Grants
23,966 grants found
Advanced Rehabilitation Research Training (ARRT) Program - Community Living and Participation
openAdministration for Community Living
Advanced Rehabilitation Research Training (ARRT) Program - Community Living and Participation
Advanced Rehabilitation Research Training (ARRT) Program - Employment
openAdministration for Community Living
Advanced Rehabilitation Research Training (ARRT) Program - Employment
Advanced Rehabilitation Research Training (ARRT) Program - Health and Function
openAdministration for Community Living
Advanced Rehabilitation Research Training (ARRT) Program - Health and Function
Advanced Technological Education
openU.S. National Science Foundation
Advanced Technological Education
Advanced Technologies and Instrumentation for the Astronomical Sciences
openU.S. National Science Foundation
Advanced Technologies and Instrumentation for the Astronomical Sciences
Advancement and Innovation in Measurement of Language Development and Predictors (R01 Clinical Trial Not Allowed)
openNational Institutes of Health
Advancement and Innovation in Measurement of Language Development and Predictors (R01 Clinical Trial Not Allowed)
Advancement and Innovation in Measurement of Language Development and Predictors (R21 Clinical Trial Not Allowed)
openNational Institutes of Health
Advancement and Innovation in Measurement of Language Development and Predictors (R21 Clinical Trial Not Allowed)
Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01 Clinical Trial Optional)
openNational Institutes of Health
Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01 Clinical Trial Optional)
Advancing Healthcare for Older Adults from Populations that Experience Health Disparities (R01 - Clinical Trial Optional)
openNational Institutes of Health
Advancing Healthcare for Older Adults from Populations that Experience Health Disparities (R01 - Clinical Trial Optional)
Advancing HIV Vaccine Development with a Lipid Nanodisc Platform
openNIAID - National Institute of Allergy and Infectious Diseases
Project Summary The envelope (Env) glycoprotein of HIV is the only viral protein on the surface of virions, making it the sole target of B cell-based HIV vaccines. While Env is natively a transmembrane protein, most vaccine development relies on soluble versions of the trimer. These versions lack the membrane-proximal external region (MPER) epitope, the native bilayer environment, and the transmembrane (TM) and C- terminal (CT) domains. Broadly neutralizing antibodies (bnAbs) targeting MPER have remarkable breadth, reaching near-complete coverage of all circulating HIV strains, thus making MPER an attractive target for vaccine development. Recent progress in MPER-targeted vaccine development has been notable on two fronts. First, in the HVTN133 clinical trial, MPER peptide presented in a liposome formulation induced a B cell lineage for bnAbs and their precursors and reached 15 % neutralization breadth of a global tier 2 panel. Second, two studies described the development of a germline targeting immunogen for 10E8-class MPER bnAb, and affinity maturation process of the primed antibodies in pre-clinical mouse models. Characterization of new and improved MPER- targeting immunogen candidates and responses they elicit will require biophysical and structural analysis. Challenges in handling Env as a recombinant transmembrane protein therefore persist. This project incorporates engineered transmembrane Env vaccine candidates into stable lipid nanodiscs using membrane scaffold proteins and a selection of lipid molecules. This solution enables scalable and reproducible in vitro characterization and optimization of engineered transmembrane Env-based immunogens and evaluation of in vivo responses from MPER-targeting immunizations. Env nanodiscs allow using transmembrane Envs under identical conditions that have been established for soluble Envs in commonly used iterative vaccine development methods. In the first specific aim of this proposal, Env nanodisc structures are solved in complex with MPER-targeting antibodies to give guideposts for vaccine development. In the second, nanodiscs are assembled with controlled lipid compositions to elucidate the contribution of the bilayer surface to MPER antibody binding. Lastly, the third specific aim establishes conditions for utilizing Env nanodiscs in electron microscopy- based polyclonal epitope mapping (EMPEM). All aims will collectively contribute to improved nanodisc assembly pipeline that can be scaled to serve multiple HIV MPER targeting vaccine development projects. This pipeline can also serve the development of any transmembrane Env immunogen that targets other epitopes. Ultimately, the tools will be made available for other virus glycoprotein vaccine development projects beyond HIV.
