Xu Li, Ph.D. - US grants

Affiliations:

Biomedical Engineering

University of Minnesota, Twin Cities, Minneapolis, MN

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Years	Recipients	Code	Title / Keywords	Matching score
2014 — 2019	Li, Xu	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Career: Effects of Nutrients On Antibiotic Resistance and Antibiotic Subsistence @ University of Nebraska-Lincoln 1351676 Li Many people have become aware of the issue of pharmaceuticals in water and wastewater and natural waters. With the pharmaceutical market worldwide estimated to be $1 trillion dollars in 2015 and with an aging population (which uses more pharmaceuticals) and water and wastewater treatment plants never designed to deal with extremely low concentrations of highly biologically active compounds, the problem will likely get worse. One of the biggest, yet very subtle is the issue of antibiotic resistance in bacteria in natural waters. Antibiotic resistance constitutes a national and global public health threat. Evidence suggests that in addition to coming from hospitals, antibiotic resistant bacteria also emerge in the environment due to prolonged exposure to antibiotics originating in livestock and human wastes. On the other hand, many antibiotic resistant bacteria can subsist on antibiotics by using them as carbon and energy sources. Because nutrients influence microbial metabolisms and vary in quantity and composition across environmental compartments, they represent an important environmental factor that can affect antibiotic resistance and antibiotic subsistence in the environment. However, how nutrients affect the emergence of antibiotic resistance and the occurrence of antibiotic subsistence in microbial communities is poorly understood. The overall goal of this project is to build an integrated research and education/outreach program to minimize the negative impacts of antibiotics and antibiotic resistance to environmental and public health. The research goal of the project is to understand the interactions between antibiotics and microbial (bacterial) communities under various nutrient levels and types (i.e., labile vs. recalcitrant). The research approach will investigate the responses of bacteria to both nutrient starvation and antibiotic presence. The results of these studies will allow implementation in municipal and agricultural wastewater treatment to control the emergence and proliferation of antibiotic resistant bacteria. The proposed project will use a novel analytical tool, quantitative (meta)proteomics, which can offer new and valuable perspectives to environmental engineering studies. The use of quantitative (meta)proteomics in the mechanistic studies on antibiotic resistance and antibiotic subsistence will lay the groundwork for exploring further application of this novel technology in other environmental engineering fields such as exposure and biodegradation studies. One major source of antibiotics in the environment is livestock manure. The education goal of the project is to promote behavioral changes in livestock producers on antibiotic administration and manure management and to educate a new generation of environmental engineers specializing in solving agriculture-related environmental challenges. This will be accomplished by: 1.) Raising the awareness of antibiotics and antibiotic resistance as environmental contaminants among livestock producers through outreach and education activities 2.) Develop an integrated course module to stimulate interest in environmental science among high school students in rural areas, and, 3.) Encourage rural students to pursue a graduate degree in environmental engineering Show summary Hide summary	0.963
2018 — 2021	Li, Xu Walia, Harkamal Snow, Daniel	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Antibiotic Resistance Genes in the Soil-Plant Ecosystem @ University of Nebraska-Lincoln Antibiotic resistance genes (ARGs) make bacteria resistant to antibiotics, and disease-causing pathogens possessing ARGs can make antibiotic treatment of infectious deceases less effective in treating pathogens, and hence, threaten public health. Soil is a major environmental reservoir of ARGs, and edible crops grown in ARG-containing soils have the potential to serve as a carrier of ARGs to humans and livestock that feed on the crops. After being introduced to the soil in croplands, some ARG-carrying bacteria will reside in the surface soil, and may transfer to plant surfaces where they may be taken up by the plant. This project aims to address the knowledge gap on how ARGs are distributed in soil following the land application of fertilizer, and whether bacteria carrying ARGs survive in and on plants. This research can help determine the significance of plants as a vector for the transport of ARGs to humans. This knowledge can guide the development of management practices to prevent or minimize the uptake of ARGs to edible plants, thus protecting the Nation's food supply for the benefit of public health. The goal for this project is to improve our understanding of the mechanisms that govern the fate and transport of antibiotic resistance genes (ARGs) in soil-plant ecosystems under field conditions. Three