University Of Illinois At Urbana-Champaign

NIH Research Projects · FY 2026 · 2024-04

Energy homeostasis is controlled by neural circuits which sense changes in energy demands to maintain body weight at a stable set point. Although body weight is remarkably stable in mammals, females must temporarily increase their energy intake during pregnancy and lactation to accommodate the massive energy demands associated with reproduction. During lactation, mice increase their food intake by 300- 400 percent, and similar changes in energy intake occur in humans during lactation. These adaptive changes are critical for the long-term health of the mother and child, as excessive or insufficient energy intake during lactation increases the subsequent risk of both the mother and child developing metabolic and psychiatric disorders later in life. This is especially apparent during lactation since critical feeding and motivational circuitry do not fully develop until the end of the lactation period in mice, and alterations in energy intake during this period result in long-lasting perturbations in metabolic, reward, and motivational circuitry. Therefore, it is of paramount importance to human health to determine the mechanism(s) mediating the elevated food intake associated with lactation. Although hypothalamic hunger circuitry, hindbrain satiety circuits, and reward based feeding circuitry are critical for normal feeding behavior, it remains unclear how these circuits are altered during lactation. Further, the neural circuitry and molecular mechanism(s) mediating the hyperphagia of lactation are unknown. We hypothesize that lactation results in widespread functional changes in hypothalamic, hindbrain, and midbrain reward circuitry, which together act to promote feeding during lactation. In this proposal we will leverage recent advances in neural circuit manipulation, single nuclei transcriptomics, and in vivo imaging approaches to determine the functional neuroanatomy mediating increased feeding during lactation in mice. Together these studies will provide the foundation for therapeutic strategies aiming to improve the metabolic health of both the mother and child, while uncovering fundamental differences in the neural circuitry regulating feeding between the sexes.

NIH Research Projects · FY 2026 · 2024-03

ABSTRACT Metastasis contributes to the vast majority of breast cancer deaths but current therapies for disseminated disease have limited efficacy and significant side effects. Immune checkpoint blockade (ICB) therapy has outstanding promise for breast cancer in late stages but is currently only approved for triple-negative cancers (TNBC) that stain positive for PD-L1 protein; of these patients, only ~25% show an initial response. Although the cause of divergent response is multifactorial, it is believed that “re-educating” immunosuppressive immune populations within tumors will increase the response rate. However, approaches to modulate cells are primarily based on systemically administered immunostimulatory drugs which have severe side effects. This project will develop a targeted therapy that delivers immunostimulatory drugs to immunosuppressive macrophages in metastatic breast tumors while minimizing effects in off-target tissues. With most macromolecular delivery strategies, the vast majority of an intravenously administered dose accumulates in the liver and spleen. We discovered that for certain nanocarriers, liver and spleen uptake can be blocked with adjuvants so that the nanocarriers accumulate in macrophages of orthotopic TNBC tumors in mouse models. We determined that this strategy could be used to deliver a compound that reduced tumor burden in combination with ICB therapy. The free drug alone is potently immune-stimulating but is too toxic for systemic treatment in humans. Remarkably, the nanocarrier and blocker combination reduces serum cytokine release 37-fold relative to the free drug. The nanocarriers and blockers are composed of highly biocompatible materials that are in routine clinical use. This project will optimize the composition of these agents for biodegradation and elimination to maximize the potential for clinical translation and further optimize the dosing and scheduling for delivery in combination with ICB therapy. At the conclusion of this project, we will have designed an optimal approach to deliver immune modulators selectively to metastatic cancerous tissue, and macrophages within that tissue, to maximize efficacy while minimizing side effects. This strategy has the potential to revolutionize cancer therapy, similar to how nab-paclitaxel (Abraxane) has improved breast cancer outcomes through targeted therapy.

NIH Research Projects · FY 2026 · 2024-03

Trajectories leading to childhood obesity result from multifactorial Gene x Environment x Behavior interactions during a period of high developmental plasticity. Defining the causal mechanisms that mediate risk for obesity development in early life and how risk can be modified by psychosocial, contextual, and/or environmental factors, requires systems biology integration, which is currently lacking. The objective of this application is to develop predictive algorithms for childhood obesity risk by integrating data on growth trajectories, body composition, and dietary intake with multi omic (genetic, epigenetic and microbiome) data sets and assessments of temperament-self-regulation and child eating behavior across early childhood. We will leverage a rich biobank of longitudinal biological samples, questionnaire, and observational data from the ongoing Synergistic Theory and Research on Nutrition and Growth Kids 2 (SK2) cohort (n=468)11. Our central hypothesis is that computational and systems biology approaches will illuminate interactions between modifiable and non-modifiable obesity-related risk factors to provide predictive indices that identify at-risk individuals in early life. The three specific aims are: Aim 1. Determine how microbial profiles implicated in rapid growth and childhood obesity differentially influence children’s weight gain and body composition and determine whether there are differential associations based on genetic and or epigenetic risk factors; Aim 2. Determine how microbial profiles implicated in executive and emotion processes map onto profiles of child temperament and indicators of self-regulation. Establish the impact of these interacting systems on assessments of children’s eating-related behavior and weight trajectories, and whether there are differential associations based on genetic/epigenetic risk; and Aim 3. Uncover and characterize interactions between dietary components, genetics, fecal microbiota, temperament, and cognitive control on obesity risk using Bayesian and neural networks. These outcomes will enable development of algorithms to predict responses to diet within the context of genetic variation, microbiome composition, temperament and other environmental factors.

NIH Research Projects · FY 2025 · 2024-02

SUMMARY This exploratory R21 application seeks to identify and characterize the molecular basis by which the Vacuolating Cytotoxin (VacA), which is the only known intracellular-acting exotoxin secreted by the human gastric pathogen Helicobacter pylori (Hp), recognizes and binds to host cells as a requisite step for host cell intoxication. Chronic infection with Hp is the single most important risk factor for gastric adenocarcinoma, the third leading cause of cancer-related deaths worldwide. Nearly all Hp isolates harbor vacA, which has been demonstrated to be important for colonization in a murine model of Hp infection. Relevant to this application, specific polymorphisms within vacA correlate with both toxin cellular activity and the severity of Hp-associated diseases. In particular, a region located in carboxyl-terminal domain of VacA, known as the “middle (m) region”, segregates into two allelic variants, m1-VacA, which is associated with higher risk of disease, and more potent cellular modulatory activity, and m2-VacA, associated with lower risk of gastric disease, and less potent cellular modulatory activity. Although incompletely understood, several studies have suggested that m1-VacA and m2-VacA may differ in host cell receptor specificity, which is a critical determinant of toxin cell tropism. Moreover, results from extensive phylogenetic analyses suggest that the m1- and m2- forms of VacA may possess different cellular activities that bestow a selective advantage for maintaining both alleles in the human population. Previous studies in the PI’s laboratory identified the abundant plasma membrane surface sphingolipid, sphingomyelin (SM), as an important determinant for m1-VacA binding to the cell surface of host cells as an important determinant of toxin cellular activity. Moreover, in vitro experiments indicate that VacA preferentially binds to SM over other common membrane lipids. These and other findings support our overall hypothesis that SM functions as a cell surface receptor for m1-VacA. Nonetheless, essentially nothing is known about how VacA recognizes and binds to the toxin’s sphingolipid receptor. Moreover, it is not currently known whether SM-dependent toxin cell surface binding and cellular activity, which we discovered to be associated with m1-VacA, are properties that extend to m2-variants of the toxin. This application proposes studies to address these gaps in knowledge in the context of two inter-related, but not co-dependent Specific Aims. In Aim 1, we propose to identify the SM-receptor binding site of m1-VacA, using both biochemical and computational approaches. In Aim 2, we will extend these approaches to evaluate whether the importance of cell-surface SM for m1-VacA, extends also to m2-VacA. Completion of these exploratory studies will address for the first time whether SM-receptor dependent cell binding and activity is a shared characteristic of both m1- and m2-toxin allelic variants, and will provide the framework for future studies to not only better understand both the molecular basis and consequences of VacA allelic variation, but also set the stage for structure-based inhibitor development to block the very earliest stages of VacA cellular intoxication.

