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A Double-Blind Randomized Controlled Trial of Daridorexant for Alcohol Use Disorder

Project Summary/Abstract This R01 application proposes integrating a randomized, double-blinded, placebo-controlled clinical trial into a real-world treatment setting to test whether the dual orexin receptor antagonist (DORA) daridorexant reduces alcohol craving and use and improves total sleep time among patients with alcohol use disorder (AUD) and co-occurring sleep disturbance. DORAs have shown promise in modulating reward and reducing alcohol self- administration in preclinical models. Further, DORAs are FDA-approved for insomnia, are highly efficacious for treatment of sleep disturbance, have a favorable safety profile, and demonstrate low abuse liability. Thus, DORAs are a highly promising treatment for AUD, particularly among persons that have co-occurring sleep disturbance. To this end, the proposed study will recruit individuals from a residential treatment facility, following completion of medically managed withdrawal and stabilization. Eligible participants will be randomized to daridorexant to placebo, and will complete measures of alcohol craving, total sleep time (assessed through both wireless electroencephalography and biometric data collection), and adverse events. Following discharge from residential treatment, participants will continue taking the study medication for two weeks while submitting daily reports of alcohol use, alcohol craving, sleep diaries, and biometric sleep data. Participants will also be prompted to submit three-times weekly random breath alcohol level using a portable BACtrack S80 breathalyzer, and will attend weekly check-in visits to assess adverse events and to confirm daily alcohol reports. A one-month follow-up assessment will be conducted to collect long-term data on alcohol use, AUD symptoms, and sleep. Ultimately, this study has the potential to identify a novel treatment for co- occurring AUD and sleep disturbance, and will address the following specific aims: (1) Test whether daridorexant reduces alcohol craving and post-treatment alcohol use relative to placebo. (2) Test whether daridorexant improves objectively measured total sleep time relative to placebo. (3) Examine the frequency of adverse events in persons assigned to daridorexant relative to placebo. If these aims are supported, then we will also explore whether effects are moderated by insomnia severity. We will also examine if the effects replicate across residential environments (with structured sleep/wake times and close monitoring of medication adherence) and outpatient environments (with self-imposed sleep/wake times and self-dosing). Currently, there are no FDA approved medications indicated for both AUD and insomnia. This innovative strategy aims to address a critical gap by investigating the effectiveness of daridorexant in modulating alcohol craving and alcohol use. This study will contribute to a growing literature on the role of the orexin system in reward and alcohol use.

Calcium signaling in MR1-dependent presentation of Mycobacterium tuberculosis antigens

Project Summary The fundamental role of the immune system is to detect self from non-self. The detection and elimination of microbial infection is critical for human survival. One challenge to the immune system is infection from an intracellular microbe because the microbe masks its presence in a host cell. One strategy of the immune system to detect microbes is the sampling of different kinds of antigens, such as peptides, lipids and glycolipids, by antigen presenting molecules. A fundamentally unique arm of the immune system is MR1, which is an antigen presenting molecule that is intracellular, ubiquitously expressed across tissues, and detects small molecules derived from microbial metabolism. These features suggest that MR1 is poised to detect intracellular microbes. MR1 presents antigens to MR1-restricted T cells. These T cells are highly prevalent in the lungs and can kill infected cells. Because MR1 presents small molecule antigens and adopts an intracellular distribution, the mechanisms governing MR1 sampling of the intracellular environment are distinct from other antigen presenting molecules. These mechanisms remain unknown. Our over-arching hypothesis is that intracellular calcium signaling is important for MR1 antigen presentation. We use Mycobacterium tuberculosis (Mtb) as a model for intracellular infection and have identified calcium-sensitive trafficking proteins and calcium channels important for MR1 antigen presentation. Aim 1 of this study will determine the mechanism of two-pore channel 1 in MR1- dependent antigen presentation, with a focus on endoplasmic reticulum-endosome contact sites. Aim 2 will determine the role of specific calcium-sensitive Synaptotagmins and their binding partners. Aim 3 will determine the mechanism behind augmented MR1 antigen presentation following modulation of the of the cystic fibrosis transmembrane conductance regulator. Successful completion of these Aims has the potential to lead to new MR1-based immunotherapies.

Factory-treated, long-lasting permethrin baby wraps for the prevention of malaria: A phase III randomized controlled trial

PROJECT SUMMARY/ABSTRACT Progress against malaria has stalled. Novel interventions – particularly those targeting outdoor and daytime biting – are needed. In a randomized, placebo-controlled trial of permethrin- vs. sham-treated baby wraps in Uganda, we found a significant reduction in clinical malaria incidence among children carried in permethrin- as compared to sham-treated wraps (Boyce et al, NEJM, 2025). Despite these promising results, our trial incorporated a monthly re-treatment strategy that would be difficult to operationalize at scale. Furthermore, we only followed participants for 6 months, which is shorter than the expected period of use. Therefore, implementation studies - and specifically trials of long-lasting, factory-treated textiles - are now needed. Factory-treated materials would not only eliminate the need for retreatment for up to 12 months, but because the chemicals are more tightly bound, result in less absorption across the skin. Therefore, we now propose to conduct a randomized, double-blind trial of factory-treated, long-lasting (FTLL) wraps. AIM 1: Determine the effectiveness of FTLL permethrin wraps in combination with existing interventions for the prevention of malaria in children. We will enroll 750 mother-infant pairs from routine immunization visits (~3 months of age) at 3 sites of varying transmission intensity across Uganda. All participants will receive new dual active ingredient (AI) bed nets and be randomized (1:1) to either FTLL or untreated wraps. The primary outcome will be clinical malaria incidence during the period of wrap use, defined as fever a positive malaria rapid diagnostic test (RDT) between the FTLL and untreated arms. AIM 2: Confirm the safety of extended exposure to FTLL permethrin wraps for use in young children. Although a review of factory-treated clothing by the US Environmental Protection Agency, including clothing for children and toddlers, did not identify scenarios of concern, the frequency of use envisioned here may be beyond that modeled. To accomplish this, we will perform semi-annual assessments of growth (e.g., height-for-weight) and neurodevelopment (ND) during the period of use and 12-months after discontinuation. AIM 3: Assess the effect of FTLL permethrin wraps on Anopheles mosquito indices and blood-meal seeking behaviors. We will conduct longitudinal entomological surveillance, including CDC-light trap and aspirator collections, supplemented by human landing catches at sentinel households (~10-15%) from both the FTLL and untreated arms. This work tests a novel intervention, which leverages technology developed by the US military, to reduce the burden of malaria in endemic countries. Addressing malaria in these countries minimizes the risk of importation into the US. If successful, the project will provide additional evidence for treated textiles, which may be used to protect American travelers and deployed military servicemembers. The project will be conducted in Uganda, where malaria is highly endemic and it will be possible to enroll at-risk women-infant pairs.

Staphylococcus aureus metabolic requirements during skin colonization

Project Summary Staphylococcus aureus causes 76% of all skin infections, and yet simultaneously this pathogen asymptomatically colonizes the skin of 8-22% of healthy adults. Since the majority of S. aureus disease is the result of autoinfection from the colonizing strain, and invasive infections often originate from the skin, there is an urgent need to understand colonization mechanisms. In colonizing the skin, S. aureus encounters abundant levels of amino acid derivatives like urocanic acid and 5-oxoproline (OP) that contribute to the skin’s “acid mantle” and have reported anti-Staphylococcal properties. The central hypothesis of this project is that amino acid transport and catabolism is a critical feature of S. aureus skin colonization. To model this environment, we developed a skin-like media (SLM) to assess S. aureus physiology on the human skin surface. We determined the S. aureus transcriptional response using RNAseq and performed metabolomics in SLM, both of which demonstrated that amino acid catabolism genes are upregulated and that amino acids are rapidly consumed. These findings indicate that S. aureus has a skin expression program that enables survival and growth in this harsh environment. In Specific Aim 1, we are investigating S. aureus metabolism of serine, the second most abundant amino acid on human skin. We hypothesize that serine transport and catabolism is critical for S. aureus skin colonization. We will assess growth of mutant strains disrupted in serine pathways in the SLM and during mouse skin colonization. With 13C-tracing experiments we will investigate serine flux in S. aureus using metabolomics. We will determine serine transport mechanisms using bioinformatic guided targets and serine analogues. In Specific Aim 2, we will assess S. aureus resistance to toxic skin metabolites. OP is abundant on human skin and is known to be deleterious to bacteria. Our preliminary metabolomics studies indicate that S. aureus metabolizes OP in SLM, and we have identified a putative oxoprolinase (genes SAUSA300_1566-1561) that is upregulated on skin. We hypothesize that the detoxification of OP contributes to S. aureus survival on the skin. We will construct mutants in the 1566-1561 locus and test their contributions to OP metabolism in SLM with growth and metabolomics experiments. We will also investigate OP transport and test mutant strains in our mouse skin colonization model. In Specific Aim 3, we will identify new determinants of S. aureus skin colonization using TnSeq. We have developed an improved TnSeq library preparation and analysis protocol, and in our preliminary studies we performed TnSeq in SLM and in our mouse skin colonization model. We will evaluate pathway hits, such as respiration and fermentation, and aspartate metabolism targets by testing constructed mutants during SLM growth and in the mouse model. Novel hits will be validated with follow-up genetic experiments and 13C-tracing experiments. Collectively, the proposed studies will advance our knowledge of S. aureus colonization and adaptation to the skin environment.

