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**AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** A MAJOR BOTTLENECK IN OUR ABILITY TO IMPROVE CROPS IS A GAP IN OUR UNDERSTANDING OF HOW GENETICS AND ENVIRONMENT INTERACT TO PRODUCE PLANT PHENOTYPES. PLANT PHENOMICS AIMS TO REDUCE THIS BOTTLENECK BY DEVELOPING IMAGING/REMOTE SENSING AND COMPUTATIONAL APPROACHES TO NON-DESTRUCTIVELY MEASURE AND MODEL PLANT PHYSICAL AND PHYSIOLOGICAL PROPERTIES IN HIGH THROUGHPUT AND AT HIGH TEMPORAL RESOLUTION. THIS IS AN INHERENTLY TECHNOLOGY-DRIVEN APPROACH, SO THE PLANT PHENOMICS COMMUNITY DRAWS ON EXPERTISE FROM THE BIOLOGICAL/AGRICULTURAL SCIENCES, COMPUTER AND DATA SCIENCES, ENGINEERING, STATISTICS, AND MATHEMATICS TO SOLVE PROBLEMS IN DATA ACQUISITION, DATA MANAGEMENT AND COMPUTING INFRASTRUCTURE, AND DATA ANALYSIS AND INTERPRETATION. WHILE EXTRACTION OF INFORMATION FROM MASSIVE AMOUNTS OF IMAGE AND SENSOR DATA IS STILL A GROWING AREA OF RESEARCH IN PLANT AND AGRICULTURAL SCIENCES, AN ABUNDANCE OF ALGORITHMS FOR INFORMATION EXTRACTION FROM THESE DATA TYPES EXISTS FROM THE COMPUTER SCIENCE, GEOSPATIAL, MEDICAL, AND OTHER COMMUNITIES. IN PARTICULAR, THE AVAILABILITY OF IMAGE AND OTHER DATASETS ON THE INTERNET HAS LED TO A SURGE IN METHODS TO MINE INFORMATION FROM THESE MASSIVE DATASETS. HOWEVER, WHILE THESE ALGORITHMS CAN BE LEVERAGED FOR PLANT PHENOTYPING PROBLEMS, SEVERAL COMMON PROBLEMS WITH IMPLEMENTING THEM IN AGRICULTURAL RESEARCH EXIST. FIRST, MOST IMAGE ANALYSIS TOOLS AND ALGORITHMS WERE DESIGNED OR TRAINED TO WORK WITH IMAGES OF PEOPLE, CARS, BUILDINGS, AND OTHER ANTHROPOCENTRIC SCENERY. SECOND, THESE ALGORITHMS ARE IMPLEMENTED SEPARATELY IN A VARIETY OF PROGRAMMING LANGUAGES AND PLATFORMS THAT MAKE IT MORE DIFFICULT FOR A NON-SPECIALIST TO USE FOR ANOTHER PURPOSE OR TO INTEGRATE WITH OTHER METHODS (INTEROPERABILITY). FINALLY, NEW ALGORITHMS ARE PRODUCED AT SUCH A RAPID PACE THAT IT IS DIFFICULT TO DISCERN THE STATE-OF-THE-ART OR MAKE DECISIONS ABOUT WHICH METHODS TO TRY AT ANY GIVEN POINT IN TIME. THROUGH THIS ALLIANCE OF PLANT PHENOTYPING SOFTWARE (APPS) DEVELOPERSCOORDINATED INNOVATION NETWORK, WE HOPE TO COORDINATE EFFORTS BY: 1) BRINGING TOGETHER DEVELOPERS OF EXISTING PLANT PHENOTYPING SOFTWARE TO MAKE TOOLS INTEROPERABLE; 2) BRINGING TOGETHER A MULTIDISCIPLINARY GROUP OF RESEARCHERS TO DEVELOP ALGORITHMS THAT WILL EXTRACT ADDITIONAL INFORMATION FROM EXISTING AGRICULTURAL DATA AND DEVELOP TOOLS THAT TACKLE CURRENT BOTTLENECKS IN AGRICULTURAL DATA ANALYSIS; 3) INTEGRATING EXISTING 'STAND-ALONE' TOOLS/ALGORITHMS FOR PLANT PHENOTYPING INTO SUSTAINABLE OPEN-SOURCE TOOLS FOR THE COMMUNITY; 4) ESTABLISHING A SUSTAINABLE NETWORK OF PHENOTYPING SOFTWARE DEVELOPERS AND USERS THAT PROMOTES REPRODUCIBLE RESEARCH AND REUSABLE AND EXTENSIBLE SOFTWARE; AND 5) ENGAGING PHENOMICS SOFTWARE USERS AND DEVELOPERS FROM THE PUBLIC AND PRIVATE SECTOR THROUGH HANDS-ON WORKSHOPS, TUTORIALS, AND NETWORK EVENTS AND ACTIVITIES. TO BE CLEAR, OUR AIM IS NOT TO BUILD A SINGLE MONOLITHIC SOFTWARE PACKAGE THAT CONSUMES ALL OTHERS. RATHER, THIS NETWORK WILL INTEGRATE TOOLS WHERE IT MAKES SENSE AND WILL CONNECT TOOLS WHEN IT MAKES SENSE TO KEEP THEM AS SEPARATE ENTITIES. ULTIMATELY, WE WANT THE NETWORK TO BUILD AN ECOSYSTEM THAT INCENTIVIZES SOFTWARE TOOLS THAT ENHANCE REPRODUCIBLE RESEARCH AND OPEN PUBLISHING OF CODE AND DATASETS.