NIH Research Projects · FY 2026 · 2024-02

PROJECT SUMMARY/ABSTRACT Between 25–44 million U.S. adults are estimated to have difficulties hearing in background noise despite having normal audiometric thresholds. These difficulties can negatively impact health and quality of life. Currently, there is no consensus on how to diagnose or treat these individuals. The long-term objective of this research program is to translate knowledge of the auditory mechanisms underlying speech-in-noise (SIN) recognition to improve the diagnosis and treatment of difficulties hearing in background noise. One potential mechanism is the medial olivocochlear (MOC) reflex, an ear-brain network in which the brainstem reduces the response of the inner ear to background noise. Previous studies in humans have yielded conflicting results regarding the association between the MOC reflex and SIN recognition. These discrepant findings may be due, in part, to lack of inclusion of individuals with SIN recognition difficulties. It is also possible that the reduction in masking produced by the MOC reflex reduces listening effort in the presence of background noise, but this area has not been investigated thoroughly. Finally, the contribution of the afferent (ascending) drive to the measured MOC reflex strength remains unknown. The proposed studies will address these gaps in knowledge through three aims. Two groups of age- and sex-matched adults with normal hearing will be recruited (n=104 per group). One group will have self-reported SIN recognition difficulties and one group will have no self-reported SIN recognition difficulties, as assessed using a validated questionnaire. Aim 1 will determine the ability of MOC reflex strength to predict self- reported SIN recognition difficulties. The strength of the MOC reflex will be assessed using contralateral inhibition of otoacoustic emissions, a non-invasive measure of efferent control of the inner ear. We hypothesize that MOC reflex strength is a significant predictor of SIN recognition group classification. Aim 2 will determine the association between MOC reflex strength and listening effort. The same participants from Aim 1 will perform a word recognition in noise task at two signal-to-noise ratios. Listening effort will be quantified by verbal response time and self-report. It is hypothesized that MOC reflex strength is a significant predictor of listening effort, and the strength of the association between MOC reflex strength and listening effort depends on the signal-to-noise ratio of the speech task. Aim 3 will determine the contribution of afferent drive to MOC reflex strength. The same participants from Aim 1 will undergo auditory brainstem response testing and MOC reflex testing. Afferent drive will be quantified as the amplitude of wave I of the auditory brainstem response. Associations between afferent drive and MOC reflex strength will be assessed using correlational analyses. This aim is exploratory in nature. The results of these studies will lead to an improved mechanistic understanding of the functional role of the MOC reflex. Additionally, the results will contribute to the development of better diagnostic tests and interventions for difficulties with SIN recognition and listening effort.

NSF Awards · FY 2024 · 2024-01

Humanoids are robots that mimic human form and function. Such robots can manuever in human-centered environments and handle human tools. This is important for dull, dirty, and dangerous tasks that are unappealing or risky for people, such as encountered in disaster response. The 2012 DARPA Robotics Challenge demonstrated humanoids mimicking first responder tasks like navigating rough terrain, climbing ladders, clearing debris, breaching walls, turning valves and driving vehicles. A decade later, these outcomes have translated into social benefits. Beyond disasters, people often suffer from tedious and strenuous work on assembly lines. The car industry is investing in humanoid robots to offset worker occupational injuries. Market forecasters thus see humanoids as a multi-billion dollar industry by 2034. However, current humanoids are still expensive, fragile, and move slowly. This demands more academic research to advance the state-of-the-art. This planning project assembles the research community to identify what is needed for the next generation of humanoids, ones that are more affordable, rugged, and moves with motions and speeds akin to people. The outline of this project's activities involves capturing and disseminating the needs of the research community. Three task forces will capture inputs from a diverse research community on (1) electro-mechanical design; (2) software architecture and control systems; and (3) mixed-reality and data-driven learning. These task forces will respectively hold hybrid workshops in universities in Lafayette (Purdue), Boston (Northeastern) and Philadelphia (Drexel). These workshops bring a diverse community in robotics, computer vision, machine learning, human-robot interaction, VR/AR digital twins, natural language understanding, brain-machine interfaces, advanced cloud and edge computing, high bandwidth communications, algorithmic and communication foundations for advanced operating systems, intuitive programming languages, and trustworthy computing. This process serves to identify both the hardware and software infrastructure the community needs to yield an affordable, durable, and customizable humanoid. Finally, the task forces will share community inputs at the flagship IEEE International Conference on Robotics and Automation (ICRA) in Atlanta 2025. The net effect will be a comprehensive list of technical design requirements. This will then be leveraged to propose a NEW or Enhance/Sustain (ENS) Medium or Grand infrastructure grant within the next 2-years. 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 2025 · 2023-12

Project Summary Sperm have a remarkable and still unexplained capacity to survive for extended periods in the oviduct, contrary to the strong innate immune response they elicit in the uterus. Following mating, when semen reaches the uterus, sperm interact with uterine epithelial cells to stimulate an inflammatory reaction. The release of pro-inflammatory cytokines induces a rapid infiltration of polymorphonuclear neutrophils (PMNs) into the uterus. PMNs then release neutrophil extracellular traps and phagocytose the majority of sperm. The few sperm that evade phagocytosis in the uterus move to the oviduct where, in stark contrast, they do not trigger a phagocytic response and can survive for extended periods ranging from hours to months, depending on the species. Indeed, in the isthmic region of the oviduct (nearest to the uterus), the presence of macrophages or neutrophils is rare. The oviduct demonstrates unique immunological privilege within the female reproductive system that enables remaining sperm to avoid elimination by phagocytes. The mechanisms underlying the different responses between the oviduct and the uterus are unknown. But the ability of sperm to survive and evade phagocytosis in the oviduct is critical for fertility. Sperm are coated with sialic acid-terminating glycans (sialoglycans) and changes in sialylation influence the ability of sperm to evade phagocytosis of uterine macrophages. Sialoglycans can interact with several proteins, including Siglecs (sialic acid-binding immunoglobulin-type lectins), the most abundant and best-known receptors for sialoglycans. There are many different Siglec proteins, found most commonly on leukocytes, and they are known for their ability to activate or inhibit the immune system, attract immune cells, and facilitate cell adhesion. However, Siglecs have also recently been localized to non-immune cells such as kidney and prostate epithelium and uterine and cervical epithelium. Using endpoint PCR, we discovered for the first time that 8 Siglecs are expressed in oviduct epithelium (porcine) and expression is biased towards Siglecs that inhibit the immune response. We also found that porcine sperm contain sialylated glycans that are high-preference Siglec ligands. These results led to our overall hypothesis that sperm sialoglycan binding to oviduct Siglecs alters cytokine production through Siglec-downstream signaling. This inhibits the innate immune response, allowing sperm to avoid immune rejection and phagocytosis during the storage period in the oviduct. To test this model using in vivo and in vitro studies, we will determine the role of Siglecs in the oviduct response to sperm by removing sperm sialic acid and blocking individual Siglecs to determine if oviduct cell gene expression, including the production of immune mediators, and chemotaxis is affected. We will determine if sperm interaction with oviduct cells is dependent on direct sialoglycan-Siglec binding. Finally, we will compare Siglec and intracellular signaling protein abundance and localization in the oviduct and uterus to investigate if that is responsible for the different innate immune responses of both organs to sperm. Collectively, these Aims will elucidate the role of oviduct Siglecs and sperm sialoglycans in suppressing the immune response in the oviduct, despite sperm being foreign cells that are largely phagocytosed in the uterus. The results may be used to enhance sperm lifespan in the oviduct and perhaps develop therapies for infertile females.

