Ming Xu - US grants

DESCRIPTION: (Applicant's Abstract) Cocaine and amphetamine are powerful psychomotor stimulants and widespread abuse of these drugs creates a major problem in the society. Understanding the molecular mechanisms underlying the behavioral and neuroplastic changes caused by cocaine and amphetamine is crucial for developing methods of the prevention and treatment of drug abuse. It has been demonstrated that the acute actions of these psychostimulants depend on the potentiation of dopamine neurotransmission in the mesolimbic dopamine pathway, particularly through the D1 dopamine receptors. However, little is known regarding the intracellular events mediating the effects of these psychostimulants. Immediate early gene c-fos encodes a transcription factor and is induced through the D1 dopamine receptors by both cocaine and amphetamine. Our hypothesis is that c-fos is necessary in mediating both the locomotor stimulating and positive reinforcing effects of cocaine and amphetamine, and in AP-1 transcription complex formation in response to acute cocaine treatments. We propose to use the conditional gene targeting technology and generate mice with forebrain mutation of c-fos. We propose to test the above hypothesis in these mutant mice using behavioral, biochemical and histological methods. The successful completion of the proposed project will allow us to determine the role of c-fos in mediating the acute actions of psychostimulants and provide basis for investigating its role in the chronic effects of these drugs, and for finding possible target genes involved in drug addiction in the future.

Drugs of abuse, such as cocaine, can elicit compulsive drug seeking behaviors upon repeated exposure and widespread cocaine abuse creates one of the foremost public health problems in this country. Understanding the molecular mechanisms underlying the behavioral and the neuroplastic changes caused by cocaine is crucial for developing methods for the prevention and treatment of drug abuse. Enduring behavioral changes such as behavioral sensitization can be induced in rodents by repeated cocaine exposure. The neurobiological mechanisms underlying such behavioral changes are associated with the brain mesolimbic dopamine (DA) pathway. The longlasting behavioral effects of repeated cocaine exposure are highly likely to be associated with underlying changes in gene expression. However, the exact molecular changes that occur in response to long-term cocaine exposure remain unclear. Based on work from our own laboratory and from others, we hypothesize that changes in gene expression mediated through the DA D1 and D3 receptors play crucial roles in the behavioral changes induced by repeated cocaine administration. We propose to combine the use of unique animal models for cocaine actions, namely, D1 and D3 receptor mutant mice, with cDNA microarray technology to test the above hypothesis. Successful completion of this proposal will pave the way for testing the physiological significance of the molecular changes in cocaine-induced neuroplasticity in the future. The combined use of DA receptor mutant mice which exhibit altered behavioral responses to cocaine, with cDNA microarray technology, and proper physiological testing of the putative target genes has tremendous potential to provide novel insights into the molecular basis of compulsive drug seeking behaviors.

DESCRIPTION: (provided by the applicant) Drug addiction is a chronic relapsing disease with psychological and social factors. Compulsive drug-taking is the central feature of drug addiction. Understanding the molecular mechanisms underlying the transition between controlled drug use and the loss of control over drug-taking is crucial for developing methods for the prevention and treatment of drug addiction. The neurobiological mechanisms underlying the development of uncontrolled drug-taking behaviors are associated primarily with the brain mesocorticolimbic dopamine (DA) pathway. Moreover, changes in gene expression are thought to mediate, in part, the neuroadaptive responses to the development of cocaine-taking behaviors. However, the molecular determinants and their temporal and spatial involvement in the transition from initial drug use to compulsive drug-taking behaviors remain unidentified. Based on work from our own laboratory and from others, we hypothesize that DA D1 and D3 receptors and c-Fos play important roles in the transition between controlled cocaine use and escalated cocaine intake. We propose to generate novel mouse models in which the expression of D1, D3 receptor or c-fos genes can be temporally controlled in D1 receptor-expressing neurons respectively. We propose then to test the above hypothesis by turning off the expression of D1, D3 receptor or c-fos genes in these mice during the escalation or abstinence phases and then measuring cocaine intake in an escalating cocaine self-administration paradigm. Finally, we propose to identify c-Fos-regulated target genes that are involved in the transition between controlled cocaine use to escalated cocaine intake. Successful completion of the proposed work will provide valuable information for the temporal and spatial requirement of DA D1 and D3 receptors and c-Fos in the development of compulsive drug-taking behaviors. Identification of c-Fos-regulated molecular changes involved in the transition to escalated cocaine intake will pave the way for testing the physiological significance of these changes in cocaine-taking behaviors in the future. The combined use of genetically engineered mouse models with proper behavioral and molecular biological analyses has tremendous potential to provide novel insights into mechanisms underlying the development of drug addiction and new strategies for the treatment of drug abuse.

