Eileen Martin - US grants

The long-term objectives of this research are to employ a cognitive neuropsychological model to conceptualize the effects of HIV and drug abuse on the brain and to relate these effects to critical behaviors in HIV-seropositive persons such as high risk sexual and injection practices. Evidence indicates that drug abuse and HIV infection cause dysfunction in overlapping frontal-subcortical brain regions and that careful study of specific cognitive functions mediated by different frontal-subcortical circuits will permit characterization of HIV-related cognitive impairment and its manifestation in persons who abuse drugs. This study will begin to evaluate the question of whether a history of drug abuse in the context of HIV infection will increase vulnerability to HIV-related cognitive deficits, a question with potential diagnostic and therapeutic implications. The specific aims of this investigation are to compare the performance of HIV-seropositive (HIV+) and HIV- seronegative (HIV-) with a current or past history of drug abuse on measures of decision-making, working memory, and response inhibition, "executive" functions dependent on the integrity of prefrontal-subcortical pathways and potential mechanisms of HIV- related cognitive dysfunction; to evaluate the relationship between parameters of drug abuse severity to deficits in executive function in HIV+ and HIV - drug users; to evaluate the presence and severity of executive deficits in HIV+ drug users at different stages of HIV disease; and to evaluate the relationships between executive functions and sexual and drug use-related risk behavior. The study will evaluate cognitive function in HIV+ and HIV- drug users employing state of the art computerized measure developed to model specific impairments associated with dysfunction of frontal-subcortical circuits. Data from the proposed study will advance knowledge of cognitive aspects of HIV-1 infection; the practical implications of how cognitive impairment associated with HIV influences behavior, and recent attempts to bridge the gap on how specific cognitive impairment can influence risk behavior

DESCRIPTION: (Applicant's Abstract) The long-term objectives of this research are to employ a cognitive neuropsychological model to conceptualize the effects of HIV and club drug abuse on the brain, to relate these effects to critical behaviors such as high risk sexual and injection practices in HIV-seropositive and seronegative men who have sex with men (MSMs), and to obtain preliminary data on the relationship between these effects and adherence with antiretroviral therapy. The abuse of MDMA ("Ecstasy'), ketamine ("Special K") and other club drugs is on the rise among MSMs and evidence indicates that the majority of club drugs have known or potential neurotoxic effects; however, neurocognition and club drug use has not been studied in MSMs or in the context of HIV infection. HIV infection and abuse of MDMA, the most common club drug of abuse among MSMs, cause dysfunction in overlapping frontal-subcortical brain regions. This study will evaluate the question of whether a history of MDMA abuse in the context of HIV infection will increase vulnerability to neurocognitive deficits, a question with significant potential diagnostic and therapeutic implications. We assume that careful study of specific cognitive functions mediated by different frontal-subcortical circuits will permit characterization of HIV-related cognitive impairment and its manifestation in persons who abuse MDMA. The specific aims of this investigation are to compare the performance of HIV-seropositive (HIV+) and HIV-seronegative (HIV-) MSMs with a current or past history of MDMA abuse and control groups of HIV+ and HIV- MSMs with no history of MDMA abuse on measures of decision-making, working memory, response inhibition and prospective memory, "executive" functions dependent on the integrity of prefrontal-subcortical pathways and potential mechanisms of HIV-related cognitive dysfunction; to evaluate the association of HIV serostatus and MDMA abuse with executive functions and sexual and drug use-related risk behavior; and to obtain preliminary data on levels of adherence with antiretroviral therapy in HIV+ MSMs with and without a history of MDMA abuse. The study will evaluate cognitive function in these groups employing state of the art computerized measures developed to model specific impairments associated with dysfunction of frontal-subcortical circuits. Data from the proposed study will advance knowledge of cognitive aspects of HIV-1 infection in the context of MDMA abuse; the practical implications of how cognitive impairment associated with HIV and club drug abuse influences behavior; and recent attempts to bridge the gap on how specific cognitive impairment can influence risk behavior and medication and adherence.

