Despite high enrollment rates in community colleges, persistence and completion rates have lagged due to students’ academic unpreparedness, challenges navigating academic paths and campus life, limited resources, and the need to combine studying with work and other responsibilities. Higher education research underscores the potential of wraparound student support programs to significantly improve persistence and graduation rates. The Accelerated Study in Associate Programs (ASAP) at community colleges of the City University of New York (CUNY) is a successful model that demonstrated doubling of graduation rates in randomized trials. However, despite the adoption of ASAP-inspired programs in many colleges, there’s a noticeable absence of research-informed guidance for effective implementation. To address this gap, we propose a qualitative study focusing on the implementation of the “Supporting Urgent Community College Equity through Student Services” (SUCCESS) initiative, introduced by the Massachusetts legislature in 2021. SUCCESS allocates funds to the state’s 15 community colleges to provide evidence-based wraparound services aimed at enhancing student persistence and degree completion. This qualitative study aims to contribute to the growing body of literature guiding the translation of research evidence into practice in higher education by examining how community colleges implement SUCCESS. This initial work will be a precursor to a more extensive study on the impact of SUCCESS on student persistence and degree attainment at Massachusetts community colleges, with plans to seek multi-year external funding for a comprehensive impact study. This project positions Brown at the forefront of educational research and state policy focused on college persistence and graduation.

Quadrotor flying vehicles ("drones") are finding widespread use in many applications including search and rescue, remote monitoring, inspection in agricultural and industrial settings, and operations in hazardous or even extra-terrestrial environments.  One critical weakness in this exciting new arena is the inability to operate dense swarms of quadrotors due to aerodynamic interference of the rotor wakes.  This weakness also prevents many new and advanced applications such as synthetic aperture imaging or cooperative assembly tasks.  The goal of this project is to acquire data on multi-quadrotor interactions - force,  torque and velocity interactions - over a wide range of operating conditions and spatial separation,  and to use data-driven analysis techniques to develop efficient, accurate and practical flight controllers to compensate for the close-proximity interference. Despite the importance of this problem to advanced flight robotics, there has been little work presented in this area. The collaboration between the professors Breuer and Ayanian - who bring expertise from the aerodynamic and computer science fields - presents an opportunity to put Brown at the forefront of high density cooperative drone flight control.  The results from this effort will provide significant first steps necessary for the PIs to apply for longer-term, more substantial funding from government agencies (NSF, DARPA, NASA, etc) and private industry.  Intellectual property related to the aerodynamic design and control of drone swarms, as well as trajectory planning for complex swarm maneuvers is anticipated.

Semiconductor technologies are rapidly facing challenges in scalability, energy consumption, and reduced latency. These challenges are driving a significant effort to develop alternatives to CMOS-based technologies to meet the demands of future computing technologies. Neuromorphic computing could address these challenges with high performance and low-power artificial neural networks. These technologies can provide increased computing performance with enhanced features and reduced cost but rely on traditional chip technologies not designed for their operation. This collaboration seeks to develop a first of its kind spin wave neural network comprised of two-dimensional magnon scattering centers, also known as magnonic crystals. We hypothesize that by using inverse design machine learning processes and high throughput micromagnetic simulations, we will optimize the array of spin wave scattering sites to create a neural network capable of number classification based on spin wave interference patterns. In this collaborative proposal, our interdisciplinary team will test our hypothesis and address design challenges associated with the vast optimization parameter space by developing a coherent computation, materials synthesis and characterization, and spin wave imaging platform. This platform will enable a learning loop, where the prediction and discovery of unique magnonic crystal topologies will be reinforced by feedback from micromagnetic simulations and experimental verification via novel quantum imaging platforms. The outcomes of this project include a framework and design protocol by which to optimize spin wave scattering platforms for advanced computing, new fundamental insight on spin wave-spin wave interactions, and the experimental realization of a low power spin wave neural network.

How does identity/identification/authentication work online? Currently, corporations collect everyone's information and act as identity verification providers. Not only is this a disaster from the privacy point of view, but it also gives these corporations the power to mess up our identities online, to cause us to be denied important services, and to report incorrect information about us to other entities. How should it work online? A better approach is one where each individual has everything they need to prove their own identity and relevant identity attributes --- or to provide no information about themselves at all other than the fact that they are authorized to participate in an online transaction. This project aims to make this vision a reality. Through my 25-year research career, I have worked extensively on anonymous credentials, which are cryptographic algorithms that enable users to prove that they are authorized and have necessary credentials without revealing any additional information. Now the time has come to put all this into practice.

Over the past 45 years, Arctic sea ice has drastically declined at an unprecedented rate that has not been seen in the past 1,500 years of historical records. This alarming trend is exacerbated by the Arctic's rapid atmospheric warming, which is four times faster than the global average. Sea ice loss not only contributes to warming but also has far-reaching ecological, societal, and geopolitical implications. We are thus urgent to accurately and quantitatively project future Arctic sea ice changes based on future climate trajectories. However, current state-of-the-art climate models exhibit significant disparities and large uncertainties, offering little value in formulating solutions for Arctic and global sustainability. Here, our proposal will leverage the unique strengths at Brown University, combining expertise in organic geochemistry, paleoclimatology, and sea ice modeling, to achieve three core objectives: (1) synthesizing robust, quantitative Arctic sea ice reconstructions based on multiple sea ice proxy records for two recent “warmer-than-present” periods (Marine Isotope Stages 5 and 11), which serve as best geological analogues for our future, (2) providing essential proxy-based sea ice data for model calibration, and (3) critically examining the underlying parameterization in sea ice models, to bolster model accuracy in projecting future Arctic sea ice. The research will generate key preliminary data, provide opportunities for career development of early career researchers, and promote outreach initiatives and mentoring undergraduate students, all of which will enhance the competitiveness of our proposal for sustained external fundings.

Position-sensitive silicon devices with internal gain, such as Low Gain Avalanche Diodes (LGADs), are capable of tens of pico-second timing resolution. Similarly, Resistive Silicon Devices, such as AC-coupled Low Gain Avalanche Diodes, achieve a fine spatial resolution while maintaining the LGAD's timing resolution with near to 100%fill factor, achieving time and space (4D) tracking measurements for collider-based experiments. Because of their low power consumption and tolerance to high radiation, they are also ideal candidates for satellite spectroscopy. However, the performance of this new technology is strongly affected by environmental factors such as temperature, humidity, and mechanical stresses. The lack of universal models that account for the path of charge carriers in the multiplication layers hinders their application to new horizons. As their performance has never been studied to account for environmental stresses, the entire operational envelope of these devices remains unmapped. This project will establish a performance-to-conditions map by characterizing the devices' performance dependence as a function of the fabrication properties and the environmental operating conditions. By accounting for this performance change, the device's output signal can be corrected for the environmental factors using Artificial Intelligence and Machine Learning techniques, thus harnessing an optimal readout performance outside the typical operating conditions. The acquired knowledge for the university will allow for a sensor fabrication that can be tuned explicitly for space applications.  Due to reducing the amount of support material brought to space, the university will produce competitive alternatives to currently planned technologies for space-based spectroscopy.

Interfaces between dissimilar materials (semiconductors, dielectrics, metals) are ubiquitous in multi-layered energy-conversion and -storage devices, such as solar cells and batteries. The reliability of these devices critically depends on the mechanical adhesion at these interfaces. Since most of these functional devices are ‘dynamic,’ during their operation under external stimuli (electric field, light) many hetero-interfaces typically accumulate charged species (electrons, holes, vacancies, interstitials), thereby generating internal charged layers. Unfortunately, to-date the charged-interface effects have not been considered explicitly in the adhesion and fracture of interfaces in these devices. The proposed research will focus on the burgeoning perovskite solar cells (PSCs) where such effects are expected to be critical for their long-term durability and reliability. The objective is to develop experimental tools for gaining fundamental understanding of the important effects of accumulated charge and external stimuli (electric field, light) on the adhesion and fracture behavior of a range of hetero-interfaces relevant to PSCs. This will address the wide knowledge gap in this important area, and help take materials science of adhesion to the next level, leading to discovery of hitherto unknown electro-photo-mechanical coupled phenomena. The basic tools and understanding developed here can be extended to the study of other energy-related devices (batteries, fuel cells, supercapacitors) for an outsized impact. The results from the proposed seed project will serve as preliminary data for at least two sustainable-energy-related proposals being developed by PI and his colleagues for submission to external agencies.

There is growing concern regarding chemical compounds from the per- and poly-fluoroalkyl substances (PFAS) family of industrially produced materials. They offer many possibilities for human exposure, and there is increasing concern, regarding negative health effects from such exposures. The term “forever chemicals” has been applied to these materials because many in this class of compounds do not break down in the natural environment. Allowable regulatory levels for PFAS in drinking water are now in the parts per trillion range.  Because there is no easy method to break these chemicals down this has led to widespread adoption of carbon adsorption technologies to remove them from water. While this removes the PFAS from drinking water, they remain in the activated carbon, which cannot be dumped in landfills. The PFAS need to be destroyed, which has often involved incineration of the PFAS-containing carbons. Hazardous waste incinerators are unpopular and difficult to operate, and there is a desire to identify alternate destruction technologies. Recent work at Brown has identified the particular chemical species which make incineration effective, and other much older work (from the coal liquefaction field) points to the possibility of designing a completely different PFAS destruction technology. What is proposed is a laboratory demonstration of the new technology. A successful demonstration would allow follow-on proposals to any of a number of agencies all of whom are interested in the problem of PFAS destruction (e.g., EPA, DOD- through its SERDP and ESTCP programs, NSF).

Advancements in quantum information sciences rely largely on the experimental realization and control of quantum optical properties, such as single-photon emissions and superfluorescence. This necessitates the development of scalable quantum light sources in solid-state materials. While significant progress has been made in engineering these properties within confined excitonic systems, achieving highly tunable homogeneous quantum light in the telecom-wavelength range (1.3-1.6 µm) remains a formidable challenge. The PIs propose a new approach involving mixed-dimensional heterostructures, comprising single-walled carbon nanotubes (SWNTs) on hexagonal boron nitride (hBN) and transition metal dichalcogenides (TMDCs), to realize homogeneous quantum light sources in the telecom-wavelength range. The combination of expertise in SWNT synthesis and high-resolution microscopies in the Kuehne Lab, and the 2D quantum device fabrications and cryogenic spectroscopy/microscopy in the Bai Lab is coherent and will uniquely enable the implementation of this project. Engineering high-quality quantum light sources is a critical task in the ascending field of quantum information science; this collaborative effort will establish the groundwork for designing mixed-dimensional heterostructures for programmable quantum light sources, and will strengthen Brown’s position in quantum optical research. Importantly, the outcomes hold promise for the development of on-chip nanoscale quantum light sources with tunable, high homogeneity in telecom-wavelength emissions, garnering significant interest from various funding programs, including NSF-DMREF, NSF-EFRI, and MRSEC IRG topics.