Eosinophils promote persistence and transmission during Bordetella spp. infections

ABSTRACT Despite widespread vaccination, Bordetella spp., the causative agents of whooping cough, continue to circulate globally. Resurgent outbreaks contribute to significant healthcare burdens and costs estimated up to $79 million annually. This persistence and reemergence highlight a critical need for new therapies and prevention methods. Our laboratory investigates bacterial and host drivers that enable Bordetella success, defined as enhanced persistence, reinfection, and transmission. We have identified the Bordetella sigma factor BtrS as a regulator of immunosuppressive pathways that modulate eosinophil function. Leveraging genetically tractable Bordetella strains, advanced murine models, and immunological tools, we are uniquely positioned to dissect how eosinophils contribute to respiratory bacterial infections. Our preliminary data reveal that eosinophils promote Bordetella persistence. Our results also show that the anti-inflammatory cytokine IL1 receptor antagonist (IL1Ra) also contribute to persistence. However, the contribution of eosinophil-derived immunosuppressors remains unclear and will be investigated in Specific Aim 1. Moreover, we have evidence that eosinophils are required for nasal shedding, through mucus enhancement, and paroxysmal coughing, via exacerbation of bronchoconstriction, during Bordetella spp. infection, two key metrics of transmission. The eosinophil-effectors that promote shedding, coughing, and transmission, will be investigated in Specific Aim 2. Based on our data, we hypothesize that eosinophils contribute to Bordetella pathogenesis by (1) promoting persistent infection and (2) enhancing transmission through mucus-driven shedding and cough reflex induction. This proposal will test this hypothesis through two specific aims: Aim 1: Delineate the immunosuppressive role of eosinophils in modulating host responses and enabling Bordetella persistence. Aim 2: Define the mechanisms by which eosinophils facilitate Bordetella spp. transmission. By reframing eosinophils as active modulators of bacterial pathogenesis, this research challenges traditional views of eosinophils as terminal effector cells and positions them as novel targets for therapeutic intervention, that might be applicable to other mucosal pathogens. The outcomes will contribute to our understanding of eosinophil biology in infection and may lead to innovative strategies to halt bacterial persistence and transmission.

Mechanisms of antigen-specific T cell activation in MOGAD

PROJECT SUMMARY / ABSTRACT The overarching goal of this application is to train Dr. Carson E. Moseley, MD, PhD, who is a clinical neurologist and a research immunologist, to become an independent investigator studying and treating neuroimmunologic disorders. Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) is a recently described, severe, neuroinflammatory syndrome of the central nervous system (CNS) with no approved therapies. Although MOG-specific antibodies helped define the disease, MOG antibodies alone are not clearly pathogenic and our understanding of MOGAD immunopathology is limited. CD4+ T cells are a dominant lymphocyte population in MOGAD lesions, yet the targets of T cell responses to MOG and how T and B cells interact to drive pathogenic immune response in MOGAD are unknown. This proposal uses a complementary approach of human and mouse immunology along with new technologies in T cell repertoire mapping and genome editing to dissect MOG-specific CD4+ T cell responses in MOGAD. Additionally, it will use new models to investigate how B cells promote pathogenic T cell differentiation and select pathogenic T cell receptors. The proposed training plan involves mentored training, seminars, formal learning, and advising to ensure completion of the proposed research and Dr. Moseley’s career development. He will train at UCSF, which is an outstanding institute for research and environment for physician-scientists. He will receive training in human immunology and CRISPR-based gene editing technologies. He will be mentored by Dr. Scott Zamvil, a leader in identifying antigen-specific T cell responses in neuroimmunologic disorders, and co-mentored by Dr. Alexander Marson, an expert in CRISPR gene editing to understand lymphocyte function. This application will provide Dr. Moseley with the long-term skills needed to become an independent investigator leading efforts to study and treat neuroimmunologic disorders.

Borrelia burgdorferi genotypic diversity, pathogenesis, and host cellular responses

PROJECT SUMMARY Lyme disease is the most common tick-borne illness in the United States, with an estimated 476,000 cases annually, and Pennsylvania (PA) consistently reports one of the highest case numbers nationwide. Borrelia burgdorferi sensu stricto (Bb) is a causative agent of Lyme disease in the US and is transmitted by Ixodes spp. ticks. Bb produces various outer surface proteins (Osp) and other mechanisms to survive in vectors, evade host immune systems, and to propagate infection within a host. Over 35 OspC genotypes have been characterized, which fluctuate in abundance in natural vector and host populations, suggesting host adaptation. While many Lyme-infected patients recover following antibiotic treatment, some may experience neurological symptoms, Lyme neuroborreliosis (LNB), which may be associated with specific genotypes. While previous studies focused on clinical manifestations, pathogenicity, genetic variations, and host immune responses using mouse models or patient samples, the genotype-specific immune responses that contribute to disease progression in humans remain poorly understood. Our central hypothesis is that certain Bb OspC genotypes, maintained in natural populations, are associated with distinct host immune responses that influence disease severity, progression, and persistence. Aim 1 will define the dynamics of OspC genotypes in tick and small mammal populations over time in Western PA to establish a 16-year longitudinal tick study and an 8-year longitudinal small mammal study. Using deep amplicon sequencing, we will quantify genotype diversity, detect low-abundance genotypes, and identify potential host-adapted genotypes. These empirical data will inform a compartmental mathematical model to evaluate OspC genotype prevalence, distribution, and public health risks, including LNB, across space and time. Aim 2 will assess how distinct Bb OspC genotypes affect the host immune landscape and cellular responses using human samples. To determine how Bb genotype contributes to disease phenotype, we will perform immune profiling studies which will include microscopy-based assessment of infected cell cultures, flow cytometric analysis of immune cell phenotypes, and measurement of genotype-specific cytokine, chemokine, and antigen production (sub-Aim2a). We will also employ multi-omics approaches that integrate single cell RNA sequencing with antibody-based protein profiling (scRNA-seq/Ab-seq) to characterize transcriptional and functional changes in immune cell populations exposed to different Bb genotypes (sub-Aim2b). This work is innovative in its integration of long-term ecological data with advanced immune profiling and single cell multi- omics to uncover genotype-specific mechanisms of Bb pathogenicity and human immune response—an approach not previously applied in Lyme disease research. These studies will clarify how specific genotypes influence immune responses and disease severity. Together, the proposed aims will identify critical genetic and immunological mechanisms that drive Bb pathogenicity and human susceptibility, informing the development of improved diagnostics, targeted therapies, and public health interventions to reduce the burden of Lyme disease.

Assessing the Efficacy of Mindfulness Apps

PROJECT SUMMARY: Rates of depression continue to rise and the mental health impact of COVID-19 has only accelerated trends. While mental health apps, specifically mindfulness apps, are not a panacea, they are popular tools that millions are turning to today for easy access, affordable, and low-stigma help. But increased reliance on mindfulness apps has not been supported by rigorous scientific evidence exemplified by few studies employing appropriate control conditions. Thus, this research is designed to focus on using 100% remote but robust methodology to assess the efficacy of mindfulness apps by applying a novel precision medicine framework. Our study first assesses the impact of the Digital Working Alliance by matching people with depression with a mindfulness app that may better support their personalized needs. We will compare those randomized to the to this matching condition to a digital placebo to better evaluate the efficacy of these mindfulness apps. For the first six weeks, participants will be asked to use the mindfulness app or digital placebo daily, and if not engaged, will receive reminders, allowing for the analysis of clinical outcomes during ideal usage patterns. For an additional six weeks, participants will be asked to use the app or digital placebo naturally, allowing for the elucidation of naturalistic usage patterns and evaluation if these usage patterns impact clinical outcomes. Across the entire study, we will capture smartphone-based digital phenotypes of behaviors (eg sleep, step, screen time), environments (eg home time, greenspace exposure), and symptoms (longitudinal ecological momentary assessment) to create personalized and predictive models of response that can be utilized to better understand factors impacting the efficacy of mindfulness apps, and in the future, better tailor apps to each person.

