2023 RESEARCH SEED AWARDS
Understanding and preventing violence against environmental activists in the Amazon
Violence against land and environmental activists has increased dramatically in recent years, with countries in Latin America registering by far the highest number of deaths. What are the causes of this violence and what can be done to prevent it? In this study, we propose to systematically explore the political determinants of environment-related violence and identify potentially promising interventions to mitigate it. We focus on the Amazon, which accounts for half of the remaining tropical forest on the planet. The project consists of two components. First, we propose to build a quantitative dataset of killings of environmental activists (including, e.g., indigenous leaders and community representatives involved in environmental protection initiatives) in Brazil over the past twenty years using reports from NGOs and other sources. Second, we will complement our quantitative data with qualitative interviews with local communities and environmental defenders to better understand the variety of threats they face, and to identify factors that might help explain variation in the timing and intensity of those threats. We will also explore the possibility of running a rigorous impact evaluation (e.g. a randomized controlled trial) to evaluate interventions aimed at reducing environment-related violence. The Amazon has a major influence on the world’s climate and hydrological cycles; as such, preserving it and the people who protect it is key in the fight against climate change. This project will advance Brown’s ongoing commitment to support sustainability research and interventions to combat environmental degradation in one of the world’s most environmentally precarious regions.
PI: Robert Blair, Arkadij Eisler Goldman Sachs Associate Professor of Political Science and International and Public Affairs
Co-PI: Mariana Carvalho, Postdoctoral Research Associate in Political Science
Probing quantum phase transitions in space- and time-domain via quantum-dot local messengers
Quantum phase transitions, headlined by strongly correlated electrons, have been a major stream in modern physical sciences and play a critical role in emerging information and energy technologies. Despite their realizations in 2D materials, experimental results often display measurement-to-measurement variabilities. Sample disorders likely contribute to experimental variations. However, the local static and dynamic information of 2D strongly correlated states currently remains elusive, since commonly-exploited transport methods characterize correlated states via device resistance; local information is thus averaged out. The PIs propose exploiting quantum dots (QDs) on 2D twistronics and using emissive QDs as local messengers to deliver the static and dynamic information of 2D correlated states, with tens-of-nm spatial and ps-to-ms temporal resolutions. The combination of expertise in 2D devices and spectroscopy/microscopy in the Bai Lab, nanocrystal and its high-order-architecture synthesis in the Chen Lab, and nano-mechanical modeling and high-precision characterizations in the Kim Lab is unique and coherent. Optical interrogations of low-dimensional correlated phases are in advent and currently remain empty at Brown. This present interdisciplinary effort will establish groundwork in the optical approach to study quantum systems in situ with spatial-temporal precisions, strengthening Brown’s position in quantum research. Notably, the major focus here tackles some grand challenges in quantum phases of matter, a potential foundation for next-generation information and energy technologies.
PI: Yusong Bai, Assistant Professor of Chemistry
Co-PIs: Ou Chen, Associate Professor of Chemistry; Kyung-Suk Kim, Professor of Engineering
Antiferromagnetic Quantum Oxide Tunnel Junctions for Beyond-CMOS Electronics
This proposal seeks to design, develop, and characterize a revolutionary antiferromagnetic tunneling junction based on epitaxial quantum oxide thin films to improve the efficiency, scalability, functionality, and bandwidth of beyond-CMOS electronics and magnetic sensors. Most modern spin-based electronic devices, such as magnetic tunnel junctions, use elemental ferromagnetic metals as active materials (e.g. Co, Fe, Ni, and their alloys). Although well-studied, these simple materials systems suffer from numerous inherent limitations. These include slow and lossy precessional dynamics, large stray fields which prevent device scaling and disturbance immunity, sizable power consumption, and poor signal to noise ratios. We aim to integrate quantum antiferromagnetic oxides into spintronics with the development of a model antiferromagnetic tunnel junction to overcome these challenges. This can only be enabled by our cross-disciplinary approach which combines atomically precise synthesis techniques and device physics. Such a device will enable high bandwidth (THz) operations, low energy (attojoule) control, high sensitivity (femtoTelsa), and high on-off device ratios (>500%) suitable for beyond-CMOS technologies. Such high sensitivity, material stability, and scalability can also enable non-invasive imaging, detection, and sensing of minute electromagnetic signals in biological systems and energy storage/conversion devices. This work will strengthen Brown University's relevance in quantum oxide materials synthesis and applications.
