Florida Atlantic University

NSF Awards · FY 2024 · 2024-09

The direct detection of gravitational waves emitted from merging black holes and merging neutron stars by the NSF's LIGO detectors over the last few years has opened a new window to the Universe. Observations of mergers of two black holes or two neutron stars provide a vast amount of data that allows the study of both strong gravity and matter at extreme densities. As the two objects get close, fully non-linear numerical simulations of the Einstein equations are required to interpret the observational data. By comparing to observations, predictions from these codes can be used to infer information about the stars, including the equation of state at supra nuclear density. The project funded by this award will carry out such simulations. It focuses on scenarios that have not been widely investigated yet, such as neutron stars containing dark matter, or possible deviations from the Einstein equations. In addition, the projects will further develop the computer codes we use for our simulations. The aim is to use more advanced numerical methods to obtain both higher accuracy and also faster simulations. This research will also lead to the publication of simulation results (e.g. gravitational waveforms) which will be useful for the emerging field of gravitational wave and multimessenger astronomy. Part of the planned research will be carried out in close collaboration with researchers at the universities of Jena and Potsdam in Germany. Visits or virtual meetings by faculty, postdocs, and students are planned. This exchange will have educational benefits for students and postdocs at Florida Atlantic University (FAU). Through regular meetings and seminars, the PI's group helps to train students in a wide range of topics ranging from general relativity and astrophysics to computer science and large-scale computing. The project also includes a week-long hands-on summer workshop for students from a nearby high school. The workshop will teach the participating students about programming, motivated by the subject of numerical relativity. All students involved in this project or the workshop will acquire valuable skills that will help build a globally competitive STEM workforce. It is now possible to observe gravitational waves from black hole and neutron star mergers, as well as electromagnetic counterparts in the case of neutron stars. These observations provide a vast amount of data that allows the study of both strong gravity and matter at extreme densities. Using numerical relativity computer simulations, the project funded by this award will investigate scenarios that have not received much attention until now. It will study how dark matter influences binary neutron star mergers in General Relativity. This will be achieved by investigating different neutron star configurations that span a range of dark matter fractions, dark matter particle masses, binary mass ratios, and spins. By comparing to observations, this will lead to limits on the dark matter fraction in neutron stars. The project will also investigate how neutron star mergers differ in massive scalar-tensor gravity, a viable alternative to General Relativity. This will allow testing for possible deviations from General Relativity. To do so, the equations of massive scalar-tensor theory will be implemented in computer programs to create both initial data and to be able to evolve them. In both the dark matter and scalar-tensor cases gravitational wave catalogs, and characteristics of the merger remnant such as final masses and spins, or disk masses, as well as the amount of ejected mass, will be published. This work will be performed with the mature BAM code. Yet, it is also planned to extend the next-generation Nmesh code that aims at achieving higher accuracy. The ultimate goal is to perform long simulations of binary black hole inspirals, where the ratio of the two black hole masses is very high. This project aims to lay the groundwork for this endeavor by deriving a new first-order evolution system that can evolve black holes as punctures when using finite differences. This evolution system will then be implemented in Nmesh, where the elements containing the punctures will use finite differences, while other elements will use a more accurate discontinuous Galerkin method. Another aim is to improve the accuracy of neutron star simulations, by combining discontinuous Galerkin with finite volume methods. The focus will be on studying finite volume methods that do not need to communicate more data than discontinuous Galerkin methods to improve parallelization performance. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-08

Alzheimer’s disease (AD), a major form of dementia, starts with synaptic dysfunction and progresses to massive neurodegeneration. Mutations of amyloid precursor protein (APP) that increase amyloid plaque (one of the two AD hallmarks) are found in the very rare familial AD (fAD, a.k.a. early-onset AD or EOAD). The discoveries of mutations in PSEN1/2 that make amyloid peptides from APP reinforce the amyloid hypothesis, positing that A (-amyloid peptide) aggregation causes synaptic dysfunction and neurodegeneration. There are many other risk factors have been discovered through genomic screen of thousands of patients with sporadic AD (sAD), highlighting that the cause of AD is likely multifactorial. Early studies about APP led to various theories about its functions, ranging from neurodevelopment to apoptosis. But the link between APP and AD remains elusive other than A. Very recently, our work in mouse neurons led to an intriguing discovery – APP and cholesterol (Chol) are inversely correlated in the plasmalemma of presynaptic terminals. Moreover, point mutations within APP’s Chol-interactive motif (CIM) causes APP increase and Chol decrease at the plasmalemma of axon terminals. Chronically, those mutations led to abnormality in synaptic vesicles (SVs), swollen synapses, disintegrated axons and tau hyperphosphorylation. Hence, we postulate that APP regulates presynaptic Chol and that APP mutations triggers neurodegeneration by disrupting neuronal Chol homeostasis. In fact, a lot of evidence supports a close tie between Chol and AD: (1) ApoE4, the highest genetic risk factor for sAD is an isoform of Apolipoprotein E and it often accompany with abnormal lipid metabolism in the brain; (2) brain Chol metabolism declines during aging, the primary risk factor for AD; (3) mutations found in Niemann-Pick Type C1 disease interferes with Chol supply to plasmalemma and cause “juvenile AD” phenotype in the mouse model; (4) APP intracellular domain cleaved off by -secretase serves as a suppressor for the expression of lipoprotein receptor; (5) both APP and Chol are concentrated at axon terminals and crucial for synaptic plasticity, the biological basis for learning and memory. Here, we will test the hypothesis that mutations affecting APP distribution, trafficking, and interaction with Chol triggers synaptic dysfunction and neurodegeneration via disrupted presynaptic Chol homeostasis. To do so, we will use human neurons differentiated from induced pluripotent cells (hiNs) for better clinical relevance. Methodologically, we will employ new imaging tools and electrophysiological recording] to systematically investigate APP, Chol, synaptic transmission, plasticity and cell pathology. If successful, this project will provide new insights about APP’s intrinsic function, the importance of presynaptic Chol, and, more importantly, the cause of AD, which will lend a hand to new therapeutic strategies for AD.