BKCa Channel Contributions to Cerebellar Regulated TSC-Associated Neuropsychiatric Disorders

Project Summary TSC is associated with neurodevelopmental disability including cognitive disability and autism spectrum disorders (ASD) that make up part of TSC associated neuropsychiatric disorders (TAND). The mechanisms for TAND remain poorly understood but studies have increasingly implicated cerebellar dysfunction in the pathogenesis of cognitive and behavioral deficits in both TSC and other neurodevelopmental disorders. A shared feature is cerebellar Purkinje cell (PC) dysfunction. Changes in intrinsic properties of PCs results in both motor and cognitive/ behavioral changes in disease models and in individuals afflicted by these disorders. Mechanistic underpinnings of these altered properties remain unknown, but a significant emerging body of data implicate ion channel dysfunction as the primary etiology of these deficits. The current proposal seeks to delineate the ion channel contribution to PC dysfunction and to TAND-relevant behaviors. In doing so, these studies will produce significant both short- and long-term impact. Short-term: These proposed studies will provide a mechanistic understanding of the contribution of ion channels to the neuronal dysfunction in the cerebellum that has been demonstrated to be causally linked to abnormal TAND-relevant behaviors. In addition, we will target specific ion channels both genetically and pharmacologically to evaluate the benefits of ion channel restoration on both electrophysiological abnormalities but also the TAND-relevant behaviors observed in the model. Long-term: These studies, thus, provide a framework for subsequent clinically-relevant therapeutic development for TAND. First, these studies will uncover the ability for TAND-relevant behaviors to be improved upon targeting ion channel alterations in TSC. These studies will also define molecular targets on which therapeutic development can be targeted, thereby potentially providing a molecular-informed pipeline for therapeutic development. In addition, these studies will utilize clinically-available, FDA-approved pharmacological agents to target ion channel function and investigate the potential therapeutic benefits for these agents for TAND-relevant behaviors. Thus, these studies will address a core gap in knowledge to achieve a better mechanistic understanding of TAND and to develop therapeutic opportunities to address TAND. These studies will not only reveal previously understudied and novel mechanistic underpinnings for these behaviors but will provide pre-clinical insights into the therapeutic utility of clinically-utilized agents for the treatment of TAND-related behaviors, thus potentially providing both immediate and long-term opportunities for the treatment of TAND. Moreover, although these studies focus on TSC, these mechanisms may prove generalizable beyond TSC and provide a shared basis and therapeutic opportunity for other neuropsychiatric/developmental conditions.

Optimization of a novel and effective antiviral agent targeting Zika NS4B

This project focuses on developing novel anti-Zika virus (ZIKV) compounds targeting the NS4B protein, which is crucial for viral replication. ZIKV poses a significant medical challenge due to its potential for severe pathogenic outcomes, such as congenital Zika syndrome and Guillain-Barré Syndrome. Furthermore, its pandemic potential has been increasing with the expansion of carrier mosquito habitats. The project aims to address the urgent need for anti-ZIKV therapeutics that could greatly reduce severity of symptoms and minimize vertical and community transmissions. We have identified a novel small-molecule series with a benzamide scaffold through a cell-based, antiviral ultra-high-throughput screen. This series demonstrates strong potency against ZIKV without measurable cytotoxicity or non-specific antiviral effects, justifying this scaffold as a lead series for further development. Preliminary mechanism-of-action studies, utilizing genetic, biochemical, and virological assays, suggest that this series may inhibit the formation of the ZIKV viral replicase complex by interfering with NS4B. Our goal for this project is to develop a preclinical therapeutic candidate for ZIKV that demonstrates promising therapeutic activity following oral administration in ZIKV-infected mice, at a dosage that shows no clinical toxicity. The project has the following significant and novel objectives: 1) Optimize the benzamide lead for potency and drug-likeness; 2) Develop a lead candidate and a backup compound with optimized pharmacokinetic, pharmacodynamic, and toxicity profiles; 3) Determine the molecular mechanisms of action of the benzamide series using novel structural approaches to assist medicinal chemistry studies; 4) Evaluate the in vivo therapeutic efficacy and safety in mouse models and develop the best therapeutic regime. This project seeks to develop effective antivirals for ZIKV with high retention in the blood and central nervous system (CNS) and high oral bioavailability. The expected successful outcomes will provide significant advancements in ZIKV therapeutics and open new avenues for treating other flavivirus infections

Regulation of neutrophil endoplasmic reticulum stress response by IRE1a

Project Summary/Abstract: The lungs are exposed to pathogens and environmental toxins that trigger stress and cause numerous respiratory diseases. Effective host defenses against lung infection by bacterial pathogens, including methicillin- resistant Staphylococcus aureus (MRSA), rely on innate immune cells including neutrophils, prominent early responders to sites of infection. If host defenses are ineffective, MRSA causes serious lung infection, resulting in severe morbidity and a significant economic burden on healthcare facilities, where it is endemic. MRSA infections have a mortality rate of up to 14% and an estimated $500 million in healthcare costs in the US alone. Increasing resistance to vancomycin, the last resort antibiotic for MRSA infections, underscore the urgent need for innovative treatment approaches. Although directly targeting pathogens with antibiotics has been a successful approach for treating infections, many pathogens, including MRSA, eventually will become resistant to these drugs. As an alternative, immunomodulatory strategies to enhance host defenses, such as those shown to be effective against cancer cells, have the potential for treating drug-resistant pathogen infections. Recently, we showed that the inositol-requiring enzyme 1-α (IRE1α), an endoplasmic reticulum (ER) stress sensor, is required for clearance of MRSA in a murine skin abscess model, where neutrophils are robustly recruited to the site of infection. Further, IRE1α coordinates signaling events upstream of calcium (Ca2+) mobilization, histone citrullination, and production of mitochondrial reactive oxygen species (mitoROS), all of which are important for neutrophil inflammatory responses including the formation of antimicrobial neutrophil extracellular traps (NETs). Because excessive neutrophil activation and NET release can be detrimental to vital organs, it is not clear whether neutrophil IRE1α-mediated stress responses aid or impede the resolution of infection in the lungs. While IRE1α activation has been linked to the development of lung fibrosis through the regulation of alveolar epithelial- to-mesenchymal transition in the context of chronic inflammatory diseases, its role in pulmonary neutrophil defenses is unknown. Thus, there is a gap in our knowledge of how cellular stress responses modulate pulmonary neutrophil defenses and infection outcomes in the lungs. The overarching goal of this proposal is to elucidate the mechanisms by which neutrophil IRE1α signaling influences production of mitoROS and Ca2+ mobilization to drive NET release, injure lungs, and regulate pulmonary host defense against MRSA. We will accomplish the following Aims: (1) Define the molecular mechanisms underlying IRE1α-mediated mitoROS hyperactivation of human and mouse primary neutrophils and excessive NET release, and (2) Elucidate the role of neutrophil IRE1α signaling in excessive NET release, lung injury, and immunity in vivo using a MRSA pneumonia infection mouse model. These studies will yield mechanistic insight into how IRE1α-driven ER stress responses impact pulmonary neutrophil defenses and lung injury revealing potential targets for anti-microbial immunotherapies.

Role of cellular physical interactions in pancreatic cancer progression

Pancreatic cancer, with a 5-year overall survival rate of 13%, has the lowest survival rate of all cancers. The goal of this project is to better understand the biological processes of pancreatic cancer progression and discover their potential as targets for efficient therapies. Pancreatic ductal adenocarcinoma (PDAC) underdoes epithelial architecture changes during its progression. However, the underlying mechanisms for these changes are largely unknown. Interestingly, our recent data demonstrate the recapitulation of the distinct epithelial architectures in the organoid culture of cells derived from the human normal pancreas, primary tumor, and metastatic lesions, thereby developing a unique organoid model for the in vitro studies of PDAC epithelial architecture changes. The primary objective of this project is to understand the regulation of the differential PDAC epithelial architectures as well as their contribution to PDAC progression. Our central hypothesis is that disruption in lumen structure drives PDAC epithelial architecture transition and promotes PDAC progression. We will combine experimental and computational approaches to test our central hypothesis by pursuing the following two specific aims: (Aim 1) define the regulators of PDAC epithelial architecture that drives PDAC progression and (Aim 2) determine the functional consequences of PDAC epithelial architecture on PDAC progression. With the completion of this aims, we expect: (Aim 1) to identify ion and water channels that are important for lumen structure as well as PDAC progression, revealing potential novel targets for therapeutic intervention, and (Aim 2) to uncover YAP’s role in PDAC progression and guide the development of YAP- targeted therapies.