PI: Lucas Caretta, Assistant Professor of Engineering
Co-PI: Gang Xiao, Ford Foundation Professor of Physics, Professor of Engineering
Data-driven high-order accurate fail-safe neural topology optimization for plastic deformation and fracture
Some of the most dramatic progress in materials science and mechanics is rising from exploring extreme phenomena such as unstable behavior (buckling), violent energy absorption through controlled plasticity, and ultra-fatigue resistant and self-healing materials. However, inverse design of materials and structures in these regimes is not possible because (1) the properties of interest are not differentiable, and (2) data generation for the problem of interest is too slow (computationally and experimentally). This project addresses these challenges by exploring for the first time the concept of neural network reparameterization of topology for derivative-free properties of interest and by creating a new entropy-based optimization method that significantly decreases the computational time of the design predictions. These synergistic contributions are believed to open new avenues such that inverse design for extreme conditions becomes feasible, unlocking future explorations of uncharted design spaces to discover materials and structures with unprecedented performance. We aim to use the results developed through this seed award to secure long-term funding from the DOE and DARPA to offer unprecedented solutions to extreme-scale, fail-safe, and risk-averse optimal design via this novel inverse design strategy involving artificial intelligence.
PI: Brendan Keith, Assistant Professor of Applied Mathematics
Co-PI: Miguel Bessa, Associate Professor of Engineering
Workshop on Sustainable Energy
We propose a first of its kind Workshop on Sustainable Energy at Brown University under the auspices of the new Initiative for Sustainable Energy (ISE). ISE is one of the signature initiatives under the Operational Plan for Growing the Research Enterprise, and it has three elements: (i) Research/Innovation; (ii) Education/Training; and (iii) Translation/Practice/Outreach. The proposed Workshop will focus on the Research/Innovation part of the ISE, and it has three thrust areas: (a) Renewable Energy; (b) Sustainable Fuels/Materials; and (c) Energy Efficiency. These interdependent areas are the most critical for fighting climate change by achieving and maintaining a zero-carbon energy global infrastructure over the next century. These are also the areas of distinct strengths with ‘critical mass’ at Brown, and are primed for elevation to the next level. The proposed Workshop will bring together Brown researchers (faculty, postdocs, students) interested in these areas. This will be augmented by invited distinguished visitors from outside of Brown. The aim of the Workshop is to coalesce around research strengths in these areas, and identify gaps that need to be filled. In addition to community building, the Workshop will create themes for large block-grant proposals where Brown would be competitive. The Workshop will include keynote lectures; thematic invited talks; panel discussions; breakout sessions; and a poster session where students and postdocs will showcase their sustainable energy-related research. A team-building excursion is also envisioned.
PI: Nitin Padture, Otis E. Randall University Professor of Engineering
Co-PIs: Rod Beresford, Professor of Engineering; Yue Qi, Joan Wernig Sorensen Professor of Engineering; Brad Marston, Professor of Physics; Sun, Shouheng, Vernon K. Krieble Professor of Chemistry, Professor of Engineering
Controlling magnetic ground states in frustrated magnets
A major challenge of quantum materials has been to tune relevant magnetic energy scales in order to affect new quantum ground states. This project will build on a series of recent findings in the Plumb lab that demonstrate the possibility for controlled tunability of magnetism across a broad class of frustrated magnets. Employing lattice strain, magnetic fields, and dimensionality as tuning parameters, we will measure the evolution of magnetic ground states in model quantum materials using resonant x-ray scattering. Work will concentrate on three material systems. First, we will use lattice strain to explicitly break symmetries and resolve the nature of magnetic phase competition in an FCC antiferromagnet. Second, both magnetic fields and lattice strain will be used to control chiral magnetic textures in transition metal intercalated NbS2. Finally, we will elucidate the nature of the magnetically disordered in an exfoliated antiferromagnet using resonant inelastic x-ray scattering. Seed funding will be used to acquire essential instrumentation for carrying out low temperature x-ray scattering measurements under applied strain and to support a graduate student who will conduct the experiments. By helping to build new capabilities for controlling and measuring the quantum states in magnetic materials, funding through the SEED program will strengthen the quantum materials program at Brown.