Advancing HIV/AIDS Research within the Mission of the NIDCD (R01 Clinical Trial Optional)
openNational Institutes of Health
Advancing HIV/AIDS Research within the Mission of the NIDCD (R01 Clinical Trial Optional)
Advancing HIV/AIDS Research within the Mission of the NIDCD (R21 Clinical Trial Optional)
openNational Institutes of Health
Advancing HIV/AIDS Research within the Mission of the NIDCD (R21 Clinical Trial Optional)
Advancing neurodevelopmental outcome prediction in children exposed to HIV using clinical features and placental imaging
openNICHD - Eunice Kennedy Shriver National Institute of Child Health and Human Development
PROJECT SUMMARY More than one million children who are HIV-exposed but uninfected (CHEU) are born to pregnant people with HIV (PPHIV) every year. CHEU have a higher risk of adverse early-life outcomes than HIV-unexposed peers, including neurodevelopmental deficits and a >2-fold risk of growth stunting. The pathophysiology of adverse CHEU outcomes is incompletely understood, but mounting evidence suggests that placental abnormalities play a key role. A better understanding of the causes and mechanisms of poor developmental outcomes in CHEU is essential to improve the care of PPHIV and their offspring. Our overarching goal is to determine which 1) clinical, 2) placental histological, and 3) placental stereologic features predict adverse CHEU neurodevelopmental and growth outcomes. Leveraging our ongoing multi-country (Uganda, South Africa) birth cohort (n=1,200) and linked placental biobank, we will perform state-of-the-art 3D placental stereology and build artificial intelligence (AI) classifier models to predict CHEU child health outcomes, employing causal inference and instrumental variable analysis to account for confounding. We will also perform mediation analysis to determine whether placental features mediate the relationship between clinical and laboratory features and child outcomes. Innovation: Distinct advantages of our proposed research include 1) simultaneous collection and comparison of CHEU and HIV/antiretroviral-unexposed placentas and children, 2) use of rich clinical data and complementary methods [3D stereologic imaging and histopathology] to evaluate associations between placental abnormalities and adverse CHEU neurodevelopmental and growth outcomes, and 3) use of causal inference and mediation analysis methods to identify key and modifiable features. Investigators: Our interdisciplinary team with expertise in placental collection and birth cohorts (Bebell, Gray), placental pathology and AI (Goldstein), bioinformatics, AI, and mediation analysis (Dreyfuss, Kawuma), placental ARV effects (Serghides), developmental psychology (Malcolm-Smith), and pediatric neurodevelopment (Donald) is well-poised to complete this work. Approach: We will leverage biobanked placental samples and extend follow-up of enrolled mother-child dyads in Dr. Bebell’s (R01HD11232) and Dr. Gray’s (R01HD102050) birth cohorts; Dr. Serghides’ laboratory infrastructure, Dr. Goldstein’s AI algorithms, and Dr. Dreyfuss’ mediation analysis and causal inference methods to elucidate the effects of HIV and specific ARV exposure on the placenta and child neurodevelopment and growth through age 5 years via these Specific Aims: 1a) Identify clinical and laboratory features that predict neurodevelopmental and growth outcomes in CHEU, 1b) Determine whether placental histologic diagnoses advance neurodevelopmental and growth outcome prediction, and 2) Incorporate placental stereology features into prediction models for neurodevelopmental and growth outcomes. Identifying HIV- and specific ARV-related placental abnormalities and associations with adverse CHEU outcomes has great potential to improve child health by informing ARV selection in pregnancy and early identification and intervention for at-risk children.
Advancing neurodevelopmental outcome prediction in children exposed to HIV using clinical features and placental imaging
openNICHD - Eunice Kennedy Shriver National Institute of Child Health and Human Development
PROJECT SUMMARY More than one million children who are HIV-exposed but uninfected (CHEU) are born to pregnant people with HIV (PPHIV) every year. CHEU have a higher risk of adverse early-life outcomes than HIV-unexposed peers, including neurodevelopmental deficits and a >2-fold risk of growth stunting. The pathophysiology of adverse CHEU outcomes is incompletely understood, but mounting evidence suggests that placental abnormalities play a key role. A better understanding of the causes and mechanisms of poor developmental outcomes in CHEU is essential to improve the care of PPHIV and their offspring. Our overarching goal is to determine which 1) clinical, 2) placental histological, and 3) placental stereologic features predict adverse CHEU neurodevelopmental and growth outcomes. Leveraging our ongoing multi-country (Uganda, South Africa) birth cohort (n=1,200) and linked placental biobank, we will perform state-of-the-art 3D placental stereology and build artificial intelligence (AI) classifier models to predict CHEU child health outcomes, employing causal inference and instrumental variable analysis to account for confounding. We will also perform mediation analysis to determine whether placental features mediate the relationship between clinical and laboratory features and child outcomes. Innovation: Distinct advantages of our proposed research include 1) simultaneous collection and comparison of CHEU and HIV/antiretroviral-unexposed placentas and children, 2) use of rich clinical data and complementary methods [3D stereologic imaging and histopathology] to evaluate associations between placental abnormalities and adverse CHEU neurodevelopmental and growth outcomes, and 3) use of causal inference and mediation analysis methods to identify key and modifiable features. Investigators: Our interdisciplinary team with expertise in placental collection and birth cohorts (Bebell, Gray), placental pathology and AI (Goldstein), bioinformatics, AI, and mediation analysis (Dreyfuss, Kawuma), placental ARV effects (Serghides), developmental psychology (Malcolm-Smith), and pediatric neurodevelopment (Donald) is well-poised to complete this work. Approach: We will leverage biobanked placental samples and extend follow-up of enrolled mother-child dyads in Dr. Bebell’s (R01HD11232) and Dr. Gray’s (R01HD102050) birth cohorts; Dr. Serghides’ laboratory infrastructure, Dr. Goldstein’s AI algorithms, and Dr. Dreyfuss’ mediation analysis and causal inference methods to elucidate the effects of HIV and specific ARV exposure on the placenta and child neurodevelopment and growth through age 5 years via these Specific Aims: 1a) Identify clinical and laboratory features that predict neurodevelopmental and growth outcomes in CHEU, 1b) Determine whether placental histologic diagnoses advance neurodevelopmental and growth outcome prediction, and 2) Incorporate placental stereology features into prediction models for neurodevelopmental and growth outcomes. Identifying HIV- and specific ARV-related placental abnormalities and associations with adverse CHEU outcomes has great potential to improve child health by informing ARV selection in pregnancy and early identification and intervention for at-risk children.