NSF Awards · FY 2024 · 2024-08

With the support of the Chemistry of Life Processes (CLP) program in the Division of Chemistry, Professor Kate Carroll from the University of Florida will investigate post-translational protein cysteine modifications. Cysteine plays essential roles in protecting the cell from oxidative damage through its thiol functional group. The importance of thiol modifications has been recognized by chemists and biologists alike, however, their impact on the chemical reactivity of sulfur has not been systematically studied until now. Through synthesis and physical-organic characterization, Dr. Carroll’s research explores how different cysteinyl thiol group modifications endow the sulfur atom with distinct chemical properties. This research will allow graduate students to gain specialized training in organosulfur chemistry and effective protein bioconjugation strategies. This project will also be integrated into an outreach program to introduce high school and undergraduate students to the science of bioorthogonal reactions. This research project seeks to expand the fundamental science of electrophilic sulfur chemistry. The reactivity of electrophilic sulfur species are being investigated by kinetic and thermodynamic evaluation of models using time-resolved nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Reactivity is to be studied by generating small molecule models using advanced methods and new reactions in organosulfur chemistry. A range of post-translational thiol modifications identified as central to reversible redox regulation in biology are being targeted for study. The sulfur-based functionalities to be studied include cyclic sulfenamides, polarized disulfides, and S-sulfonates. Information gleaned from these studies is expected to provide both mechanistic guidance and new research tools in support of the investigation of protein cysteine oxidation-reduction chemistry in biology, particularly in dynamic redox environments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-07

Soil degradation affects 33% of Earth’s land surface and is exacerbated by climate change. Climate-driven soil degradation is an especially urgent problem in drylands, which have unique soil microbial communities that include surface biological soil crusts that reduce erosion. Drylands generate feedback to climate change because they account for ~⅓ of global soil organic carbon and make the largest contributions to interannual carbon fluxes of any terrestrial biome. Despite the importance of microbes to dryland soil health, little is known about how individual dryland soil microbes respond to climate change. The project aims to discover microbial solutions that promote soil health in hotter, drier climates. Research activities characterize the climate resistance of common dryland microbe species exposed to heat and drought, discover how to assemble communities of these species that maximally resist heat and drought, and seek use-inspired solutions that inoculate climate-ready microbes into soils of the Chihuahuan Desert, New Mexico, USA. Ecologists and microbiologists work collaboratively on activities that leverage prior NSF-funded infrastructure and biological collections. Synergistic broader impacts include an innovative program for high school teachers to bring contemporary research into underserved K-12 classrooms, a Course-based Undergraduate Research Experience for a gateway majors course, summer REU students, a new community science photography project to raise public awareness of the ecological services of biocrusts, annual workshops for park personnel, volunteers, land managers, retirees, school teachers, and students with Joshua Tree National Park Association, and a schoolyard Data Jam with students from Nevada, Florida, New Mexico, and Puerto Rico. Climate change can accelerate soil degradation through changes to soil microbes. Vegetation-poor drylands are soil microbe-driven ecosystems with unique microbiomes that influence soil health. Ecologists and microbiologists work collaboratively on soil health solutions that leverage prior NSF-funded infrastructure and biological collections, including collaboration with Sevilleta LTER. The integration of knowledge in a hierarchical framework that spans the individual organism to the ecosystem has high potential to improve predictions (theory) and solutions (use-inspired applications) for improved soil health. At the individual-population level, lab experiments characterize heat and desiccation resistance and traits for 30 species of dryland Cyanobacteria and Fungi and molecular mechanisms of resistance. At the population-community level, greenhouse experiments test how heat and drought alter microbe interactions, and, in turn, how microbial composition affects resistance to heat and drought. At the community-ecosystem level, field research applies climate-ready microbial assemblages to reverse long-term soil degradation. This project builds the first comprehensive database on dryland microbe physiological resistance to heat and drought. Trait-based work seeks generalizable rules on microbial climate resistance, tests whether conservative traits confer greater stress-resistance than acquisitive traits, and evaluates the novel hypothesis that cross-domain assemblages composed of bacteria and fungi maximize the resistance of soil health to heat and drought. Altogether, research activities have high potential to generate novel predictions and solutions that maximize the resistance of drylands to soil degradation under climate change. Broader impacts span K12 classrooms to graduate training and build new collaboration with regional managers of soil health. This project is jointly funded by Integrative Ecological Physiology (IOS/IEP) and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-07

ABSTRACT GPR37L1 is a recently deorphanized receptor belonging to the larger family of seven transmembrane receptors that couple through G-proteins to regulate numerous biological functions. Using an unbiased computational approach to probe its clinical significance, we identified a statistically significant association between human genetic variants in GPR37L1 and a clinical diagnosis of migraine in a large, unselected patient population. Our subsequent characterization of GPR37L1 receptors carrying human coding variants revealed robust signaling differences and further study of gene targeted mice lacking the receptor demonstrated some interesting behavioral features such as altered sex-dependent anxiety-like behavior, which is often associated with chronic migraine-like states. Altogether, the results from these complementary approaches and the restricted GPR37L1 expression in astrocytes, whose dysfunction promotes migraine-like pain, strongly support the hypothesis that GPR37L1 signaling plays a protective role in migraine. Here, we propose to dissect the novel role of GPR37L1 signaling in the neuropathology of this disorder through a concerted effort combining a wide range of complementary approaches to: 1) Assess GPR37L1 expression and localization in mice exposed to a chronic migraine-like state; 2) Address the impact of genetic GPR37L1 deletion on astrocyte modulation of neuronal activity; and 3) Examine the effects of genetic GPR37L1 deletion on a chronic migraine model that involves progressively increased measures of cephalic allodynia, photophobia and anxiety-like behavior associated with repeated systemic administration of exogenous CGRP in female and male mice. To accomplish these aims, we have assembled an investigative team with the interdisciplinary expertise to conduct the broad range of genetic, biochemical, electrophysiological, and behavioral approaches that are necessary for a full understanding of the contributions of GPR37L1 to chronic migraine. Altogether, we expect the results will show that altering the GPR37L1 signaling pathway produces astrocyte dysfunction that critically affects neuronal function(s), resulting in increased sensitivity to head pain triggers and other responses consistent with migraine. If validated, the demonstration that GPR37L1 activation is protective with respect to migraine may have broad implications for other neurological disorders.