The goal of this project is to demonstrate feasibility for a long-circulating treatment targeting bacterial toxins that contribute to the debilitating effects of bloodstream infection (BSI). Technologies developed in the participating investigators’ laboratories will be combined as a novel solution to the problem. Dr. Shukla brings expertise in creating nanoparticle formulations that are responsive to bacterial virulence factors, such as hemolysins. Lipid vesicle nanoparticle formulations developed by Dr. Shukla will be combined with a technology developed by Drs. Darling and Mathiowitz, hyper-compliant microparticles (HCMPs), that hold great promise as long-circulating vascular carriers. HCMPs are spherical hydrogel microparticles sized similarly to white blood cells but with an extremely low elastic modulus that allows them to squeeze through small constrictions in the vasculature. The primary goals of the proposed project are to 1) develop a hemolysin-sorbent HCMP using red blood cell (RBC) membrane-derived nanoparticle vesicles for reducing RBC morbidity associated with BSIs and 2) assess HCMP persistence, biodistribution, and ultimate fate in an in vivo model. A combination of in vitro and in vivo experiments will be completed to achieve these goals. The anticipated findings will lay the groundwork for a larger project and external proposal to demonstrate the therapeutic effectiveness of continuously circulating HCMPs that contain hemolysin-sorbent nanoparticles for ameliorating the negative impact of BSI.

Calcium entry that results from neuronal activity is an essential second messenger implicated in critical processes including synaptic activity and intrinsic neuronal firing; processes that ultimately impact circuit function and behavior. There are only a handful of tools to accurately monitor calcium levels at high spatial resolution, but no tools exist that use activity-driven calcium entry to provide feedback control to downstream elements. Furthermore, current calcium indicators use damaging wavelengths that cause tissue overheating. Here, we propose to expand the capabilities of BioLuminescent OptoGenetics (BL-OG) to measure intracellular calcium levels but also manipulate circuit activity. In this pilot project, we propose to optimize LumiPoreIns (LMPs) where a voltage-gated calcium channel (CaV) is tethered to a calcium-sensitive luciferase. CaVs are naturally targeted to the terminal and open during neuronal activity. This will trigger bioluminescence only when cells are being activated. We expect to use this bioluminescence triggered by calcium to activate optogenetics elements localized on the same cell or postsynaptically to either stimulate or suppress neuronal activity. We predict that these new tools can have multiple applications: a) By measuring the calcium-sensitive bioluminescence, we will be able to precisely image cells and synapses that are activated when neurons are exposed to natural stimuli; and b) our optical design allows for activity-dependent real time feedback at the cell and synapse-specific level. This re-wiring of synapses has the potential to be utilized to treat neurological disorders where there is altered neuronal activity including epilepsy, addiction, and pain. 

How children learn language is a major puzzle for cognitive science. A core piece of this puzzle is vocabulary acquisition. How do children connect words, especially nouns, to real-world objects amid many possible referents? In this project we develop a project that explores how children may exploit not just the words, but the way the words are said, to learn what they refer to. Prosody, involving variations in pitch, duration, and loudness, can act as a signal that guides interpretation. For instance, the sentence “I like broccoli” can have different meanings based on whether “I” “like” or “broccoli” bears prosodic emphasis, by indicating which word contrasts with salient alternative meanings. Our initial findings from a study manipulating prosody reveals that children's interpretation of novel nouns depends on such prosodic cues. We plan to further explore this possibility with three main objectives: (1) Investigating infants use of prosody in learning word meanings, (2) examining the ecological validity of prosodic cues in caregiver-child dyads, and (3) conducting a systematic review and prosodic analysis of prior word learning studies. This comprehensive approach seeks to establish the degree to which prosody shapes word learning, potentially deepening our understanding of how children approach language learning.

Understanding the neural mechanisms responsible for the perceptual and cognitive capacities of higher mammals, especially primates, is essential for better understanding how normal, and abnormal, brains develop and function in the real world.  The aim of this proposal is to begin to understand how large populations of single neurons in the brain adapt to efficiently process objects of the visual world. Our working hypothesis is that in the normal adult brain of both human and non-human primates, cells in higher visual areas remain plastic and modifiable with experience.  Specifically, evidence shows that individual neurons in the inferior temporal lobes (IT) of the monkey have physiological properties that remain modifiable into adulthood. Adult primates can clearly learn to recognize visual objects, but the neural correlates of this have only been indirectly traced back to the activity pattern of single neurons.  Recent advances in recording technologies make it possible to record from hundreds of neurons from target regions, potentially transforming our understanding of how circuits in the brain operate in real time to control behavior.  The goal of this project is to obtain preliminary data using these probes.

Strong individual differences in neural sensitivity to normal hormone changes can drive lability in a wide range of emotional, interpersonal, and behavioral symptoms (hormone sensitivity); however, neural mechanisms underlying these effects are not well understood. Based on evidence across studies of menstrual-related mood disorders, our team has proposed a Dimensional Affective Hormone Sensitivity framework (DASH) in which sensitivity to one or more types of hormone changes produces or exacerbates distinct sets of psychiatric symptoms. The proposed study is a pilot test of an innovative, scientifically rigorous approach to modeling neural underpinnings of DASH with resting state and task-based fMRI. Study design capitalizes on the infrastructure and sample of PI Peters’s ongoing study examining links between specific steroid hormone changes, proposed behavioral mechanisms, and symptom flux. A subsample (N=5) with demonstrated hormone sensitivity and data for personalized estimates of menstrual cycle phases will undergo scans at four time points across a cycle, in counterbalanced order, with urine hormone testing on scan days. Aim 1: Evaluate the feasibility of using 4 resting state scans to develop idiographic models of cyclic hormone shifts and changes in the functional connectivity of default, frontoparietal, reward, and salience networks. Aim 2: Evaluate a task battery for sensitivity to cycle-based within-person differences in neural activation, using paired contrasts to minimize participant burden while testing multiple tasks per proposed mechanism. We will develop a subsequent fully-powered proposal applying these methods to differentiate between specific patterns of menstrual cycle exacerbation and disseminate methods for use in the broader field.

We are on the cusp of a genomics revolution to usher in an era of precision wildlife parasitology—but achieving it requires reforming long-standing traditions in the field. Biologists and health practitioners need to monitor wildlife to ensure effective conservation and identify emerging infectious diseases that may threaten humans and livestock. But we may often misunderstand host-parasite interactions because we rely on overly simplistic methods to study parasite diversity in nature. Fortunately, emerging molecular and bioinformatic techniques can help overcome traditional limitations. We plan to establish genomic workflows to more precisely characterize the diversity and distribution of gastrointestinal parasites that infect wildlife in tropical hotspots. We will accomplish this by constructing and utilizing one of the largest expert-verified databases of helminth DNA in the world. This database will bridge the gap between today’s ‘gold-standard’ practice of using microscopes to painstakingly identify parasites in the field and tomorrow’s need for ‘field-ready’ methods that provide more cost-effective, accurate, and timely parasite identifications—especially for the practitioners who need these data at the right times and places to take action. We will initially use these emerging tools to map hard-to-identify parasites onto wildlife hosts in tropical forests—sloths, monkeys, and tapirs among others—in ways that are more robust than standard techniques could provide. This exciting venture features interdisciplinary collaboration among veterinarians, parasitologists, molecular biologists, and ecologists. It will provide world-class opportunities for students and researchers at Brown to engage with non-profit organizations that focus on wildlife conservation, health, and human livelihoods.

The human polyomavirus JC (JCPyV) infects 50-80% of people worldwide. Initial exposure typically occurs during childhood and becomes a lifelong, persistent infection of peripheral organs, including the kidney. Under immunosuppression, such as when a patient has AIDS or is treated with immunotherapies for multiple sclerosis or cancer, JCPyV can migrate to the central nervous system (CNS) and cause the often-fatal demyelinating disease, progressive multifocal leukoencephalopathy (PML). A critical gap in our understanding of JCPyV pathogenesis is that it is not known how the virus overcomes the barriers that restrict the access of pathogens to the CNS, including the blood-CSF barrier formed by the choroid plexus (BCSFB) and by the endothelial cells of the blood brain barrier (BBB). Recently, we discovered that JCPyV can productively infect choroid plexus epithelial cells, leading us to hypothesize that JCPyV enters the CNS via the BCSFB. Our preliminary data shows that virus infection of choroid plexus epithelial cells triggers the downregulation of tight junction proteins and the upregulation of inflammatory molecules, both of which are associated with barrier disruption and neuroinvasion. In addition, it is unknown if JCPyV can invade the CNS through the BBB, despite clinical evidence that PML lesions often form near the brain vasculature. Here, we propose to analyze how JCPyV disrupts barriers and crosses into the CNS. This work investigating how the virus traffics from the periphery to the brain to cause PML is critical for the discovery and design of therapies to prevent this fatal disease.

Alternative splicing (AS) is a highly regulated mechanism that increases transcriptomic and proteomic diversity. AS occurs co-transcriptionally in the context of a dynamic chromatin environment that implicates changes in histone modifications. Genes linked to human neurodevelopmental processes are highly co-transcriptionally spliced in the human fetal frontal cortex. Dysregulation of AS has been associated with autism spectrum disorders (ASD). Chromatin regulators are overrepresented among high-risk confidence genes in ASD. However, how chromatin regulators modulate AS in relation to ASD pathogenesis is a gap in knowledge. We propose to study SETD2 which encodes a histone methyltransferase and is a major ASD genetic risk factor. SETD2 trimethylates lysine 36 on histone H3 (H3K36me3) regulating transcription and AS. However, whether SETD2 coordinates both transcription and AS in pathways relevant to ASD pathogenesis is unknown. We will use human neurons with pathogenic variants in SETD2 to: (1) Define the molecular mechanisms regulated by SETD2 by focusing on genomewide scale changes H3K36 methylation, as well as transcriptomic and AS alterations; and (2) Determine how the interplay between MRG15 and SETD2 regulates alternative splicing.  MRG15 is a chromodomain-containing protein that binds to H3K36me3, and acts as an “intermediary” between H3K36me3 and the AS machinery. We will define the interaction of MRG15 with splicing machinery and will determine changes in MRG15 genome-wide occupancy using epigenetic approaches. This work will be impactful to the study of ASD as the intersection between chromatin regulatory mechanisms and AS has been overlooked with respect to ASD pathogenesis.

Resident Memory CD8 T cells (TRM) in the female reproductive tract (FRT) have a proven protective role against viral infections. As such positioning of CD8 TRM of high quantity and quality that are durably maintained is a key goal to achieve protective antiviral immunity in the FRT. Detailed understanding of molecular cues that guide FRT TRM differentiation is essential to attain this objective. Cells in the local environment i.e., reproductive mucosa is thought to be a big source of signals that shape CD8 TRM differentiation. Rodent models have long been used to uncover these molecular signals and local interactions. However, the complex nature of the in vivo vaginal microenvironment along with technical issues associated with inefficient FRT TRM isolation process have limited execution of high throughput studies focused on identifying these cellular communications. We have established a first of its’ kind in vitro three-dimensional vaginal epithelial organoid system (VEO) that accurately captures the features of in vivo multilayered stratified vaginal epithelium. By culturing these VEOs with CD8 T cells, we were able to induce CD8 TRM differentiation and the resulting TRM phenotypically and transcriptionally resembled antiviral TRM generated in mouse. Here we propose to leverage this VEO-CD8 coculture model to rapidly uncover fate-specifying transcription factors that govern TRM differentiation. The proposed study will establish a robust reductionist alternative to the in vivo mouse models currently in use and will provide novel mechanistic insights into epithelial-CD8 T cell interaction in the vaginal mucosa.

