name": "Icahn School of Medicine at Mount Sinai", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Many patients who have recovered from SARS-CoV-2, the virus that causes COVID-19, continue to experience a constellation of symptoms long after the initial illness. Known as “long-COVID”, or Post- Acute Sequelae of SARS-Cov-2 infection (PASC), the most frequently reported symptoms are fatigue, post exertional malaise and cognitive dysfunction, which are also the primary symptoms of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). Many of the PASC patients fulfill diagnostic criteria for ME/CFS, but differ from non-PASC ME/CFS patients in that they share a common infectious trigger and have a shorter duration of illness, which reduces heterogeneity. Understanding whether PASC ME/CFS shares overlapping mechanisms with non-PASC ME/CFS is critical, as this could provide insights into the mechanisms and inform treatment strategies of ME/CFS in general. To address this question, we propose a comparison study of PASC ME/CFS patients with sudden onset illness to non-PASC ME/CFS patients who reported a sudden flu-like illness onset. Limited studies have shown reductions in cerebral blood flow and increased cerebroventricular lactate in ME/CFS patients suggesting alterations in perfusion and metabolic properties. Our recent preliminary results show that the oxygen extraction fraction was elevated in PASC ME/CFS patients, which may be attributed to reduced cerebral blood flow and mitochondrial dysfunction. In this project, we aim to conduct non- invasive brain magnetic resonance imaging (MRI) to compare the similarities and differences in cerebral oxygen and glucose metabolism between the two patient groups as well as healthy controls. We will measure and compare the oxygen extraction fraction, cerebral blood flow, and cerebral metabolic rate of oxygen and glucose uptake and metabolic rate in the patient groups and healthy controls. The MRI derived parameters will then be correlated to the disease symptom burden. Additional, since many PASC patients recover over one year, we aim to perform a follow-up study on the PASC and non-PASC ME/CFS groups. Completion of this timely and important study will provide comparison of PASC and non-PASC ME/CSF in terms of changes in glucose and oxygen metabolic properties, as well as how these imaging parameters are related to the disease burden. Through analysis of the longitudinal data, we will be able to determine whether the changes in metabolic properties are associated with changes of patient reported outcome measures. The knowledge learned will deepen our understanding of the ME/CFS/PASC (long-COVID) disease mechanisms, aid in ME/CFS diagnosis, inform treatment decisions, and inspire new treatment targets.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15102", "attributes": { "award_id": "2337089", "title": "Collaborative Research: Point-of-Care Additive Manufacturing for Health: Cultivating and Assessing Engineering Students' Technical Knowledge and Professional Skills", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Directorate for STEM Education (EDU)", "IUSE" ], "program_reference_codes": [], "program_officials": [ { "id": 2088, "first_name": "Jennifer", "last_name": "Ellis", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-10-15", "end_date": null, "award_amount": 59688, "principal_investigator": { "id": 31649, "first_name": "Ebtesam", "last_name": "Islam", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 782, "ror": "", "name": "Texas Tech University Health Science Center", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "This project serves the national interest by preparing a qualified engineering workforce with important technical and professional skills for the health-based point-of-care (POC) additive manufacturing (AM) industry. Health-based POC-AM is a non-traditional form of manufacturing referring to the just-in-time creation of anatomical models, surgical instruments, prosthetics, scaffolds, etc., based on medical imaging data and need at the place of patient care. The growth of POC-AM requires the collaboration of medical, engineering, and social science professionals in that engineers must be trained to be socially adept and communicative about additive manufacturing specifically for healthcare applications. Despite the exponential growth in POC-AM market value and scholarly activities, the needed education and training components are underdeveloped, especially for undergraduate students in public engineering schools. This IUSE Engaged Student Learning Level 2 project will bridge this talent gap by creating an undergraduate engineering course that is broadly accessible and will be able to define, cultivate, and assess students' technical and professional skills needed by the booming POC-AM industry. This project features a project-based learning plan to develop students' theoretical and hands-on skills to create a broad range of medical objects from non-patient-specific personal protection equipment and anatomical models to patient-specific prosthetics, tissues, and implants. This project will strongly emphasize the development of students' reflective communication skills, both written and verbal, with colleagues in both engineering and in healthcare. The project will also design a protocol for assessing and developing those communication skills using objective and subjective metrics.