NIH Research Projects · FY 2025 · 2023-12

Abstract. The emergence of abnormal movement synergies following a stroke presents a major limitation to the recovery of independent function by constraining voluntary movements to stereotypical muscle coactivation patterns. The resulting expression of the flexion synergy limits arm/hand function, like reaching and hand opening; and has also been reported to be linked to hyperactive stretch reflexes or spasticity. Previous studies found that flexion synergy and spasticity are associated with the recruitment of contralesional descending cortico- bulbospinal pathways. However, how the somatosensory system adapts to this change in the use of motor pathways and the role of adaptive sensory feedback to the abnormal motor control of the paretic arm remain largely unknown. The ascending sensory pathways that convey somatosensation from the paretic arm project contralaterally to the primary sensory cortex in the lesioned hemisphere. Our preliminary data, however, suggests that, in individuals that express the flexion synergy and spasticity, this sensory information is subsequently transferred to the contralesional hemisphere, a process that may support the manifestation of the abnormal movement patterns in hemiparetic stroke. The overall goal of the proposed research is to examine the pathophysiology of this maladaptive hemispheric somatosensory “shift” and its relationship to the upper limb motor impairments following a hemiparetic stroke. The results will lead to a greater understanding of abnormal limb synergies and spasticity by closing the sensorimotor loop, which should provide a novel means by which to therapeutically prevent and mitigate the emergence and expression of upper limb motor impairments, following a stroke. The proposed research aims to test the following key hypotheses in our specific aims: Following a unilateral motor stroke, a hemispheric shift in somatosensory processing provides sensory feedback to support the maladaptive hemispheric shift in the motor system. This hemispheric sensory shift not only influences volitional movement control which contributes to the expression of the flexion synergy (Aim 1), but also the transcortical loop of the stretch reflex that is related to the hyperactive stretch reflexes (or spasticity) and the increased onset delay of the long-latency stretch reflex (Aim 2). Furthermore, the hemispheric sensory shift, as a result of neuroplasticity in an injured brain, can occur in the absence of motor output; and this sensory shift can indicate the extent of motor deficits (Aim 3). By testing these hypotheses, the proposed research will improve our understanding of the role of sensory feedback in post-stroke motor impairments. This should allow for the determination of motor deficits from a new sensory perspective for more impaired individuals or acute/subacute patients who have difficulty performing motor tasks. Furthermore, the knowledge gained in this study will facilitate the future development of targeted, hypothesis-driven therapeutical interventions that aim at reducing maladaptive cross-hemispheric sensory-motor connectivity during recovery thus, promoting motor function without inducing abnormal synergy and spasticity impairments.

NIH Research Projects · FY 2025 · 2023-12

Abstract Seasonal influenza A viruses (IAV) cause hundreds of thousands of deaths every year, despite widespread pre- exposure and vaccination. IAV persists in the human population by continually evolving resistance to herd immunity through a process known as antigenic drift. The evolutionary potential of RNA viruses like IAV is often considered enormous due to their rapid replication and high mutation rates. In reality, the evolutionary potential of IAV is highly constrained by the need to maintain a wide array of molecular functionality in a tiny genome. The specific constraints limiting IAV evolution are very poorly characterized and defining them is critical for understanding and potentially predicting the specific evolutionary pathways most likely to be taken by these viruses. We discovered that phenotypic variation in the viral neuraminidase (NA) gene results in the viral hemagglutinin (HA) gene taking divergent mutational pathways to escape neutralizing antibody pressure. These data suggest that the need to maintain a functional balance between the opposing activities of the viral glycoprotein genes (HA and NA) significantly constrains how the virus evolves to escape from host immune pressure. We hypothesize that these viral constraints, along with additional constraints imposed by the host environment, play significant roles in shaping the specific pathways of IAV antigenic evolution that occur in humans. We will use a combination of in vitro and in vivo experimental evolution and mechanistic approaches to define the specific host and viral factors that constrain the antigenic evolution of the HA gene. In Aim 1, we will quantify phenotypic variation amongst recently circulating NA genes and quantify how this phenotypic variation alters the evolutionary landscape of the HA gene. In Aim 2, we will explore how natural phenotypic variation in NA influences antigenic escape in vitro and in vivo. Finally, in Aim 3, we will define how changes in the host environment and sialic acid profile influence the potential for recent human seasonal H1N1 viruses to escape from humoral immune pressure. Collectively, these studies will deepen our mechanistic understanding of the antigenic evolution of seasonal influenza viruses in humans.

NIH Research Projects · FY 2025 · 2023-12

The inferior colliculus is a major integration site in the central auditory system. Rate tuning for certain behaviorally-important sound features, such as amplitude modulation, is first elaborated upon in the inferior colliculus, suggesting that it plays an essential role in complex sound processing. Dysfunctional inferior colliculus organization has been seen in a number of disorders of auditory processing, including tinnitus, dyslexia and schizophrenia. Unfortunately, our understanding of IC circuitry, particularly amongst its subdivisions, remains limited. We recently found an unexpected degree of functional heterogeneity in a substructure within the inferior colliculus known as the dorsal cortex (DC). Previous work has suggested that the DC does not have subdivisions or a tonotopic arrangement. However, using two-photon imaging of the DC which allows dense sampling of its surface, our group and others have found two mirror-image tonotopic maps on the DC surface. These maps divide the DC into a lateral portion (DCL) and a medial portion (DCM). We have further found that the DCL shows strong preferences for amplitude-modulated white noise, whereas the DCM shows preferences for pure tone unmodulated sounds. These data suggest that there may be at least two functionally distinct nuclei within the DC. Here, we will further characterize these functional differences between DCM and DCL and will determine if there are differences in response properties to complex sounds, and will determine if DCM and DCL show differential plastic responses to noise exposure. Successful completion of this work has the potential to add clarity to our currently murky understanding of the role of the DC in auditory processing and potentially to define new brain subregions in this structure. More broadly, given the importance of the inferior colliculus in auditory processing, this work will provide additional insights into the general organization architecture of the inferior colliculus which will facilitate a greater understanding and targeted therapies for its disorders.