PI: Kemp Plumb, Assistant Professor of Physics
Sampling CSG Models with Articulations and Additional Degrees of Freedom
Point Clouds are one of the primary representations for 3D objects in Computer Graphics and in 3D Computer Vision. Most existing Deep Learning algorithms to recognize and estimate the pose of 3D objects in complex scenes represented as point clouds can only handle rigid objects. Parameterized objects, which includes articulated objects, is an emerging area of research. Vast data sets are required to train these algorithms, but generating such training datasets using 3D sensors and real physical objects is usually not feasible. Generating training datasets by simulation is a well established methodology in Machine Learning. We propose to develop algorithms to generate these data sets by simulating the sampling processes associated with 3D sensors. Important applications include industrial inspection, as well as robot navigation and manipulation. Constructive Solid Geometry, or CSG for short, is a popular way of representing solids in Computer Aided Design (CAD), particularly in manufacturing, and can also be considered a design methodology. A CSG solid is constructed from a few primitives defined by implicit inequalities (such as planes, spheres, cylinders, cones, torii, etc.) with Boolean operators (i.e., set union, intersection and difference). A CSG solid may be parameterized by a finite number of parameters. While some parameters may represent articulation angles or relative translations of subparts, other parameters may describe shape features such as radii or lengths of subparts. The proposed formulation, based on sampling CSG objects, will generalize algorithms introduced by the PI years ago to rasterize algebraic curves and surfaces by space subdivision.
PI: Gabriel Taubin, Professor of Engineering, Professor of Computer Science
Efficacy of a Novel Reinforced Engineered Cardiac Tissue for Heart Regeneration
Many patients who survive a heart attack experience loss of heart function over time that often leads to heart failure, and there are no therapies that mechanically support and restore the heart to reverse this life-threatening condition. The mission of the Coulombe lab is to advance heart health and regeneration by leveraging technologies in cardiac tissue engineering, stem cell biology, biomaterials, and regenerative medicine to improve the heart’s electromechanical function after injury or disease onset. Our proposed Seed Award project is rooted in the biomechanics of tissue and scaffold engineering and stems from our ongoing work to develop a robust regenerative therapy for the heart after injury caused by a heart attack, or myocardial infarction (MI). We aim (1) to enhance the mechanical support and strength of our implantable engineered cardiac tissue using computational-experimental iteration and rapid prototyping of customized scaffolds, and (2) to evaluate cardiac function and remodeling with implantation of our mechanically reinforced engineered cardiac tissue in an ischemia/reperfusion MI model. We leverage our background with architected fibrous composite biomaterials to direct the orientation-dependent deformation to optimize support computationally, biomanufacture a scaffold, and evaluate its efficacy in vivo. With successful completion of this proposal, we will be able to advance a mechanically robust engineered cardiac tissue therapy for translational applications.
PI: Kareen Coulombe, Associate Professor of Engineering
Bayesian Modeling of Climate-Dependent Mortality Risk among US Residents from 1989 to 2020
Extreme temperatures, both heat and cold, lead to increased morbidity and mortality (Zhao 2021). While carbon emissions continue, average temperatures and humidity will continue to increase, and the effects of heat on human health will worsen. Cold snap exposure in mid-latitudes involves complex statistics due to polar vortex dynamics (Cohen 2021). Emissions mitigation and resilient physical infrastructure are two methods for reducing climate risk, but a public-health perspective on risk factors for extreme temperature-related mortality can also improve adaptation policy. Which patients are most vulnerable to heat or cold, and do additional weather or economic circumstances modify this vulnerability? How well can we project the particular extreme conditions affecting health outcomes over the next century? We plan to address these question by utilizing Bayesian inference to combine 1) individual-level data in a CDC record of over 80 million deaths that occurred in the United States from 1989 to 2020, 2) extreme weather reanalysis from the National Center for Climate Information and European centers, 3) US Census data on income, employment, education, and other demographic variables, and 4) the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) at the county level (Vos 2020). A Bayesian framework will establish the added value of each dataset in estimation of the health effects of climate on different patient populations. This project builds toward a complete, transparent estimation of mortality from the latest generation of climate model projections to 2100.