$999,992Donald Danforth Plant Science Center · · FY2022 · National Institute of Food and Agriculture
NCS-FO:Distortions in Memory for Aversive Naturalistic Events
$999,864Vishnu P Murty · Temple University · · FY2021 · EDU
SBIR Phase II: Data Analytics and Physics-Based Insights into Vehicle Mobility Patterns
$999,600Samveg Saxena · Green Light Labs, Inc. · · FY2021 · TIP
Reforming Undergraduate Education in Environmental Engineering: Urban Studios as Knowledge Delivery Systems and Vehicles for Service Learning
$999,494Jack McGourty · Columbia University · · FY2004 · ENG
A Phase 1, Open Label, Multicenter Trial to Assess the Safety, Tolerability and Efficacy of MB-106 in Patients with Relapsed or Refractory CD20+ B-Cell NHL or CLL
$999,336Manuel Litchman · Mustang Bio, Inc. · R44 · FY2022 · CA
A Phase 1, Open Label, Multicenter Trial to Assess the Safety, Tolerability and Efficacy of MB-106 in Patients with Relapsed or Refractory CD20+ B-Cell NHL or CLL
$999,336Manuel Litchman · Mustang Bio, Inc. · R44 · FY2021 · CA
PyroTIMER Technology: Enabling T-Cell Persistence in Immunosuppressive Tumor Microenvironments
$999,283Archis Bagati · Pyrojas Inc · R44 · FY2025 · CA
Development of GIFT4: a B cell focused immunotherapy for cancer
$999,088Paul Guyre · Celdara Medical, Llc · R44 · FY2017 · CA
Programatic-Strengthening Medical Education for Improved Health Outcomes in Kenya
$999,000James Njogu Kiarie · University Of Nairobi · R24 · FY2011 · TW
SBIR PHASE II TOPIC 308 IMAGE BASED MOBILE SYSTEM FOR DIETARY ASSESSMENT AND COACHING
$998,909Praduman Jain · Vignet, Inc. · N44 · FY2014 · CA
Transforming Elementary Science Learning through LEGO(TM) Engineering Design
$998,145Chris B Rogers · Tufts University · · FY2006 · EDU
THIS PROPOSAL AIMS TO DEVELOP AND VALIDATE A NEAR-REAL-TIME PREDICTIVE WATERFOWL TRACKING SYSTEM IN TWO AREAS (CENTRAL VALLEY OF CALIFORNIA AND MID-ATLANTIC COAST ACROSS DELAWARE, MARYLAND, VIRGINIA, AND NORTH CAROLINA) WITH HIGH WATERFOWL AND COMMERCIAL POULTRY POPULATIONS (FIGURE 1). AFTER VALIDATION, THIS APPROACH COULD BE FURTHER EXPANDED TO OTHER POULTRY DENSE AREAS OF THE U.S. THAT SPATIALLY AND TEMPORALLY INTERFACE WITH WATERFOWL. OUR GOAL IS TO LEVERAGE A SERIES OF WELL- DEMONSTRATED AND CUTTING EDGE REMOTE SENSING TECHNOLOGIES AND RESEARCH PRODUCTS INCLUDING:NEXT GENERATION RADAR (NEXRAD) FOR WATERFOWL ROOSTING LOCATION AND DENSITYHIGH SPATIAL RESOLUTION AND TEMPORAL FREQUENCY WATERFOWL TELEMETRY (I.E. LOCATION TRACKING) DATASATELLITE IMAGERY AND LAND-BASED SENSING FOR TRACKING DYNAMIC CHANGES IN SURFACE WATER AND LAND COVER (I.E. WATERFOWL HABITAT) WHICH ARE USED TO BUILD PREDICTIVE STATISTICAL MODELS WITH RESPECT TO WATERFOWL