DESCRIPTION (provided by applicant): Drug addiction is a chronic relapsing disease that is characterized by the compulsive seeking and taking of a drug despite known adverse consequences. A prominent feature of drug addiction is that it is a longlasting condition. Effective treatment strategies of this disease depend on a thorough understanding of the molecular mechanisms underlying the persistent nature of drug-induced behaviors. Changes in gene expression through specific dopamine (DA) receptor subtypes have been thought to play a key part in mediating enduring neuroadaptations to repeated drug exposure. The immediate early gene product c-Fos is an ideal candidate to couple repeated cocaine stimuli to persistent neuroadaptation in the brain DA system by regulating gene expression. We have investigated these assumptions using novel genetically engineered mouse models and found that the DA D1 receptor mediates both the locomotor sensitization and the reinforcing effects of cocaine. The D1 receptor also mediates cocaine-induced neurophysiological responses, dendritic remodeling and gene expression changes in the brain, including c-fos and genes containing AP-1 binding sites in their promoter regions. Furthermore, proper c-Fos expression in D1 receptor-producing neurons contributes to cocaine-induced behavioral sensitization, dendritic remodeling and gene expression changes. Noticeably, mutations of the D1 receptor gene and c-fos share several common consequences following repeated cocaine injections. These findings led us to hypothesize that c- Fos is a significant intracellular signal transducer downstream of the D1 receptor that contributes to the behavioral effects of cocaine, and that c-Fos-regulated gene expression changes participate in persistent neuroadaptation to repeated exposure to cocaine. The overall goal of this proposal is to test the above hypothesis. We propose to determine the role of c-Fos in the behavioral effects of cocaine by combining the use of behavioral sensitization and self-administration paradigms with novel DA D1 receptor neuronspecific c-fos mutant and inducible c-fos mouse models. We also propose to identify D1 receptor-mediated and c-Fos-regulated gene expression changes that persist long after cocaine withdrawal. Successful completion of the proposed work will establish a molecular framework on how c-Fos couples repeated cocaine exposure to persistent behavioral changes and neuroadaptation by regulating specific gene expression in DA D1 receptor-expressing neurons in the brain. These experiments may provide novel insights into mechanisms underlying drug addiction and new strategies for the treatment of drug abuse.

This award supports the development field-capable instrumentation capable of high frequency (10 Hz) sampling of isotopic fluxes of carbon dioxide (12CO2 and 13CO2). Study of atmospheric gases, atmospheric chemistry, and global carbon cycle would greatly benefit from the availability of instrumentation capable of accurate, precise, and high-speed measurements of isotopic fluxes. The instrumentation will enable long-term measurement of net ecosystem exchange (NEE) of carbon with concurrent, real-time partitioning of NEE into its photosynthetic and respiratory components when coupled to existing high frequency eddy covariance (EC) micrometeorological techniques. The interdisciplinary development team includes a physicist expert in use of lasers in stable isotope analysis, an ecosystem modeler with extensive field experience, and a plant ecophysiologist specializing in leaf-level photosynthetic gas exchange. The team will expand the capabilities of a new laser-based stable carbon isotope analysis system (acronym LARA) and to perform validating field experiments. The LARA technique is based on the existence of large isotope shifts in molecular spectra, the use of fixed frequency isotopic lasers and sensitive detection via the laser optogalvanic effect. The effort will involve the participation of post doctoral associates, graduate and undergraduate students of physics, biological and environmental science and high school interns who will be trained in optical science, measurement science, biometeorology, environmental physics and ecology. Undergraduate and graduate courses taught by the faculty participants will include trips to the field site and exercises utilizing data gathered during the project.