NIH Research Projects · FY 2025 · 2023-09

This study is part of the NIH’s Helping to End Addiction Long-term (HEAL) initiative to speed scientific solutions for the overdose epidemic, including opioid and stimulant use disorders. The NIH HEAL Initiative bolsters research across NIH to address the national opioid public health crisis and improve treatment for opioid misuse and addiction. Moment-to-moment infant-parent interactions are a central context in which infants learn to regulate emotions. Investigating infant-parent interactions in which emotion regulation unfolds is particularly important for infants at risk for emotion dysregulation and/or relationship disturbance, including infants with prenatal substance exposure. Yet, current state-of-the art methods to assess infant emotion regulation and infant-parent interaction predominantly rely on brief laboratory tasks. These procedures pose burdens on participants, especially families experiencing demographic and psychosocial risk, and place limits on generalizability and ecological validity of findings. Technological advances in (a) machine learning methods, including deep learning approaches that mine for complex patterns in raw unlabeled data, and (b) wearable sensors have the potential to transform our ability to capture infants’ moment-to-moment emotional experiences in their real-world environments, while also lowering burden on families participating in infant research. With these issues in mind, we will develop next-generation methods to assess infant emotion regulation and infant-parent interaction. In doing so, we will use LittleBeats, an infant multimodal wearable device developed by our team, to collect time-synced data on infant and parent vocalizations (via microphone), infant motor activity (via motion sensor), and infant cardiac vagal tone (via electrocardiogram [ECG]) for extended periods of time (~8-10 hours per day) in the home. We propose three specific aims. First, we will validate a virtual visit protocol for the gold-standard Still Face Paradigm, which is typically conducted in a laboratory setting, for assessing emotion regulation among infants during the first year of life. Second, we will validate multimodal deep learning algorithms to detect infant emotional states in real time using LittleBeats audio, ECG and motion data. Third, we will validate deep learning algorithms to detect and label vocalization types of infants (babble, fuss, cry, laugh) and parents (infant-direct speech, adult-directed speech, sing, laugh), which create the build blocks of infant-parent vocal interactions, such as turn taking. By bringing together innovative wearable technology with cutting-edge deep learning algorithms, we aim to advance understanding of the mechanisms through which prenatal substance exposures contribute to adverse outcomes. Further, prenatal substance exposure is a heterogeneous phenomena that transacts with environmental risk and protective factors, thereby making a one-size-fits-all approach ineffective. By monitoring moment-to-moment changes in infants’ emotion regulation, combined with deep learning algorithms that detect and classify infant-parent interactions during moments when infant show signs of distress, the proposed methods have the potential to transform our understanding of the dynamic processes through which prenatal substance exposure leads to poor outcomes and pinpoint protective factors that promote optimal development.

NIH Research Projects · FY 2024 · 2023-09

PROJECT SUMMARY The suicide rates among U.S. military service members and Veterans (MV) remain alarmingly high. The suicide rate for active military service members has increased from 20.4 suicides in 2014 to 28.7 suicides in 2020 per 100,000. Veterans’ suicide rates have remained high, approximately 2 times higher than the general population (14.5 per 100,000). Unfortunately, the current suicide approaches from the Department of Defense and the Department of Veterans Affairs are insufficient. Further, recent literature shows inconsistent findings of suicide causes and suicide attempts across measures and time points, and lack of effectiveness of suicide screening and interventions. This is problematic for proactively and effectively preventing and stopping suicide among the MV populations. Additionally, less research has focused on suicide ideation than suicide completion/deaths, which means we are ultimately missing the first chance to stifle suicide and address risk factors. We will use secondary datasets and innovative machine learning (ML) to develop early screening and intervention modeling to address military suicide issues. The study will apply data-driven ML to improve MV healthcare quality by accelerating the implementation of patient-centered outcomes research, using several personalized-contextual variables of 10 clinically applicable dimensions, to predict suicide risk levels. Further, we will develop person-centered, context-sensitive ML modeling for suicide ideation (SI) and suicide attempt (SA) data-visualization profiles, which will assist in clinical screening, evaluation, and intervention. Our specific aims are to (1) establish ML algorithms detecting SI/SA at different military statuses to inform clinicians and (2) develop an SI/SA cross-sectional and longitudinal risk data-visualization profile for clinicians. Our overarching goals are to demonstrate (1) a new SI/SA screening paradigm and (2) a new SI/SA prevention, evidence-based intervention, and policy-making model for the MV populations. We harness big data and innovative ML applications to provide a 360-degree view of MV patients, which will improve healthcare quality and MV patient outcomes, specifically decreasing SI/SA. Our project will exemplify the Healthcare Effectiveness and Outcomes Research mission to make healthcare safer, higher quality, more accessible, equitable, and affordable. Most importantly, we will ensure that clinical professionals and relevant stakeholders who serve the MV populations can understand and apply the study’s findings.

NIH Research Projects · FY 2025 · 2023-09

Identifying Convergent Circuit Disruptions Across Genetically-Distinct Rat Models of ASD Summary: Recent advances from human genetic and animal studies have greatly increased our understanding of the molecular and cellular basis of autism spectrum disorders (ASD). Connecting these risk factors to clinical symptoms in autism remains a significant challenge that has impeded the development of ASD therapies, as evidenced by disappointing results from recent large-scale clinical trials. A fundamental question is if distinct ASD mutations converge on shared disease mechanisms at some level of neuronal function to ultimately give rise to the behavioral and neurocognitive phenotypes that define autism. Identifying these pathophysiological convergence points is essential for developing treatment strategies that may generalize across genetically heterogenous forms of ASD. We have previously shown that rodent models of the two most common genetically-defined causes of autism— Fmr1 KO mouse model of Fragile X syndrome (FX) and Tsc2+/- mouse model of tuber sclerosis complex (TSC)— exhibit opposite synaptic and cellular phenotypes that responded to opposite pharmacological interventions, despite sharing a molecular pathway and presenting with similar behavioral phenotypes. This proposal will determine if Fmr1 and Tsc2 mutations converge on common circuit disruptions that can account for shared behavioral phenotypes in these disorders. We will address this question through the lens of the auditory system, as auditory processing impairments are a common and debilitating sensory phenotype in ASD that directly impacts communicative and social behavior while also providing robust and translationally-relevant behavioral and physiological read-outs, due to its well- characterized neuroanatomy and evolutionary conserved nature. Specifically, this proposal will test the hypothesis that circuit hyperexcitability due to altered excitatory/inhibitory synaptic balance and dysregulated parvalbumin expressing (PV+) interneuron function is a convergent disease mechanism that leads to shared deficits in auditory perception and information processing in rat models of FX and TSC. This will be accomplished by combining the unique behavioral advantaged of rat models with in vivo and ex vivo electrophysiological recordings, cell-type specific optogenetic manipulations, and molecular profiling techniques. Determining how Fmr1 and Tsc2 mutations lead to auditory processing deficits and neural circuit dysfunction will not only help identify novel therapies for disabling sensory phenotypes in these disorders, but may shed light on recurring pathophysiological motifs that generalize across neurocognitive domains and extend to diverse forms of ASD.