Phthalic acid esters (phthalates) are a class of male reproductive toxicants used in the manufacture of certain plastics. Nearly all humans are exposed to small amounts of various phthalates, and at least ten phthalates are known male reproductive toxicants. Four phthalates are listed as priority substances by the Agency for Toxic Substances and Disease Control, and it has been proposed that phthalate risk should be assessed cumulatively (as a class), rather than for each individual chemical separately. Although phthalates are antiandrogenic, phthalate effects on germ cells are not mediated by androgen signaling, and there is reason to believe that altered germ cell development is directly linked to the most serious human health effects of early-life phthalate exposure, reduced fertility and increased risk of testicular cancer in adulthood. Here we will test whether a nine-phthalate mixture has cumulative (additive) effects on germ cell development. Timed pregnant rats will be exposed to a nine-phthalate mixture to generate dose-response data for multinucleated germ cells, a well-characterized histological biomarker of phthalate toxicity. We will also sequence fetal testis RNA to test the hypothesis that transcriptional changes are a more sensitive endpoint than histology and could be used for risk assessment.

Vitamin A metabolite Retinoic Acid (RA) is key in regulating immune homeostasis and regeneration of the epithelial lining in the gut. Vitamin A is acquired exclusively from the diet and its conversion into RA, its active form was thus far thought to be performed exclusively by mammalian intrinsic vitamin A metabolic machinery. In a landmark recent study, we showed that bacteria residing in the murine gut can metabolize dietary Vitamin A into RA quite effectively. Crohn's disease is one of the two main types of inflammatory bowel disease (IBD), characterized by chronic inflammation of the gastrointestinal tract. Many studies have shown that individuals with Crohn's disease often exhibit alterations in the composition and diversity of their gut microbiome, a condition called dysbiosis. The vitamin A metabolic potential of the human gut microbiome has not been established so far. Importantly, whether vitamin A metabolism by the gut bacteria is altered and causative of disease pathogenesis is not known. In the current proposal, we want to determine if Vitamin A metabolism is a feature of a healthy human microbiome and if Vitamin A metabolic potential of gut microbiome can be linked to disease pathogenesis. To achieve this goal, we partnered with Prof. Jason Shapiro, who focuses on understanding IBD's natural history and immuno-microbial pathogenesis using patient-derived samples. Dr. Shapiro’s deep expertise in performing meaningful translational studies detailing microbiome and host-associated markers in IBD patients synergizes perfectly with our expertise in dissecting mechanistic underpinnings of host-microbiome interactions.

What can we learn from the pandemics of the past to inform our responses to the pandemics of future? This is the central question to be answered by the pilot project proposed in this application for research seed funding from the Office of the Vice President for Research. This historical epidemiological project aims to delve into the Rhode Island State Archives to, for the first time, leverage advances in artificial intelligence for handwriting recognition to transcribe and analyze scanned images of vital statistics records of deaths recorded before and during the Great Influenza Pandemic (1916–1920). By analyzing these historical records, we aim to explore temporal trends in pandemic diseases (e.g., cholera, influenza) and endemic diseases (e.g., tuberculosis, malaria); to investigate geographic patterns within Rhode Island’s cities and towns; and to examine differences across demographic subgroups. This project will provide valuable insights of the historical burden of infectious diseases, shedding light on disease dynamics that can inform contemporary public health strategies, assist in disease modeling, and help contextualize the current battle against infectious diseases. By examining historical vital statistics records, this project bridges the gap between past and present, enriching our understanding of epidemiological trends and contributing to the broader goal of the control of infectious diseases. Further, this work will set the foundation for future funding applications using archival vital statistics, census, and medical records to build a multigenerational cohort that allows us to understand the impacts of infectious diseases on the health and well-being of generations of Rhode Islanders.

This study will assess differences in infant oral and gut microbiota by exposure to tobacco smoke and breastfeeding. This innovative study will expand the outcomes available for interventions combining breastfeeding and tobacco smoke avoidance, which will greatly improve the likelihood of successful research in this area. Addressing breastfeeding and tobacco smoke avoidance simultaneously is hypothesized to significantly improve the success of both breastfeeding and tobacco smoke avoidance behaviors with synergistic effects on infant health outcomes. Because resultant health outcomes occur much later, we are exploring earlier options to measure in a five-year R01. Infant gut and oral microbiota will be measured as proximal indicators of health risk and a potential mechanistic pathway between breastfeeding and tobacco smoke exposures in infancy and later health risks. Infant/mother dyads will be recruited late in pregnancy (>34 weeks gestation) from the Women and Infants Hospital clinic. Breastfeeding will be self-reported during the first week postpartum. Infant saliva and fecal samples will be collected during delivery admission and one week postpartum at home. Salivary cotinine will be analyzed as an objective measure of tobacco smoke exposure. Infant microbiota will be assessed by sequencing the V3–-V4 region of the 16S rRNA gene from the extracted DNA of saliva and fecal samples at both time points. This research builds on Dr. Risica’s prior successful work showing lower salivary cotinine in infants of mothers exposed to a perinatal newsletter/ tailored video intervention and Dr. Jamieson’s prior work exploring microbiota indicators of cancer. We anticipate submitting applications for R01 funding using this method as an objective outcome of behavioral interventions.

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.

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.

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. 

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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. 

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.

The interaction of matter with high-intensity laser radiation can lead to the absorption of multiple photons. For ultrashort laser pulses, the sudden deposition of large amounts of energy creates non-equilibrium states that rapidly evolve in time. This project explores the outcome of the interaction of intense, femtosecond duration laser pulses with the surface of liquid water. In analogy to the well-known process of Matrix-Assisted Laser Desorption/Ionization, we anticipate that water can be ejected from the bulk and form a plume that carries with it any molecules and ions that were dissolved in the liquid. The absorption depth of water for high intensity pulses is very small, on the order of one micrometer, so that only a thin surface layer of water is ejected. In this project, we use non-equilibrium molecular dynamics simulations to simulate the laser ablation of analyte molecules suspended in a liquid water bath. Both coarse-grained models using the CHARMM molecular dynamics solver and fully atomistic simulations will be performed to probe the underlying fundamental physical processes driving the desorption-ionization process and to characterize the ejected plume composition. This project has important applications for mass spectrometry, which is a frequently used analytical method in research labs and in the field. Advances could lead to smaller and more compact instruments, as well as tools with unique capabilities.This research will advance Brown's position in the field through high-impact publications and by generating preliminary data that will lead to external funding to support collaborations with experimentalists from the Chemistry Department.

Our understanding of the universe has been revolutionized by the detections of exoplanet worlds beyond our Solar System. Specifically, these detections have informed us about the diversity and quantity of planetary systems in existence, how planets evolve, and where extraterrestrial life may exist beyond Earth. Yet these exoplanet worlds are sufficiently far away from the Earth that only minimal information on these worlds is available (e.g., mass, density, atmospheric composition). For this project, we will demonstrate that the expertise within DEEPS of modeling the linked tectonic, volcanic, and atmospheric evolution of planetary bodies coupled with the expertise of Physics in exoplanet/stellar observations can be used to reliably infer surface properties of exoplanets and identify environments capable of sustaining life. We will use the preliminary results of this project to apply to available external funding sources throughout NASA and NSF.

We propose to adapt a newly designed fiber-optic sensor to dramatically improve the resolution of stress measurement in our high-pressure deformation apparatus at high temperatures. Pilot data acquired at ambient temperature demonstrate the efficacy of the approach; here we request funds to test a modified design for experiments at pressures and temperatures where earthquakes occur in plate boundary subduction zones. Subduction zones host Earth’s largest and most damaging earthquakes and tsunamis. While characterization of earthquakes and slip behavior along subduction zones has advanced rapidly, our understanding of the underlying processes that control mechanics lags behind. The roles of pressure and temperature are central to this problem. Currently, the stress resolution in the apparatuses capable of reaching these conditions is not high enough to resolve the transient behavior that is key to understanding the relevant processes. Thus, models of these processes rely on data acquired at much lower pressure, where in situ devices can be incorporated in the experimental design. With our new fiber-optic cell, we have demonstrated the ability to improve stress resolution by approximately a factor of 30 (at ambient temperature) relative to other apparatuses capable of deforming samples at relevant pressures. With successful pilot data demonstrating the application of the fiber-optic sensor at high pressure temperature conditions, we will be poised to write competitive proposals to the NSF Geophysics panel and a new NSF initiative to study earthquake processes in subduction zones, and leverage continued support for our NSF funded rock deformation facility.

Proteins containing [Fe-S] clusters carry out multiple crucial biological functions, including gene regulation. This proposal addresses redox sensing by [Fe-S] clusters via a synthetic modeling approach. By studying the geometric and electronic structures, reactivity, and bonding properties of discrete biomimetic model complexes, we seek to understand strategies used in [Fe-S] regulatory proteins to battle against oxidative and nitrosative stress at the molecular level. Specifically, the goal of this Seed proposal is to understand the mechanisms by which a pH and redox sensor, mitoNEET, activates its function of [Fe-S] transfer in response to oxidative stress. The human mitoNEET protein has a unique asymmetric [2Fe-2S] cluster ligated by three cysteines and one histidine. MitoNEET transfers its own [2Fe-2S] cofactors to its partner apo-proteins when the [2Fe-2S] center is oxidized (e.g., under oxidative stress) and the His ligand is protonated. However, it is not well understood what causes this redox-dependent cluster transfer upon protonation and how the [Fe-S] core is transferred without complete disassembly. In our preliminary studies, we developed a novel synthetic method to prepare site-differentiated [2Fe-2S] clusters bearing a neutral N-donor ligand as a model system for the unstable mitoNEET intermediate en route to cluster transfer. Our proposed studies include the elucidation of the electronic structures of mitoNEET models to understand how the presence of a neutral N-donor ligand influences the neighboring Fe-S(sulfide) and Fe-S(thiolate) bonds. We will also examine the feasibility of [Fe-S] transfer from mitoNEET analogs to another chelate without disassembly of the [Fe-S] core.

This proposal has two main focuses: (i) develop the ability to directly probe and characterize spin excitations in 2D material structures using resistively detected microwave resonance techniques; (ii) develop necessary experimental schemes to couple microwave to 2D material-based quantum-bit (qubit) and realize fundamental qubit control. Observation of microwave resonance in 2D material structures has remained elusive since the discovery of graphene almost 2 decades ago. Recently, we have demonstrated for the first time that microwave resonance in 2D material structure can be resistively detected. This experimental breakthrough is achieved by introducing spin-orbit coupling to a flat energy band of graphene moiré structures. The ability to coupling microwave radiation to the spin structure of 2D material will establish a powerful addition to the toolbox of condensed matter research, which will be widely adopted by research groups worldwide. At the same time, this technique could enable experimental control on quantum-bit based on 2D material structures, which is the essential ingredient for various schemes of quantum computation. The support of the Seed award will allow us to achieve three main outcomes in a reasonable time frame: (1) we will build a microwave setup in my research lab at Brown University; (2) we will further develop the microwave resonance technique by defining the parameter range for optimal operation, which will establish resistively detected microwave resonance a powerful tool for condensed matter research; (3) we will demonstrate coupling between microwave and electrons in the quantum dot device geometry and perform basic qubit controls.