PI: Baylor Fox-Kemper, Professor of Earth, Environmental, and Planetary Sciences
Co-PI: Katelyn Moretti, Assistant Professor of Emergency Medicine
Key Personnel: Charles Lawrence, Professor of Applied Mathematics (Research); John Nicklas, PhD candidate
Uncovering the Mechanisms of Transport & Metal Dissociation of Copper-based Radiopharmaceuticals
Copper-based radiopharmaceuticals have emerged as best-in-class imaging agents for positron-emission tomography (PET) and have received increasing attention as theranostic agents (imaging + therapy). Despite these desirable properties, the performance of these materials is limited by their stability in vivo. Nearly 2/3 of all active clinical trials evaluating 64-Cu imaging agents feature bifunctional chelators (BFCs) based on macrocyclic polyaminocarboxylates, yet next to nothing is known regarding the structure, reactivity, and mechanisms of metal dissociation for these agents. Our collaborative, interdisciplinary team will address these key gaps in knowledge by establishing: (i) the solution structure and properties of these agents, (ii) the primary mechanisms for metal dissociation (loss) in vitro, and (iii) liver uptake pathways. These studies will clarify fundamental transport pathways of these critical agents and enable targeted design strategies for imaging agents with enhanced stability and selectivity in vivo. Support from this seed award will enable the generation of key preliminary data needed to advance competitive proposals for sustained external funding.
PI: Jerome Robinson, Manning Assistant Professor of Chemistry
Co-PI: Thomas Bartnikas, Associate Professor of Pathology and Laboratory Medicine
Generating icTango, a technique for tracking developing cellular networks
Intercellular contacts are essential for the normal development and functioning of multicellular organisms. These interactions are particularly relevant in the nervous system, but they are also fundamental to developmental processes as well as to the immune response and in metastatic cancer. I propose to adapt trans-Tango, a method for transsynaptic labeling of neural circuits developed by my laboratory, to establish icTango, a technique aimed at defining the history of cell-cell contacts during development. In trans-Tango, a synthetic signaling pathway is introduced into all neurons, and a membrane-tethered version of the ligand that activates the pathway is presented at the synapses of the presynaptic neurons of choice to label the relevant circuit. In icTango, the ligand will be presented all around the cell membrane of the initiating cells. Thus, the first step in adapting the trans-Tango design to generate icTango requires a structural change in the ligand construct. Further, trans-Tango is established in Drosophila and in zebrafish, and we will establish icTango in mice. Therefore, several additional adaptations of the signaling pathway are necessary. Here we will implement icTango to study macrophages, one of the diverse types of immune cells. However, our proposed project will serve as a proof of concept for establishing versions of icTango to study other interactions in the immune system as well as the interactions that cancer cells have with their environment during metastasis.
PI: Gilad Barnea, Sidney A. Fox and Dorothea Doctors Fox Professor of Ophthalmology and Visual Science, Professor of Neuroscience
Understanding the dynamics of conceptual development in early childhood
Within the first few years of life, children successfully learn complex categories, ranging from the colors in their language to the structure of biological taxonomies. Despite considerable research, there is an ongoing debate about how children develop complex, abstract category representations. Do all children build adult-like categories in the same way? Answering these questions requires methods that can measure children's categorical organization and chart the trajectory of categorical development. Previously, this was not possible, partly because traditional approaches require asking questions difficult for young children to understand and partly because current methods are data-intensive, even for adults. We propose a novel experimental methodology that overcomes these limitations. We focus on two critical domains for conceptual development: (1) How do children's concepts about biological kinds (e.g., animals) transform to form the complex structures adults can access? (2) Languages differ in how they carve up the perceptual color space. We ask if the development of adult-like color categories progresses similarly across languages. Our project offers several exciting prospects. First, our method allows us to relate categories across age groups, expanding our understanding of learning and development. Second, since our method can capture inference tasks from different experiments, our project offers the prospect of producing general computational models of development, advancing Brown's position in fields from machine learning to cognitive (developmental) psychology. In summary, the funding would allow us to conduct crucial experiments on the theoretical foundations of learning and development, providing us with a solid foundation to apply for further external funding.