Baby Toolbox Training and Certification Program

PROJECT SUMMARY Our objective is to improve early childhood outcomes and support the expansion of the NIH Infant and Toddler Toolbox (Baby Toolbox) by providing comprehensive training support to those interested in using it. The Baby Toolbox is a brand new, nationally-normed assessment for infants 1-42 months, commissioned by NICHD and released for public use in 2025. The Baby Toolbox is administered entirely on an iPad and includes 35 measures across six domains using novel technology (e.g., gaze tracking, automatic scoring, computerized adaptive testing). It has the potential to bring harmonization to the developmental fields, but in order for it to become a common currency for developmental research as envisioned, researchers need to know how to administer it and how to train others to administer it. We propose an education program that will include a week-long training workshop, certification activities, and post-workshop support to create expert cohorts of Baby Toolbox test administrators. Individuals who attend the workshops can become certified test trainers, capable of training others at their home institutions to administer the assessment thus creating a self-sufficient training model. Through the proposed educational program, we will provide funding to cover lodging, meals, and incidentals during the workshop, in addition to subsidizing transportation to/from the workshop and provide a one-year subscription to the Baby Toolbox. A portion of slots will also be set aside for those without current grant funding. Our team is highly qualified to complete these tasks because we have led the effort to develop the Baby Toolbox assessment and have already completed multiple training workshops for contract deliverables. This grant would continue the efforts started by the NICHD in funding the Baby Toolbox by helping support its rollout, implementation, and growth. To meet these goals, we have the following aims: Aim 1: Create cohorts of trained Baby Toolbox examiners who can catapult the Baby Toolbox into widespread use by hosting a comprehensive week-long education program (training workshop) yearly for individuals to learn how to administer and train others to administer the Baby Toolbox, Aim 2: Expand the use of the Baby Toolbox by recruiting and financially supporting individuals who will bring the Baby Toolbox into a variety of research and clinical settings. Aim 3: Build a virtual training resource of videos and materials to support ongoing fidelity checks with certified trainers, and future training efforts.

From B-cell decisions to antibody repertoires

PROJECT SUMMARY/ABSTRACT Vaccine responses are highly variable across the population and not without risk for debilitating side-effects. Antibody-mediated immunity is generated by a Darwinian process to generate B-cells that contain B-cell receptors (BCR) that have high affinity for the pathogen-derived antigen, while also eliminating B-cells that happen to react to self-antigens. This process depends on cell fate decisions such as (i) death vs survival, (ii) entry into a proliferative program, (iii) differentiation into antibody-secreting plasma cells. According to clonal selection theory, B-cell fate decisions are made based on the genetically encoded affinity of the the BCR to the antigen (Signal 1) and the cognate T-cells’ TCR to the antigen peptide (Signal 2). However, single-cell resolution studies have revealed that fate decisions of genetically identical B-cells are remarkably heterogeneous. Our studies of the previous funding period revealed that B-cell epigenetic heterogeneity is in fact dynamically controlled: it is generated during the selection process but remains largely stable during the proliferative burst. This leads to our newly proposed Aim 1 to examine how the dynamic control of epigenetic state variability affects antibody responses. An innovative multi-scale model of Darwinian evolution directs and interprets experimental studies by life cell video microscopy in vitro and in immunization studies in vivo. Our previous studies also found that B-cells are capable of sensing the time gap between signal 1 and 2, suggesting a temporal proofreading mechanism for negative selection. This leads to newly proposed Aim 2 which seeks to identify the regulatory circuits that control the stringency of negative selection, as well as contextual germinal center (GC) cytokines that could be manipulable in vivo. These in silico and in vitro studies are followed by in vivo immunization to extend their physiological relevance. Finally, in Aim 3, we will ask what determines the time-gap of signal1 and signal 2, which occur in the immune- induced structure of the GC. We will develop a new model that simulates B-cell fate decisions as a function of their interactions with antigen-presenting stromal cells and T-cells that may be cognate or non-cognate. Model simulations will be used to interpret spatial transcriptomic data to test different adjuvants and predictions will be tested in in vivo immunization studies. With mouse models of inflammation and aging we will examine how adjuvants alter vaccine efficacy and risk.

Delineating the role of TREM2 in chronic pancreatitis

PROJECT SUMMARY Chronic pancreatitis (CP) is a progressive digestive disorder characterized by persistent inflammation, irreversible fibrosis, and acinar cell damage. However, current treatment options remain limited, underscoring the need for effective, targeted therapeutic strategies through a deeper understanding of the disease microenvironment. Macrophages are pivotal players in the CP microenvironment, exhibiting dual roles in inflammation and tissue remodeling. A defining feature of macrophages is their remarkable phenotypic plasticity, enabling them to transition between pro-inflammatory and anti-inflammatory phenotypes. However, the specific macrophage phenotypes contributing to the immune imbalance in CP and their precise mechanisms of action remain poorly understood. TREM2 (Triggering Receptor Expressed on Myeloid cells 2), a transmembrane receptor of the immunoglobulin superfamily, has emerged as a critical modulator of tissue damage responses in multiple disease settings, though its function in CP remains unexplored. Our preliminary single-cell RNA-seq analyses of human CP tissues reveal an enrichment of inflammatory macrophages alongside a marked downregulation of TREM2 compared to non-diseased controls. This reduction in TREM2 correlates with marked increases in pro-inflammatory mediators, such as IL-1β and NF-κB, suggesting that TREM2 in macrophages contributes to maintaining homeostasis and restraining inflammatory signaling. Accordingly, diminished TREM2 expression appears to skew macrophages toward a pathologically hyper-inflammatory state. We hypothesize that loss of TREM2 disrupts the delicate balance among immune cells, fibroblasts, and acinar cells, fueling a self-reinforcing cycle of inflammation and fibrosis that exacerbates pancreatitis. To test this hypothesis, our R01 will leverage integrative single-cell transcriptomics, spatially resolved imaging, transgenic mouse models, functional organoid co-culture assays, and in vivo experiments to elucidate TREM2’s regulatory mechanisms in CP. This research aims to address two key scientific questions: (1) How does TREM2 suppress pro-inflammatory macrophage phenotypes and restrain IL-1β-induced inflammatory signaling? (2) How does the crosstalk among pro-inflammatory macrophages, fibroblasts, and acinar cells exacerbate the local inflammatory environment, leading to further pancreatic damage? Through this study, we aim to establish TREM2 as a pivotal inhibitory checkpoint in the NF-κB/NLRP3/IL-1β axis, preventing unchecked macrophage-driven inflammation, fibroblast activation, and further acinar cell damage. Successful completion of this project will deepen our mechanistic understanding of CP and identify new therapeutic strategies to mitigate fibrotic progression and preserve pancreatic function. Ultimately, these insights may guide the development of immunomodulatory treatments to attenuate CP severity, thereby transforming the clinical management of this devastating disorder.

Mechanisms of Commensal- Specific CD8+ T Cell Differentiation, Restraint and Dysregulation in Intestinal Inflammation

PROJECT SUMMARY Our understanding of immunity largely stems from models of infection with pathogenic microbes. However, the vast majority of microbial-immune encounters occur as a symbiotic relationship with the commensal microbiota. Recently, the contribution of commensal-specific T cells to host physiology has received significant attention. These commensal-specific responses not only control microbiota containment but also promote immune tolerance within the gastrointestinal tract. While commensal-specific CD4+ T cell responses in the lamina propria have dominated models of mucosal immune regulation, these are vastly outnumbered by CD8+ intraepithelial lymphocytes within the epithelium. How CD8+ T cell responses to gut microbiota are primed, differentiate and function under homeostasis has not been addressed. Conversely, aberrant immunity to commensal microbes has been proposed to underlie pathologies of barrier tissues, including inflammatory bowel disease (IBD), where commensal-specific T cells accumulate in blood and intestinal tissues of afflicted patients. A better understanding of the properties and functions of commensal-specific T cell responses is therefore fundamental to studies of tissue immunity in health and disease. Our long term goal is to better understand how commensal-specific T cell responses contribute to barrier tissue homeostasis, and the objective in this application is to investigate the mechanisms regulating induction of commensal-specific CD8+ T cells in homeostasis and how they become dysregulated in IBD. Our rationale for the proposed work is that uncovering these mechanisms has the potential to translate into new therapeutic approaches. Our central hypothesis is that commensal-specific CD8+ T cells develop as functionally restrained intraepithelial lymphocytes (IEL) under homeostasis, but that perturbation of local immune regulation within the intestinal epithelium, in the case of patients with ulcerative colitis, by autoantibody-mediated blockade of integrin avb6 results in aberrant CD8+ effector T cell responses in IBD. Based on strong preliminary data, we will test three specific aims: (1) Determine key antigen-presenting cells (APC) priming SFB-specific CD8⍺β+ IEL. (2) Identify how cell-intrinsic pathways drive differentiation, maintenance and restraint of SFB-specific CD8⍺β+ pIEL. (3) Determine how pathogenic KLRG1+Eomes+ CD8+ T cells arise and contribute to inflammation in murine models of ulcerative colitis Our approach is innovative as it investigates new mechanisms of immunity unique to commensal-specific CD8+ T cell responses. The proposed work is significant because it will establish new insights into the interaction and communication between commensal microbes and immune cells in the gut environment and identify potential targets for therapeutic intervention in conditions of chronic intestinal inflammation.

