Zhe Zhang - US grants

DESCRIPTION (provided by applicant): Our multidisciplinary team of clinicians and researchers seeks novel patient-individualized approaches for understanding and managing pediatric acquired aplastic anemia (aAA), a rare but devastating condition characterized by bone marrow hematopoietic stem cell (HSC) hypoplasia with life threatening bleeding, anemia and infections. Pediatric aAA is believed to occur via immune cell attack of HSCs, but little more is known about the pathogenesis and current treatments are not mechanism-based. Some patients with aAA develop clonal hematopoiesis, which is typically viewed pessimistically as a sign of impending myelodysplasia or leukemia. However, this may not always be the case, as our preliminary studies have identified numerous aAA patients with clonal hematopoiesis who have been in healthy remission for years. Moreover, many of these patients harbor unique mutations within their dominant hematopoietic clones. Thus, we hypothesize that clonal hematopoeisis in aAA results from mutational events that impart a growth or survival advantage to HSCs or early progenitors, particularly in the face of disease-associated insults. We will use modern genomic approaches to define the scope of these mutations in a large cohort of aAA patients (Aim 1), follow the clinical course and genetic evolution of the patients longitudinally (Aim 2) and study the functional consequences of the aAA associated acquired mutations through genetic manipulation and in vitro hematopoietic differentiation of patient-derived induced pluripotent stem cells (iPSCs) (Aim 3). Several unique aspects of our study enhance its likelihood of success: First, we are a team of accomplished investigators with broad, synergistic expertise in the clinical management of aAA, bioethics, genomics/genetics, hematopoeisis and pluripotent stem cell biology. Second, M. Bessler (lead PI) follows all of the patients longitudinally in a comprehensive pediatric- adult bone marrow failure clinic at The Children's Hospital of Philadelphia and The Hospital of the University of Pennsylvania. Finally, our study will utilize a large clinically well-annotated tissue collection obtained serially from over 100 aA patients over 13 years, consisting of DNA and cryopreserved skin, blood and bone marrow cells. Dr. Bessler (lead PI) will continue to follow these patients clinically and procure additionl samples throughout the study. If successful, our work will identify sets of genes and gene mutations that will sub- classify aAA molecularly to predict prognosis more accurately and to identify more effective, mechanism-based patient-specific therapies.

The project funds the acquisition of a composable high-performance data-analysis and computing instrument, named FASTER (Fostering Accelerated Scientific Transformations, Education, and Research). FASTER will enable transformative advances in scientific fields that rely on artificial intelligence and machine learning (AI/ML) techniques, big data practices, and high-performance computing (HPC) technologies. The FASTER platform removes significant bottlenecks in research computing by leveraging a technology that can dynamically allocate resources to support workflows. It will support researchers from across the Texas A&M University System and their collaborating institutions. Thirty percent of FASTER?s computing resources will also be allocated to researchers nationwide by the National Science Foundation (NSF) XSEDE (Extreme Science and Engineering Discovery Environment) program. FASTER?s composable interface allows it to simultaneously support both emerging and traditional workloads in research computing. Transformative research projects benefiting from FASTER will include the development of AI/ML models, cybersecurity, health population informatics, genomics, bioinformatics, computer-aided drug design, agricultural sciences, life sciences, oil and gas simulations, de novo materials design, climate modeling, multi-scale simulations, quantum computing architectures, biomedical imaging, geosciences, and quantum chemistry. In addition to supporting a wide-range of fields of research, the project contributes to code development, education, and the workforce development goals of several NSF Big Ideas.