DESCRIPTION (provided by applicant): Advances in quantitative image processing have facilitated greatly the capacity of structural magnetic resonance imaging (MRI) to detect subtle and previously unappreciated changes in brain regions among HIV+ persons without dementia. These provide a powerful tool to advance knowledge of key clinical and neuropathological features of neuroAIDS as they have evolved since the introduction of HAART. These new methods may allow for mapping more precisely subtle brain changes among HIV+ subjects with significant comorbid conditions such as substance dependence, which are currently not well understood. We propose to conduct a two-year methodological pilot to establish feasibility of morphometric studies MRI at UIC in collaboration with investigators at the University of Pittsburgh who have developed Automated Language Programming, a state of the art post processing system that has been employed successfully to study subtle changes in cerebral morphology. Over the next two years we will perform MRI scans on a total of 40 individuals recruited from an existing cohort of subjects from a larger study led by the PI, with varying history of HIV and substance dependence and establish the capability to define and compare subtle changes in selected brain regions of critical interest in the study of neuroAIDS and addiction, to be conducted with a small group of subjects enrolled in a larger study of HIV and substance dependence led by the PI. Results of this project have significant translational potential for characterizing and tracking CNS involvement among substance-dependent HIV+ persons without frank dementia. Findings will enable us to formulate and test new and exciting hypotheses regarding neuroAIDS and its real life consequences, including vulnerability to risky sexual behavior, in significantly understudied population with multiple health problems. PUBLIC HEALTH RELEVANCE People with HIV/AIDS are living longer since the introduction of potent antiretroviral therapies but HIV still affects the brain and can impair memory and other cognitive functions, so it is important to develop new methods for tracking these brain changes. This project will test a very precise brain imaging method that is able to pick up very small brain changes before development of serious neurologic problems such as dementia. The information gathered in this project may be able to help us develop treatments with the potential to prevent dementia or other mental problems

DESCRIPTION (provided by applicant): Breakdown in decision making and propensity for risk taking are common features of drug addiction that contribute in part to increased rates of unsafe sexual and drug using practices. Compelling evidence demonstrates that HIV+ drug users are more vulnerable to decision making defects. However, there are essentially no studies of the integrity of decision making among drug-using HIV+ men who have sex with men (MSMs), whose patterns and context of drug abuse and sexual risk taking are substantially different from the crack or opiate-dependent participants of previous studies. We propose a two year feasibility study of neurocognitive aspects of decision making among a sample of participants from the Chicago MACS cohort. This site-specific pilot study will address the feasibility and scientific utility of: 1) characterizing the integrity of decision making among drug using participants enrolled in the Chicago MACS;2) comparing the performance of drug-using HIV+ with HIV- MACS participants and 3) obtaining preliminary data regarding potential associations between performance on these measures with high risk sexual and drug use behavior. Models of impaired decision making in neuroAIDS have clear translational potential for the design of more specific interventions for risk prevention and substance abuse treatment among MSMs. People with HIV/AIDS are living longer since the introduction of potent antiretroviral therapies but HIV still affects the brain and can impair memory and other cognitive functions. A history of drug abuse may increase the risk of HIV-associated neurocognitive impairment;in particular, it appears that both HIV and drug abuse can affect a person's ability to make safe decisions in risky situations. This pilot project in Chicago will evaluate how well MACS participants who have used drugs can make safe decisions and whether this will predict subsequent risky sexual activity and drug use. The information gathered in this project may be able to help us develop more specific prevention methods and substance abuse treatments.

Climate change is resulting in warming of the permafrost across the Arctic and sub-Arctic, which results in changes in the geological and mechanical properties of soils. Quantifying the changes in soil properties are critical for both understanding the natural environment and assessing the effects of these changes on the existing and future built infrastructure, both of which have long-lasting societal impacts. This project will embed fiber optic sensing cables into the ground in an Alaskan coastal community. Fiber-optic-sensed signals will be converted into the geological and geomechanical properties of the ground material and then used to quantitatively forecast future impacts on permafrost properties. The project outcomes will enable realistic evaluation of the performances of infrastructure in Arctic Alaska and improve the design of more robust infrastructure in the Arctic. The research team will actively recruit and train women scientists and engineers through convergent research, and the research team will be involved in educational and outreach activities in Utqia?vik, Alaska?s indigenous community.

The goal of this project is to understand and forecast long-term variations of in-situ geophysical and geomechanical characteristics of the active layer and permafrost in Arctic Alaska using an innovative sensing technology, data transmission and analysis, and modeling. Through advances in sensor systems and modeling, the project will transform existing capabilities for understanding dynamic, near-surface soil processes in the active layer and permafrost in an Arctic coastal community, thus generating quantitative knowledge of long-term and in-situ permafrost degradation in the Arctic due to climate change. Five tasks will be conducted: (1) develop and deploy a 1.5-kilometer-long fiber-optic distributed acoustic sensing (DAS) array in Utqia?vik, Alaska for long-term in-situ permafrost monitoring; (2) develop innovative data transmission and analysis of DAS signals in permafrost and derive temperature-dependent S-wave and P-wave velocity profiles of changing permafrost in spatial and temporal scales; (3) obtain ground-truth measurements of geophysical and geomechanical properties through in-situ and laboratory characterizations; (4) develop correlations between geophysical and geomechanical properties of permafrost and S- and P-wave velocities as well as between permafrost temperature and S- and P-wave velocities; and (5) forecast future changes of geophysical and geomechanical properties of degrading permafrost. Research outcomes will directly inform current infrastructure evaluation and future infrastructure development in the North Slope Borough, Alaska. Methodology developed in this project will provide transformative and cost-effective geophysical and geotechnical monitoring in the Arctic and sub-Arctic regions.