We will use quantum computers to find the statistics of classical nonlinear dynamical systems far more efficiently than is possible with classical computers. Dynamical systems of interest range from those describing chemical reactions to climate models. We will use high quality trapped-ion based quantum computers developed by IonQ, Inc. (we have received time on their machines through the IonQ research credit program). To take full advantage of this resource we are requesting seed funding to support a PhD student based in the Departments of Chemistry or Physics to work on implementing quantum linear algebra algorithms on the IonQ computer to complete the project. We will then be in a strong position to apply for external funding, helping to fulfill Brown’s ambition to develop strengths in quantum information science.

Metachronal swimming is a propulsive gait allowing small aquatic organisms of O(10) mm to perform up to 1000-meter-long vertical migrations in the ocean. By sequentially beating appendage pairs and modulating the forces on their body while swimming, marine crustaceans (e.g., krill) can effectively sustain long-distance migrations. However, the mechanism of metachronal swimming is poorly understood due to the small size of the organism and the lack of force and flow field measurements. In this project we will combine standard experimental techniques in fluid mechanics and unique robotic models to answer fundamental scientific questions regarding thrust generation and flow-structure interactions. Using our unique metachronal robotic model, we reproduce the swimming kinematics of Antarctic krill, an abundant animal species of Earth. We will combine flow visualization with force measurements to provide a quantitative evaluation of the links between swimming kinematics, force production, and vortex dynamics during forward swimming. Our results will lay the foundation for the development of a new generation of underwater robotic platforms that can effectively perform essential underwater activities, including exploration, targeted sensing, and filtering of micro-particles.

One of the challenging aspects of engineering a wireless network at very high frequencies is to determine how to maintain a high-quality link even when the receiver is in motion. In existing 4G wireless systems, which operate at lower frequencies below 6 GHz, this problem is addressed by using quasi-omnidirectional broadcasts. If the signal is broadcast in all directions, then a receiver is always within the broadcast sector of the base station or tower, and can move freely without worrying about losing the connection. However, at higher frequencies, particularly those above 100 GHz that are under increasingly intense investigation for use in future (beyond 5G) systems, this problem is much more challenging. At these high frequencies, connections will need to rely not on omnidirectional broadcasts, but instead on very directional pencil-like beams. To maintain a link even when the receiver is mobile, this beam must be dynamically steered so that it continuously points in the correct direction. To date, no realistic solution to this challenge has been identified; as a result, beam steering is now a primary concern in the design of systems that will operate in this frequency range. In the proposed research program, we will explore the use of a space-time-modulated metasurface, a micro-antenna array subject to a complex temporal and spatial modulation pattern, to provide this beam steering functionality. If successful, our results will establish a new paradigm for the design of terahertz wireless links.

Deepfakes can spread misinformation, defamation, and propaganda by faking videos of events, like public speaker or protests. We assume that future deepfakes will be visually indistinguishable from real video and will also fool current deepfake detection methods. As such, we posit a social verification system that instead validates the truth of an event via a set of videos captured by multiple different people. To confirm which, if any, videos are being faked at any point in time, we propose to embed videos within the model space of learned generative deep neural networks and enforce multi-camera constraints that factor the change in appearance across camera views. Then, we propose to check for inconsistent appearance across videos using graph analysis, where each camera is a node and where edge weights are formed from the embedding distance. Initially, we will focus on facial appearance as it is a high-value fake target; then, given future funding generated from this seed, we will expand our remit to cover human body and multiple human interaction appearance. Overall, this project combines socially responsible computing ideas with new techniques in multi-camera appearance modeling to provide new tools to combat deepfakes.

A dream technology would capture CO2 directly from the air and use it as a feedstock to produce renewable carbon-based fuels and chemicals, rather than relying on fossil fuels. Nearly all approaches to date have separated CO2 capture and CO2 conversion into two distinct steps, but the compounding inefficiencies make the process impractical. This proposal targets a key step in the CO2 capture/conversion processes by studying catalytic approaches to carbonate reduction. CO2 can be easily captured by an alkaline solution and by converting CO2 to a carbonate, but this carbonate is difficult to reduce. In this project, we will first react (saturate) atmospheric CO2 in an alcoholic alkaline solution to produce an alkylcarbonate, and will then reduce this carbonate via either electrochemical or chemical reduction method. Aided by computational design, we will prepare and study Cu-based nanoparticle catalysts to reduce the carbonate to an active form of carbon. Our goal is to demonstrate a scientifically viable catalytic approach to bridge CO2 capture and conversion. The research will provide promising solutions to climate change and sustainability issues associated with CO2 emissions.

The breeding program that generates farm raised Atlantic Salmon is in its 17th generation. A growing awareness of the environmental impact of aquaculture has driven regulation reducing the use of outdoor pens. Here, we propose the application of state-of-the-art genomic technology to animal breeding to bring fish to market faster and reduce the use of outdoor pens. A successful breed/strain contains naturally occurring genetic variations that increase or decrease the levels of genes that positively influence growth, resistance to disease/cold, and physio-metabolic qualities such as adiposity. While many genes influence salmon commercial appeal, it is clear that increased growth hormone (GH) production is desirable as it reduces growth time. GH, along with antifreeze proteins (AFP) has been the target of all transgenic aquaculture lines developed for research purposes in the past 30 years. Here, we propose technology that will screen every possible variation in the salmon growth hormone promoter using a high throughput massively parallel reporter assay. Briefly, this technique will determine the effect of every possible variant that could occur naturally and measure how it a) affects growth hormone level and b) retains proper growth hormone expression (i.e. remains expressed only in the pituitary gland). This proposal represents the first proof of principle application of a massively parallel reporter system in a model organism (zebrafish). Variants that increase GH in the reporter system and transgene will be tested in a “salmonized’ zebrafish.

The cell utilizes multiple controls to ensure that each origin of replication (ORI) is activated only once per cell cycle. When these controls are overridden and an origin fires more than once, local DNA amplification results. DNA amplification is a hallmark of cancer, but the mechanism of the initiating events that drive re-replication is unknown and cannot be studied in cultured cancer cells. Instead, we are using the fly Sciara that is one of only two known examples where locus-specific intrachromosomal DNA re-replication results in DNA amplification at 18 “DNA puffs” in larval salivary gland polytene chromosomes as a normal developmental event. We have focused on DNA puff II/9A, the most highly amplified of the DNA puffs. We have mapped the II/9A ORI of re-replication, a DNase hypersensitive site (DHS) 600 bp upstream and bent DNA between the DHS and the ORI. Injection of the steroid hormone ecdysone induces premature DNA amplification. Our ChIP and CUT&RUN experiments revealed that the ecdysone receptor (EcR) binds to the DHS that we hypothesize loops back to contact the ORI since EcR co-immunoprecipitates the origin recognition complex that is part of the pre-replication complex bound to the ORI. We propose to develop a new method using CRISPR for site-directed mutagenesis for insertion or deletion of large stretches of DNA to test if deletion of the DHS abrogates DNA amplification. The results will be of significance to the fields of DNA replication, cancer, and genomic engineering (“editing”), underscoring Brown’s support of conceptual and technical advances.

In order to produce a functioning nervous system, neurons must form precise connections with each other during embryonic development. The guidance of growing axons to their correct targets is central to sculpting neuronal connectivity, and understanding this process is critical, as neuronal miswiring can cause neural circuit dysfunction and disease. Our project investigates if molecular cues instruct axon pathfinding by triggering changes in the axonal membrane potential. We propose to employ and improve our cutting-edge, genetically encoded voltage sensors to monitor the membrane potential of axons in response to various attractive and repulsive guidance cues, with the goal of identifying patterns of membrane de- or hyperpolarization that dictate the axonal response to attractants versus repellants. This will lay the foundation for a long-term plan to investigate the causal relationship between guidance cues, axonal membrane potential, and axon steering. Our work will uncover fundamental mechanisms of axon guidance and neural circuit assembly, which is essential for understanding disorders of brain wiring and developing therapeutic approaches for the restoration of damaged neuronal connections after physical injury or onset of neurodegenerative disease.

The U.S. is in the midst of an opioid epidemic and overdose crisis, which has only been exacerbated by the COVID-19 pandemic. It is imperative that the health community have access to the most effective treatments to help solve this epidemic. However, effective treatment development requires a better understanding of the neurobiology of opioid use and dependency. The lasting physiological effects of opiates on reward memory circuits contribute to cravings for the drug and change the brain’s response to other drugs of abuse. Opiate drugs bind to opioid receptors (ORs) in the brain, hijacking a complex endogenous neuromodulatory system. In mammals, µ opioid receptors (µORs) are the key molecular targets for the biological effects of clinically useful and abused opioids. The sheer number and heterogeneity of neurons within reward circuits, combined with their elaborate connectivity, has prevented a deeper understanding of the identity of µOR expressing circuits. A small but sophisticated brain and impressive array of neurogenetic tools for in vivo analysis have proven the fruit fly, Drosophila melanogaster, to be an ideal model for discovery of novel mechanisms underlying the effects of drugs of abuse on the brain. Here we propose to establish Drosophila as an effective model to understand the neural and molecular mechanisms underlying the motivation to seek the high-potency synthetic opioid fentanyl. Our goal is to use a functional neurogenetic approach to identify the Drosophila µOR and map the neural circuits through which this receptor is eliciting fentanyl-induced behavioral responses.

SARS-CoV-2 infection relies on the ACE2 receptor for its cellular entry. Although cellular entry of the virus is the primary target for antiviral therapeutics, it is understudied how entry of SARS-CoV-2 is regulated. Here we show that Leucine-rich repeat-containing protein 15 (LRRC15) is a novel restriction factor for SARS-CoV-2. Using a focused CRISPR activation screening targeting all known cellular surface proteins, we identified LRRC15 as a cellular restriction factor that binds to Spike protein of SARS-CoV-2. Expression of LRRC15 in SARS-CoV-2 permissive cell lines strongly inhibits the infectivity of Spike-pseudo-typed VSV but not G-pseudo-typed VSV, indicating the restriction activity is coronavirus-specific. The binding between Spike and LRRC15 is confirmed by a cell-free binding assay. In this proposal, we will examine the physiological role of LRRC15 in restricting SARS-CoV-2 infection with two specific aims. Aim 1, we will define the specificity of the restriction activity of LRRC15 across human coronaviruses including SARS-CoV-1, MERS, and seasonal coronaviruses. Aim 2, we will test whether LRRC15 is associated with severity of disease progress, robustness of viral replication, and asymptomatic/symptomatic disease outcome in patients using publicly available datasets. This study will provide one of the first human cellular restriction factors regulating SARS-CoV-2 infection and shed an insight into novel design for therapeutics.

Amyotrophic Lateral Sclerosis (ALS) is an adult-onset neurodegenerative disease that causes paralysis and death within 5 years of diagnosis. Although the disease has been clinically recognized for over 140 years, effective therapies for ALS have yet to be developed. Riluzole and Radicava (Edaravone), the only therapies approved for ALS, are minimally effective, only extending life by several months. A hallmark of ALS is early and progressive destruction of the neuromuscular junction (NMJ), the peripheral synapse that controls all skeletal muscles and thus voluntary movements. Development of treatments that target the NMJ have been hampered by the paucity of information about molecular mechanisms critical for NMJ maintenance and repair. To address this gap, our lab has focused on the molecular composition of synaptic glial cells of the NMJ, which have been largely overlooked. We have discovered that these cells express three purinergic receptors with well-characterized roles in synaptic maintenance in the central nervous system. In this work, we will test the hypothesis that modulating the activity of these purinergic receptors, using FDA-approved pharmacological agents, will mitigate NMJ degeneration in a mouse model of ALS. The preclinical data arising from this work may set the stage to target purinergic receptors to treat patients suffering with ALS.