research objectives are established for the project: 1) characterize genetic resistance genes (resistome) in surface and rhizosphere soils following manure application and determine the correlation of the resistome with root exudates and antibiotics; 2) identify the source and measure the diversity of the resistome in the endophytic and epiphytic microbial communities in and on plants; 3) elucidate the metabolic adaptations that ARG-carrying bacteria use to survive in and on plants. Shotgun metagenomics will be used to study the resistome of the microbial communities in soil and plant samples, and quantitative proteomics will be used to study the protein expression of ARG-carrying bacteria living on and in plants. The research team will disseminate research findings directly to farmers and crop producers through agricultural extension education materials. The project education plan will focus on enriching student learning experiences with interdisciplinary knowledge of engineering, agriculture, and environmental science. Undergraduate students from underrepresented groups will be recruited to the project, and a new course module will be developed to show students the behaviors of ARGs in the environment. 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. Show summary Hide summary	0.943
2019 — 2020	Li, Xu Qiao, Ye [⬀]	R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.)	Contribution of Cerebral Iron Load to Elderly Individuals With High Risk to Develop Alzheimer's Disease. @ Johns Hopkins University Project Summary: Dementia has a high global prevalence due to the aging population, places an enormous burden on health care systems. Alzheimer's disease (AD) is the most common cause of dementia, and it is widely believed that the accumulation of Amyloid beta (A?) peptide is a key event in the pathogenesis of AD, representing preclinical disease stages. Cerebral iron is strongly implicated as a cofactor in the pathogenesis of AD, and its overload accelerates A? production and promotes the toxicity of the A? peptide. However, the impact of brain iron load on cognitive performance and prevalence of regional A?-plaque-load in AD and its precursor, mild cognitive impairment (MCI), is lacking. Our overall aim is to study the role of brain iron load in the development of cognitive decline, MCI and dementia, in particular AD. We are uniquely positioned to carry out this project in the Atherosclerosis Risk in Communities (ARIC) study, which has collected clinical data from cohort participants over the past 30 years. A biracial sample of elderly adults was evaluated by brain MRI and cognitive tests at study visit 5 with repeat testing underway at visit 6. We will utilize the often-discarded phase signal from gradient echo MRI data at visit 6 (n=1,000) to compute quantitative susceptibility mapping (QSM). Brain iron load will be automatically quantified using our recent developed susceptibility multi-atlas tool. Accordingly, we propose to determine the contribution of cerebral iron load in ARIC participants based on QSM approach with the following specific aims. Aim 1: Establish if increased cerebral iron measures are independently associated with dementia or mild cognitive (MCI) in ARIC participants aged 73-94 years. Aim 2: To relate known midlife dementia risk factors and dietary intake with cerebral iron load measured late-life. Show summary Hide summary	0.939
2019 — 2021	Li, Xu Li, Yusong [⬀]	N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information	Collaborative Research: Real-Time Investigations of Anisotropic Nanoparticle Aggregation and Consequences For Deposition in Porous Media @ University of Nebraska-Lincoln Nanoparticles are prevalent in nature and widely produced in a variety of shapes and sizes in ever-increasing quantities. These nanoparticles often aggregate in water, and thus they typically transport and deposit in environmental media in the form of aggregates instead of individual nanoparticles. However, how the structure of nanoparticle aggregates influence nanoparticles' movement in the environment is not well understood. The overall objective of this project is to better understand the interactions of nanoparticulate aggregates with environmental media and how these interactions can be governed by the shape and size of the individual nanoparticles. Findings from this work can benefit the design and optimization of a broad range of engineered processes, such as filter-based water treatment, groundwater remediation, and drug delivery. This project will also benefit K-12 education through outreach activities involving videos and pictures of nanomaterials. Additional outreach programs include 1) the Summer Coding Camp, at Ohio University to introduce middle school girls to the STEM fields, and 2) various science activities offered by Nebraska Center for Materials and Nanosciences at the University of Nebraska-Lincoln to broaden the exposure of K-12 students to materials science and engineering, nanoscience, and nanotechnology. In addition, the PIs will leverage the existing REU programs at the University of Nebraska-Lincoln to train Ohio university undergraduate students during summers. In the past, nanoparticle aggregation and deposition were often