NIH Research Projects · FY 2025 · 2023-09

Abstract The stunning clinical success of Gleevec (imatinib) two decades ago appeared to usher in a new era for cancer treatment, whereby a molecular defect in a patient’s tumor was known and could be exploited with a selective drug. A suite of such selective drugs were envisioned, 100s of different drugs that could be prescribed to appropriate patients based on tumor profiling of 100s of different potential defects. Unfortunately this vision has not come to pass, and, with only a handful of approved drug-target pairs, the full potential of personalized medicine in oncology has not been realized. While drugs such as imatinib (and vemurafenib, osimertinib, and a few others) have been game-changers for those cancer subtypes (e.g., certain cancer types with Bcr-Abl translocation, BRAFV600E mutation, and EGFRT790M mutation, respectively), there remain 100s of cancer subtypes and hundreds of exploitable molecular defects that are not matched with drugs. The plodding progress of traditional drug discovery in this realm suggests new approaches are needed to fully realize the potential of targeted therapy for oncology. My lab has developed a discovery platform – from compound synthesis, to cell culture, to target identification, to sophisticated animal models, to translation – that has resulted in 4 novel cancer drugs licensed and moving to cancer patients in 15 years. Building off the observation that truly selective drugs that are successful in human cancer patients also show exquisite selectivity in cell culture, we have identified compounds that have wide activity differential for killing sensitive cell lines versus non-sensitive cell lines; through this method we have identified compounds with >100-fold selectivity and that have advanced (or are advancing) to human cancer patients. In work for the OIA we will create an unprecedented collection of complex-and-diverse compounds, with the novel twist that these compounds will be biased for anticancer activity through incorporation of an electrophile. Compounds able to induce selective death in a panel of >100 cancer cell lines and normal cell types will be advanced through medicinal chemistry optimization. Top compounds will then progress through two parallel tracks, 1) discovery of the biological target (basis for the anticancer selectivity), with our experience showing that in most cases this work will reveal novel exploitable defects in cancer, and 2) translational advancement through the pharmacokinetic/toxicology/efficacy studies and assessment of the ability to engage the immune system, experiments needed to move the very best compounds to clinical trials in cancer patients. We have demonstrated the ability to accomplish all parts of this workflow at a high level, enlisting key collaborators as needed. Through this OIA we will increase our output 2-5-fold, meaning the discovery and development of 4-10 novel cancer drug/target pairs during the 7 year OIA. As importantly, this work will provide a blueprint for success that others can mimic, which will ultimately enable full realization of the potential of personalized medicine, with hundreds of drugs for the hundreds of different cancer subtypes.

NIH Research Projects · FY 2026 · 2023-09

Project Summary/Abstract: In 2020, 10% of U.S. infants were born preterm and ~2%, or 60,000 infants, were born very preterm (VPI; <32 weeks PMA). VPI infants are at high risk for of substantial medical complications, including necrotizing enterocolitis (NEC). In VPI, advancing and maintaining nutritional support reduces disease risk and improves neurodevelopmental outcomes; however, up to 25% of preterm infants demonstrate feeding intolerance, which may be benign or may progress to NEC. However, precise measures and clinical tools that reliably differentiate benign, intestinal immaturity from life-threatening symptoms are lacking. Therefore, the overall objective of this application is to establish intestinal host and microbial biomarkers of intestinal function from an existing, longitudinal, prospective cohort of 400 analyzable VPI and to relate those biomarkers to the spectrum of intestinal function, from consistent enteral nutrition tolerance to intermittent intolerance to ischemic injury. For this purpose, we will utilize our novel non-invasive (exfoliated mucosal cell) methodology to simultaneously assess host- microbiome interactions in the VPI gut. Our central hypothesis is that the transgenomic cross-talk between intestinal mucosal cells and the fecal metagenome and metabolome will provide mechanistic insight into the spectrum of clinical presentations ranging from normal gut developmental biology to abnormal pathophysiology. Three specific aims will test our central hypothesis. Aim 1 will annotate the host exfoliated mucosal cell transcriptome and fecal bacterial metagenome and metabolome profiles to identify biomarkers for preterm infants who have consistent tolerance to enteral feeding or who are diagnosed with feeding intolerance. Aim 2 will annotate the host exfoliated mucosal cell transcriptome and fecal bacterial metagenome and metabolome profiles to identify biomarkers for preterm infants who are diagnosed with feeding intolerance compared to those who develop ischemia. Aim 3 will utilize machine learning algorithms to construct putative diet-health outcome driven Artificial Neural Networks (ANNs). Completion of these aims will provide the necessary data to develop predictive algorithms to enable identification of at-risk VPI who would benefit from precision medicine/nutrition guided interventions targeting specific risk factors.

NIH Research Projects · FY 2025 · 2023-09

ABSTRACT Modern medical imaging systems comprise complicated hardware and sophisticated computational methods. Given the sheer number of system parameters that impact image quality, the large variety in objects to be imaged, and ethical concerns, the assessment and refinement of emerging imaging technologies via clinical trials often is impossible. For these reasons, there is great interest in virtual imaging trials (VITs) that permit the automated simulation and analysis of clinically relevant imaging experiments. During the development and refinement of new imaging technologies via VITs, there is an important need for assessing objective image quality measures (OIQMs) that quantify the best possible utility of the resulting images for different diagnostic tasks—independent of the ability of the observer (human or algorithm) who interprets the images. In effect, such OIQMs can reveal the extent to which task-related information is present in imaging data and thus can be potentially extracted by a human observer or other numerical algorithm that is sub-optimal; this can permit the identification of opportunities for improved image processing or other technology changes that lead to improved performance on diagnostic tasks. The broad objective of the proposed research is to address this challenge by developing the next generation of open source and modality-agnostic computational methods for computing OIQMs that quantify the best possible performance of an imaging system—the so-called ideal observer performance—for clinically relevant tasks. Estimation of the best achievable performance of medical imaging technologies using realistic stochastic digital object phantoms and clinically relevant diagnostic tasks has been a holy grail for the medical image-quality assessment field, and the lack of success to date has limited the field to unrealistic object models and tasks for decades. When employed in VITs, our new methods will permit assessment of the amount of task-relevant information in image data and will accelerate the refinement and translation of promising new imaging technologies to the clinic. The Specific Aims of the project are: Aim 1: To develop and validate ambient generative adversarial networks (AmGANs) for creating ensembles of clinically relevant digital phantoms; Aim 2: To develop methods for estimating the optimal task performance of an imaging technology; Aim 3: To use the developed tools for assessing deep learning-based image restoration. The developed computational tools for computing OIQMs will be made open source. This will open entirely new avenues for assessing and refining emerging medical imaging technologies with a level of rigor and clinical relevance previously not possible.