PI: Daphna Buchsbaum, Assistant Professor of Cognitive, Linguistic and Psychological Sciences
Co-PI: Pablo Leon-Villagra, Postdoctoral Research Associate in Cognitive, Linguistic and Psychological Sciences
Causes of dangerous short-term and long-term coagulation issues with SARS-CoV-2 and other potential pandemic respiratory virus infections
COVID-19, the disease caused by the SARS-CoV-2 has caused more than a million deaths in the United States alone since the start of the pandemic. At the time of writing this about 500 people are dying of acute COVID in the United States, and a significant number of people are impacted by “long-COVID”. Not only does COVID-19 cause lung damage which has both short- and long-term effects, it also impacts the blood vessels. This attack of the vascular system causes some of the most severe manifestations of the disease, including stroke, arrhythmia, and kidney damage. Such clotting related pathologies have recently been observed in children and young people who were not previously considered to be at high risk for severe SARS-CoV-2 morbidities and mortality. The Jamieson lab has recently shown that SARS-CoV-2 infected lung epithelial cells have dysregulated expression of key factors that are important in blood coagulation. This study investigates how small vesicles from the lung, that have coagulation factors on them, make their way into the general circulation causing these systemic problems in COVID-19 patients. The Jamieson and Abbasi labs will work with researchers in the MICU to get patient plasma samples to study this. There is also mounting evidence that this may occur in other respiratory infections, therefore understanding this potential cause of severe disease is important to help us with this pandemic and prepare us for treating the next.
PI: Amanda Jamieson, Esther Elizabeth Brintzenhoff Associate Professor of Molecular Microbiology and Immunology
Co-PI: Adeel Abbasi, Assistant Professor of Medicine
Identifying new therapeutic target genes and candidate small molecules to treat Glioblastoma Multiforme
With an average life expectancy of 15 months and high post-treatment recurrence, Gliobastoma Multiforme (GBM) severely lacks an effective therapeutic treatment. To develop new therapeutics, clinicians need new insights into the mechanisms that drive the evolution of heterogeneous GBM tumors. The frequent post-treatment recurrence of GBM is likely due to the presence of resistant glioma stem cells that exhibit a high degree of genomic instability. In contrast to healthy cells, cancers with a high degree of genomic instability were recently shown to be highly sensitive to loss of the dosage compensation complex (DCC/MSL) which corrects for the gene dosage imbalances caused by deletions and duplications. In contrast, the growth of healthy cells was not affected by the DCC. Therefore, we will combine translational expertise (Tapinos lab) with basic scientific knowledge of DCC function which has been best studied in Drosophila (Larschan lab) to define new mechanisms that drive GBM by: 1) defining how the DCC functions in GBM using patient-derived glioma stem cell lines; 2) performing a pilot small molecule screen for compounds that block DCC function using our available Drosophila DCC reporter system at the Brown University Cancer Biology core facility. We will integrate and iterate these approaches by testing small molecules identified in Drosophila screens with patient cell line models. The synergy between basic science and translational expertise is essential to advance our understanding of how to treat GBM and submit a competitive NIH proposal on this work.
PI: Erica Larschan, Associate Professor of Molecular Biology, Cell Biology and Biochemistry
Co-PI: Nikos Tapinos, Sidney A. Fox and Dorothea Doctors Fox Associate Professor of Ophthalmology, Visual Science, and Neuroscience
Identifying non-canonical functions for macrophage in development and disease
Macrophage are phagocytic cells best known for their critical roles as cellular mediators of innate immune responses to injury and infection. However, an increasing body of evidence indicates that tissue resident macrophage have essential non-canonical, non-immune functions in organogenesis and organ health. The Plavicki and Morrison labs have established a new collaboration to examine whether tissue resident cardiac macrophage are required for the development of the cardiac conduction system. In this proposal, we will substantially extend this collaboration, combining the expertise of both labs to determine how non-canonical macrophage functions and early life inflammation shape heart development and health. Our exciting preliminary data indicate that macrophage are electrically coupled to pacemaker cardiomyocytes in the sinoatrial node in both larval zebrafish and postnatal mice. Furthermore, we found that loss of embryonic tissue resident macrophage predisposes the adult zebrafish heart to arrhythmia. In this proposal, we will ask if myocardial inflammation, which has increased due to SARS-CoV-2 infections, alters the composition of cardiac macrophage populations such that it also predisposes the zebrafish heart to arrhythmia. We will pair our zebrafish studies with a mouse model of prenatal inflammation, a risk factor for preterm birth and adverse perinatal outcomes, to determine the impact of inflammation on macrophage function in mammalian heart development. Together, this work will contribute to our fundamental understanding of macrophage biology and cardiac development and simultaneously inform our understanding of the risk factors that predispose the adult heart to arrhythmias and disease. This project will generate a multi-PI R01 application.