<br/><br/>Thus, the goal of this project is to remove barriers between POC-AM research and education while interconnecting key concepts in multiple related sub-disciplines through teaching this unique skillset to undergraduate students at two large public universities. The innovative course that focuses on students' technical and communication skills development will train holistic and well-rounded engineering students who can solve complex problems that require a broad integration of technical knowledge and communication skills. The combination of cutting-edge learning about POC-AM and a targeted and efficient communication skills development targeted to the needs of the post-COVID student population makes this project highly effective for undergraduate education. The developed instructional and assessment materials will be publicly available as this project can be a model for other similar upper division engineering courses, especially in an emerging and practical field. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. This project is jointly funded by the Established Program to Stimulate Competitive Research. This project is jointly funded by IUSE and the Established Program to Stimulate Competitive Research (EPSCoR).<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14873", "attributes": { "award_id": "1U18HS029937-01", "title": "Supporting Patients Recovering from COVID-19 (SPaRC)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "Agency for Healthcare Research and Quality (AHRQ)" ], "program_reference_codes": [], "program_officials": [ { "id": 31564, "first_name": "Latrice", "last_name": "Vinson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-07-01", "end_date": "2029-06-30", "award_amount": 1000000, "principal_investigator": { "id": 31565, "first_name": "Ann Marie", "last_name": "Parker", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 344, "ror": "https://ror.org/00za53h95", "name": "Johns Hopkins University", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "Project Summary: Long COVID impacts 10-30% of people after a SARS-CoV-2 infection, with potentially devastating long-term impact on quality of life. Moreover, Long COVID disproportionately affects minority, rural, older, and other at-risk populations. Multidisciplinary Long COVID clinics provide clinical care and offer infrastructure for evaluating promising interventions to improve Long COVID outcomes. The Johns Hopkins Post-Acute COVID-19 Team (JH PACT) is among the country's first and largest Long COVID programs. Via this AHRQ U18 proposal, JH PACT proposes the following Aims: (1) To deliver a comprehensive, multidisciplinary program (Supporting Patients Recovering from COVID, “SPaRC”) to patients with Long COVID, with an expanded focus on underserved populations. The SPaRC program will expand on the existing expertise of the JH PACT multidisciplinary Long COVID outpatient program to increase capacity and decrease wait times, with expanded services to underserved patient populations, including older adult, minority race/ethnicity, socioeconomically disadvantaged, and geographically distant and rural populations via enhanced partnerships with key existing organizations (e.g., Medicine for Greater Good, Center for Clinical Global Health Education). (2) To iteratively evaluate and refine the SPaRC Long COVID program to increase access and improve patient-centered, evidence-based care. The SPaRC program will be evaluated and iteratively refined in quarterly cycles via mixed methods evaluation (via patient data from electronic medical records and semi-structured qualitative interviews of patients/caregivers and staff/clinicians) to inform implementation strategies based on the “Expert Recommendations for Implementing Change” (ERIC) framework within a learning health system. In each review cycle, the implementation team and key SPaRC internal and external stakeholders will evaluate the program and outcomes and select goals for refinement and advancement for the next quarterly review cycle. An external Stakeholder Advisory Council, led by an independent Chair, will provide ongoing feedback via quarterly meetings throughout the project. (3) Partner with regional Long COVID stakeholders, including primary care providers (PCPs), to create and expand access to comprehensive, patient-centered, coordinated Long COVID care across the mid-Atlantic region. We will build a multi-disciplinary Long COVID provider-to-provider e-consult service, customized educational curriculum (delivered via both live and on-demand electronic formats), and continuing education toolkit for PCPs, in conjunction with key stakeholders (e.g., patients, caregivers, community leaders, and PCPs). JH PACT and the SPaRC Team include internationally-recognized experts in Long COVID care, patient outcomes assessment, implementation science, stakeholder/community engagement, and primary care education. JH PACT is ideally positioned to create a Long COVID Center of Excellence, leveraging the outstanding expertise available via Johns Hopkins Medicine, and to optimally engage with the AHRQ Learning Community.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 5, "pages": 1419, "count": 14184 } } }