Th17 plasticity in rheumatoid arthritis

ABSTRACT The objective of this grant application is to explore the plasticity of Th17 in arthritis. Interleukin-17A (IL-17A) producing Th17 are present in the blood and synovium of patients with rheumatoid arthritis (RA). However, targeting of IL17A has been insufficient to control joint inflammation of RA patients. One potential scenario is that in the context of worsening RA joint inflammation, Th17 undergo conversion into pathogenic IL17A- negative cell populations, collectively called exTh17. The conversion of Th17 into exTh17 has been documented in the context of neuroinflammation, colitis, and infection. However, the occurrence of Th17 plasticity in autoimmune arthritis and its potential role in perpetuating synovial inflammation has remained mostly unexplored. We generated a novel fate-mapping mouse model of autoimmune arthritis, which allows to follow the conversion of Th17 into exTh17, and collected preliminary data suggesting that Th17 undergo significant loss of IL17A expression and conversion into exTh17 in the context of synovial inflammation. We also identified exTh17 signatures which might help exTh17 perpetuate joint inflammation despite their loss of IL17A expression. Here our objective is to further elucidate intrinsic (Aim 1) and extrinsic (Aim 2) mechanism of Th17-exTh17 conversion and exTh17-mediated joint inflammation, and explore the potential role of exTh17 in RA interstitial lung disease (ILD, Aim 3) a feared and often untreatable complication of established RA. Our long-term goal is to leverage the knowledge of local immune cell phenotypes and how they change at various stages of disease to enable stage-specific and personalized therapies of RA which minimize non- specific immunosuppression.

Urothelial Resurfacing with Irreversible Electroporation for Adjuvant Therapy of Bladder Cancer

PROJECT SUMMARY Over 70% of bladder cancer (BCa) patients are diagnosed with early-stage and localized non-muscle invasive disease (NMIBC), yet achieving durable cancer-free survival remains a significant challenge. Most of these patients will experience local tumor recurrence within five years following standard of care (SoC) transurethral resection of bladder tumor (TURBT) and intravesical adjuvant chemo- or immunotherapy. Recurrence is driven by microscopic tumors and premalignant lesions dispersed within the urothelial layer that survive and escape these treatments. As TURBT effectively treats tumors visible on imaging, current research has predominantly focused on drugs and biologics for improving intravesical adjuvant therapy. In this proposal we pose the provocative question whether a TURBT-like ablative technique can be extended to debulk malignancy in the entire bladder and investigate the synergy with intravesical adjuvant therapy in improving outcomes. Our objective is to address this technology and knowledge gap by developing and validating whole bladder urothelial resurfacing (WBUR) using irreversible electroporation (IRE). During IRE, microsecond-long pulsed electric fields (PEF) are used to induce rapid cell death by catastrophic permeabilization of the cell membrane, without affecting the extracellular matrix (ECM) within the treated tissue. In prior work, we designed devices that utilized this unique mechanism of IRE for performing penetrative ablation in the ureter, bile duct and bronchus of swine while preserving lumen function. Our findings provided strong rationale for IRE being an ideal candidate for WBUR as alternate techniques such as thermal ablation or ionizing radiation must be performed with extreme care in the bladder to avoid perforation or fistula formation. In subsequent preliminary work we developed technology to demonstrate the feasibility and safety of WBUR with IRE in a rat model of BCa and scalability in human-sized swine bladder. In Aim 1, we will investigate the cancer treatment efficacy of combination WBUR and intravesical adjuvant therapy. In Aim 2, validate WBUR derived liquid biopsy for monitoring cancer status. In Aim 3, engineer PEF delivery strategy to enhance the safety and specificity of WBUR. The innovation of our proposed work is defined by developing whole bladder ablation as a debulking strategy and examining its synergy with SOC adjuvant therapy (Aim 1), enabled by new electrode paradigm and PEF delivery strategy (Aim 3), monitoring by an unconventional liquid biopsy approach (Aim 2). Our work can immediately aid the management of NMIBC patients who cannot undergo radical cystectomy, with future application as a cancer prevention strategy in high-risk patients. Success of individual aims will result in major contributions to the topics of IRE, BCa treatment and diagnosis.

Cartilage targeting exosomes for OA gene therapy and pain treatment

Project Summary Gene therapy has the potential to facilitate targeted expression of therapeutic proteins to promote cartilage regeneration in osteoarthritis (OA). The dense, avascular, aggrecan-glycosaminoglycan rich negatively charged cartilage, however, hinders their transport to reach chondrocytes in effective doses. While viral vector mediated gene delivery has shown promise, concerns over immunogenicity and tumorigenic side-effects persist. To address this, we have developed surface-modified cartilage-targeting MSC exosomes as non-viral carriers for gene therapy. MSC derived exosomes have intrinsic therapeutic potential as they can induce cartilage repair and are non-immunogenic, making them desirable for gene delivery. We have engineered charge-reversed cationic exosomes by anchoring cartilage targeting optimally charged arginine-rich cationic peptide (CPC) motifs into the anionic exosome bilayer (Exo-CPC) by using buffer pH as a charge-reversal switch. Exo-CPC use charge interactions to penetrate through the full thickness of arthritic cartilage (close to tidemark) and deliver the packaged genetic material cargo to chondrocytes residing in the deep tissue layers while native anionic exosomes cannot. They can also bind within the synovial joint, making them effective for OA pain relief gene therapy. Here we will engineer charge-reversed Exo-CPC for delivery of IL-1RA (receptor antagonist of interleukin-1) mRNA and NaV1.8 (voltage gated sodium channel 1.8) inhibitor siRNA to stimulate both disease modifying response and long-term pain relief with a one-time intra-articular dose. IL-1RA mRNA targets are in the chondrocytes and synovium cells; Nav1.8 expressing nerves innervate into synovium and subchondral bone in OA – sites that Exo-CPC can readily target. Aim 1 will engineer cartilage targeting Exo-CPC for delivery of IL- 1RA mRNA and Nav1.8 inhibitor siRNA. Their ability to deliver IL-1RA mRNA to chondrocytes and IL-1RA protein translation efficiency will be evaluated in-vitro. Exo-CPC-Na v1.8’s ability to reduce NaV1.8 bioactivity of sensory nerves will also be evaluated. In Aim 2, their distribution intra-articular (proximity to NaV1.8-positive nerves), extra-articular, and DRG and spinal cord using partial meniscectomy NaV1.8-tdTomato reporter mice OA models will be evaluated. Additionally, their dose dependent reduction on MMP activity, neuronal excitability and pain- related behaviors, and any immunogenicity will be assessed. Aim 3 will use the determined functional doses to study the long-term disease modifying and pain-relief effects of mono and combination therapy with Exo-CPC- IL-1RA and Exo-CPC-Nav1.8 in rescuing injury induced tissue structural damage as well as in reducing pain (weight bearing asymmetry) for up to one month following IA administration in early vs. late stages (intervention at 2 vs 6 weeks) of MMT (medial meniscectomy) induced OA rats. The project paves way for utilizing the intrinsic therapeutic potential of MSC Exosomes as viral-free, non-immunogenic carriers for OA gene therapy by employing cartilage as a drug depot. Cationic exosomes can be used to deliver other OA gene targets, and can be widely used for targeting other negatively charged tissues like meniscus, ligaments, discs, fracture callus etc.