DESCRIPTION (provided by applicant): Drug addiction is a brain disease that is characterized by the compulsive seeking and taking of a drug despite known adverse consequences. A prominent feature of drug addiction is that drug-associated cues can elicit drug-seeking behaviors and contribute significantly to the high propensity to relapse. The development of effective treatment strategies of this disease depends on a thorough understanding of molecular mechanisms underlying the development and extinction of drug-induced behaviors. We have been investigating the notion that the dopamine D1 receptor and the immediate early gene product c-Fos expressed in D1 receptor-bearing neurons mediate the development of persistent neuroadaptation in the brain dopamine system by regulating cell signaling and gene expression. We generated and analyzed novel genetically engineered mouse models and found that the D1 receptor and c-Fos expressed in D1 receptor-bearing neurons mediate the locomotor sensitization and reinforcing effects of cocaine. Moreover, these molecules regulate cocaine-induced dendritic remodeling, electrophysiological responses, and changes in cell signaling and gene expression in the brain. Of particular relevance, a lack of c-Fos expression in D1 receptor-bearing neurons in mice results in no change in the induction but a delayed extinction of cocaine-induced conditioned place preference. Further, synaptic depression is induced in the nucleus accumbens following the acquisition, and this depression is apparently reversed after extinction of the behavior. Extinction training also modifies c-Fos-regulated expression of certain glutamate receptor subunits in the nucleus accumbens. These findings led us to hypothesize that up- regulation of c-Fos expression in D1 receptor-bearing neurons facilitates the extinction of cue-elicited cocaine seeking, and that D1 receptor-mediated and c-Fos-regulated changes in neuronal excitability, cell signaling and gene expression play key roles in the extinction process. The overall goal of this proposal is to test the above hypothesis. In Aim 1, we propose to genetically up-regulate c-Fos expression in D1 receptor-bearing neurons by using a novel D1 receptor neuron-specific inducible c-Fos mouse model, and investigate whether up-regulation of c-Fos facilitates the extinction of cocaine-induced conditioned place preference. In Aims 2 and 3, we propose to identify D1 receptor-mediated and c-Fos-regulated changes in neuronal excitability, signaling and gene regulation that are associated with the acquisition and extinction processes using the two complementary c-Fos mouse models. Based on their key involvement in the circuitry underlying cue-elicited cocaine seeking, we will focus on the nucleus accumbens and basolateral amygdala. Successful completion of the proposed work will establish a molecular framework for the role of c-Fos in the extinction of cue-elicited drug seeking by regulating specific changes in dopamine D1 receptor-expressing neurons in the brain. We expect these experiments to provide novel insights into mechanisms underlying facilitation of extinction of drug seeking, identifying potential new targets for the treatment of drug abuse.

0903619
B. Allenby

"The First Symposium on Industrial Ecology for Young Professionals" is designed and organized by young professionals (e.g., graduate students and post-doctoral researchers), including members of the Student Chapter of the International Society for Industrial Ecology (ISIE). The focus of the symposium is research and application in the area of Industrial Ecology, emphasizing sustainability. The symposium, to be held at Arizona State University on May 17, 2009, will immediately precede the joint international conference at the same site for the IEEE International Symposium on Sustainable Systems and Technology (ISSST ' 09, formally the annual International Symposium on Electronics and the Environment) and the annual International Symposium on Technology and Society (ISTAS ' 09). Both ISSST ' 09 and ISTAS ' 09 are closely related to industrial ecology. The primary goal of the symposium for young professionals is to provide an opportunity for them to present ongoing research, receive constructive feedback, and network with senior professionals in the field. Additionally, the event will enable young professional in the U.S. to establish a national network of young industrial ecology researchers for ongoing exchange and future collaborations. Research foci will include Material and Substance Flow Analysis (MFA/SFA), Life Cycle Assessment and Management (LCA/LCM), design for the environment, resource productivity, energy efficiency, and industrial symbiosis. The award of travel funds and accommodation subsidy will enable a number of young professionals, including women and minorities, to attend the symposium when they otherwise would be unable to do so. For this event, the faculty PI is Braden Allenby (Arizona State University [ASU] and Immediate Past President, ISIE), and the faculty co-PIs are Roland Geyer (University of California, Santa Barbara) and Eric Williams (ASU). Additionally, Prof. Clinton Andrews (Rutgers U.) serves on the Technical Committee for the symposium.