Prions are a type of protein domain that can trigger normal proteins to fold abnormally. Human proteins with domains that resemble yeast prions form protein aggregates that cause cell death in neurodegenerative diseases. Yet, these same domains are able to form dynamic liquid-like droplets that contribute to the formation of membraneless organelles including numerous cytoplasmic and nuclear compartments. We recently learned that Bindin from sperm of a sea urchin has two prion-like domains, is secreted, and is essential for fertilization. Extracellular prions are very unusual (and no extracellular eukaryotic prion-like proteins or prion-like phase separated assemblies have been described in detail). These prion-like domains have highly variable sequences between species, thought to be species-specific recognition elements. We will dissect the prion-like domains and test their role in sperm-egg interaction and species specificity by in vitro egg interaction. Three features make this work of high impact: 1) Is the prion-like domain essential for its function? We currently know only that the Bindin product is essential. 2) Does the prion-like domain confer species-specific sperm-egg recognition? Production of the prion-like domain and modifications thereof will be used to test egg interactions species specifically. 3) Does the prion-like domain self-assemble into extracellular liquids, gels, or aggregates – the spectrum of states seen for intracellular prion-like domains? This preliminary work will have high impact in several fields of biomedical research and clinical application, breaking new ground in the molecular mechanism of critical steps in fertilization and describing the unexplored atomic details of this extracellular assembly.

We aim to develop a revolutionary quantum magnetic gradiometer designed to non-invasively register femtoTesla (fT) scale magnetic fields from the human brain and examine its operating characteristics during simple voluntary movements and visual stimulation. The sensor, with its miniaturized size, will substantially exceed the spatial resolution of existing systems, operate at room temperature, will not require expensive magnetic shielding, can be used untethered, thus, in the field, and the expected system will have a far lower initial purchase price and lower maintenance costs than available magnetoencephalographic (MEG) systems. These features should expand the utility, accuracy, and accessibility of magnetic field recording technology for human neuroscience applications to advance our understanding of human brain function in health and disease.

The onset of COVID-19 has made the rapid and accurate detection of irregular oxygen saturation levels important in curbing the number of resulting deaths. As a result, the past year has seen significant interest in traditional photoplethysmography (PPG) technology, namely pulse oximeters, to monitor oxygen saturation levels. Moreover, there has been an increased demand for smartwatches and other wearables that can accurately carry out on-demand PPG measurements. However, several studies have reported that this optical technique overestimates the actual oxyhemoglobin saturation in patients with darker skin tones, leading to silent hypoxia and a potentially disproportionately higher number of deaths for black and brown patients, in particular. This work will focus on developing a novel PPG technique to mitigate the issue of skin tone, and other related skin-based confounding effects such as wrinkles and tattoos, using an optical polarization vector beam. Compared to other algorithms that exploit polarization to suppress skin effects and increase accuracy, our approach enables multiple polarization measurements in parallel, thereby offering increased speed.

Co-occurring PTSD and alcohol use disorder (PTSD-AUD) is common following combat and associated with more severe symptomatology, increased suicidality, and poorer response to treatment than either disorder alone. Available PTSD-AUD treatments effectively treat only a fraction of people who engage in them for adequate dose and duration, leading to growing interest in alternative medications, including psychedelics. The combined neurobiological effects of MDMA increase compassion, reduce defenses and fear of emotional injury, and enhance communication and introspection, making MDMA-AT especially useful for treating PTSD-AUD. This pilot trial will be the first to assess feasibility and acceptability of MDMA-assisted psychotherapy (MDMA-AT) in veterans with combat-related PTSD and AUD (N=20) and will result in a new interdisciplinary collaboration at Brown. Participants will be recruited via social media and clinician referrals and will complete an initial screen and baseline appointment including informed consent. Eligible participants will receive MDMA-AT, including three Experimental Sessions with MDMA administration that will be conducted under established protocols. Follow-up data will be collected at post-treatment and at one-month. This project will allow us to: 1) assemble a research team including the training of two MDMA-AT clinicians, 2) determine the feasibility of recruitment, 3) determine the acceptability of and safety of MDMA-AT, 4) provide preliminary evidence of the effects of MDMA-AT, and 5) refine study procedures in preparation for a fully powered RCT to test the effectiveness of MDMA-AT for PTSD-AUD. This collaboration will help to position Brown at the forefront of psychedelic research for common and impairing mental health problems.

Patients commonly search their symptoms and diseases online, and mobile phone apps for digital diagnosis (“Symptom Checkers”, SC) are used by >40 million US patients annually. However there is minimal evidence from real patient use in the community on accuracy of diagnosis or triage, patient safety, or usability. This research builds on collaborations between Brown Center for Biomedical Informatics, The Rhode Island Hospital (RIH) Emergency Department (ED) and Brown Medicine to research the role and potential impact of symptom checker (SC) apps used by patient seeking urgent primary care, and the performance of SCs and new algorithms for diagnosis of transient ischemic attacks (TIA) and stroke. AIM 1 will extend an evaluation of a leading SC from Ada Health, with use by 200 patients requesting urgent care appointments at Brown Medicine, including a usability questionnaire, prior to their appointment. Reviews of the symptom data and results from the App and the physician who sees the patient will allow comparison of diagnosis and triage. AIM 2 will analyze the accuracy of symptom checkers including Ada and develop new algorithms using 2 data sets of symptoms of patients presenting with TIA or stroke - high risk diseases with hard to recognize symptoms, requiring urgent treatment. Data sets include 1800 patients admitted with suspected TIA to the clinical observation unit, RIH, and 100,000 patient consults with Ada App, and possible stroke diagnosis. We will study diagnostic performance of multiple SCs and new algorithms including effects of age and gender, Quick patient recognition of stroke and prompt arrival in the ED should reduce the current high morbidity and mortality. 

The aim of this proposal is to test the hypothesis that we can prepare high school teachers to teach students about autonomous aerial robots on their own, at scale by 1) providing a project-based curriculum targeted at the high school level on an open-source low-cost autonomous robot with few infrastructure requirements; 2) providing remote professional development workshops for teachers; and 3) pairing teachers with Brown students familiar with the curriculum who will provide help and technical support. We will study the interactions between teachers and curriculum materials, tools, and Brown students who facilitate the learners' conceptual development, and what characteristics our online PD and remote support give rise to these interactions. Our work will assess each of these three interventions by assessing teacher content knowledge as well as self-efficacy. We will also assess the effectiveness with which we can engage students in both urban and suburban districts through hands-on remote learning curricula that emphasize physical hardware, in the hands of the students as well as via remote laboratories. This work has the potential to directly benefit students in Rhode Island, consistent with President Paxson's commitment to Providence public schools. Moreover this funding will provide critical preliminary work enabling us to apply for follow-on funding for larger expansions from NSF and industry resources to grow our project to a nationwide and international effort to teach students about autonomous robotics. 

As more and more analyses depend on machine learning, physicists need to understand the biases induced in their models by the training data they use. In many situations they face a tradeoff between two types of data: (1) abundant but low-resolution, synthetic, or otherwise approximate data, and (2) scarce but high-resolution, high-fidelity, or otherwise more realistic data. The ideal would be to correct the biases in the abundant data so that it is more like the scarce data in the ways that affect the predictions of the machine learning models trained on that data. If done, then scientists would have access to higher quality, abundant data. The problem is that, even though it is easy to tell that models trained on each type of data disagree in their predictions, it is hard to tell which aspects of the input are leading to that disagreement. Our proposal is to create a software framework for identifying these key causes of differences.

The interdisciplinary team proposes to test the idea that the fundamental principle of a complex brain operation is quantum processing involving nuclear spins of phosphorus as a neural qubit. This idea originates from a reputable theoretical physicist M. Fisher, UCSB. He identified the hypothetical Posner molecule as one that can protect neural qubits very long times and thereby serve as a working quantum-memory. Our novel approach involves harnessing the properties of nuclear spins to study quantum information processing (QIS) in the brain by reverse engineering specific polymers and biomolecules to provide sufficiently long coherence times required for quantum processing. This is orthogonal to the UCSB’s approach that focuses on the search of Posner molecule. The team members are highly complementary and have a well-established prior record of collaborations. Palmore will synthesize  polymer based biomaterials with appropriate nuclear spin species, while Mitrovic and Walsh will use the nuclear magnetic resonance (NMR) technique to test possible coherence propagation and test whether such bio-materials can be used as a quantum register to process information. The team has identified the appropriate synthesis and patterning of phosphates into specific isotopically labeled and DNA nanostructure. They have also designed the NMR experiment to test the quantum nature of neural signal transmission, and NMR experiments to test nuclear spin coherence. Our long-term goal is to identify essential biomaterial properties required for QIS and quantum signal transmission using nuclear spins of phosphorus. The ultimate goal is synthesis of artificial neural synapses and memory registers.

In the past few years, significant developments in high-power, massively parallel computing, made in part possible by the advancement of fast GPUs, FPGAs, and specialized processors, took artificial intelligence (AI) to a qualitatively new level, making it a valuable tool for scientific research. Some of the AI methods, such as supervised and unsupervised machine learning (ML) using deep neural networks, are now being widely deployed in large scientific experiments in particle and astroparticle physics, both for data reconstruction and for unraveling subtle signals over otherwise overwhelming backgrounds. Typical data from these large detectors, organized in a series of “events,” i.e., snapshots of the detector triggered by a certain, interesting activity, naturally allow for massive parallel processing of the data and for identifying characteristic patterns within. We propose to utilize advanced AI methods and a combination of supervised and unsupervised ML algorithms to look for unusual patterns in the data of experiments underground, on the surface of the Earth, and in the sky. More specifically, we will focus on unconventional experimental signatures of new physics in the Brown-led LUX/LZ detectors at the Sanford Underground Research Facility by exploring new methods for identifying heterogenous particle recoil signatures involving both nuclear and electron recoil components, at the CMS experiment at the Large Hadron Collider at CERN by looking for jets with unconventional structure or patterns, and in the sky using forecasting weak gravitational lensing data from the Square Kilometer Array to discern the presence of dark matter substructure using time dependent spatial correlations.

Cancer cells are known to create acidic extracellular environments through the excretion of acid byproducts due to irregular metabolic pathways. This unusually acidic extracellular tumor microenvironment compared to healthy tissues may be targeted through cancer therapies. Counteracting the pH of the tumor microenvironment in in vivo mouse models by ubiquitous bicarbonate delivery has shown promise. Currently, an effective method of locally regulating the pH of the tumor microenvironment to reduce cancer progression due to acidosis does is lacking and our research aims to fill this important need by developing a responsive hydrogel pH regulating system by demonstrating its efficacy in cancer treatment. We aim to develop a novel biocompatible pH regulating hydrogel that reduces cancer metastasis and invasion by continuously counteracting the acidosis of the extracellular space.  We will conduct in vitro experiments to test proliferation, motility, and invasion of MDA-MB-231 breast cancer cells when exposed to our novel hydrogel. Completion of our study will allow further research into targeted delivery of pH regulating hydrogels in vivo as well as new studies of subcellular cancer cell mechanisms that can be regulated through pH control.