The Role of the Intestinal Microbiota in Sepsis Mortality

Project Summary/Abstract Sepsis is a life-threatening condition characterized by a dysregulated host response to infection that can cause multi-organ damage and death. As the leading cause of in-hospital mortality, sepsis mortality rates reach up to 50%, and account for approximately 270,000 deaths and $38 billion annually in health care costs in the United States. Notably, patients with similar medical backgrounds can have vastly different sepsis outcomes— some survive with medical treatment while others die. The reasons for this dichotomy are unknown but is seen across all forms of bacterial bloodstream infections, is not specific to any strain-level differences in the infecting pathogen and cannot be explained by human genetic differences. Human microbiota studies suggest that gut microbial dysbiosis is associated with sepsis mortality and that these alterations influence gut barrier breakdown, leading to gram-negative bacteremia—one of the most common causes of sepsis and mortality. However, there are a lack of studies that investigate the causal role of the intestinal microbiota in sepsis mortality. This K08 proposal will elucidate the role of the intestinal microbiota in sepsis mortality. Utilizing the well- established murine model of sepsis by intraperitoneal injection of lipopolysaccharide (LPS), we combine microbiota taxonomic sequencing and metagenomics, advanced bioinformatic techniques and prediction modeling, with knowledge of mucosal immunity and germ-free mouse systems to characterize the microbiota features and members that correlate with, predict, and cause sepsis mortality. This proposal is organized into two specific aims: (1) identify baseline stool microbial features associated with and predictive of sepsis outcomes and (2) determine how colonization with immunostimulatory microbes heightens sepsis mortality. In this work, I will holistically characterize the host immunologic and microbiota features that are associated with and predictive of mortality and experimentally identify microbes and microbial pathways that cause death in our model. These findings will reveal new microbial and host biomarkers of sepsis mortality and identify novel targets for sepsis prevention and treatment to reduce the overall mortality rate of this deadly disease. My long-term goal is to become an independent physician-scientist who integrates cutting-edge computational methods with experimental biology to identify predictive biomarkers of disease onset and outcomes, investigate how they influence disease processes, and develop novel therapeutic and preventive strategies to improve patient care. This proposal details specific research aims and a structured career development and training plan that will allow me to acquire focused, in-depth and multidisciplinary training under the guidance of an internationally recognized team of experts in clinical infectious diseases, host-microbiota interactions, immunology, immunometabolism, and computational biology. The knowledge generated will address the fundamental role of the microbiota in sepsis outcomes and inform future preventative and therapeutic strategies that will lower the sepsis mortality rate worldwide.

Causal mechanisms driving germline predisposition to myeloproliferative disorders

SUMMARY/ABSTRACT Although human genetic studies have indicated a significant hereditary predisposition to myeloproliferative neoplasms (MPNs) the underlying mechanisms driving the genetic risk remains unknown. Our large genome wide association study (GWAS) on MPNs identified several non-coding genetic risk loci associated with disease and implicated modulation of hematopoietic stem cell (HSC) self-renewal by the genetic variants. The long-term goal is to utilize our GWAS results to better understand MPN disease initiation and progression and draw out key unknown MPN predisposition genes. The overall objectives in this application are to elucidate the mechanisms by which MPN risk variants promote disease initiation and progression. The central hypothesis is that common genetic variants increase MPN risk by affecting regulatory elements that influence clonal expansion of HSCs carrying MPN driver mutations. The rationale for this project is that the HSC clones with most prevalent driver mutation found in MPN, JAK2V617F show individual specific growth rates and can develop into MPN or remain as clonal hematopoiesis without any consequences indicating that germline genetic factors influence this process. The central hypothesis will be tested by pursuing two specific aims: 1) To determine the mechanisms by which genetic variation at the GFI1B locus influences MPN predisposition in vivo. 2) To define upstream transcriptional mechanisms disrupted by common genetic variants that predispose to MPN. Under the first aim, a newly generated mouse model will be used to evaluate clonal expansion of JAK2V617F HSCs in the context of a germline Gfi1b enhancer deletion by in vivo competitive transplantation assays. The murine studies will be complemented by an assessment of Gfi1b allele specific clonal expansion in primary human hematopoietic stem and progenitor cells (HSPCs) engineered to carry JAK2V617F mutation. Mechanistically activated mitochondrial respiration will be examined in germline enhancer inactivated JAK2V617F HSPCs in murine models and human patient samples. For the second aim, perturbation of RUNX1 bound cis-regulatory elements by MPN risk variants will be evaluated as a mechanism of clonal expansion in MPN by using lentiviral reporter assays and endogenous CRISPR/Cas9 editing approaches in primary human HSPCs and degron tagged RUNX1 cell lines. A Runx1 haploinsufficiency mouse model will be used to assess global influences of RUNX1 transcriptional network on MPN initiation. Collectively, our proposed studies aim to bridge the gap between inherited genetic variations and the clonal expansion dynamics of MPN stem cells, shedding light on crucial factors influencing disease development. The mouse models proposed in this study provide the in vivo physiological context and functional readouts required to investigate HSC clonal expansion and MPN pathogenesis.

Cardiorespiratory and autonomic impacts of coolants in e-cigarette aerosols

PROJECT SUMMARY / ABSTRACT Coolants such as menthol, WS-3, and WS-23 are widely used in electronic cigarettes (e-cigs) to reduce irritation and enhance appeal—especially among youth. Despite their prevalence, the cardiopulmonary toxicity of these agents remains poorly characterized. Recent work shows that e-cig aerosols can disrupt autonomic nervous system regulation and cardiac electrophysiology, increasing catecholamine release, enhancing sympathetic regulation of cardiac rhythm, and provoking arrhythmias. Proof is also mounting that nicotine’s sympathomimetic traits mediate these pathogenic effects. Preliminary data from our laboratory show that coolants increase systemic nicotine levels, blunt respiratory reflexes, and potentiate arrhythmias upon exposures to e-cigarette aerosols, suggesting a paradoxical role for coolants in suppressing ventilatory responses while intensifying cardiovascular risk. These findings take on added significance in light of recent case reports of sudden cardiac arrest in young e-cigarette users, including some in otherwise healthy individuals. This project will elucidate how e-cigarette coolants alter exposure to harmful and potentially harmful constituents (HPHCs)—particularly nicotine and aldehydes—concurrent with their effects on cardiovascular and respiratory physiology. Using robust murine models with continuous ECG, blood pressure, and pleural pressure telemetry, we will assess how coolants alter the acute and chronic effects of e-cigarette aerosols on cardiac electrophysiology, autonomic tone, ventilatory function, hemodynamics, and toxicant exposure. We will also evaluate how coolant concentration and device power modulate these effects. In parallel, we will determine whether adolescent mice exhibit heightened susceptibility to these effects compared to adults, with attention to sex differences and the persistence of cardiotoxicity after exposure cessation. This comprehensive, multi-modal approach incorporates novel protocols for arrhythmia inducibility, high-resolution physiologic monitoring, and complementary analyses of biomarkers of exposure and effect. By clarifying how coolants interact with HPHCs—especially nicotine and aldehydes—to drive cardiopulmonary injury across age and sex, this work addresses high-priority research areas identified in RFA-OD-25-001, including the toxicological evaluation of e-cigarette constituents and their cardiopulmonary effects. The results will inform regulatory policy and public health strategies aimed at mitigating cardiovascular risk associated with e-cigarette use, particularly among vulnerable youth.

Weak Cell Adhesion is a Prognostic Signature of Invasive Cancer

Project Summary Despite early detection, low-grade and localized breast cancers such as ductal carcinoma in situ (DCIS) can relapse in up to 20% of cases despite standard of care. For DCIS, relapse affects over 12,000 U.S. women annually and has increased 60% in the last 40 years. Current diagnostic assessments including histopathological markers often miss early disseminating cells, lack specificity, or cannot distinguish cancer from non-cancer cells in the stroma. Hence there is an unmet need for cancer diagnostic technologies that employ radically different characterization methods. For example, significant physical differences exist between metastasizing and benign breast cancer cells, owing to metastasizing cells detaching from the primary tumor, migrating through the surrounding stroma, intravasating and extravasating, and ultimately engrafting in distant tissues. We recently demonstrated that cancer cells with weaker adhesion migrate faster and metastasize more frequently in murine breast cancer models than strongly adherent cells. In a small pilot study of human breast tumors, we also observed that the abundance of weakly adherent (WA) cells scales with disease severity; subpopulations from invasive carcinomas were the least adherent. However, a subset of DCIS cases displayed much less adhesion, suggesting that these patients may have a tumor subpopulation that progresses to metastatic disease despite standard-of-care treatment. Weak adhesion is a defining physical characteristic of tumors, but to establish their role in initiation, metastasis, and patient outcomes, we will leverage model systems and our newly patented adhesion technology to answer these fundamental questions of cancer biology and clinical translation. To understand the impact of adhesion on cancer progression, we will evaluate the tumor-initiating potential of WA versus strongly adherent (SA) tumor cells in a murine breast cancer model before confirming how weak adhesion advantages cells to cause secondary disease using bioengineered in vitro models. In dissecting the stages of metastasis where WA cells exhibit advantages, e.g., recapitulating stromal niche, transendothelial migration, and tissue-specific colonization, we will identify mechanisms that enable WA cells to thrive and evaluate therapeutic targets that disrupt these pathways. Finally, we will analyze the adhesion profiles of resected tumors and stroma from 80 breast cancer patients with DCIS or invasive disease. Adhesion data will be correlated with conventional assessment methods and ultimately with patient outcomes, e.g., disease-free and progression-free intervals. We anticipate that the DCIS subpopulation that aligns with the adhesion signature of invasive carcinomas will have shorter intervals and survival time. This integrated study design bridges mouse models, mechanistic bioengineering assays, and human samples to clarify the metastatic potential and prognostic value of WA breast cancer cells. Our use of mouse models in this grant is required to study the interactions among tumor cells, immune cells, vasculature, and stromal tissues that drive tumor formation in vivo. Bioengineered in vitro systems lack the complexity to ask such questions and using injected tumor cells is not possible in humans.