1132581 (Xu). This project has two major goals. First, a spatially-explicit agent-based LCA framework will be developed to improve the standard LCA modeling technique by overcoming the issues involved with analyzing emerging technologies with dynamic and evolving supply chains. The achievement of this goal will advance LCA methodology and provide a new tool for environmental sustainability analysis. Second, this improved LCA modeling framework will be applied to the U.S. switchgrass bioenergy system (biofuels and biomass electricity) to examine the future supply chain dynamics and evolution under a variety of policy scenarios and evaluate the associated life cycle environmental impacts. The completion of this work will provide a roadmap for the nation and selected states to achieve bioenergy development goals while meeting market demand and minimizing environmental impact. The proposed spatially-explicit agent-based LCA modeling framework will integrate conventional LCA modeling with an agent-based modeling technique to allow feedback between the environmental intervention database and the dynamics and evolution of supply chain. The model will be spatially-explicit by incorporating geospatial data and tools. The proposed framework addresses some of the grand challenges identified by the LCA community in both bioenergy LCA and LCA methodology in general, and will be generally applicable to other systems beyond the bioenergy case study. The success of this project will improve the state of the LCA method to analyze dynamic, emerging systems. In addition to this methodological advancement, results of this project may directly impact decisions pertaining to bioenergy development. Through this project, we will be able to 1) understand how the entire bioenergy supply chain will respond to different policy interventions, 2) provide decision support information for the development and deployment of biofuels and biomass electricity at national and state levels, 3) guide the biofuel and biomass electricity industries to advance technology development, and 4) educate the next generation of engineers and policy makers for understanding complex issues in the bioenergy system and obtaining multidisciplinary skills. The impacts of this research are potentiallly broader than providing critical information about switchgrass bioenergy development and its environmental impacts. The techniques established using a coupled agent-based model with LCA can be used for any developing system. The method developed in this research can address one of the key challenges of trying to predict the environmental impacts of a non-established system, adding dynamic components that assist in the understanding of developing complex adaptive systems and the aggregate effect of a technology change. The educational impact of this project includes integration of undergraduate and graduate courses and curricula. One PhD student will be trained working on cutting edge research on a topic of intense international interest. Master's students will see aspects of this research integrated into the curriculum of the Engineering Sustainable Systems dual degree program between the UM College of Engineering and School of Natural Resources and Environment. The project team will also participate in the UM UROP program which provides mentoring and research experiences for underrepresented minority undergraduate students. To broadly disseminate research results for educational purposes, the team will develop and submit relevant course modules to the Center for Sustainable Engineering's electronic library for peer review. The models developed in this project will be shared with the scientific community through the OpenABM Consortium.

In many mountain regions there is evidence that temperatures are changing at different rates than the global average. Three questions arise: Are temperatures in mountain regions increasing faster than the global average? Within mountain regions are warming rates dependent on elevation? And if the answers to the above are yes, why do such differences occur? Several different feedbacks can contribute, including those related to snow-albedo, atmospheric water vapor, cloud cover, and cloud properties. These feedbacks are difficult to quantify because the relationship between two climate variables is invariably interconnected with other variables as well. Also, the sparsity of observations in high-altitude regions exacerbates this difficulty.

This project will combine surface-based and satellite observations with climate model simulations and a neural network analysis scheme to (1) quantify some of the principal relationships that contribute to feedbacks on temperature in high altitude regions, and (2) investigate how these relationships and feedbacks might change through the 21st century in response to increasing atmospheric greenhouse gases. The focus will be on the Tibetan Plateau and the Rocky Mountains in southwestern Colorado. The neural network analysis calculates partial derivatives between pairs of climate variables (e.g., downward longwave radiation and cloud cover) so that the strength of the various links in a feedback loop can be determined.

Broader impacts of this work include: (1) The neural network can be applied in other regions and can enable researchers to quantify important feedbacks in the climate system and analyze non-linear processes; (2) By combining surface-based and satellite observations, a new spatially and temporally expanded observational data base will be available to the research community; (3) A better understanding of climate change in mountain regions will benefit the public by improving management practices that affect the future of water resources, agriculture, tourism, and ecosystems in high altitude regions; (4) A high-school teacher will be supported to work with the investigators to help develop and implement podcasts on mountains and climate change; (5) There will be training for a postdoctoral fellow and undergraduates; and (6) Educational materials will be developed in collaboration with the Mountain Studies Institute in Colorado.