This award was made through the "Signals in the Soil (SitS)" solicitation, a collaborative partnership between the National Science Foundation and the United States Department of Agriculture National Institute of Food and Agriculture (USDA NIFA).

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.

Computational seismology methods analyze data that measure vibrations of the Earth. These methods allow scientists to understand earthquake hazards, to measure stability of the ground underneath structures, to monitor groundwater systems, to study changes in threatened Earth systems such as glaciers and permafrost, to safely and efficiently explore natural resources underground, and to monitor civil infrastructure health, among other applications. Seismology has undergone a radical shift recently; new sensor technologies have made data collection much easier, enabling hundreds to thousands of times larger datasets that can be used for detailed studies of larger regions for long periods of time. Most scientists cannot use these data because: (1) data are only shared internally among groups that have new sensors, (2) public seismology data storage facilities cannot support such large data quantities, and (3) most geoscientists do not have the computational resources to analyze the data. Because of these three issues, there is an inequitable research environment, much data remains unexplored, and important geoscience discoveries cannot occur. While there are ongoing efforts to address the first issue, without major cyberinfrastructure advances addressing the second and third issues newly acquired data is unlikely to be fully analyzed. This project aims to create new computational algorithms, software and models of open data sharing to ensure that any geoscientist can glean valuable insights from large-scale seismology data. The education and outreach program will create opportunities for more people to participate in mathematical modeling and large-scale data analysis for science and engineering applications. The project PI will develop and strengthen existing efforts to support diverse and inclusive research and learning environments. She will continue to develop a program to introduce women undergraduates to mathematics research, growing it to be a sustainable multi-faculty course serving more students from underrepresented groups. The project will increase the impact of the annual data science conference led by the PI. The conference features research by women data scientists and tutorials on modern data science techniques, and connects the interdisciplinary data science community on a rural campus.

The project will derive and analyze new geoscience algorithms, develop community software and explore models of open data distribution. The project goal is to ensure that any seismologist can gain valuable geophysical insights from extreme-scale seismic data in the field, at institutions with limited computing resources, and on modern high performance computing (HPC) systems. Expertise in large-scale seismic sensing, mathematics, high-throughput computational science, and algorithm design are necessary to achieve these advances. The project proposes a new model for public seismology data archives that allows for the storage of lossy-compressed data and data products, thus creating a new capacity to host ultra-high-density and large-scale seismic data, without displacing existing systems for high-quality seismometer data. To address large-scale data analysis, the PI has previously created several scalable algorithms, and theoretical analyses suggest that a complete suite of scalable, parallelizable algorithms for multiple types of passive seismic data processing can be developed. Many of the algorithms operate directly on compressed information without reconstructing the original data, which reduces costly data movement. The project will develop fast serial and parallel software algorithm implementations, and investigate the use of accelerator hardware for high computational efficiency. For each algorithm the project will theoretically derive and computationally verify trends governing tradeoffs between computational efficiency, memory footprint, and end-to-end accuracy specific to the geophysical analyses. The algorithms will incorporate error bounds for realistic non-idealized data and will be included in predictive software for geoscientists to make informed decisions prior to requests for compressed data or data products. The new methods will be tested by applying them to cutting-edge passive seismic data at the scale of tens to hundreds of terabytes. The data will enable seismology analyses in for urban hydrology and geotechnical engineering, and also analyses to aid in understanding glacier movements to improve climate models via improved boundary conditions and mechanistic understanding. In addition to earthquake seismology, hydrology, geotechnical engineering, and cryosphere studies, the methods developed can be applied to many high-throughput computational science problems utilizing sparse or compressed representations (e.g., structural health monitoring, imaging science, solar physics, radioastronomy, wireless communications, industrial facility monitoring). To increase adoption of new methods by geoscientists, the project will develop tutorials, promote scientific community collaboration, and organize research workshops.

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.