NIH Research Projects · FY 2025 · 2023-09

Project Summary This Focused Technology Research and Development proposal addresses the urgent need for new tools to perform in vitro site-specific modification of DNA and RNA nucleobases of long nucleic acid substrates. The biochemistry, biophysics, and biology of DNA and RNA are heavily influenced by particular nucleobase modifications. However, studies of these modifications are often limited by the ability to synthesize the modified nucleic acids. Therefore, innovative new technologies are required to circumvent the limitations of the existing chemical and enzymatic modification approaches. DNAzymes (deoxyribozymes) are artificial DNA sequences with enzymatic function, analogous to protein enzymes as catalytic sequences of amino acids. Although DNAzymes are unknown in nature, they can be identified de novo in the laboratory by starting with random DNA sequence pools and performing in vitro selection for the desired enzymatic activity. DNAzymes are operationally simple to obtain and use: they are readily prepared commercially by solid-phase synthesis, and they easily modify their substrates in simple aqueous incubation conditions with standard buffers and salts. DNAzymes have been identified for a growing range of catalytic activities, but most applications of DNAzymes are limited to the two long-known reactions of RNA cleavage and hemin-dependent peroxidation, which are unrelated to DNA and RNA nucleobase modification. In the proposed studies, DNAzymes will be identified for a qualitatitvely new approach to site-specific in vitro modification of DNA and RNA nucleobases, by either N-acylation or (via reductive amination) N-alkylation at N4 of cytosine, N2 of guanine, and N6 of adenine. Rather than relying on natural protein enzymes, either as found in nature or evolved by directed evolution, entirely new DNAzymes whose sequences are unconstrained by natural evolutionary history will be identified by in vitro selection. Three specific aims are proposed. In Aim 1, in vitro selection will be used to identify DNAzymes for N- acylation of C, G, and A nucleobase amines in DNA and RNA substrates. In parallel Aim 2, in vitro selection will be used to identify DNAzymes for N-alkylation by reductive amination of C, G, and A nucleobase amines in DNA and RNA substrates. In both of these aims, the electrophilic reaction partner will be either an oligonucleotide or a small molecule, as a tunably fluorinated aryl ester for the acyl donor in Aim 1, and as an aromatic or aliphatic aldehyde, or activated imine variant thereof, for the reductive amination partner in Aim 2. In Aim 3, the DNAzymes from Aims 1 and 2 will be characterized with regard to their substrate sequence scope and refined by reselection for improved function, to facilitate practical use as an innovative new technology for site-specific DNA and RNA nucleobase modification. By the conclusion of the proposed efforts, we will have established DNAzymes as an important new technology for in vitro site-specific DNA and RNA nucleobase modification by N-acylation and N-alkylation.

NIH Research Projects · FY 2024 · 2023-08

The main objectives of this proposal are to (i) identify volatile organic compounds (VOCs) produced by Pseudomonas aeruginosa (PA) that cause goblet cell metaplasia (GCM) and mucus hypersecretion in Cystic Fibrosis (CF) airways, (ii) characterize the mechanism of induction, and (iii) determine its importance to CF pathogenesis. PA is a frequent cause of acute and chronical lung infections, including CF and non-CF bronchiectasis, ventilator-associated pneumonia (VAP), and chronic obstructive pulmonary disease (COPD). Infections by PA are associated with a significant increase in morbidity and mortality in these patients. One of the major pathological features shared by these diseased lungs is in their dysregulated, hypersecretion of mucus and failure in clearance, resulting in clogged airways that reduces gas exchanges and deteriorates lung function. PA is known to secrete a variety of secondary metabolites, including the VOCs. In recent years, microbial VOCs detected in the breath of patients have been scrutinized as potential biomarkers for disease diagnosis, including CF, VAP and COPD. Unfortunately, the biological effects of VOCs on lung pathogenesis, including GCM and mucus hypersecretion, are poorly understood. In preliminary studies, we demonstrate that several dominant species of PA VOCs previously identified in the breath of people with CF (e.g., 2-aminoacetophenone, 2-AA) induce GCM and mucus hypersecretion in human airway epithelial cells, and in mice. In this application, we will test the hypothesis that VOCs are major contributors of GCM and mucus hypersecretion in the diseased airways. Aim 1 will characterize major PA VOC species individually and in a cocktail that are capable of inducing GCM and mucus secretion in normal human primary bronchial epithelial cells (NHBECs) vs. CF diseased primary bronchial epithelial cells (CF-DHBECs) cultured in the air-liquid interface (ALI), under normoxic and hypoxic conditions, mimicking normal and CF airways, respectively. Top VOCs will be further examined individually or in cocktail for their ability to induce GCM and mucus hypersecretion in wild-type vs. b-ENAC overexpressing (Scnn1b-Tg) CF mice. Finally, both wild-type PA strain PA14 and its isogenic DpqsE mutant deficient in 2-AA will be compared for their ability to induce GCM and mucus hypersecretion in wild-type vs. b-ENAC mice. Aim 2 will examine mechanisms of GCM and mucus biosynthesis induction by PA VOCs. First, we will determine whether VOCs activate pro-GCM pathways, including AhR and EGFR-AKT/ERK1/2, to inhibit the expression of FOXA2, a key regulator of airway mucus homeostasis. Then, we will examine if VOCs also induce GCM and mucus biosynthesis by modulating macrophage polarization, neutrophil influx and Th1/Th2/Th17/ILC2s immune responses, which are known drivers of GCM and mucus hypersecretion in diseased airways. Completion of the proposal will reveal the mechanistic link between VOCs and excessive mucus in CF and other diseased lungs, and, potentially novel therapeutic approaches against bacterial pneumonias.

NIH Research Projects · FY 2024 · 2023-08

Abstract: In this proposed research project, we seek to develop an advanced brain SPECT system that offers a unique hyperspectral imaging capability substantiated by an excellent energy resolution (e.g., <2.5 keV at 140 keV and <3.5 keV at 250 keV) across a wide energy range (25-600 keV), and at the same time deliver a 1- mm spatial resolution and a very high sensitivity to allow detailed visualization of multi-tracer uptakes in various brain regions. This device could potentially have a transformative impact on brain research by allowing for microscopic, multi-functional assessment of brain functions under various experimental conditions. This proposed research project will integrate the disruptive high-performance 3D CZT imaging-spectrometer technologies with a novel synthetic compound eye (SCE) camera design, as well as an innovative iterative image reconstruction method using deep-learning based priors, to develop a next-generation clinical brain SPECT imaging system with transformative spatial resolution and imaging sensitivity unattainable previously. The long-term objective is to apply this innovative imaging system to human brain SPECT studies using a collection of various SPECT radiotracers, and develop and advance physiological parametric imaging methodologies, in order to investigate the long-standing issues in neurobiology and improve our understanding of the interplay and relationship among cerebral blood flow and perfusion, brain tissue oxygenation, neuronal cell metabolism, and brain cell tracking under different cognitive challenges and biophysical conditions in healthy and in disease. We would envision the proposed system to serve as a unique imaging platform to significantly advance our understanding of neural cell biology and regional brain functions in response to various cognitive, behavioral, and physiological challenges by employing these unprecedentedly innovative SPECT imaging methodologies in order to assess all relevant quantitative physiological measurements that will be interpreted in an integrated fashion and synergistically so that new perspectives in brain research unattainable previously can be formulated.