1438197 (Xu). The completion of this project will provide an integrated tool to evaluate water scarcity risks for industries with global supply chains. The results will help businesses develop strategies
to mitigate water scarcity risk and contribute to global water conservation. Although the results are specific for water scarcity risk, the modeling framework will be generally applicable for studying risks posed by other environmental challenges such as biodiversity loss and ecosystem degradation. An interactive web-based visualization tool will be developed to broadly disseminate the research results to raise awareness of water scarcity risk for the global trade network. The results of this research are targeted to help decision-making in trade and environmental policies to mitigate water scarcity risk for industries with significantly globalized supply chains.

The objective of evaluating risks for the global trade network will be achieved by developing and applying a probabilistic network analysis framework. Based on multi-regional input-output models, the world economy will be studied as a trade network in which nodes are industries in each country and links represent exchanges of goods and services between industries. Relative risks of economic losses in those industries due to local water scarcity at either the country level or river basin level will be used to weight the global trade network. The weighted global trade network will be analyzed using complex network analysis metrics and methods to identify "hotspots" vulnerable to water scarcity risks. The probabilistic network analysis framework will be generalized for broader applications to risks posed by other environmental challenges in addition to water scarcity. The project will also develop an interactive web-based visualization tool to present research results and facilitate effective teaching and learning.

DESCRIPTION (provided by applicant): Memories of drug experience and drug-associated environmental cues can elicit drug-seeking and taking behaviors. There are no effective medications for treating relapse in cocaine addicts. Dopamine (DA) mediates reward-related learning and drugs of abuse can change reward circuits in the brain mesolimbic DA system. DA D3 receptors are preferentially expressed in limbic regions. We and others have used D3 receptor mutant mice and D3 receptor-selective antagonists to demonstrate that these receptors are a major mediator of the rewarding effects of cocaine. Despite its key role in mediating the neurobiological effects of cocaine, medications directly targeting D3 receptors, however, are still limited to preclinical studies. Targeting D3 receptors requires precise knowledge on how D3 receptors contribute to all aspects of drug-induced behaviors and pharmacological ligands with improved D3 receptor specificity. The vast majority of studies so far have attempted to pharmacologically attenuate reinstatement to drug-seeking. We have obtained new preliminary results suggesting that reconsolidation and extinction of cue-cocaine memories may provide alternative action windows for D3 receptor-based therapies. The objective of this developmental proposal is to initiate studies to expand our knowledge on potential new ways to reduce craving and relapse by better understanding and targeting D3 receptor-mediated mechanisms. We propose to engineer and characterize a novel mouse model in which levels of D3 receptors can be up- or down-regulated in the brain. We will then use this mouse model, together with pharmacological methods and the intravenous cocaine self-administration paradigm, to investigate the hypothesis that manipulating D3 receptor levels or activity reduces cocaine- seeking by interrupting the reconsolidation and accelerating the extinction of drug-induced reward memory. The proposed work will have a high impact in that the results will lay important groundwork for developing novel D3 receptor-based therapies in humans, for validating and improving utilities of new D3 receptor agonists and antagonists in reducing relapse, and for investigating how D3 receptors contribute to vulnerability to developing cocaine-seeking and to other cocaine-induced behaviors in the future.

1554349 (Xu)

This research aims to advance the current practice of developing Life Cycle Inventory (LCI) databases into a faster, less expensive process that still generates reliable LCI data. The research will (1) create a framework for modeling and analyzing LCI networks, (2) develop computational models for estimating missing LCI data, and (3) apply these models to evaluate LCI data quality and predict LCI data for emerging technologies. The education plan will (1) engage a diverse group of LCA practitioners during the course of the project, (2) deliver open source software add-ons for LCA practitioners to easily use the computational models developed in the proposed research, (3) develop an education theory grounded curriculum module incorporating research outcomes for broader dissemination, and (4) train undergraduate and graduate students with diverse background in STEM fields by engaging them in the research program and other education activities.