Nanoparticles display properties that are different from bulk materials and in particular can be excellent catalysts for important chemical reactions. However, because of the size and surface inhomogeneity, the mechanisms of catalytic reactions by nanoparticles are often challenging to be deciphered. This project aims at advancing nanochemistry through the syntheses of novel ligand-protected and atom-precise gold nanoclusters with uncoordinated sites, which can serve as well-defined in situ activation centers for catalysis. While there have been major advances in the syntheses of atom-precise nanoclusters, information about the active sites of these nanoparticles in catalytic applications are still challenging to obtain because often times the ligands need to be removed to create active sites that can introduce uncontrolled structural changes. The motivation of this project is to address this challenge by synthesizing ligand-protected nanoclusters with uncoordinated atoms, that can be used as in-situ active sites. The first goal of the project is to find new ligands that allow the syntheses of gold or bimetallic gold nanocluster with precisely-defined size and structure. The second goal is to explore their catalytic properties and obtain preliminary data about hydrogenation reactions and electrocatalysis.

If current prevention and intervention strategies remain the same, one in three of us will be diagnosed with Alzheimer’s disease (AD) in our lifetime. Therefore, it is critically important to discover new, effective treatments, and the key to doing so is to fully understand how AD develops. Unfortunately, this understanding is limited by the absence of an appropriate humanized model system and the deficiency in general knowledge to guide an experimental path forward are the major reasons for this gap. To tackle such a challenge, our two research teams have combined our distinct expertise and devised original techniques based on stem cell technology and computational genomics, to study the neuron-glial communications that become disrupted in AD and aged brains. Specifically, the objective of this pilot project is to develop an integrated platform to discover the nature of direct synaptic interactions between neurons and oligodendroglia in both healthy and diseased individuals. The work proposed here represents a novel research horizon for the field, ultimately aimed at inspiring a new therapeutic logic for AD and relevant brain aging disorders. We will leverage our multidisciplinary expertise uniquely established at Brown to couple cellular reprogramming methods with modern genome scanning and editing techniques. Our preliminary data have provided the very first evidence supporting the neuron-OPC synaptic mechanism as an emerging therapeutic target for further translation. Our approaches are amenable to contemporary studies of neurodegeneration and aging beyond AD and we hope to extend our collaboration with Brown’s vibrant faculty to further synergize our discoveries.

The ability of macromolecules to undergo liquid-liquid phase separation (LLPS) is now recognized as underlying a number of key biological phenomena. Our studies have revealed that transcriptional regulation in the pathogenic fungus Candida albicans is controlled via LLPS, as multiple transcription factors can come together to form phase-separated condensates that are critical to the regulation of transcription networks in this species. This mechanism has been directly linked to the presence of prion-like domains (PrLDs) in transcription factors (TFs) that promote their propensity to undergo LLPS and thereby form transcriptional hubs. In this proposal, we seek to determine how structural features and post-translational modifications (PTMs) alter the ability of TFs to undergo LLPS. A number of recent studies have shown that LLPS processes can be exquisitely sensitive to both PTMs and transient secondary structures that can impact phase separation. This is particularly relevant to fungal transcription networks where domains of unknown structure contribute to function and PTMs may enable cells to rapidly respond to external stimuli and activate an appropriate transcriptional response. We will therefore seek to define the structures and PTMs associated with the master TFs in C. albicans networks, and also examine how these features impact LLPS and transcriptional output by these factors. These findings are expected to have broad significance to the regulation of TF networks, and will provide fundamental insights as to how these features can regulate the properties of LLPS condensates.

Schizophrenia is among the most devastating and enigmatic conditions affecting the human brain. It has a strong genetic component, and it shares neurodevelopmental components with other neuropsychiatric illnesses, such as autism. The project proposed here relates to study of 17q12 deletion syndrome, a highly-penetrant genetic mutation that confers susceptibility to both autism and schizophrenia. Using CRISPR/Cas9 genome editing and human stem cell methods, we will establish experimental models (mice and patient-derived stem cells) for 17q12 deletion syndrome. In validating our mouse model, we have identified a prominent and high-impact phenotype involving perturbation of forebrain development. Here, we will define the molecular mechanisms underlying these abnormalities in forebrain development. We will also establish a human iPSC resource with 17q12 deletion mutations. These 17q12 deletion studies will put us in a unique position to capitalize on human genetics and discover pathways critical to human forebrain development and neuropsychiatric disorders. The impact of this work will be to define new pathophysiologic mechanisms in schizophrenia (and other neuropsychiatric disorders), stemming from genetically-inspired, neurodevelopmental studies in patients and animal models. The research group involves a multi-disciplinary team that spans psychiatry, computational biology and molecular and cellular biology, and clinical and basic research, and includes two junior faculty (Moreno De Luca and Uzun) and a senior faculty (Morrow). Together, our efforts will provide important insights into the genetic underpinnings and the underlying mechanisms of 17q12 deletion syndrome as well as related developmental neuropsychiatric illness more broadly.

Pulmonary hypertension (PH) is a devastating disease marked by endothelial cell (EC) dysfunction and vascular stiffness. While EC dysfunction is at the core of PH pathobiology, the PH EC phenotype is incompletely characterized and remains controversial. Current methods to study this gap source cells from end-stage patients, non-diseased cell lines, or outside of the pulmonary vasculature. Right heart catheterization is the fundamental diagnostic procedure in PH and is repeated throughout the disease course. We have shown that ECs from the balloons of pulmonary artery catheters can be harvested, propagated ex vivo and characterized and that the behavior and function of these cells is influenced by clinical traits and PH severity. We contend that ECs in severe PH display abnormal programmed cell death triggered by cell detachment, known as anoikis resistance. We will leverage this source of pulmonary artery ECs from living patients to define patient-, time- and substrate-based factors that influence EC phenotype. We will characterize the behavior and function of cultured ECs over the course of disease with established assays. We will measure and compare the response of these ECs on a biomimetic synthetic pulmonary vessel platform with variable stiffness and topography. We will identify the gene expression signature of cultured ECs and compare across samples and against that from primary cells. Our experiments will include ECs from patients with different forms of PH, diseased controls, and biological replicates from the same patients over time. Data derived will be used to further develop the project for a Multi-PI grant.

Pulmonary fibrosis is a common side effect of thoracic radiotherapy; it limits treatment options for cancer patients and increases the risk for cancer metastasis to the lungs. This treatment modality is highly effective in killing mitotic cancer cells by damaging their DNA and inducing apoptosis. However, even low dose radiotherapy is capable of inducing cellular senescence in normal cells, and the accumulation of these senescent cells and their secretory phenotype described as key mediators of pulmonary fibrosis. Ionizing radiation also results in rapid activation and persistent expression of transforming growth factor-b (TGFb), a pleiotropic cytokine involved in extracellular matrix (ECM) remodeling. Yet, there remains a gap in our understanding of how radiation-induced senescence drives pulmonary fibrosis through TGFb-mediated ECM remodeling. Our recent study demonstrated that senescent cells deposit and crosslink ECM proteins altering the architecture and mechanics of the surrounding collagen-rich environment. Although senescent cells are relatively scarce in vivo, it is possible that their ECM modifications are transferred throughout the lung via senescence-associated exosomes (SA-EVs). Previous studies have shown SA-EVs can activate nearby fibroblasts promoting collagen matrix remodeling through TGFb. The proposed studies will investigate the role of SA-EVs in transferring TGFb-mediated ECM remodeling in the lung to promote radiation-induced fibrosis and malignancy.

Ischemic wounds occur when blood flow is reduced in a specific body area, leading to cell death and tissue damage. In diabetes, microvascular complications and unbalanced activation of the immune cells markedly compromise the repair from ischemic wounds, causing slower healing, development of chronic wounds and increased risk for infections.The overall objective of this proposal is to explore the mechanisms of wound healing in diabetes, by signaling of anti-inflammatory cytokines (CSF-1, IL4 and IL-13) via the JAK-STAT pathway, and to develop a novel treatment using preclinical models of non-healing diabetic ulcers. My preliminary data show that CSF-1, IL-4, and IL-13 regulate immune cells polarization and ischemic wound healing in monocyte cultures and non-diabetic animal models. With this proposal, we will elucidate the cytokines-driven regulation of the JAK-STAT signaling cascade in diabetes (Aim 1), we will deliver CSF-1, IL-4 and IL-13 from biomaterials to modulate the plasticity of monocytes isolated from the blood of diabetic rats and humans (Aim 2), and we will examine the healing of ischemic wounds in diabetic rats (Aim 3). This work will advance Brown’s position in the fields of immune engineering and wound healing therapy, will allow the PI to lay a solid foundation for expanding her research program in diabetes, and will be instrumental for attracting external funds. If successful, this project will identify suitable therapeutic targets for treating chronic wounds in diabetic patients, and will accelerate the translation to the clinic of novel immunomodulatory treatments for a patient population in great need.

Stroke is a leading cause of long-term disability, and outcome in regaining functionality in areas supplied by anterior circulation large vessel is directly related to timely endovascular therapy (EVT). However, not all patients benefit from rapid intervention. CT perfusion is widely recognized as the selection tool to identify patients who will most likely benefit from reperfusion based on stroke core and penumbra size estimation as well as mismatch quantification. However, it is not routinely performed at many institutions in the United States and around the world. In this proposal, we propose to develop a fully automated artificial intelligence (AI) pipeline that identifies the images/series of interest, detect emergent large vessel occlusion and predicts immediate (e.g. the Thrombolysis in Cerebral Infarction [TICI[ score) and functional (e.g., modified Rankin score [mRS[) outcomes from EVT based on pre-procedure CT angiography. We will establish an end-to-end AI platform that interfaces with the Rhode Island Hospital (RIH) Picture Archiving and Communications Systems for real-time clinical use. The ability to predict immediate outcomes of EVT will affect management because proceduralists will be able to anticipate different reperfusion based on these predictions and adjust their treatment approach accordingly, while prediction of functional outcome assists in patient selection, resulting in improved outcome. We anticipate that the proposed project will further collaboration between the Department of Computer Science and the Department of Diagnostic Imaging, which is crucial in advancing Brown University's position in research on AI, machine learning and computer vision applied to the healthcare system and medical imaging.

Smoking is the leading cause of preventable morbidity and mortality in the US, contributing to 480,000 deaths this year. Despite increasingly strong tobacco control, annual deaths are no different than 30 years ago and tobacco-related diseases continue to disproportionately burden individuals from lower socioeconomic populations. Prevention of use and cessation remain the primary goals. However, for those unwilling or unable to quit, substituting combustible tobacco smoking with electronic nicotine delivery systems (ENDS) can significantly reduce tobacco-related harms. We propose to randomize 50 socioeconomically disadvantaged smokers who are not planning to quit to three conditions: one of two ENDS conditions (4th generation nicotine salt pod e-cigarette [EC] or heat-not-burn tobacco [HNB]) or assessment only control. We will provide participants in the ENDS conditions with devices and 8 weeks of complimentary nicotine supplies and investigate the impact on cigarette use, dependence, full substitution (quitting cigarettes), and biomarkers of exposure, toxicity, disease, and inflammation. The results of this pilot project will elucidate the magnitude and clinical meaningfulness of these effects and inform the design of a fully-powered NIH R01 application comparing ENDS to gold-standard treatments. The multidisciplinary research team established by this Category 2 OVPR Research Seed Fund proposal spans the areas of clinical psychology, medicine, public health, and social epidemiology. This project will be one of the first to compare HNB to EC and investigate their harm reduction potential. Further, the study will fill a critical gap in the literature on the feasibility and acceptability of these procedures in socioeconomically disadvantaged populations.