NIH Research Projects · FY 2026 · 2023-08

Alcohol’s ability to improve mood in the face of stress is among its most prized reinforcing properties, long held by researchers to be of critical importance for the understanding of the etiology of alcohol use disorder (AUD). Drinkers overwhelmingly report that the mood-enhancement they gain from alcohol is most pronounced in the context of stress, and individuals who report higher levels of stress relief from alcohol are at risk for developing AUD. But attempts to capture this key element of alcohol reinforcement using experimental methods have yielded strikingly inconsistent results. One remarkable feature of the extant experimental literature is that, in attempting to capture alcohol’s stress-relieving effects, researchers have strayed far outside the range of stressors typically encountered in everyday drinking settings, contexts that are overwhelmingly social in nature. Here, we harness the power of stressful stimuli that emerge naturally within everyday contexts, focusing on social novelty as a compound stress-trigger ubiquitous to real-world heavy drinking settings. Building on our prior work indicating enhanced alcohol reward in novel compared with familiar social context, together with pilot findings pointing to potential links between social novelty and hazardous patterns of drinking, we draw on innovative methods and measures to further build the understanding of social-contextual factors driving consumption. Specifically, we leverage multi-participant neuroimaging recording arrays (i.e., hyperscanning) to pinpoint both inter- and intra-brain processes underlying alcohol reinforcement, a mechanistic analysis we complement with ambulatory and longitudinal methods for tracing real world patterns of consumption. Participants (N=240) will attend two experimental laboratory sessions, on one of which they will consume alcohol and on the other a control beverage. Participants will complete tasks in the company of either a stranger or familiar individual while EEG is recorded from both participants simultaneously. Participants will also engage in a 14-day ambulatory assessment period during which drinking will be assessed continuously via transdermal alcohol biosensor while social context is explored via in-vivo photographic image- capture methods. Finally, longitudinal changes in hazardous drinking and AUD symptoms will be assessed for 24 months post-baseline. The aims of the project are to: 1) Explore diminished threat sensitivity and enhanced social engagement as mechanisms driving alcohol reward in novel social context; 2) Examine social reward- attentive processes as well as social-contextual novelty as predictors of hazardous drinking and AUD. The proposed research contributes to the understanding of AUD by addressing one of the most fundamental questions in the alcohol literature—the question of why people drink. Further, representing a critical step towards building a contextually-informed, mechanistically precise model of AUD etiology, the proposed study might have a variety of key implications including for refining harm-reduction and prevention programs, reducing rates of relapse, informing public health policy, and the early identification of those at risk.

NIH Research Projects · FY 2023 · 2023-08

Project Summary/Abstract Reductions in telomere length (TL), a biomarker of cellular stress, are linked with later atypical human development, including elevated risk for psychopathology, chronic disease, and mortality. Understanding factors that either positively or negatively impact children’s TL is needed to enhance children’s long-term health and well-being. Currently, stress-inducing adverse experiences (risk exposures), such as household economic strain, exposure to violence, and neighborhood disadvantage, have both an independent and a dose- dependent effect on TL, with the occurrence of each additional adverse experience accelerating TL shortening. Prior work in this area is limited, however, in that it has conceptualized risk exposures as static rather than dynamic and has failed to investigate protective factors that mitigate the effect of cumulative risk exposures on children’s outcomes. The proposed project aims to (1) examine how fluctuations in cumulative risk exposure are prospectively associated with children’s telomere length and (2) examine how parents’ supportiveness towards each other serves as a moderator between cumulative risk exposure and children’s telomere length. To achieve these aims, the research team will conduct a dyadic, longitudinal analysis of data from the Fragile Families and Child Wellbeing Study (FFCWB). Findings from this project will contribute to a broader understanding of factors that positively or negatively impact children’s TL and elucidate sensitive periods in which cumulative exposure to adverse experiences may be most harmful for children.

NIH Research Projects · FY 2025 · 2023-08

Abstract While a growing arsenal of drugs is available to treat specific molecular abnormalities across cancers, therapy effectiveness can now be predicted by detecting specific genomic circulating tumor DNA (ctDNA) in plasma. While next-generation sequencing (NGS) can provide a comprehensive readout of genomic tumor variants that may provide biological and clinical efficacy insights, its cost, complexity, and sample-to-answer timeframe are not compatible with frequent, routine, point of care diagnostics. Meanwhile, currently available laboratory-based methods for quantifying strategically-selected ctDNA biomarkers in plasma for liquid biopsy lack sensitivity, multiplexing, and workflow simplicity required for clinical needs. A genomic liquid biopsy that can be rapidly performed in a clinical setting in the timeframe of an office visit offers a compelling alternative for identifying the presence, absence, and concentration changes in circulating nucleic acid molecules whose specific base sequences represent mutations that drive cancer-associated cellular processes. Such an approach would enable therapy selection to be performed at the earliest time while facilitating more frequent remission monitoring. To address the gaps in current technology, we seek to develop and rigorously validate a novel assay method called “Activate, Cleave, Capture, and Count” (AC3) that combines two innovative elements. First, we apply a recently-demonstrated photonic crystal (PC) biosensor microscopy technology with digital resolution capability for quantifying surface-captured gold nanoparticle (AuNP) tags. Second, we utilize the CRISPR/Cas system with target-specific guide RNA probes that selectively activate cleavage of ssDNA tethers linking AuNPs to a surface, generating many released AuNPs for each ctDNA molecule. The released AuNPs are subsequently captured on a PC biosensor, where they are digitally counted. Our ”amplify-then-digitize” strategy offers a compelling alternative to digital PCR-based technologies while also circumventing the limitations inherent with thermal amplification, microdroplet partitioning, and fluorescence-based detection. Based upon preliminary results for the detection of cancer-associated ctDNA, AC3 offers a detection limit of 50 zM and a measurement of mutant allele frequency of <0.001%. Importantly, AC3 utilizes a small and inexpensive (~ $7K) detection instrument. In this project, we will apply AC3 for characterization of plasma ctDNA biomarkers across six mutations and characterize performance using spiked-in calibration standards, and in banked human plasma samples. We will rigorously characterize the sensitivity, selectivity, and repeatability of AC3 compared to droplet digital PCR (ddPCR). We envision AC3 as a complement to tissue-based NGS, applied to routine initial cancer screening for therapy selection, monitoring the effects of treatments, and as a remission monitoring tool. Compared with alternatives, the inherently greater sensitivity of AC3 offers opportunities to perform earlier cancer detection, integrate higher levels of multiplexing, and reduce plasma volume requirements.