NIH Research Projects · FY 2024 · 2024-07

This investigation aimed to identify the mechanisms and molecular functions of ribosome stalling in Huntington disease (HD). HD is caused by the polyglutamine (CAG) expansion of huntingtin (mHTT), which promotes neurodegeneration in the brain, causing motor, cognitive, and psychiatric symptoms. Multiple abnormal functions have been proposed for mHTT, but its pathogenic mechanisms remain unclear. Using super-resolution ribosome profiling (aka Ribo-Seq) and biochemical tools, we demonstrate that mHTT promotes ribosome stalling and inhibits protein synthesis, which is the topic of the current investigation. The central hypothesis is that mHTT interacts with RNA and ribosomal binding proteins (RBPs) to inhibit ribosomal movement and increase HD pathogenesis. Our published and preliminary data indicate that mHTT copurifies with 40S ribosomal subunits, directly binds to elongating ribosomes, and suppresses protein synthesis both in vitro and in vivo. Interestingly, Ribo-Seq revealed that mHTT mRNA exon1 also had substantial ribosome occupancy before CAG expanded repeats, which we validated using biochemical reporter experiments. We found that the RBP fragile x-mental retardation protein (Fmrp), a negative regulator of synaptic mRNA translation, is upregulated in HD and that Fmrp deletion inhibits age-dependent motor deficits in a humanized HD model. On the basis of these solid data, the proposed research has three interrelated objectives: 1) to identify the ribosome-bound protein/RNA component that interacts with mHTT; 2) to determine the mechanisms of ribosome stalling on mHTT mRNA; and 2) to delineate the role of Fmrp in modulating protein synthesis at the synaptic level in HD. Consequently, the outcomes will likely reveal novel hypothesis-generating ribosome stalling mechanisms in HD, identify critical cis and trans components implicated in mHTT RNA stalling, and determine how the mHTT-Fmrp nexus regulates aberrant synaptic translation in HD. These findings will help develop translation mechanism-based treatment and diagnostic modalities for poorly understood neurological illnesses.

NIH Research Projects · FY 2026 · 2024-06

PROJECT SUMMARY (See instructions): Dr. Rosedahl's long-term career goal is to understand how vision operates in tasks that involve the interaction between multiple visual processes such as category learning, visual perceptual learning, and visual attention. This knowledge could be used to design better training paradigms for visual tasks and increase the efficiency of visual rehabilitation training. In this project, Dr. Rosedahl will examine how attention can induce visual perceptual learning transfer. Visual perceptual learning is long-term improvement in visual tasks like telling the difference between the angle of two lines or detecting the presence of stripes. Visual perceptual learning is one of the most promising methods to improve vision in individuals with visual impairment. Unfortunately, research has found that visual perceptual learning is very specific to the part of the visual field trained in the task. This specificity greatly limits the use of visual perceptual learning in training paradigms for visual rehabilitation and motivates the goal of this work: to understand the mechanisms by which visual perceptual learning can transfer to untrained visual field locations. This work focuses on understanding the mechanism of an experimental paradigm that causes visual perceptual learning to transfer across visual field locations: double-training. In this paradigm, training on an irrelevant task at a new visual field location causes previous learning to transfer to the new location. To understand the mechanism of this transfer, Dr. Rosedahl will build a unified model of visual processing, visual perceptual learning, feature-based attention, and spatial attention (Aim 1). Dr. Rosedahl will use this model to interpret the results of four experiments to determine if the combination of feature-based attention and spatial attention causes transfer in double-training (Aim 2). The experiments will measure performance improvement, neural activation using functional Magnetic Resonance Imaging, and changes in neurotransmitter concentrations using Magnetic Resonance Spectroscopy. Overall, the work proposed here will establish a novel unified model of visual processing, visual perceptual learning, feature-based attention, and spatial attention and provide insight into the mechanisms of VPL transfer, knowledge that is currently lacking. The model will be a valuable resource for the broader scientific community to study visual learning in real-world scenarios. Additionally, the knowledge gained here could yield novel insights into optimizing visual perceptual learning training paradigms, providing critical

NIH Research Projects · FY 2025 · 2024-04

PROJECT SUMMARY Substance abuse disorders including opioid dependence are characterized by brain oxidative stress and neu- roinflammation. In addition to dopamine autooxidation, chronic drug consumption increases the expression of pro-oxidant enzymes such as NADPH-oxidase (NOX), leading to excessive production of reactive oxygen spe- cies (ROS) primarily in the form hydrogen peroxide (H2O2). Endogenous H2O2 can transiently and/or irreversibly oxidize cysteinyl residues depending upon its concentration and duration of exposure. In proteins, H2O2 reacts with redox-sensitive cysteine thiols to form sulfenic acid (Cys-SOH). Cysteine S-sulfenation has emerged as a major post-translational modification that exerts significant effects on protein function, analogous to phosphory- lation. A small but compelling literature suggests that changes in cysteine redox state affect mu opioid receptor (MOR) function, as thiol alkylation, site-directed mutagenesis, and redox-modulating agents can alter ligand binding and downstream signaling events. In addition to structural and regulatory roles, oxidation of the cysteine thiol blocks the reaction of this residue with a,b-unsaturated carbonyls and alkyl halides, significantly limiting the utility of conventional electrophile-fragment screening as a tool for covalent ligand discovery. To address this issue, we have recently developed a strategy that employs nucleophilic covalent fragments to target S-sulfenated (oxidized) cysteines. These sulfenic acid-reactive activity-based protein profiling (ABPP) probes have been cou- pled with state-of-the-art quantitative proteomics to identify S-sulfenated cysteines in human cells, which presage the development of covalent fragments therapeutically targeting redox-active cysteines. Here, the following Spe- cific Aims are proposed: 1) Increase the size and structural diversity of our nucleophile-fragment libraries; 2) Map cysteine redox reactivity changes and S-sulfenated (oxidized) cysteine ligandability in differentiated mature SH- SY5Y neurons that are unstimulated (control) or treated with morphine agonist (stimulated). These studies are rationalized based on proof-of-concept experiments which demonstrate that unique ligandable sites are identified when fragments are functionalized with nucleophilic reactive groups that react with S-sulfenated (oxidized) cys- teine residues. Deliverables from these studies are a novel chemoproteomic method, chemical matter that can be mined as a source of small-molecule probes and as starting points for drug discovery.