Advancing neurodevelopmental outcome prediction in children exposed to HIV using clinical features and placental imaging
openNICHD - Eunice Kennedy Shriver National Institute of Child Health and Human Development
PROJECT SUMMARY More than one million children who are HIV-exposed but uninfected (CHEU) are born to pregnant people with HIV (PPHIV) every year. CHEU have a higher risk of adverse early-life outcomes than HIV-unexposed peers, including neurodevelopmental deficits and a >2-fold risk of growth stunting. The pathophysiology of adverse CHEU outcomes is incompletely understood, but mounting evidence suggests that placental abnormalities play a key role. A better understanding of the causes and mechanisms of poor developmental outcomes in CHEU is essential to improve the care of PPHIV and their offspring. Our overarching goal is to determine which 1) clinical, 2) placental histological, and 3) placental stereologic features predict adverse CHEU neurodevelopmental and growth outcomes. Leveraging our ongoing multi-country (Uganda, South Africa) birth cohort (n=1,200) and linked placental biobank, we will perform state-of-the-art 3D placental stereology and build artificial intelligence (AI) classifier models to predict CHEU child health outcomes, employing causal inference and instrumental variable analysis to account for confounding. We will also perform mediation analysis to determine whether placental features mediate the relationship between clinical and laboratory features and child outcomes. Innovation: Distinct advantages of our proposed research include 1) simultaneous collection and comparison of CHEU and HIV/antiretroviral-unexposed placentas and children, 2) use of rich clinical data and complementary methods [3D stereologic imaging and histopathology] to evaluate associations between placental abnormalities and adverse CHEU neurodevelopmental and growth outcomes, and 3) use of causal inference and mediation analysis methods to identify key and modifiable features. Investigators: Our interdisciplinary team with expertise in placental collection and birth cohorts (Bebell, Gray), placental pathology and AI (Goldstein), bioinformatics, AI, and mediation analysis (Dreyfuss, Kawuma), placental ARV effects (Serghides), developmental psychology (Malcolm-Smith), and pediatric neurodevelopment (Donald) is well-poised to complete this work. Approach: We will leverage biobanked placental samples and extend follow-up of enrolled mother-child dyads in Dr. Bebell’s (R01HD11232) and Dr. Gray’s (R01HD102050) birth cohorts; Dr. Serghides’ laboratory infrastructure, Dr. Goldstein’s AI algorithms, and Dr. Dreyfuss’ mediation analysis and causal inference methods to elucidate the effects of HIV and specific ARV exposure on the placenta and child neurodevelopment and growth through age 5 years via these Specific Aims: 1a) Identify clinical and laboratory features that predict neurodevelopmental and growth outcomes in CHEU, 1b) Determine whether placental histologic diagnoses advance neurodevelopmental and growth outcome prediction, and 2) Incorporate placental stereology features into prediction models for neurodevelopmental and growth outcomes. Identifying HIV- and specific ARV-related placental abnormalities and associations with adverse CHEU outcomes has great potential to improve child health by informing ARV selection in pregnancy and early identification and intervention for at-risk children.
Advancing Research on the Application of Digital Health Technology to the Management of Type 2 Diabetes (R01- Clinical Trail Required)
openNational Institutes of Health
Advancing Research on the Application of Digital Health Technology to the Management of Type 2 Diabetes (R01- Clinical Trail Required)
Advocacy and Public Education Programs
openThe Municipal Art Society of New York
Advocacy and Public Education Programs
AECOM- INCREASE & RENEWAL
openAECOM
Engineering and Research and Technology Based Services
AED Purchase for Recreation & Firehouse Meeting Room
openMorris
AED Purchase for Recreation & Firehouse Meeting Room
AEDC CDFI 17
openCDFI
AEDC CDFI 17
AEDC CDFI 18
openCDFI
AEDC CDFI 18
AEDC CDFI 19
openCDFI
AEDC CDFI 19
Aerospace 9100 ("AS9100") Certification
openContinuous Solutions LLC
Aerospace 9100 ("AS9100") Certification
Aerospace 9100 (“AS9100”) Certification
openFulcrum Technologies, Inc.
Aerospace 9100 (“AS9100”) Certification