This research will develop computational approaches for estimating missing data in Life Cycle Inventory (LCI) databases based solely on limited known data, without relying on time-consuming, expensive empirical data collection. The approach transfers the latest knowledge from network science to LCI database development. An LCI database represents the interdependence of unit processes and environmental interventions. The ensemble of such interdependence characterizes the structure of the underlying technology network (or LCI network). If sufficient enough, observed LCI data, although limited, can be used to extract structural features of the underlying LCI network. Such structural features, in turn, can be used to predict the structure of the unknown area of the LCI network, which is equivalent to estimating the unknown data in the LCI database. This research will first create a framework for modeling and analyzing LCI networks. This framework will then be used to develop and validate a variety of link prediction models to estimate missing data for LCI databases. Finally the validated link prediction models will be used to evaluate LCI data quality and predict LCI data for emerging technologies for testbed databases selected in consultation with stakeholders.

1605202 (Xu)

This project will advance the science and engineering of Food-Energy-Water (FEW) nexus modeling by developing and applying an integrated systems modeling framework. The modeling framework will enable quantitative characterization of urban FEW nexus, identify areas for efficiency improvement, and evaluate the consequences of policy and technology scenarios. Results from the case studies in Detroit and Beijing will guide policy and technology development for better managing FEW resources for these two testbeds as well as other similar cities in the U.S., in China, and around the world. The collaboration between the U.S. and China on this project provides opportunities for a group of researchers with diverse background to share data, expertise, and experience on modeling urban FEW nexus. The project will also engage stakeholders for seeking inputs to improve the modeling framework and scenarios. Research results will also be provided to stakeholders to support their decision making relevant to FEW nexus. Through the U.S.-China collaboration, unique opportunities will be created for a diverse group of graduate and undergraduate STEM students to conduct cutting-edge research in an international, interdisciplinary environment.

The research employs the latest knowledge from multiple disciplines for developing an integrated systems modeling framework to understand urban FEW nexus. Dynamic material flow analysis will characterize urban FEW resource stocks and flows. The structure and importance of network components will be examined using network-based metrics and methods from different but related fields (ecological network analysis and complex network analysis). Policy and technology scenarios will be evaluated using these network-based metrics and methods to identify co-benefits and avoid unintended consequences. The resulting urban FEW nexus modeling framework will address multiple dimensions and scales: systems (integrated FEW systems), spatial (key system processes that are both within and outside the city boundary), and temporal (short-term flows and long-term stocks). The modeling framework will also be applied to two distinct testbeds (Detroit and Beijing) for demonstration. While the case study results are specific for the testbeds, the integrated systems modeling framework will be generally applicable for understand the FEW nexus for other urban areas.

Many cities across the globe are facing difficult challenges managing their food, water and energy systems. The challenges stem from the fact that the issues of food, water and energy are often tightly connected with each other, not only locally but also globally. This is known as the Food-Water-Energy (FWE) nexus. An effective solution to a local water problem may cause new local problems with food or energy, or cause new water problems at the global level. On a local scale, it is difficult to anticipate whether solutions to one issue in the nexus are sustainable across food, water and energy systems, both at the local and the global scale. Innovative solutions that encompass the nexus are particularly important to enable cities to better manage their food, water and energy systems and understand the benefits and tradeoffs for different solutions.

This award supports U.S. researchers participating in a project competitively selected by a 29-country initiative through the joint Belmont Forum- Joint Programming Initiative (JPI) Urban Europe. The Sustainable Urbanization Global Initiative (SUGI)/Food-Water-Energy Nexus is a multilateral initiative designed to support research projects that bring together the fragmented research and expertise across the globe to find innovative solutions to the Food-Water-Energy Nexus challenge. The call seeks to develop more resilient, applied urban solutions to benefit a much wider range of stakeholders. The rapid urbanization of the world's population underscores the importance of this focus. International partners were invited to develop solutions for this challenge. The funds requested will be used to support U.S. participants to cooperate in consortia that consist of partners from at least three of the participating countries and that bring together natural scientists, social scientists and research users (e.g., civil society, NGOs, and industry). Participants from other countries are funded through their national funding organizations.