PI: Jessica Plavicki, Manning Assistant Professor of Pathology and Laboratory Medicine
Co-PI: Alan Morrison, Associate Professor of Medicine
Mechanisms integrating mental and sensorimotor workspaces
The proposed research aims to determine the interplay between mechanisms involved in maintaining information in the mental workspace (e.g., working memory) and those involved in learning a new sensorimotor skill (e.g., visuomotor rotation). Our working hypothesis is that representation-specific spatial working memory is selectively involved in the visuomotor rotation. This cognitive and sensorimotor synergy is at the root of complex adaptive behavior in the real world. Nevertheless, these domains have been primarily examined in isolation. Such a divide-and-conquer approach has focused researchers' efforts on behavioral phenomena that fall under well-defined categories, leading to scientific rigor and significant insights into each subsystem, such as working memory and sensorimotor learning. However, this approach can lose sight of their interrelation, which may be fundamental to realistic adaptive behaviors. By combining methods and insights from cognitive psychology and motor control, the proposed research intends to shift focus to a new interactive framework, representing a substantive departure from the status quo. With demonstrated feasibility from preliminary data, this endeavor will advance our understanding of the dynamic interdependence between cognitive and sensorimotor mechanisms. It will explain adaptive, real-world adaptive behavior eventually beyond laboratories. Furthermore, the outcome of this project will have implications for developing effective training methods in medical and non-medical fields, including most classroom activities, sports, and rehabilitation, in which learners integrate cognitive and motor skills.
PI: Joo-Hyun Song, Associate Professor of Cognitive, Linguistic and Psychological Sciences
Predicting and controlling seizure spread in people with pharmacologically resistant epilepsy
Focal epileptic seizures can remain localized or spread across brain areas. When they spread, this can lead to major disruptions in sensorimotor and cognitive function, often including loss of consciousness, one of the most debilitating aspects of the disorder. For pharmacologically resistant epilepsy, recent therapeutic options include intracranial closed-loop brain electrical stimulation devices for seizure control. Common approaches consist of detecting a seizure soon after onset and triggering stimulation to prevent its spread. Recent research in the Truccolo Lab, involving a large cohort of participants implanted with these devices, has shown that interictal epileptiform activity and multiscale rhythms in brain excitability spanning from hours to days modulate seizure likelihood and spread size. We have additionally developed stochastic nonlinear models of neural dynamics for predicting, given a detected focal onset in a specific individual, whether and how a seizure will spread across brain areas. The models incorporate patient-specific brain network connectivity obtained via (diffusion MRI) white-matter tractography, time delays in the interactions between brain areas due to axonal conduction, and our new understanding of how neural excitability and connectivity strength affect the nonequilibrium dynamics of seizure spread. The next significant challenge is the development of better closed-loop interventions to control and prevent seizure spread. Currently, most neuroengineering control applications rely on heuristic or linear feedback approaches, which are not optimal for controlling seizures with highly nonlinear dynamics. In this proposal, we aim to build on our recent research and develop a new framework for optimizing the control of seizures and preventing their spread in large-scale neuronal networks in the brain.
PI: Wilson Truccolo, Pablo J. Salame Goldman Sachs Associate Professor of Computational Neuroscience
Feasibility and acceptability of using wearable devices to measure sleep in people living with dementia
The pilot represents a new partnership between public health and computer science. Our interdisciplinary team is planning to submit a R01 proposal to conduct an early-stage, real-world efficacy trial under PAR-21-359. The primary aim of that trial will be to identify the optimal dose and timing of artificial lighting for improving sleep outcomes in nursing home residents living with dementia. The aims for this one-year pilot are to: 1) leverage the IMPACT Collaboratory’s national Lived Experience Panel, a diverse group of persons living with dementia, to review our R01 study protocol and conduct preliminary feasibility tests of the sleep monitoring devices; and 2) review the extant literature to describe limitations of using sleep monitoring devices in people with dementia. Ellen McCreedy, PhD has led several pragmatic trials of interventions for persons living with dementia and has expertise in assessing feasibility of measurement strategies in the nursing home setting. Jeff Huang, PhD is the director of the human-computer interaction research lab at Brown University and has expertise in extracting data from sleep monitoring devices and aggregating raw sleep data into meaningful sleep outcomes for users. The proposed work will directly improve the planned R01 application by providing preliminary feasibility data and identifying a gap in the existing literature. The National Institutes on Aging is increasingly interested in funding research into the use of wearables and other remote sensing technologies for ongoing monitoring and early detection of status changes in older adults with dementia. This new partnership positions the University at the forefront of this exciting research.