NIH Research Projects · FY 2025 · 2023-12

7. Project summary. Protein–protein interactions (PPIs) play a pivotal role in regulating a plethora of biological processes and their misregulations have been associated with a variety of diseases. Modern proteomic tools enabled over 600,000 PPIs to be identified as potential targets, which can be validated at an incredible pace by programmable gene-editing point-mutations in mammalian cells. Given these technological advances, the modulation of intra- and extracellular PPIs has emerged as one of the most exciting strategies towards next- generation therapeutics. Yet, the development of PPIs inhibitors is lagging far behind the other successful drug modalities (antibodies and small molecules) due to the challenges associated with the large, shallow, often dynamic, and water-exposed binding interfaces. Therefore, we propose to study novel PPI inhibitors modalities via -hairpin peptides featuring large binding-surface areas inspired by the long non-canonical loops forming antibody paratopes. Our goals are to preserve the high-affinity and binding specificity of antibodies by mimicking the binding-competent conformation of CDR-H3 loops sequence to disrupt PPIs. This research proposes to exploit -hairpin scaffolds synthesized in our lab to recreate antibody loops of conceptually any sequence, length, and conformational plasticity (aim 1). As a proof-of-concept (PoC), a structure-guided approach from X-ray crystal structures of protein–antibody drug complexes will be followed to rationally design PPI inhibitors of the programmed cell death 1 (PD1) immunoreceptor and its ligand 1 (PDL1). Indeed, the PD1/PDL1 interaction inhibits T-cell effector function in a process known as tumor immune evasion, and its blockade has proven to be an effective strategy to restore T-cell proliferation in different cancer-types. To validate our PoC, covalent inhibitors will be designed by crafting electrophilic warheads at specific loop positions of the most potent -hairpin binders (aim 2). Overall, our strategy combines the synthesis of -hairpins bearing strained loops (N > 12- residues) that closely mimic the large binding contacts of antibodies CDR-H3 loops to create high-affinity inhibitors with the positioning of electrophilic warheads for covalent binding at the PPI interface. A series of novel electrophilic warheads will be evaluated to target a distinctive lysine residue (K131) located at the center of PD1 binding epitope. A structure–activity optimization will also be achieved by alanine-scanning to validate the most promising cell-penetrating hairpin peptides in living cells (PBMCs). This strategy of CDR-H3 mimicry into covalent -hairpins could potentially be a game-changer by revisiting peptide drugs that are not able to bind tightly and selectively to extra- and/or intracellular proteins and often abandoned during preclinical studies due to a lack of in vivo activity. As a result, a large number of protein targets associated with various diseases could become druggable and offer new possibilities in the space of PPI inhibitors for drug discovery.

NIH Research Projects · FY 2026 · 2023-08

Both social isolation and cognitive decline are urgent threats to public health, as they predispose persons to Alzheimer’s disease and related dementias. Air pollution and the built environment are community-based factors that have been shown to adversely affect cognitive function. Individual factors such as social isolation further contribute to cognitive risk. Rural settings have more limited opportunities for social engagement, when compared to urban settings. These conditions converge to form a perfect storm of social isolation and accelerated cognitive decline, yet prior studies have not focused on rural residents. Using a multi-method approach, we propose to demonstrate how a rural Florida population (N = 1087) is at risk for social isolation and decline in cognitive function due to the unique characteristics of the physical and social environment. We will recruit community-dwelling, non-clinical, dementia-free, middle aged and older adults from 5 communities in the Lake Okeechobee area of Florida for a 5-year study incorporating time-series individual social and cognitive measures and community-level measures of the physical and built environment. Apple watches will be used by a subsample of 120 participants representative of 5 communities to continuously monitor sensory data, daily routine and predefined activities for 2 months. Ecological momentary assessment (EMA) will be used to collect data daily over periods of agricultural burning and no burning. Using a combination of primary data collection, secondary data analysis, subsample continuous monitoring and EMA, we will examine the following aims over 36 months among rural, low-resourced, multilingual community-dwelling adults aged 45 years and older: Aim 1: Examine the contribution of smoke-related PM2.5 exposures to SI and cognitive function, through multilevel growth modeling. Aim 2. Determine the effects of the built (e.g., retail destinations, park space) and social environment (e.g., crime SES) on social isolation and cognitive function through mixed linear modeling. Aim 3. Contextualize social isolation and cognitive function among residents from different racial/ethnic groups using EMA and sensor-derived behavior models with a subsample of 120 stratified by Lake O communities during burn and non-burn seasons.