NIH Research Projects · FY 2026 · 2023-06

PROJECT SUMMARY/ABSTRACT The percent of Gram-negative bacterial infections that are resistant to common antibiotics has increased at an alarming rate over the last decade, and there is now an acute need for the discovery of novel antibiotics effective against multidrug-resistant Gram-negative pathogens. We have made progress understanding the relationship between physicochemical traits and compound accumulation in Gram-negative bacteria, enabling us to convert several antibiotics with Gram-positive-only activity into versions that possess activity against key Gram-negative pathogens. Most advanced is our FabI inhibitor fabimycin; FabI inhibition is a novel strategy with no approved antibiotics that hit this target. The nature of the FabI enzyme is that it is only essential in certain pathogenic bacteria, chief among them E. coli, K. pneumoniae, and A. baumannii; thus while fabimycin is effective against large clinical isolate panels of these pathogens, it has no activity against beneficial commensal bacteria that reside in the gut. A Gram-negative active antibiotic that spared the gut microbiome is without precedent and would be a very significant development, given the well-documented deleterious effects of broad-spectrum antibiotics in causing gut dysbiosis. In addition, our X-ray structures of fabimycin bound to FabI reveal critical interactions between the ligand and the protein backbone, making bacterial resistance much more challenging to arise than if interactions were solely with amino acid sidechains. Indeed, fabimycin has a low frequency of resistance, and resistance in cell culture only evolves over a long period of time. Excitingly, fabimycin is also active in multiple mouse and rat infection models, including those of soft tissue infection, pneumonia, sepsis, and UTI. To become a true clinical candidate the Therapeutic Index (TI) of fabimycin needs to be widened. Herein we propose development of more potent versions of fabimycin through application of a recent understanding of the relationship between compound efflux and structure that has emerged from our laboratories. Applying these lessons to fabimycin will enable us to systematically reduce its efflux liability, leading to MIC values for optimized derivatives that are 5-fold more potent than fabimycin and will thus have the appropriate TI for advancement. We have assembled a team of experts with the full suite of tools needed for this work: medicinal chemistry, understanding of efflux, access to large panels of clinical isolates, sophisticated models of antibacterial efficacy in mice and rats, and detailed pharmacokinetics and toxicology in mice, rats, and dogs, and microbiome studies in mice and dogs. Our Critical Path provides specific criteria for compound advancement and we are guided by best practices for antibiotic drug development as deliniated by the FDA. Our plan is to select the lead candidate by the end of Year 2, and then spend the remaining three years building a sophisticated data package that will facilitate rapid translation of this antibiotic to the clinic.

NIH Research Projects · FY 2026 · 2023-06

Project Summary The correlation between health and income is one of the most persistent observations in the social sciences, supported by research across countries, demographic groups, and time periods. The relationship between income and health is large, emerges early in life, and is present across many indicators considered proxies for health. Despite the striking nature of the association, there is relatively little evidence in the U.S. context on whether income has a causal impact on health outcomes, and less information on what mechanisms may be responsible for such a causal relationship if one exists. Income and health may be correlated because higher income has a direct impact on health (e.g., by allowing individuals to purchase medical care), or health may directly affect income (e.g., because poor health makes it difficult to work). It may also be the case that a third factor—such as education—influences both income and health, driving the observed correlation between the variables. Without the ability to randomize variation in income, discerning the true nature of this relationship is difficult. We propose to provide new evidence from a large-scale, randomized intervention in the U.S. on the relationship between income and mental and physical health through a randomized evaluation of a sustained unconditional cash transfer program being implemented by two non-profit organizations. This program will randomly assign participants to a treatment group that receives $1,000 per month or to a control group that receives $50. Both groups will receive the transfer monthly for three years. We will examine treatment/control differences to estimate the effect of the additional income on behaviors and environmental factors (e.g., nutrition, food security, exercise, substance use, sleep quality, and neighborhood characteristics) that could affect longer-term health outcomes (Aim 1) and on medical care access and utilization (Aim 2). In order to understand the effect of the increase in income on health, we will assess treatment/control differences in subjective measures of physical and mental health as well as blood pressure, height, weight, and blood spots that can be analyzed to provide cholesterol, A1c (a measure of glycated hemoglobin that indicates diabetes risk), and C-reactive protein (Aim 3). We will measure the outcomes associated with these aims using a combination of in person and online survey questions, nutrition diaries (ASA 24), time diaries, and biomarkers collected in person by trained enumerators. We will also conduct long term follow up after the end of the payments. This study will provide groundbreaking, policy-relevant new information on the impact of income on health, healthy behaviors, and well-being.

NIH Research Projects · FY 2026 · 2023-06

PROJECT SUMMARY Neuronal Kv7/KCNQ channels are homotetramers of Kv7.2 and heterotetramers of Kv7.2 and Kv7.3 that are highly expressed in the cortex and hippocampus, key brain regions for seizure, cognition and behavior. They produce voltage-dependent outward K+ current (IM) which potently suppresses neuronal excitability. Dominant mutations in Kv7.2 and Kv7.3 cause early-onset epileptic encephalopathy (EE) with severe cognitive and behavioral deficits, stressing a critical need to understand how EE variants dysregulate Kv7 channels. Our published studies show that Kv7 channels are preferentially enriched at the axonal plasma membrane via calmodulin (CaM) binding to intracellular helices A and B of Kv7.2, which mediates their trafficking from the endoplasmic reticulum to the axonal surface. Epilepsy variants in these helices reduce their axonal enrichment and seizures in mice, underscoring the key role of axonal Kv7 channels in excitability. Importantly, membrane lipid PIP2 is an essential cofactor for opening Kv7 channels as they are potently inhibited by its membrane depletion. However, the PIP2 binding residues that regulate neuronal Kv7 channels in different states (open or closed) and complex (homomers, heteromers, or CaM-bound) are unknown. Our recent work has revealed that the PIP2-binding residues in open Kv7.2 channels are different from those in closed state and CaM-bound open channels, and that select EE mutations of these sites induce both loss and gain of PIP2 sensitivity, and reduce their axonal enrichment. Thus, the PIP2-binding landscape is dynamic and may regulate both function and trafficking of Kv7 channels. The goals of this project are to identify (i) dynamic changes in PIP2 binding residues of neuronal Kv7 channels that control their axonal enrichment and function, (ii) mechanisms by which EE variants disrupt this modulation, and (iii) compounds that reverse this dysregulation. Our central hypothesis is that dynamic and coordinated binding of PIP2 and CaM regulates activation and trafficking of axonal Kv7 channels, whereas EE mutations increase neuronal excitability by impairing formation of this complex. To test this, the present project will execute 3 specific aims using interdisciplinary approach including molecular dynamic simulations, biochemistry, imaging, and electrophysiology. Aim 1 will identify PIP2 binding residues in CaM-bound and unbound Kv7 channels and test if their PIP2 binding and sensitivity are regulated by EE mutations, Kv7 agonists and PIP2 mimetic compounds. Aim 2 will identify how PIP2 binding modulates axonal surface enrichment of CaM-bound and unbound Kv7 channels by examining their exocytosis, endocytosis, and plasma membrane retention. Aim 3 will test if loss- and gain-of PIP2 modulations of axonal Kv7 channels lead to neuronal hyperexcitability in culture and conditional knock-in mice. In contrast to a well- established role of PIP2 in gating modulation of Kv7 channels, this project will provide novel concepts that their PIP2 binding sites change dynamically and modulate both function and trafficking of axonal Kv7 channels to impact IM and neuronal excitability, and reveal novel pathogenic mechanisms of EE variants in Kv7.2 and Kv7.3.