This projects seeks to develop a FEW system incorporating the localized production of healthy food. The production and consumption of healthy food is constrained by both future climate change and current diets: the project aims to mitigate these by designing strategies for the localization of healthy food production and test these within the context of far-future climate impacts. The scale at which this production is localized differs in each location, spanning scales from a single rooftop to an entire metropolitan region. The design outputs will be used as cornerstones of the entire field of possible solutions and are used to inspire other places to engage with these issues. Integrated within the program of stakeholder workshops is the development of an analytical decision-support tool, the M-NEX. Each successive workshop adds complexity and detail to the tool which aims to support decision-making in the planning and integration of local food production. The project uses a research-based design approach to develop inspiring urban solutions in six differing regions across the world. The new knowledge generated in each of these projects will be used incrementally to develop an analytical decision support tool that will help integrate FEW solutions in future urban designs and developments.

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.

This funding is to support 20 U.S.-based early-career researchers (students and postdoctoral researchers) to attend the 2019 International Conference on Resource Sustainability - Cities (icRS Cities 2019) to be held in Adelaide, Australia on July 1-3, 2019. The conference serves as a platform for researchers and practitioners around the world with diverse background and expertise to share the most recent ideas, outcomes, and practices on resources management for sustainable urban systems. Given that more than half of the world population now lives in cities, urban centers have become the primary sink of resources and energy, and major source of emissions and waste. icRS Cities 2019 will bring together researchers and practitioners to discuss how to achieve urban sustainability through wise resources management policy and practices. Attending the conference will allow the U.S.-based early-career researchers to showcase their research and develop networks with their peers around the world.

A wide range of topics will be covered at the conference related to sustainable urban systems. Solutions to the complex urban sustainability challenges can only be developed via inter- and trans-disciplinary approaches. With participation of natural scientists, engineers, social scientists, industry practitioners, and policy makers, we expect that icRS Cities 2019 will provide an excellent venue for the broad sustainable resources management community to share their findings and opinions on urban sustainability. We also expect icRS Cities 2019 will fill key knowledge gaps which in turn contribute to enhance the holistic understanding of sustainability challenges facing urban systems worldwide.

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.

Research from the last decade has identified cellular senescence and alteration of gut microbial composition as primary physiological processes that facilitate aging and a wide range of age-related diseases. Because of their profound impact on health and disease, they represent two promising ideas in developing innovative strategy to improve health and increase longevity. However, the interplay of the microbiome and cellular senescence in age- related metabolic dysfunction is largely unknown. The major goal of this proposed study is to elucidate the causal connection of cellular senescence and the microbiome in older mice under metabolic stress. We showed a high fat diet (HFD) induced senescent cell loads, increased the abundance of pro-inflammatory gut bacteria, and aggravated metabolic function. In contrast, caloric restriction (CR) decreased gene expression associated with senescence in humans and mice. An intermittent fasting (IF) diet that mimics CR improved metabolic function, and increased the abundance of Akkermansia known to have strong anti-inflammation and anti-aging property. Using our novel p21-Cre mouse model, we found that depletion of senescent cells expressing high levels of p21 (p21high) profoundly increased the relative abundance of Akkermansia, and improved metabolic dysfunction in male mice on a HFD. In Aim 1, we will test the hypothesis that cellular senescence modulates the microbiome composition and function. This will be achieved by directly transplanting or genetic clearance of senescent cells in older male and female mice, and determine their impact on the gut microbiome and microbial metabolites (Aim 1a). The microbiome changes will be determined at population level and functional level as these have not been well-defined previously in aging or age-related diseases. Using our novel p21-Cre mouse model, we will further assess if senescence induced alteration of the microbiome is a novel mechanism by which senescent cells influence metabolic function. We will also test the hypothesis that SASP mediates the senescence-induced microbiome changes by inactivating NF-?B in p21high senescent cells (Aim 1b). In Aim 2, we will test the hypothesis that the gut microbiome modulates senescence development. We will examine development of senescence in mice receiving fecal microbiota derived from a HFD (Aim 2a). We will determine the potential suppression of senescent cells by fecal microbiota transplantation of the microbiota derived from IF or mono- colonization of Akkermansia (Aim 2b). Establishment of reciprocal modulation of the microbiome and cellular senescence will deepen our fundamental understanding of the pathophysiology of aging and age-related metabolic diseases, and pave the way to develop robust interventions targeting senescence, microbiome or both to improve health and increase longevity.