NIH Research Projects · FY 2026 · 2023-02

Project Summary Estimates from the Alzheimer's Association indicate that approximately one in ten older adults in the US have Alzheimer's disease (AD) while 15 to 20% have mild cognitive impairment (MCI), projecting that about a third of those will develop dementia within five years. Several variables have been associated with delaying the onset and rate of cognitive decline in AD and have been grouped under the Cognitive Reserve/ Resilience (CR/R) theory; it postulates that complex mental activity throughout the lifetime creates resistance to cognitive decline despite the biological risk (brain loss). Emerging evidence shows that bilingualism may be one of these neuroprotective factors in the aging brain, but results in bilingualism and CR/R remain inconsistent. Our objective is to analyze the contribution of bilingualism to CR/R in a large cohort of aging Spanish/English bilinguals and Spanish monolinguals with amnestic MCI (aMCI). To overcome limitations in previous research, we will use a longitudinal design, operational characterization of bilingualism, refined sociocultural measures, and multimodal neuroimaging. The current study will leverage and extend a large ongoing NIH cohort prospective study from the 1Florida Alzheimer's Disease Research Center (1Florida ADRC), in which Spanish/English bilingual Hispanics with aMCI are well-represented (n = 120), but Spanish monolinguals are underrepresented although they comprise approximately 40% of foreign-born Hispanics in the US. In the present study, we directly address this by deploying an intensive, culturally-informed, community-engaged research approach in the Miami area to increase outreach and recruit 120 Hispanic monolinguals with aMCI. We will make the ADRC MCI bilingual and monolingual groups ethnically equivalent and create a longitudinal data set (n=240), ensuring that we are well-powered to determine the contribution of bilingualism to CR in the aMCI population. As co-investigators on the 1Florida ADRC, our research team is well-positioned to execute the proposed study. We will collect neuropsychological data at years 1, 2, and 3 and neuroimaging data (MRI and DTI) at years 1 and 3. The neuropsychological battery will include the Loewenstein-Acevedo Scale for Semantic Interference and Learning (LASSI-L), a cognitive stress test that evaluates failure to recover from Proactive Semantic Interference (frPSI) and is highly sensitive to subtle cognitive changes in early AD. The innovation lies in studying the relationship between brain diffusivity measures of WM and frPSI, as measured by the LASSI-L in combination with volumetric brain data; the use of Bilingual indexes of language proficiency and degrees of acculturation, and levels of education. Our findings will advance our understanding of the complex interactions between neural, environmental, and sociocultural factors and the role of bilingualism in CR/R in AD/ADRD, paving the way for new targets for interventions and providing fundamental insight into the role of language(s) in the aging brain.

NIH Research Projects · FY 2024 · 2022-09

The polyglutamine expansion in the huntingtin (mHTT) causes HD. Before HD onset, striatal atrophy occurs, with subsequent loss of cortico-striatal white matter (WM) connections in layer V. As HD progresses, it affects other parts of the brain and the peripheral tissues. The mechanisms underlying the neuronal vulnerability in HD are not entirely understood and likely several, including aggregation, transcriptional dysregulation, energy metabolism deficits, synaptic dystrophy, oxidative stress, inflammation, and others. We demonstrated that striatal enriched protein Rhes interacts with mHTT via the farnesylation domain and promotes cellular toxicity by increasing the soluble forms of mHTT via small ubiquitin-like modifier (SUMO)-1 modification. However, the mechanisms by which the Rhes-SUMO pathway mediates neuronal vulnerability in HD are unclear. We hypothesize that Rhes and SUMO1 signaling circuitry orchestrate striatal vulnerability and HD progression by altering mHTT levels and promoting the spread of mHTT in the brain. This hypothesis is formulated based on the following findings: a) Rhes mediates mHTT transmission between cultured neurons involving actin-based tunneling nanotube-like (TNT-like) membranous protrusions, b) SUMO depletion or SUMO-defective mHTT diminishes transport of mHTT via Rhes–TNTs. c) SUMO1 deletion enhances autophagy activities and decreases mHTT abundance in the striatum and prevents HD-related behavioral and anatomical deficits in Q175HD KI mice, and d) Rhes transits within striatum and from the striatum to the cortex (V, VI, layers) and spread mHTT. These data indicate an intricate link between Rhes and SUMO pathways in HD pathogenesis. But the detailed mechanism of action(s) of Rhes–SUMO1 pathways in HD is unclear. This proposal addresses two distinct yet interrelated Aims: Aim 1. To uncover the role and mechanisms of Rhes-mediated mHTT spreading in the brain. Here will test the hypothesis that Rhes spreads mHTT and promotes neuropathology involving posttranslational mechanisms and TNT-like routes. Aim 2. To identify the mechanisms of SUMO1- mediated HD pathogenesis. Here we test the hypothesis that SUMO1–mHTT inhibits autophagy, thereby allowing accumulation and spread of mHTT from the striatum to the cortex. This project will provide novel mechanistic insights into SUMO-mediated autophagy deficits in HD and SUMO roles in Rhes-mediated mHTT transport between brain regions while also potentially identifying novel therapeutic targets that can limit mHTT spread in the HD brain.

NIH Research Projects · FY 2026 · 2022-05

Abstract Text ABSTRACT Florida Atlantic University (FAU), the University of Miami (UM) and Florida International University (FIU) propose a six-week Florida Summer Institute in Biostatistics and Data Science (Florida SIBDS) focused on health disparities related to cardiovascular and infectious diseases. Currently, Florida SIBDS would be the first SIBDS in the southeastern United States. FAU and FIU are both Hispanic Serving Institutions (HSI) and State Universities, and the University of Miami is a private institution; all institutions have significant funded research activity. Florida SIBDS is innovative: 1) It introduces rigorous quantitative careers to young adults through the combined efforts of faculty from three pre-eminent institutions; 2) The leadership team and faculty have unique complementary skillsets in biostatistics, epidemiology, health economics, computational biology, AI, machine learning (ML), and big data analytics; and 3) SIBDS students will be actively involved in “learning through teaching”, culminating in a short curriculum they will teach to first year high school students. This novel partnership approach will address the shortage of biostatisticians in government, academia and industry by providing a well-qualified pipeline of future biostatisticians and data scientists, many of whom may not have had the opportunity due to lack of awareness, educational access and financial barriers. Florida SIBDS will recruit nationally to enroll 136 undergraduate and early graduate school students over five years with requisite mathematics coursework and a budding interest in health, while targeting students who will be introduced to biomedical and behavioral science research. Recruitment methods include social media, websites, professional organizations, and personal contacts with administrators and student influencers. Florida SIBDS will engage students in a multi-faceted, peer and faculty mentored, intensive 6-week training experience driven by research questions that highlight health disparities and social drivers of health, using current cardiovascular and infectious diseases databases. Although the curriculum encompasses basic, advanced and cutting-edge statistical and data science methods delivered in ways to engage students, it also highlights scientific communication, collaborative skills, project teamwork, social interactions and career guidance. Quantitative and qualitative methods will be used to evaluate peer and faculty mentors and students annually. An External Advisory Committee, pedagogy and evaluation consultants, leadership team and student advisors will use their experience and these data to inform the curriculum. Florida SIBDS alumni will retain mentorships with faculty and have access to revised curriculums for five years after completion.