PI: Ellen McCreedy, Assistant Professor of Health Services, Policy and Practice
Co-PIs: Jeff Huang, Associate Professor of Computer Science; Terrie Fox Wetle, Professor of Health Services, Policy and Practice; Rosa Baier, Professor of the Practice of Health Services, Policy and Practice
Migration among Medicare Beneficiaries from Puerto Rico
Patients with complex needs may be exposed to high levels of out-of-pocket spending, with much of this spending on long-term care. The combination of healthcare access and socioeconomic factors may result in a relatively large proportion of vulnerable patients needing specialty services and more coordinated care, which the island may not be able to provide. Since Medicaid does not cover institutional care in Puerto Rico, people with high needs may seek to reduce health care costs by migrating to the US mainland, where they may be eligible for long-term services and support. The proposed project has the capacity to advance research related to migration among patients with vulnerable conditions and access and quality of care among high-need patients on the island. Older Puerto Ricans and patients with high needs who require specialized care, particularly long-term services and support, may have no choice except to leave the island to seek better quality of care. Our specific aims are as follows: 1) Identify high-need patients among Medicare beneficiaries in Puerto Rico. We will define beneficiaries with high needs based on disability, age, chronic conditions and difficulty with activities of daily living (ADL); 2) Examine migration trends among Medicare beneficiaries in Puerto Rico with and without high needs. The working hypothesis is that out-migration rates will be higher among older adults with high needs compared to those without high needs. This contribution is significant because older adults in Puerto Rico have lower quality of care, high poverty rates and often suffer from poor outcomes.
PI: Maricruz Rivera-Hernandez, Assistant Professor of Health Services, Policy and Practice
Workshop on Nature and Health: A Cells to Society Approach
Emerging empirical evidence suggests exposure to nature impacts multiple health outcomes and dimensions. Notwithstanding, conceptual and methodological approaches remain inconsistent, with relevant disciplines working in silos. The proposed workshop will bring together researchers at Brown and globally with expertise in public health, computer science, engineering, molecular biology, geography, and medicine, as well as community organizations working in nature and health. The multidisciplinary group of researchers will tackle several challenges related to the study of nature and health, including: a) Disentangling which specific aspects of nature influence health; b) Quantifying exposure to nature; and c) Understanding the mechanisms through which nature "gets under the skin" to influence health. By examining existing conceptualizations of nature, methods used to measure nature and the impact on health and well-being, we hope to make recommendations on equitable and inclusive ways to tackle examinations of nature and health.
PI: Diana Grigsby-Toussaint, Associate Professor of Behavioral and Social Sciences, Associate Professor of Epidemiology
Co-PI: Kevin Mwenda, Assistant Professor of Population Studies (Research)
Drinking Water Per- and Polyfluoroalkyl Substances (PFAS) Concentrations in Jackson, Mississippi and Children’s Health
The water crisis in Jackson, Mississippi, has made national headlines as a major environmental catastrophe, impacting the public health and well-being of residents. The Community Noise Lab at the Brown University School of Public Health has been on the front lines of this water crisis, working with faculty and students at The Piney Wood School, a historically black, private, co-educational boarding high school in Greater Jackson. Together, we have implemented The Greater Jackson Water Watch (GJWW) and have operated a mobile tap water testing laboratory, traveling to different locations in the city, testing tap water quality on-site for pH, dissolved oxygen, and turbidity. Residents are able to view summarized tap water sample levels by city and zip code and all residents who had their tap water tested received a summary of their results. Recently, we quantified concentrations of forty per- and polyfluoroalkyl substances (PFAS) in 49 random samples collected by the GJWW. In these samples, we detected twenty-eight PFAS species, including several above the EPA Health Advisory levels. This Seed Grant proposal centers on two specific aims, (1) Conduct an exposure assessment to characterize the PFAS levels from tap water in homes across the City of Jackson, Mississippi, (2) Collect biological and self-report health data from children living at these homes to examine the relationship between water quality and pediatric health. The data collected will provide pilot data, which will be leveraged to apply for an NIH R01.
PI: Erica Walker, RGSS Assistant Professor of Epidemiology
Co-PI: Katherine Manz, Assistant Professor of Engineering (Research); Joseph Braun, Associate Professor of Epidemiology