African cities will double in population by 2050, and will require thoughtful solutions to get around. In many emerging cities, transit is private: operated by many small bus companies, some so small they only own a single bus. This system is flexible, but can be disorganized and dangerous. In recent years, many cities have invested in formal public transit to replace private transit. But mass rapid transit is costly. And it may not be necessary: new technologies like dynamic routing may make it possible to increase the efficiency of decentralized transit, without the need for costly investment. This project will develop a new data partnership to study transport in Africa’s largest city. It will use that partnership to study how informal transit systems respond when the city of Lagos, Nigeria, introduces 820 new formal, government-owned and regulated buses across 50 routes. The study will assess how the introduction of this new travel option affects riders and operators, in collaboration with the Lagos Metropolitan Area Transport Authority (LAMATA).

“Unmasking COVID-19” examines the disproportionate effects of the coronavirus pandemic on Pacific Islander communities in New Zealand and the United States. While both countries have adopted different approaches to managing the pandemic at a national level, Pacific Islanders in both nations have been diagnosed with and suffered the impact of COVID-19 in numbers disproportionate to their representation within the overall population. Thus, a closer investigation of the historical and structural factors shaping Pacific Islanders' health outcomes, the pandemic’s role in exacerbating those factors, and local level organizations’ role in mitigating the impact of these circumstances is needed. Our team will conduct interviews with leaders and members of Pacific Islander serving organizations in New Zealand and the United States that have actively sought to provide much-needed community assistance during the pandemic. These interviews will then be supplemented by interviews with physicians and local government officials. Drawing on this data we will: (1) co-author and publish a series of Op-Ed pieces in New Zealand and U.S. news outlets on COVID-19’s disproportionate impact on Pacific Islander communities; (2) develop and publish a co-authored research paper on the importance of reconciling national and community-based narratives during the coronavirus pandemic; (3) build a website using the StoryMaps platform to showcase the virus’s impact on individuals’ everyday lives and highlighting the diverse array of community-based responses to managing the pandemic’s effects; and (4) apply for external grant funding to include additional nations/overseas territories across the Pacific region.

This project makes use of the Pandemic Journaling Project (PJP) – an online journaling platform that Mason and Willen created and launched in May 2020 to chronicle and preserve first-hand experiences of the pandemic. We will examine the impact of the Covid-19 pandemic on the entwined life projects of first-generation college students and their parents. We ask: Has the Covid-19 pandemic impacted the content or trajectory of the life projects of first-generation college students and their parents, and if so, how? We will use a mixture of online journaling, semi-structured interviews, focus groups and the curation of an online photo exhibition to answer this question. Seed funds from Brown would allow Mason, Willen, Flores and Baines to build a long and lasting collaboration, would ensure the viability of the PJP platform through 2021, and would position our group well to procure extramural funds for this project. PJP currently has about 750 users and more than 6700 journal entries have already been submitted. By assisting our group in demonstrating that this platform can successfully be utilized to conduct virtual ethnographic research on a timely topic of importance during the pandemic, Brown can establish itself as a leader in virtual research methods in anthropology and education.

Queer Iranian American director Reza Abdoh’s Father was a Peculiar Man is an important work of US avant garde theatre history. Based on Fyodor Dostoyevsky’s Brothers Karamazov, the play, combined aspects of the novel with other texts that explored the relationship between patriarchy, violence and the AIDS crisis. Father was staged in New York City’s meatpacking district—near sites of queer sex commerce and celebration in 1990. Unlike Abdoh’s other works, Father was never edited into a production video because it was a highly moveable site-specific performance which was nearly impossible to “capture” in a linear format. This project attempts to creatively reconstruct this performance through a multimodal digital archive of the performance including video footage, artist testimony, an annotated production “script,” critical essays and an urban spatial representation of the play. This project has two major contributions: 1) Providing scholars with access to a performance that radically shaped this history of avant-garde performance, and queer performance 2) modeling a new way of recreating performance works that are left out of traditional archives. A seed grant will fund the work of a research assistant (who has begun work as an UTRA recipient) and team of artists involved in the production to curate and organize the content to be made into the annotated reconstruction of the performance and to provide basic technical support for this project. This award will advance Brown's reputation for innovative arts scholarship in the digital humanities.

Reducing a material to the atomic 2-dimensional limit has been shown to have profound effects on its properties. Since the successful exfoliation of graphene from bulk graphite [4], a large family of layered van der Waals materials have been thinned down to a single atomic layer, forming a new material platform covering a wide range of physical properties. The van der Waals assembly technique allows any 2D material to be re-assembled into a designer structure, which has recently led to a flurry of discoveries establishing 2D material heterostructure as a new paradigm for discovering novel quantum phenomena and advancing our understanding of quantum science. Here, we propose a new direction to study an entangled quantum phenomenon called Majorana mode, which is at the heart of topological quantum computation. The PIs plan to develop the capability of thermal transport measurement on materials that are one-atomic layer thin. Measurements of quantized thermal conductance in these materials will offer direct and unambiguous identification of Majorana modes. This effort will build on the established expertise of the PI and co-PI. Prof. Li has developed the necessary techniques of working with 2D materials and performing quantum transport measurements, Prof. Plumb is a leading expert in bulk material growth and neutron scattering, and Prof. Feldman has done pioneering research on Majorana modes in the 2D limit. The proposed effort will establish Brown University as a center for studying and engineering future 2D magnetic material and nano-scale quantum technology.

Funds are requested to purchase electronic equipment and cover travel expenses to UCLA's Basic Plasma Science Facility (BaPSF) to make a first observation of a plasma wave of topological origin using the Large Plasma Device (LAPD).  The search was inspired by my 2017 Science paper ""Topological Origin of Geophysical Waves"" that reported the surprising discovery that Kelvin and Yanai waves have a topological origin analogous to edge modes in the quantum Hall effect.  My collaborators and I have now theoretically predicted, and simulated, other waves of topological origin in a magnetized plasma. We used a realistic model of the LAPD plasma, and the Director of BaPSF (Troy Carter) has granted us time on the LAPD to conduct experiments provided that we can supply the necessary microwave amplifier to drive the waves.  If the existence of the waves is confirmed by experiment, it would represent a breakthrough in plasma physics likely leading to both publication in prestigious journals and external funding. 

One common application of data science across scientific domains is extracting signals from increasingly large data sets. Recent advances in deep learning and artificial intelligence have become a practical necessity for such applications. Given the size of the datasets and the ever growing needs for CPUs for effective training of deep learning algorithms, quantum computing is an attractive solution. Even though there are remaining challenges to make quantum computing devices widely usable, it is important to understand and explore what this new technology and applications of quantum computing algorithms could bring to our fields. We propose to use quantum simulators to perform sensitivity studies for extracting rare signals of new physics in the environment proposed for future particle colliders and free electron lasers. The proposed interdisciplinary work has important implications beyond the disciplines involved as it will develop the technology of quantum machine learning. As quantum computers become available they will allow us to meet computational challenges in many fields and solve scientific questions that are out of reach with current technologies. This seed project will complement and strengthen the core group of faculty members in Physics and Chemistry who explore quantum information science.

Measuring the intensity of 21 cm emission from neutral hydrogen gas is a novel technique that enables mapping large volumes of the universe in three dimensions.  The Tianlai Pathfinder has been carrying out a North Celestial Cap Survey (NCCS). The Tianlai Pathfinder is unique among 21 cm instruments in being able to point and integrate continuously on a limited patch of sky for extended periods.  With seed funding Brown could contribute to analyzing this rich data set and produce initial results which will strengthen subsequent proposals. One of the ultimate goals of this research is to measure baryon acoustic oscillations over cosmic time to help understand dark energy, which is currently not understood.  This research will also, for example, shed light on the mysterious fast radio bursts (FRBs), detect radio counterparts of gravitational events from sources such as merging neutron stars and lead to a better understanding of galaxy formation. The Tianlai Pathfinder will demonstrate the feasibility of using wide field of view radio interferometers to map the density of neutral hydrogen in the universe after the Epoch of Reionization (EoR).  Such radio interferometers are relatively new, and the necessary techniques are still being developed. The Tianlai Pathfinder is also unique in that it consists of two co-located interferometers utilizing different types of antennae (cylinders and dishes), which provides an important opportunity to compare the ultimate performance of these two types of telescopes as the next generation of more sensitive instruments is planned.

Obsessive-compulsive disorder (OCD) is a neuropsychiatric disorder that affects ~2% of the population over their lifetime and is associated with impairments in behavioral flexibility and compulsive, ritualistic behaviors.  Such behaviors can often be conceptualized as sequences that are stuck in a “loop” and have to be performed repeatedly and in a ritualized way, such as hand washing or lock checking. As shown by Dr. Desrochers, control over behavioral sequences is governed by an increase in activity (“ramp”) from the beginning to the end of the sequence in the frontal polar cortex (FP) of healthy adults. Sequence performance is disrupted with transcranial magnetic stimulation (TMS) to the FP. The FP is also known to show reduced recruitment in OCD during a variety of experimental paradigms. We hypothesize that patients with OCD may have a deficit in this ramping activity in the FP. Dr. Garnaat is a licensed clinical psychologist and expert in OCD who has recently been awarded a grant to study cognitive flexibility in OCD patients (and healthy age-matched controls) using fMRI and TMS, with the FP as a main target. We therefore propose to expand Dr. Desrochers’ research into a new field, research in clinical populations with OCD, in collaboration with Dr. Garnaat. The proposed project will capitalize on the patient recruitment, assessment, and experiments already scheduled with Dr. Garnaat’s funded project to add a component to scan OCD patients performing a sequential task. These studies will compliment both lines of research, and contribute to our fundamental understanding of the neural circuits underlying OCD.

Neurodegenerative diseases represent a major threat to human health. We here propose to establish the experimental protocols and analyses pipelines for the discovery of new biomarkers for neurodegenerative diseases. Specifically, we will take advantage of access to the cerebral spinal fluid (CSF) of patients with normal pressure hydrocephalus, a neurodegenerative disease characterized by progressive cognitive and motor deficits. We will use state-of-the-art proteomics, metabolomics and next generation RNA sequencing technology to identify alterations in the expression of molecular signaling pathways that correlate with clinical signs of the disease. To this end, we will develop supervised and unsupervised machine learning algorithms to extensively mine the gene and metabolite expression data obtained from patient samples. We will specifically test the hypothesis that inflammation is a causative mechanism driving neurodegeneration. Our short-term goal is to identify new CSF biomarkers for normal pressure hydrocephalus, and to establish experimental and analysis pipelines that will allow us to extend our approach to target other neurodegenerative diseases including Alzheimer’s Disease. Our interdisciplinary project is timely and highly innovative, bringing together world-class expertise in neurosurgery, molecular neurobiology, and data science. Preliminary results obtained with OVPR support will allow us to attract long-term financial support through federal grants, private foundations, and industry partnerships.