NIH Research Projects · FY 2026 · 2022-01

Project Summary Although antiretroviral therapy (ART) is effective in saving AIDS patients' lives, the implementation of ART worldwide has been drastically hampered by the lack of treatment monitoring diagnostics and disease management. According to the recent statistics by USAIDS, the coverage of ART is still only 59%, despite ART being affordable or freely available in most countries. In addition, worldwide, about 1 in 4 of the people that contracted the virus are unaware of their HIV status. One of the fundamental challenges to reduce HIV burden and its prevalence is the absence of HIV self-testing assays which are sensitive enough to detect new HIV infections during the first two-weeks (acute phase) post-infection and viral rebound in virally supressed patients receiving ART. Current self-testing technologies only detect the host antibody response to HIV infection, which usually arises 3-4 weeks after the initial infection and it is not an indicator of therapy failure and viral rebound. No self-testing technologies have yet been commercialized that are able to detect HIV during the early stages of acute infection or viral rebound in suppressed patients on ART. To increase access to HIV testing and to improve treatment outcomes, there is an urgent need to develop reliable and affordable HIV self-testing technologies. To address these challenges, we propose to develop a disposable self-testing HIV-1 chip that can (i) selectively detect HIV from whole blood samples, (ii) be highly sensitive to detect HIV during the acute infection, treatment and viral rebound (<1000 copies/ml), (iii) be rapid (within 40 minutes), (iv) be highly stable (refrigeration-free), and (v) be fully automated (true sample-in-answer- out).

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY Structural variations are key drivers of both evolutionary adaptation and human disease. My group develops and applies computational and statistical approaches for understanding the evolution of structural variations from patterns in their genomic and transcriptomic data. During the past few years, our studies have focused primarily on gene duplication, which represents the most common type of structural variation observed in nature. In particular, we investigated the origins of evolutionary innovation after gene duplication, a problem of long- standing interest in the evolutionary genomics community. To answer this question, we designed the first method for classifying evolutionary outcomes of duplicate genes from phylogenetic comparisons of their gene expression profiles. By applying this decision tree method to multi-tissue gene expression data, we were able to classify evolutionary outcomes of duplicate genes in Drosophila, mammals, and grasses. These studies revealed frequent tissue-specific expression divergence after duplication, as well as sequence and expression differences within and among taxa that are consistent with natural selection. In a follow-up population-genomic analysis, we demonstrated that natural selection indeed plays an important role in the evolutionary outcomes of young duplicate genes in Drosophila. Later, we developed analogous decision tree classifiers for two additional types of structural variations: gene deletion and translocation. Applications of our methods to sequence and expression data from multiple tissues and developmental stages in Drosophila uncovered rapid divergence concordant with adaptation, suggesting that natural selection shapes the evolutionary trajectories of structural variations generated by deletion and translocation as well. However, our recent analyses revealed that there are many limitations of these decision tree methods, including sensitivity to gene expression stochasticity, lack of statistical support, and inability to predict parameters driving the evolution of structural variations. Thus, during the next five years, my group will develop a suite of tailored model-based statistical and machine learning approaches for classifying the evolutionary outcomes and predicting the evolutionary parameters of structural variations arising from duplication, deletion, inversion, and translocation events. Our preliminary studies indicate that these techniques will be much more powerful and accurate than previous approaches, and will therefore compose major advancements in evolutionary investigations of structural variations. In addition to implementing our methods in open source software packages, we will apply them to assay the evolutionary implications of different types of structural variations in humans and several other animal and plant taxa. Comparisons will be made among different types of structural variations, their evolutionary outcomes, and taxonomic groups. The major goal of these studies will be to ascertain the general rules by which different types of structural variation contribute to evolutionary innovation. Together, these studies will shed light on how gene duplication, deletion, inversion, and translocation work in concert to generate a diversity of complex adaptations across the tree of life.