studied separately, with limited research linking mobility of nanoparticles in environmental media to the structure of nanoparticle aggregates. However, new evidence suggests that anisotropic nanoparticles, the most common form of nanoparticles in the environment, often form non-compact aggregates. The formation of these non-compact aggregates cannot be explained by classic colloidal aggregation theories. Moreover, non-compact aggregates undergo unusual deposition and modify hydrodynamics in environmental porous media, which is not described by the classical filtration theory. Acquisition and integration of quantitative data from all steps involved in nanoparticle aggregation and deposition is critically needed. The research objectives of this project include: 1) Quantifying the anisotropic diffusion dynamics of nanoparticles with various aspect ratios in water; 2) Elucidating the role of the shape of primary nanoparticles on the formation kinetics and morphological structure of aggregates; and 3) Evaluating the impact of aggregate structure on the transport and deposition of aggregates in environmental porous media. Hematite nanoparticles with different aspect ratios (i.e., nanosphere, nanorod, nanodisk) will be synthesized in the study. Advanced techniques will be employed to visualize and quantify nanoparticle diffusion, aggregation, transport, and deposition in environmental matrices. Furthermore, the experimental data will be used to update classical filtration theory for predicting nanoparticle behaviors in porous media. The expected intellectual outcomes from this work will include development of a series of quantitative metrics from measurements of anisotropic diffusion, aggregate formation, and aggregate deposition and flow dynamics in porous media. These quantitative characterizations will allow us to elucidate the mechanisms which control anisotropic nanoparticle aggregation and deposition in environmental porous media. This will, in turn, improve the utility of colloidal science principles in understanding and predicting nanoparticle behaviors, such as colloid Brownian motion theory, colloid aggregation theory, and the classical filtration theory. 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. Show summary Hide summary	0.943
2019 — 2021	Li, Xu Qiao, Ye [⬀]	R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. R56Activity Code Description: To provide limited interim research support based on the merit of a pending R01 application while applicant gathers additional data to revise a new or competing renewal application. This grant will underwrite highly meritorious applications that if given the opportunity to revise their application could meet IC recommended standards and would be missed opportunities if not funded. Interim funded ends when the applicant succeeds in obtaining an R01 or other competing award built on the R56 grant. These awards are not renewable.	Contribution of Cerebral Iron Load to Cognitive Function in Older Adults With High Risk to Develop Alzheimer's Disease @ Johns Hopkins University Project Summary: Dementia has a high global prevalence due to the aging population, places an enormous burden on health care systems. Alzheimer's disease (AD) is the most common cause of dementia, and it is widely believed that the accumulation of Amyloid beta (A?) peptide is a key event in the pathogenesis of AD, representing preclinical disease stages. Cerebral iron is strongly implicated as a cofactor in the pathogenesis of AD, and its overload accelerates A? production and promotes the toxicity of the A? peptide. However, the impact of brain iron load, and its combined effect with regional A?-plaque-load on cognitive performance in AD and its precursor, mild cognitive impairment (MCI), is lacking. Our overall aim is to study the role of brain iron load and its possible synergistic effect with A?- plaque-load in the development of cognitive decline, MCI and dementia, in particular AD. We are uniquely positioned to carry out this project in the Atherosclerosis Risk in Communities (ARIC) study, which has collected clinical data from cohort participants over the past 30 years. A biracial sample of elderly adults was evaluated by brain MRI, brain florbetapir positron emission tomography (PET), and cognitive tests at study visit 5 with repeat testing underway at visit 6. We will utilize the phase signal from gradient echo MRI data at visit 6 (n=1,000) to compute quantitative susceptibility mapping (QSM). Brain iron load will be automatically quantified using our recent developed susceptibility multi-atlas tool. Accordingly, we propose to determine the contribution of cerebral iron load based on QSM measures in ARIC participants with the following specific aims. Aim 1: To determine if increased cerebral iron measures are independently associated with cognitive performance in dementia or MCI in ARIC participants aged 73-94 years. Aim2: To estimate the combined effects of A?-plaque-load as measured by florbetapir PET and increased cerebral iron-load on the progression of cognitive outcomes. Aim 3: To relate known midlife vascular risk factors and blood ferritin levels with cerebral iron load measured in late-life. Show summary Hide summary	0.939