SLC13A5 deficiency is a newly diagnosed form of genetic epilepsy and developmental delay with seizures beginning within the first days of life. In these patients, homozygous mutations in the SLC13A5 gene, which encodes a plasma membrane citrate transporter result in a severe, early onset multi-focal epilepsy, in addition to cognitive and behavioral symptoms. Progress in finding treatments for this condition has been hampered by the lack of appropriate models to study the brain phenotype. We have already developed a novel model with the human SLC13A5 gene transgene inserted into a mouse with a deletion of the native murine Slc13a5. This mouse expresses only the fully human SLC13A5 in the central nervous system. Furthermore, we have created a knock-in of the human SLC13A5 with pathogenic mutations in Drosophilia. The studies proposed here are for the purpose of creating the full panel of model systems with pathogenic mutations and to obtain preliminary data needed for the submission of a multi-investigator grant to the NIH in order to address key questions: 1) what is the normal function of SLC13A5 in brain physiology 2) how do pathogenic mutations in SLC13A5 result in neural dysfunction and 3) what are the genetic modifiers of SLC13A5 which affect disease expression. This will begin to address our underlying hypothesis that epilepsy associated with SLC13A5 is related to specific neuronal metabolic requirements, which impact neuro-transmitter pools.  The identification of the metabolic and neurotransmitter changes may lead to new treatments for epilepsy and also cognitive/ behavioral symptoms associated with SLC13A5.

When deciding how much effort to invest in a given task, individuals weigh both positive outcomes that could accrue (e.g., praise) as well as negative outcomes such efforts could avoid (e.g., admonishment). However, little is known about the neural and computational mechanisms by which different incentives determine how much and how long we invest effort into cognitively demanding tasks, including whether different substrates exist for different strategies for responding to negative incentives (e.g., working harder vs. more cautiously). Moreover, while both incentives contribute to one's decision to invest effort, a person's relative sensitivity to negative versus positive incentives can significantly impact their health and wellbeing, leading to chronic stress and anxiety. This proposal aims to identify neural substrates underlying cognitive effort allocation in the face of these different incentive types, and measure how differences in sensitivity to these incentives influence a given person's motivation to invest effort in their daily tasks as well as their susceptibility to negative health outcomes. We will leverage a computational model our lab has developed to predict variability in effort investment, combining this model with measures of behavior and neural activity taken while participants perform a novel task. This work will bridge research in neuroscience, economics, psychiatry, and public health, and advance Brown’s position across those fields. Receiving an OVPR Research Seed Fund Award to carry out this foundational research will position us to apply for external funding to make further inroads into what motivates people to exert the effort necessary to achieve their goals.

Deep learning (e.g., convolutional neural networks (CNNs)) has gained a lot of attention in the past few years, especially for object identification and classification problems.   Despite their strengths, CNNs have several shortcomings, such as their opacity to understand how they make decisions, fragility for generalizing beyond overfit training examples, and inability to recover from bad decisions. These weaknesses play to the strengths of techniques in artificial intelligence (AI) based on generative probabilistic inference, techniques that are inherently explainable, general, and resilient by distribution of many hypotheses representing possible decisions. Unfortunately, probabilistic inference, in contrast to CNNs, is often computationally intractable with complexity that grows exponentially with the number of variables.  Combined discriminative-generative algorithms have been proposed as a promising avenue for robust perception by balancing computational complexity with explainability and reasoning, but still may not provide for real-time response, even after careful optimization. Instead, we propose bringing humans back into the loop to provide essential functionality to guide decisions, planning, and management of an AI-enhanced system. In particular, the models that have proven useful for understanding human agency are Causal Bayes Nets. This project seeks to explore how humans and intelligent computers can collaborate effectively by integrating technical functions (i.e., discriminative-generative decision making) with human cognitive processes.  A driving theme of this exploration will be complexity (and energy) optimization. Applying more effort and thereby computational and cognitive assistance in a hybrid fashion, and only as needed, will minimize energy consumption, improve response time, and be more likely to optimize users’ needs.

Trehalose has been found to be an effective treatment for preeclampsia, a potentially life-threatening condition affecting some pregnant women. Unfortunately, administration of trehalose can result in additional complications from undesired bacterial growth and infection from microbes that metabolize trehalose. We propose to prepare analogs of trehalose that retain efficacy in the treatment of preeclampsia but cannot be utilized by bacteria. The prepared analogs will be evaluated using a variety of models for their effectiveness in treating preeclampsia while not serving to promote bacterial growth. The project team of Basu and Sharma provide expertise in carbohydrate synthesis and preeclampsia biology respectively.

Alzheimer’s disease (AD), a progressive neurodegenerative disorder affecting millions of people worldwide, and related dementia are becoming the biggest epidemic in medical history.  However, AD is a heterogeneous and multifactorial disease, making it challenging to fully understand how the multiple etiologies and age-related prodromal processes in AD contribute to its pathophysiology.  Among other factors, deficits in cerebral microvascular structures and functions are recently considered to play a key role in the onset and development of AD. But, it is still unclear whether they are a causal factor for AD pathogenesis or an early consequence of multifactorial conditions that lead to AD at a later stage, despite its importance for early diagnosis and as a therapeutic target.  To address this knowledge gap, we performed a longitudinal imaging experiment of tracking progressive microvascular alterations in AD mice for almost their lifespan.  Although these data provide us with unprecedently rich information about various cerebral microvascular deficits and cognitive impairment, they were insufficient to determine the cause-effect relationships.  Here, in this Seed project we will develop a computational methodology to investigate the mechanistic question. First, we will improve our computational model of microvascular flow and functional hyperemia (Aim 1), and then combine the model with the experimental data for the mechanistic study (Aim 2).  The computational model will enable us to essentially “turn on” and “turn off” each microvascular deficit (e.g., thinner vessels, tortuous capillaries, hypoperfusion) and test its effect on oxygen delivery to neurons, which is difficult and sometimes impossible to achieve experimentally.

The Petra Terraces Archaeological Project (PTAP) aims to study the long-term history of agricultural infrastructure in the hinterlands of the ancient city of Petra in southern Jordan. The project brings together an international team of archaeologists, anthropologists, geologists, and architects to study the construction, use, repair, and collapse of ancient terrace walls, dams, and related anthropogenic features that have enabled agriculture in a semi-arid environment over the last three thousand years. PTAP’s purpose is to produce a detailed, diachronic analysis of how people have shaped the local landscape by controlling—and at times also failing to control—flows of water and sediments along a single major watershed north of the city. The project builds on previous work by Brown archaeologists, both in the Petra city center, and more recently, in Petra’s outskirts. Specifically, it expands and refines the findings of an ambitious regional survey (based at Brown) that documented the ubiquity of anthropogenic modifications in the northern hinterlands of the city. PTAP will shed light on various matters of urgent importance in the contemporary Levant such as environmental inequality, human resilience and adaptability, and local responses to colonialism and imperialism, while also strengthening Brown’s ties to academic and non-academic communities in Jordan and neighboring regions.

Decades of social science research has taught us that social discourse is governed by narratives, stories about how actors’ intentions and actions relate to outcomes. The narratives one buys into reflect one’s affiliations and how one makes sense of the social world. We are a team of cognitive scientists, applied mathematicians, and computer scientists. We propose to use cutting edge machine learning technology—OpenGPT-2, a deep learning algorithm partly developed at Brown—to discover the narratives that guide social discourse using big data from online sources. In the process, we hope to develop a general theory of narrative that can be computationally realized. Our plan is to examine text generated by OpenGPT-2 on three classes of topics: Topics showing significant polarization in the US (e.g., immigration); topics with less polarization, reflecting emerging consensus (e.g., gay marriage); and non-political topics such as video game strategies. We will analyze the text with the goal of developing a formal model of the narratives underlying discourse, apply that model to enhance understanding of what OpenGPT-2 is doing and to improve the theory and measurement of narratives in discourse, and increase the scalability of these methods to ease application to different timeframes and disparate cultures. The work is inherently interdisciplinary involving both computational and social sciences, with implications for machine learning and theories of narrative. It will cement Brown’s status as a hub for cutting edge research that applies computational methods informed by cognitive science to social issues.

Exposure to greenspace, broadly defined as various forms of vegetation, has been shown to confer various health benefits. Specifically, reducing the likelihood of adverse birth outcomes, reducing the mental health impact of stressful life events, decreasing symptoms associated with behavioral problems, as well as reducing the risk of the onset of obesity.  The evidence base of the positive impact of greenspace on health has proliferated to such an extent that in 2015, the United Nations adopted the exposure to greenspace as a sustainable development goal, with target 11.7 stating "By 2030, provide universal access to safe, inclusive and accessible, green and public spaces, particularly for women and children, older persons, and persons with disabilities." With regard to the association between greenspace and birth outcomes, however, the findings are equivocal. The purpose of this multidisciplinary collaboration across public health, medicine, and geography is to attempt to reconcile conflicting findings on the association between greenspace exposure and birth outcomes.  By examining the relative contributions of varying measures of green space exposure hypothesized to be associated with mental and physical health during pregnancy, we hope to develop the types of assessments that capture the relevant environmental features that will permit a better understanding of the mechanisms that underpin associations between greenspace exposure and birth outcomes.

Every year approximately 3.6 million Americans miss or delay health care due to transportation barriers. Though lacking access to a vehicle is the most commonly reported transportation barrier to care, 43 states currently have policies to suspend driver’s licenses as a means of compelling compliance with laws and regulations unrelated to driving (e.g., failure to pay a court fee or appear in court).  Approximately 80% of all suspensions are for a non-driving-related offense, and the impact of these suspensions falls primarily on low-income and racial/ethnic minority drivers. Supporters of suspensions view them as one of a limited set of tools for compelling compliance with state regulations. However, little is known about the population of suspended drivers, or the unintended consequences of a suspension for accessing health care. We propose to close this gap using a unique dataset of linked driver’s licensing histories with Medicare and Medicaid claims to provide the first individual level descriptions of this population and how it has changed over time. In the last two years, six states have passed legislation ending non-driving-related license suspensions and several more are considering doing the same. The findings from our proposed work will provide policy makers with the essential information on suspended drivers necessary for developing informed and effective suspension policies and will establish the empirical foundation required for extending our work to estimate the causal effect of a suspension on access to health care, health care utilization and ultimately health outcomes.

Each year in sub-Saharan Africa, over 1 million children are born exposed to HIV-infection in utero, but uninfected (HEU). Compared to HIV-unexposed (HU) children, HEU face a range of health consequences including metabolic abnormalities, such as hypertension, dyslipidemia, and impaired glucose function. To date our understanding of factors that affect metabolic health of women living with HIV and their children has been hampered by the vastly different social environments and health status between those living with and without HIV. These differences may lead to important variations in maternal biomedical and psychosocial factors during pregnancy, such as maternal substance use, food security, body mass index, gestational weight gain, which may influence long-term metabolic health for both women and children but have not been explored in HIV-infected populations. This proposal brings together the unique disciplinary perspectives of a psychologist and an epidemiologist to examine how maternal factors during pregnancy influence metabolic outcomes in women and children and to design an intervention to mitigate these factors to be evaluated through subsequent external funding. We propose to leverage the Drakenstein Child Health study, an established cohort of mother-child pairs in South Africa with rich psychosocial and biomedical data. OVPR Seed Funds will be used to examine markers of metabolic function during pregnancy and prospectively evaluate metabolic outcomes in women and children at 5-8 years postpartum. We expect this pilot award to result in a R01 application focused on testing an intervention to improve cardio-metabolic outcomes in women with and without HIV and their children.