NIH Research Projects · FY 2025 · 2021-07

Project Summary/Abstract: The introduction of multi-gene panel testing for hereditary breast and ovarian cancer (HBOC) syndrome has rapidly changed the clinical approach to genetic testing for patients and their families. Young breast cancer survivors (YBCS), diagnosed at age ≤50 years old, may have inherited a pathogenic/likely pathogenic (P/LP) variant in a breast cancer susceptibility gene, e.g., BRCA1, BRCA2, PALB2, etc. Recent studies have found suboptimal rates of genetic testing among young breast cancer patients with less than 50% completion rates for hereditary breast and ovarian cancer (HBOC) syndrome. Racial and ethnic disparities in genetic testing completion and results have been well documented. My long-term career goal is to become a leading independent investigator in breast cancer prevention and control, focusing on cancer genetics/genomics, risk communication, biobehavioral oncology, and reduction of cancer health disparities among racial/ethnic minority women. The specific aims are: In Aim 1, we propose to identify factors associated with completion of HBOC multigene panel testing, cancer risk-reducing behaviors, and family risk communication among racially/ethnically diverse young breast cancer survivors (YBCS) (N=300) within a sequential explanatory mixed-methods study. In addition, we will conduct qualitative interviews with (N=40) YBCS who completed genetic testing and those who have not completed genetic testing to explore knowledge, attitudes, beliefs about genetic testing, and to identify barriers and facilitators to the communication of genetic risk to their at-risk relatives. We will illuminate quantitative findings with qualitative data collected. In Aim 2, we will apply user-centered design to modify the existing genetic testing module within the RealRisks decision aid to meet the needs of YBCS and to add family risk communication content and conduct participatory workshops and usability testing (N=20). Lastly, in Aim 3, we will conduct a pilot randomized controlled trial of standard patient education alone or in combination with the modified RealRisks decision aid among racially/ethnically diverse YBCS. This career development award will provide me with protected time and the opportunity to pursue my training goals in several targeted areas: (1): Acquire and apply advanced statistical analytics for conducting mixed methodology and intervention research; (2) increase knowledge and skills in biobehavioral oncology, cancer survivorship, clinical application of genetic/genomic medicine, risk communication in families, cascade genetic testing, adapting web-based decision support interventions for underserved populations, and breast cancer health disparities; (3) gain didactic and experiential learning in the conduct of randomized controlled trials; and (4) develop leadership skills in the ethical conduct of scientific research, grant writing, increasing scholarly productivity, and management skills for scientific independence. In summary, this Mentored Research Scientist Development Award to Promote Diversity will provide me with invaluable experiences to successfully transition into a scientific independence, ultimately reducing health disparities.

NIH Research Projects · FY 2026 · 2020-04

PROJECT SUMMARY The physiological function of neuronal IL-1R1 is not understood. In the last funding cycle of this project, we have demonstrated that neuronal IL-1R1 is critical for chronic social stress-induced changes in behavior. In this renewal, we propose that the physiological function of the neuronal IL-1R1 is to modulate synaptic activity and plasticity in the nIL-1R1-regulate neurocircuits. We will pursue three aims: Aim 1: Characterize the dynamic nIL-1R1 expression in the brain; Aim 2: Elucidate the molecular mechanism by which neuronal IL-1R1 influences synaptic activity and restructuring; and Aim 3: Demonstrate nIL-1R1 in the dentate granule cells is essential for social discrimination. These aims are based on our previous findings and preliminary results that nIL-1R1 is expressed in select neurocircuits that are modified by sensory experience and its dynamic expression is controlled by experience-dependent circuit remodeling. In addition, nIL-1R1 regulated hippocampal circuit is critical for proper social behavior. Finally, nIL-1R1 was found to change synaptic activity and plasticity on neurons that do not express IL-1R1 but are connected directly with the IL-1R1 expressing neurons. The results of this project will result in a paradigm shift on our understanding of the neuronal IL-1R1 function and suggest new targets for the treatment of psychiatric disorders such as autism.

NIH Research Projects · FY 2026 · 2019-08

Project Summary Low-cost DNA sequencing has provided researchers with abundant genomic data in which to search for the unique footprints left by natural selection. However, many nonadaptive forces can obscure these signals, making it important to develop statistical methods that can account for multiple factors that influence genetic variation. My research in this area focuses on the design and application of statistical approaches for identifying regions undergoing positive selection, which increases the frequency of beneficial alleles in a population, and balancing selection, which maintains the frequency of distinct alleles in a population. During the past four years of my MIRA ESI, my group contributed to a number of methodological advances, including designing the first likelihood methods to detect positive selection from haplotype distributions, state-of-the-art likelihood methods to detect ancient balancing selection within and across species, the first likelihood method to detect positive selection by adaptive introgression, and the first machine learning method to detect positive selection by explicitly modeling genomic autocorrelation. Applications of our methods to empirical data led to several novel insights, including evidence of convergent positive selection in Europeans and East Asians, positive selection at olfactory genes that affect communication and behavior in New York City rats, and balancing selection at venom genes that may influence predator-prey coevolutionary dynamics in rattlesnakes. During the next five years, I propose to develop improved statistical and machine learning approaches to detect complex modes of adaptation by leveraging information about how different evolutionary forces simultaneously shape the distribution of genetic diversity around adaptive sites. In particular, my future research program will be subdivided into several interrelated goals: designing likelihood frameworks to identify positive and balancing selection while accounting for genomic, temporal, and spatial autocorrelations; developing methods to identify regions that underwent complex positive and balancing selection from ancient variation; introducing signal processing approaches to extract features from images of genomic variation for use in machine learning models of adaptation; and building innovative domain adaptation procedures to circumvent genetic and demographic parameter uncertainty when training machine learning predictors of adaptation. Availability of these methods will empower researchers to address important questions about adaptation in model and non-model organisms from ancient and contemporary samples, increasing inclusivity in the field, and thereby broadening our knowledge about adaptation. Further, we will apply these methods to answer or revisit key evolutionary questions about the roles of different adaptive mechanisms in primates, rodents, snakes, insects, plants, and other organisms with complex or unknown demographic histories. Advantages of these studies are two-fold, in that they will yield powerful new approaches for identifying signatures of diverse modes of adaptation from genomic data, as well as elucidate evolutionary forces underlying the acquisition of adaptive phenotypes, such as those involved in disease resistance and pathogen defense.