Targeting VIP–VPAC Signaling to Reverse Immune Exclusion and Enhance Immunotherapy Response in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer that is largely unresponsive to chemotherapy and current immune checkpoint blockade drugs, highlighting a critical need for the development of innovative therapeutic strategies. This R01 proposal targets vasoactive intestinal peptide (VIP), an immunosuppressive neuropeptide overexpressed in PDAC, which signals through VIP receptors (VPAC) on cancer cells, T cells, and myeloid cells within the tumor microenvironment. Based on our recent success in developing selective and potent VPAC receptor antagonists, we hypothesize that blocking VPAC signaling will reverse immunosuppression in the PDAC TME by reducing immune checkpoint expression, enhancing chemokine-driven infiltration of cytotoxic T cells, and disrupting immunosuppressive interactions between T cells and myeloid cells, ultimately leading to durable anti-cancer immunity. We propose three specific aims to explore the immunosuppressive roles of VPAC signaling in PDAC. Aim 1 will identify the primary sources of VIP in PDAC tumors and characterize the effects of VPAC signaling on immune cell function and phenotype within the tumor microenvironment. Aim 2 will investigate how VPAC signaling influences immune cell migration into tumors by modulating chemokine receptors and directional signaling. Aim 3 will determine how VPAC signaling regulates interactions between T cells and immunosuppressive myeloid cells, particularly tumor-associated macrophages, and the resulting impact on anti-cancer immune responses and immunological memory. Our preliminary findings indicate that combined inhibition of VPAC signaling and PD-1 significantly enhances the regression of PDAC tumors in multiple mouse models, generating lasting protective immunity in cured mice without triggering autoimmune responses. We will use novel methods to pursue our aims, including inducible genetically engineered mouse models (GEMM) of PDAC, long-acting VPAC antagonists engineered with immunoglobulin Fc domains to improve their plasma half-life, and advanced microfluidics technologies to analyze immune cell movement within tumors. Animal experiments will be used to validate the translational potential of observations from in vitro organoids and microfluidic experiments. The GEMM and orthotopic mouse models of PDAC are necessary to provide critical insights into the 3-D structure of the TME and tumor regression in response to our novel immunotherapy. This research will be conducted by a multidisciplinary team with complementary expertise that will clarify the therapeutic potential of VPAC signaling inhibition in PDAC using sophisticated experimental tools and single-cell RNA sequencing. Ultimately, these findings could significantly improve the development of immunotherapeutic strategies for PDAC, potentially enhancing patient outcomes in pancreatic cancer and other malignancies expressing high VIP levels.

TACTIC: Tuberculosis Active Case Tracking via Interpersonal Connections

PROJECT SUMMARY/ABSTRACT Tuberculosis (TB) remains the leading infectious cause of death worldwide. Interruption of transmission is the most effective strategy to reduce incident infections, yet current approaches often fail to reach individuals for timely testing and treatment. This study addresses that gap by leveraging social networks to identify individuals at highest risk of transmitting TB, specifically, people who use drugs (PWUD). We will evaluate respondent-driven sampling (RDS), a peer7 based community recruitment strategy, to identify TB cases among PWUD and the household contacts (HHCs) of those with TB disease (RDS-TB) in Kampala, Uganda. Conducting this work in a high-prevalence setting such as Kampala where our team has established expertise allows us to overcome recruitment challenges common in settings in the United States while generating findings that are directly translatable. This is particularly relevant given that higher TB prevalence and larger outbreaks in the United States have been associated with the use of methamphetamine, heroin, and crack/cocaine, drugs that we will study. In Aim 1, we will compare the effectiveness and reach of RDS-TB with a traditional clinic-based index case HHC approach for TB case finding. We will screen 2,000 PWUD and their HHCs, estimate the number needed to screen to identify one case of TB disease, and compare the demographic and network characteristics of RDS-TB recruits with clinic-based HHCs. Whole genome sequencing will be used to characterize transmission dynamics. In Aim 2, we will compare the yield of individual and combined TB diagnostic strategies for community-based active case finding. Participants will undergo chest radiography with computer-aided detection, tongue swab testing for TB nucleic acid amplification tests (NAAT), and sputum testing for NAAT and mycobacterial culture. We will identify the minimal combination of tests needed to meet World Health Organization target product profile thresholds for screening. In Aim 3, we will define the conditions under which RDS-based screening can effectively interrupt TB transmission. We will develop an agent-based model informed by social network data from individuals with and without TB, incorporating drug use patterns and demographic characteristics. This project will generate a practical, scalable roadmap for social network–based TB active case finding in high28 risk communities. The approach will be readily adaptable to settings in the United States and will inform strategies to interrupt transmission and advance progress toward TB elimination, in alignment with the NIH Strategic Plan for TB Research.

Short-wave infrared Cerenkov imaging to better visualize targeted radiotherapy and diagnostic radiotracers

SUMMARY. The problem: Cerenkov luminescence (CL) imaging (CLI) is a new imaging method that utilizes light emitted during decay of radiotracers. CLI merges optical and nuclear imaging by utilizing affordable yet highly sensitive optical cameras with clinical radiotracers. It provides fast and cheap clinical optical imaging to explore radiotracer distribution in patients. While not tomographic, CLI systems have a lower price, smaller footprint and higher resolution than nuclear imaging scanners. Yet, due to the very low signal intensity of CL its versatility remains limited since CLI requires strict exclusion of ambient light with an enclosure. Therefore, CLI requires novel approaches to make clinical imaging more feasible. We hypothesized that we could explore the short-wave infrared (SWIR) part of CL to enable CLI under ambient light without enclosure, providing improved and facile CLI, particularly of isotopes used for therapy that cannot be imaged otherwise. SWIR imaging (900- 1300 nm) has almost no autofluorescence, absorption or scatter but provides significantly higher depth penetration, yielding images with higher contrast and resolution compared to the visible range. Since typical LEDs do not emit light beyond 850 nm, they do not interfere with the SWIR camera. We can therefore perform CLI in the SWIR range (SWIR-CLI) without the limiting light-tight box and under ambient LED light and also achieve better signal penetration and accuracy. We will investigate if SWIR-CLI can be used to monitor distribution of therapeutic isotopes for targeted radiotherapy (TRT), a fast-expanding field as highlighted by Novartis’ acquisition of Lutathera and Pluvicto for the price of $6 bn. These agents are targeting 177Lu as therapy to neuroendocrine and prostate cancers. For TRT α-emitting isotopes are particularly attractive due to the α- particle’s short path length with high linear energy transfer. However, α-emitters are very difficult to image with conventional equipment. The α-emitter could be swapped with an imaging isotope, but this can alter the agent’s biodistribution. The α-particle itself does not have sufficient energy to produce CL but several daughters in the decay chains of most α-emitters produce electrons with sufficient energy to create CL. We have already imaged the α-emitter 223Ra in patients and have recently shown that CLI of α-emitters in the SWIR is possible. SWIR- CLI could therefore provide a facile imaging approach for α-emitters. We will answer with our three independent Aims the following questions: (1) Can we image diagnostic isotopes with SWIR-CLI? (2) Can we image therapeutic emitters with SWIR-CLI? (3) Can we use SWIR-CLI to image patients undergoing PET and/or TRT? Animal studies will employ established mouse cancer models to optimize imaging parameters and validate findings, directly informing the co-clinical Aim 3 trial. By eliminating the requirement for a light-tight enclosure and enabling CLI under ambient light, SWIR-CLI represents a significant shift in the practical deployment of CLI rather than an incremental improvement. Our study will broaden the reach of CLI by enabling imaging under ambient lighting, unlocking innovative new opportunities for CLI (monitoring TRT) in research & clinical settings.