FASTER adopts the innovative Liqid composable software-hardware approach combined with cutting-edge technologies such as state of the art CPUs and GPUs, NVMe (Non-Volatile Memory Express) based storage, and thigh speed interconnect. Workflows on FASTER will be able to dynamically integrate disaggregated GPUs and NVMe to compose a single node, allowing them to scale beyond traditional hardware limits. The composable and configurable techniques will allow researchers to use resources efficiently, enabling more science. Best practices gathered from managing the resource will be shared with the community. FASTER will coordinate a three-pronged effort to effectively broaden participation in computing by focusing on training, education and outreach. FASTER will leverage existing efforts that promote STEM (Science, Technology, Engineering and Mathematics) and broaden participation in computing at the K-12, collegiate, and professional levels to have a transformative impact nationally. FASTER activities are designed to expand the participation of traditionally underrepresented groups in computing and STEM, particularly at minority-serving institutions.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Convergence Accelerator Track E: Combining high-resolution climate simulations with ocean biogeochemistry, fisheries and decision-making models to improve sustainable fisheries.

Fish and shellfish populations are a vital source of protein for many of the world’s people, and several of the largest are found along the eastern boundaries of the Pacific and Atlantic Oceans, where cold, deep water moves towards the surface, bringing nutrients that support both production by plants (phytoplankton) and the fish populations that feed on them. To ensure sustainability, fish and shellfish managers need information not only on the number of animals available at any given time, but also on potential future numbers, so that they can plan for such things as the number of fishing boats required or the size of seafood processing plants. Forecasting what will occur in such eastern boundary areas is difficult, however, because local winds rapidly change conditions. Adverse climate impacts, such as rising ocean temperatures and increasing acidity, are already affecting many coastal fishing-dependent communities, and such longer-term changes also have to be considered. The project aims to develop a decision support system, which uses the latest ocean models incorporating marine physics, chemistry and biology, to assist fish and shellfish managers in making their decisions. This is important as there are many stakeholders involved in harvesting fish and shellfish, who may have potentially conflicting interests. To this end, the research is aimed at integrating the outputs from the ocean models with a web-based decision support system that will help fisheries managers and industry make informed decisions to ensure that both the industry and its associated food production are sustainable. The investigators will work directly with the stakeholders to develop tools that are specifically able to meet their needs. The initial focus of the work is the California Current system along the U.S. west coast from California to Washington, which supports a local seafood industry valued annually at about $12 billion, with additional billions from catches landed by foreign boats in the U.S. If successful, the new tools should be extendable to other similar regions of the global ocean, thus increasing the value of the research. The project will provide training for students, including those from under-represented groups, in the use of the latest ocean models, as well as development opportunities for young faculty members at the participating institutions.

Climate change-driven adverse ocean impacts are already affecting many rural, coastal, fishing-dependent communities, and these adverse impacts will likely accelerate for the foreseeable future.
Forecasting potential changes in eastern boundary upwelling systems has benefitted recently from improvements in the resolution of global Earth system models, so that the latest eddy-resolving models at 10 km ocean resolution have greatly reduced systematic errors relative to observations. This project aims to use these advancements to improve forecasts of the fisheries potential of the California Current Ecosystem and improve decision making by managers and other stakeholders. The project will couple the output from such a high-resolution model simulation with the Marine Biogeochemistry Library and Fisheries Size and Functional Type models, thus incorporating physics, chemistry and biology with climate variability. The results will be integrated with a prototype, web-based decision support system, that uses mathematical decision analysis capabilities, to assist fisheries managers to model the complex, climate-related decision problems on which fisheries production depends. This is vital to ensure that the region can continue to support a sustainable fishery in the long term and the communities that depend on fishing for a living. In Phase 1, the project will develop a prototype of this linked decision system. The project will also develop a well-networked multidisciplinary team of modelers, social scientists, fisheries managers, economists, and industry and community stakeholders to advance convergence science and develop avenues for more sustainable fisheries under a changing climate. This team is essential for developing tools that are directly applicable to the needs of fishery stakeholders and will be fostered by meaningful communication between all groups throughout the project period. If successful, the model suite and decision support system should be extendable to other similar regions of the global ocean. Students and post-doctoral researchers, the next generation of scientists, will be trained in decision analysis and to use the most current high-resolution models. Furthermore, the project will provide valuable professional development opportunities for early career female Co-PIs involved in the program.

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.