NIH Research Projects · FY 2026 · 2019-08

Project Summary/Abstract During ocular development, the vasculature feeding the eye lens retracts leaving the developing lens without a direct source of oxygen. This results in a 20-fold drop in oxygen levels from the undifferentiated epithelial cells of the lens surface to the mature fiber cells of the lens core. Intriguingly, the sharpest drop in lens oxygen levels occurs in the region of the lens where newly formed fiber cells initiate the rapid and robust expression of essential genes required to achieve their mature structure and transparency. These unique features of the lens lead us to hypothesize that the hypoxic microenvironment of nascent fiber cells drives transcription of essential fiber cell genes to achieve their mature structure and function through activation of novel hypoxia- dependent transcriptional regulatory and epigenetic control pathways. This hypothesis is supported by a study showing that lens exposure to artificially high oxygen levels disrupts formation of the lens organelle-free zone (OFZ) that forms from elimination of organelles during lens fiber cell maturation and by a study showing that lens-specific deletion of the master regulator of the hypoxic response, hypoxia-inducible transcription factor 1a, (HIF1a) disrupts lens fiber cell structure and results in disintegration of the entire lens shortly after birth. These studies provide a foundation for AIM1: To establish the requirements for hypoxia, HIF1a and HIF1a- co-regulators for lens fiber cell transcription, mature lens structure and lens transparency. The feasibility of this AIM is supported by our recent CUT&RUN studies showing that HIF1a binds within -10kb of the 5’- regulatory regions of over 500 lens fiber cell genes and that HIF1a binding to these regions directly correlates with their fiber cell transcript levels. These include the mitophagy gene BNIP3L that directs the elimination of non-nuclear organelles to form the OFZ. We have now discovered that exposure of cultured chick lenses to hypoxia results in rapid and robust increases in fiber cell levels of gene activating histone modifications including H3K4me3, H3K9ac, H3K14ac and H3K27ac. These studies provide a foundation for AIM2: To identify novel hypoxia-dependent epigenetic pathways governing transcription of essential lens fiber cell genes. The feasibility of this AIM is supported by our preliminary CUT&RUN studies showing that hypoxia-exposure of cultured chick lenses induces H3K27ac and H3K4me3 modification within -10kb of the 5’-regulatory regions of a wide range of fiber cell genes and that these modifications correlate with their fiber cell expression levels. The completion of this application will establish hypoxia as a novel requirement for adult lens structure and transparency through activation of novel hypoxia-dependent transcription and epigenetic pathways regulating lens fiber cell transcription. The data will provide a foundation for establishing a role for hypoxia in formation of more complex tissues.

NIH Research Projects · FY 2026 · 2012-08

PROJECT SUMMARY Post-translational changes in the redox state of cysteine residues can rapidly and reversibly alter protein function, modulating biological processes and drug pharmacology. During the last funding period, our lab reported several innovations in organosulfur chemistry, small-molecule tools, and computational methods for proteomic analysis that dramatically improved selectivity, cellular application, and site-specific quantitation of the cysteine redoxome (J. Am. Chem. Soc., 2017; Nat. Chem. Biol., 2018; Nat. Chem., 2021; Nat. Comm., 2022). Application of these chemoproteomic methods has contributed to meaningful discovery of new paradigms in redox biology (Nat. Cell Biol., 2019; Cell Metab., 2019; Blood Adv., 2020; Nat. Comm., 2021; Redox Biol., 2021 & 2022; Proc. Natl. Acad. Sci., 2022) and raise interesting new questions about the links between the cellular redox landscape, molecular thiol-based redox switches, and the emerging field of redox medicine. Herein, the following three Specific Aims are proposed: Development and application of 1) chemical methods to address spatiotemporal control in redox signaling; 2) genetic incorporation of oxidized cysteine in proteins to pinpoint molecular mechanisms underlying thiol-based redox regulation; and 3) nucleophile-fragment libraries to discover covalent ligands that target redox- regulated proteins in the cysteinome. Strong preliminary data demonstrate that studies proposed herein are both promising and feasible in our hands. Deliverables resulting from these studies include: 1) valuable new chemical biology approaches to understand fundamental mechanisms in thiol-based redox signaling, and 2) novel chem- ical matter that can be mined as a source of small-molecule probes and as starting points for drug discovery.

NIH Research Projects · FY 2025 · 2008-12

PROJECT SUMMARY Antibiotics are central to modern medicine and rising antibiotic resistance is one of the biggest threats to global health. Identifying new and different drug targets for the development of new antibiotics is crucial to overcome resistance. Adjuvant strategies that either enhance the activity of existing antibiotics or improve clearance by the host immune system provide another mechanism to combat antibiotic resistance. Targeting a combination of essential and non- essential enzymes that play key roles in bacterial metabolism is a promising strategy to develop new antimicrobials and adjuvants, respectively. The enzymatic synthesis of L-cysteine is one such strategy. Cysteine plays a key role in proteins and is vital to the synthesis of biomolecules important for defense against the host immune system. In contrast to mammals, the biosynthesis of cysteine occurs de novo in microbes using sulfide (S2–) as the sulfur source derived from the reductive sulfate assimilation pathway. Inhibition of sulfate assimilation has been proven to interfere with a pathogen’s ability to fight oxidative stress, infect the host and establish long-term infection. Inhibition of sulfate assim- ilation has also been associated with a dysregulated oxidative stress response, enhancing the antimicrobial activity of existing antibiotics. In previous funding cycles, we have defined the mechanism and structure of mycobacterial 5’- adenylylsulfate (APS) reductase an iron-sulfur protein that catalyzes the two-electron reduction of APS to sulfite (SO32– ) using thioredoxin (TrxA) as the preferred electron donor. We subsequently used these insights to discover first-in- class inhibitors of mycobacterial APS reductase (APR), with potent in vivo bactericidal activity against MDR and XDR clinical isolates of Mycobacterium tuberculosis (Mtb) and synergistic activity with known anti-TB drugs (isoniazid, ri- fampicin, clofazimine) in killing H37Rv Mtb. In this renewal, we now seek to expand our early focus on cysteine bio- synthesis and redox metabolism in mycobacteria to pathogens implicated in fatal secondary bacterial infections in influenza infection, specifically in patients with COVID-19: Pseudomonas aeruginosa and Streptococcus pneumoniae. Given the importance of microbial sulfur metabolism in oxidative stress resistance and virulence, in this renewal ap- plication we propose the following Specific Aims: (1) Define the mechanistic and structural basis for inhibition of the Fe-S protein APR from P. aeruginosa; (2) Investigate the effect of P. aeruginosa APR inhibitors on sulfur metabolism and redox metabolism in cells; (3) Determine whether a virus family that infect S. pneumoniae in human environments and encode genes for reductive sulfate assimilation increase the fitness of the bacterial host, which lacks this pathway.