LOCATION AND DENSITY IN NEAR REAL-TIME IN THE CENTRAL VALLEY OF CALIFORNIA AND THE MID-ATLANTIC COAST ANDHIGH-SENSITIVITY ULTRA-FILTRATION OF WETLAND WATER AND WHOLE-SEGMENT M-RTPCR OF AIV OF WETLAND WATER, SEDIMENT AND CLOACAL WATERFOWL SAMPLES . WE WILL LEVERAGE NEXRAD, TELEMETRY, AND THE GEOSPATIAL HABITAT DATA TO IDENTIFY AND TARGET SELECTED HABITAT (WATER AND SEDIMENT) AT HIGH AND LOW WATERFOWL DENSITIES IN ORDER TO UNDERSTAND THE VIRAL ECOLOGY OF AIV IN WETLANDS IN CLOSE PROXIMITY TO COMMERCIAL POULTRY.SPECIFICALLY, WE WILL COLLECT CLOACAL SWABS FROM WATERFOWL, WETLAND SEDIMENT AND WATER FOR ULTRA-FILTRATION (E.G. 10 GALLONS OF WETLAND WATER WILL BE FILTERED TO LESS THAN 50 ML IN ORDER TO CONCENTRATE VIRUS). SUBSEQUENT M-SEGMENT RT-QPCR, WHOLE-SEGMENT M-RTPCR AND SEQUENCING WILL BE USED TO ESTABLISH THE RELATIONSHIP BETWEEN WATERFOWL DENSITY AND AIV VIRAL PREVALENCE IN WATER, SEDIMENT AND ASSOCIATED WATERFOWL. OUR INITIAL RESULTS WHICH ARE IN REVIEW BY THE JOURNAL TRANSBOUNDARY & EMERGING DISEASES4 DEMONSTRATE THAT ULTRA-FILTRATION IN COMBINATION WITH THE WHOLE SEGMENT RT-PCR IS SUPERIOR TO COMMONLY USED DETECTION METHODS FOR AIV IN WATER (I.E. NO FILTRATION WITH M-SEGMENT QPCR) WHICH ARE WELL KNOWN TO LACK SENSITIVITY AND ARE NOT CONSIDERED REPRESENTATIVE OF AIV PREVALENCE.5THE ABOVE DESCRIBED DATA WILL BE INTEGRATED INTO NEAR-REAL-TIME PREDICTIVE MODELS WHICH WILL BE FURTHER VALIDATED AND SUBSEQUENTLY DEPLOYED AS A WEB-APP THAT POULTRY FARMERS, VETERINARIANS, AND REGULATORS (USDA-APHIS AND STATE DEPARTMENTS OF AGRICULTURE) CAN USE AS A RISK-MANAGEMENT TOOL TO ASSESS AND MANAGE RISK RELATED TO AIV TRANSMISSION TO POULTRY FROM WATERFOWL.THE COMBINED ANALYSIS OF WATERFOWL LOCATION, DENSITY, AIV PRESENCE AND THE MOLECULAR ECOLOGY OF AIVS IN WATERFOWL AND THE ASSOCIATED ENVIRONMENT CAN BETTER INFORM PRODUCERS AND OTHER STAKEHOLDERS ENABLING ENHANCED BIOSECURITY PRACTICES (I.E. CHANGES IN HUSBANDRY PRACTICES, REPAIRS TO FARM FACILITIES AND EQUIPMENT, INCREASED UTILIZATION OF CAR-WASH STATIONS, FOOT BATHS, LIMITING SHARING OF EQUIPMENT AND WORKERS BETWEEN RISKY AND NON-RISKY FARMS). SIMILARLY, THE ANALYSIS OF THESE DATA COULD SIGNIFICANTLY IMPROVE DECISION MAKING (I.E. PROCESSING A FLOCK EARLY, PLACING OF A FLOCK LATER, AND TRIAGING VETERINARY VISITS) AT AN INDIVIDUAL FARM LEVEL DURING TIMES OF INCREASED RISK. TO PROMOTE ENHANCED BIOSECURITY DECISIONS, FROM AN EXTENSION PERSPECTIVE IN YEAR ONE WE WILL USE OUR UNIVERSITY EXTENSION CAPABILITIES TO DEVELOP A MULTI-DISCIPLINARY ADVISORY TEAM WHICH WILL HELP GUIDE WEB-APP DEVELOPMENT WITH THE GOAL OF MAXIMIZING ADOPTION OF THE WEB-APP FOR VARIOUS STAKEHOLDERS. DURING YEARS 2-4, THE WEB-APP WILL BE BETA TESTED AND DISSEMINATED TO STAKEHOLDERS IN A SERIES OF EXTENSION- BASED WORKSHOPS ACROSS THE CENTRAL VALLEY OF CALIFORNIA AND THE MID-ATLANTIC COAST AREA BY UC DAVIS AND UNIVERSITY OF DELAWARE FACULTY AND EXTENSION FACULTY. ADDITIONALLY, SURVEYS EVALUATING THE WEB-APP WILL BE DELIVERED TO PRODUCERS AND OTHER RELEVANT STAKEHOLDERS IN YEARS 2-4 ELECTRONICALLY AND VIA IN-PERSON EXTENSION BASED MEETINGS IN ORDER TO OPTIMIZE THE FUNCTIONALITY/USABILITY OF THE WEB-APP.
$998,135University Of California, Davis · · FY2020 · National Institute of Food and Agriculture
Role of Viral Reservoirs in the Pathogenesis of HIV Disease
$997,850Anthony S. Fauci · National Institute Of Allergy And Infectious Diseases · ZIA · FY2013 · AI
Characterization of CAR-directed T-cells to suppress HIV-1 in vivo
$997,645Scott G Kitchen · University Of California Los Angeles · U19 · FY2016 · AI
Contractor to develop COMPASS, a device agnostic platform that measures and delivers customizable, evidence-informed rehabilitation services to cancer suvivors using mobile phones tablet
$997,190Fahd Albinali · Every Fit, Inc. · N43 · FY2014 · CA
Modeling Combination Immunotherapy for HIV Cure in Humanized Mouse Models
$996,589James L Riley · University Of Pennsylvania · U19 · FY2020 · AI
Modeling HIV CAR-T cell trafficking and persistence in Non-Human Primates
$996,038Hans-Peter Kiem · University Of Pennsylvania · U19 · FY2020 · AI
Reprogramming of T cells for the Treatment of Melanoma
$995,664Kai W Wucherpfennig · Dana-Farber Cancer Inst · R01 · FY2014 · CA
Reprogramming of T cells for the Treatment of Melanoma
$995,664Kai W Wucherpfennig · Dana-Farber Cancer Inst · R01 · FY2016 · CA
Reprogramming of T cells for the Treatment of Melanoma
$995,664Kai W Wucherpfennig · Dana-Farber Cancer Inst · R01 · FY2015 · CA
Phase IIB - Smart Eyewear Assistant for the Support of Seniors and their Caregivers in the Long-term Care Setting
$995,645Mark A Fauci · Gen-9, Inc. · R44 · FY2018 · AG
Suicide risk reduction in the year following jail release: the SPIRIT Trial (Suicide Prevention Intervention for at-Risk Individuals in Transition)
$995,508Jennifer E Johnson · Michigan State University · U01 · FY2018 · MH
2/2 Sickle Cell Disease and CardiovAscular Risk - Red cell Exchange Trial (SCD-CARRE Trial)
$994,923Maria Mori Brooks · University Of Pittsburgh At Pittsburgh · U24 · FY2019 · HL
CTO1681 to prevent and mitigate cytokine release syndrome in CAR T-cell recipients
$994,859Arthur P Bertolino · Cytoagents, Inc. · R44 · FY2024 · CA
Phase IIB - Smart Eyewear Assistant for the Support of Seniors and their Caregivers in the Long-term Care Setting
$994,259Mark A Fauci · Gen-9, Inc. · R44 · FY2019 · AG