Modulating the Action of Cylindrical Proteases to Eliminate Neisseria Gonorrhea and Chlamydia Trachomatis Infections

Project Summary/Abstract Sexually transmitted bacteria diseases caused by Chlamydia trachomatis (Ctr) and Neisseria gonorrhoeae (NG) are the two most common sexually transmitted bacterial diseases. The infections caused by these pathogens may result in infertility, ectopic pregnancy, blindness, and perinatal mortality. Over 1.70 M cases of chlamydia and 0.65 M cases of drug-resistant gonorrhea are reported yearly in the US. Women with gonorrhea are co- infected with chlamydia in 17.6%–57.9% of cases, while women with chlamydia are co-infected with gonorrhea in 2.1%–17.2% of cases. These infections are treated with broad spectrum antibiotics, which can favor the development of resistance on NG/CTr but also in other bacteria, or damage the microbiota, diminishing its protective function and allowing bacteria and viruses to infect the patient. The Caseinolytic protease (ClpP) proteolytic machinery regulates protein turnover and homeostasis and is key in bacterial growth and development The machinery consists of the proteolytic unit (the ClpP) and its chaperone (ClpX), which transports proteins to be degraded, and it is termed the ClpXP. Our theory is that molecules that inhibit the action of the ClpX chaperone can become efficient antibacterial agents against both pathogens. We have found that the dihydrothiazepines can erradicate both pathogens and prevent the action of the ClpXP complex. Our goal is to advance the dihydrothiazepines as selective agents against Ctr and NG infections. To develop these therapeutic agents, we have envisioned four specific aims. Specific Aim 1. Synthesis and Optimization of the Pharmacophore. Our goal is to use computational models to design dihydrothiazepines molecule that will be synthesized, purified, and characterized using chemical techniques. The molecules will be tested against Ctr and NG and their toxicity against human cells evaluated. Also, we will determine their effect in other bacterial, including those from the microbiota. Specific Aim 2. Assessment of Stability and In Vivo Activity. We will study the stability of the most active molecules under various conditions. Then, we will study the pharmacokinetics, biodistribution , and antibacterial activity against Ctr and NG in mice. Specific Aim 3. Target Validation and Effect. We will study the ability of the compounds to inhibit the activity of ClpX using a luciferase assay and to block protein degradation. We will try grow crystal of the protein and the molecule and will study if the molecules prevent the assembly of the ClpXP system. Finally, we will assess the ability of the bacteria to develop resistance to the molecules.

Exploring in vivo Treg function in T1D through the lens of expanded Tregs

PROJECT SUMMARY/ABSTRACT A critical barrier to optimally treating Type 1 Diabetes (T1D), an autoimmune disease in which the islet beta cells are destroyed by immune cells, is understanding how autoimmunity is regulated in vivo. Several lines of evidence suggest that defective CD4+FOXP3+ regulatory T cells (Treg) likely contribute to the loss of tolerance in T1D. Yet, less is known about how human Treg function in vivo. In the Sanford T-rex study in which adolescents diagnosed with T1D were treated with a single dose of polyclonal autologous in vitro expanded Treg (expTreg), we found that a lower degree of in vitro Treg expansion significantly correlated with better preservation of C- peptide (a biomarker of insulin secretion and beta cell function) a year after treatment. This correlation could not be explained by age, expTreg phenotype or in vitro expTreg suppressive function. However, we did identify an expTreg gene signature that correlated with better C-peptide preservation and this expTreg signature was consistently expressed over time within individuals. Further, lower- and higher- expTreg differed phenotypically and transcriptionally by signatures implicating metabolic, homing and suppressive functions. Together, these data suggest that intrinsic features of an individual’s Treg may contribute to the extent of in vitro Treg expansion. They also suggest that strong activation and expansion can differentially amplify or alter the state of Tregs, leading to changes in homing and function that may impact clinical response. Based on these findings, we hypothesize that Treg proliferative capacity is driven by the activation and metabolic state of Treg resulting in differential in vitro fold expansion, homing potential and in vivo suppressive function that impacts clinical outcome. We will test this hypothesis by leveraging existing primary human samples from both the T-rex clinical trial and the Benaroya Research Institute Registry and Repository that includes individuals with known degree of in vitro Treg expansion and known C-peptide decline. In Aim1, we will identify how activation states of pre- and post- expansion Treg and longitudinal Treg in T-rex participants contribute to proliferative capacity and outcome using cellular, transcriptomic and epigenetic assays. In Aim 2 we will determine how metabolic shifts during Treg in vitro fold expansion alter Treg suppressive function, thereby impacting clinical outcome. In Aim 3, we will compare the in vivo suppressive function of lower- versus higher-expTreg from clinical samples using a xenogeneic graft versus host disease (GvHD) mouse model in addition to assessing in vivo expTreg homing and function using the assays from Aims 1 and 2 and a novel in vitro assay of cell trafficking to pancreatic islets. Successful completion of these aims will reveal mechanisms regulating Treg proliferative capacity and in vivo function that impact clinical outcome. Understanding these mechanisms will guide development of next generation Treg activation and expansion protocols for Treg therapies and help tailor the Treg expansion process to an individual’s baseline Treg signature.

TARGETING VAV1 SCAFFOLDING AND ENZYMATIC FUNCTIONS IN MULTIPLE SCLEROSIS VIA BRAIN-PENETRANT MOLECULAR GLUE DEGRADERS

Abstract Multiple Sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS) with significant unmet medical needs, as current therapies offer limited efficacy against neurodegeneration and can have considerable side effects. VAV1, a key signaling protein predominantly expressed in hematopoietic cells, plays a crucial role in T and B lymphocyte activation and is genetically and functionally validated as a therapeutic target in MS. This project proposes an innovative approach to target VAV1 through the development of brain-penetrant molecular glue (MG) degraders. Distinct from Proteolysis Targeting Chimeras (PROTACs) that require a high- affinity ligand for the target protein, molecular glues can mediate degradation by engaging specific protein surface features, such as loops, without the necessity of a dedicated binder. These degraders aim to induce the proteasomal degradation of VAV1, thereby ablating both its enzymatic and scaffolding functions, which are implicated in neuroinflammation. The research strategy involves three primary aims: 1) To optimize lead VAV1 molecular glue degraders for enhanced potency, brain penetration, and favorable pharmacokinetic properties using advanced computational modeling and medicinal chemistry. 2) To evaluate the in vivo efficacy of the optimized VAV1 degraders in preclinical mouse models of MS (Experimental Autoimmune Encephalomyelitis - EAE), assessing their ability to ameliorate disease severity, reduce CNS inflammation and demyelination, and engage VAV1 in the CNS. 3) To investigate the Structure-Activity Relationship (SAR) of a novel non-canonical VAV1 degron motif, aiming to expand the understanding of molecular glue-mediated degradation and enable the rational design of degraders for other challenging therapeutic targets. Successful completion of this project is expected to deliver preclinical candidate VAV1 degraders with the potential for a novel, effective, and safer treatment paradigm for MS. Furthermore, the insights gained into non-canonical degron recognition will significantly advance the field of targeted protein degradation, broadening the scope of "undruggable" targets for therapeutic intervention in various diseases.

Neuroinflammation in Cerebral Small Vessel Disease

Project Summary/Abstract Cerebral small vessel disease (cSVD) is a leading cause of vascular contributions to cognitive impairment and dementia (VCID), which is the 2nd leading cause of dementia and a significant contributor to Alzheimer’s disease (AD). Thus far, the underlying pathogenesis of cSVD is poorly understood. Several lines of evidence, including animal models, postmortem human brain pathology, and systemic inflammatory markers, demonstrated the damaging role of chronic neuroinflammation in cSVD. Direct evidence of neuroinflammation at the tissue level in patients with cSVD is still critically needed. The sphingosine-1-phosphate receptor 1 (S1PR1) regulates neuroinflammation through microglial and astrocyte activation and trafficking and has emerged as a promising target for neuroinflammation. In postmortem brains of patients with cSVD, we observed elevated S1PR1 expression and colocalization of S1PR1 with astrocytes and microglia. A novel 11C-CS1P1 PET radiotracer with high affinity and specificity targeting S1PR1 has been recently developed and validated in animal models and post-mortem human specimens. Under an FDA-approved eIND (IND 146548), we have successfully completed the safety and dosimetry study in healthy participants and performed preliminary studies in patients with cSVD. We found that 11C-CS1P1 PET uptake is significantly associated with WMH lesion burden in patients with cSVD after controlling for age, sex, race, vascular risk factors, and amyloid deposition. We hypothesize that 11C-CS1P1 PET uptake is a tissue-level biomarker of neuroinflammation to provide insight into cSVD severity, progression, and prognosis. We will 1) evaluate the relationship between 11C-CS1P1 PET uptake and cSVD neuroimaging abnormalities and cognitive impairment, 2) evaluate the test-retest repeatability and longitudinal evolution, and 3) determine whether 11C-CS1P1 PET uptake at baseline predict cSVD progression. The successful completion of this study will establish 11C-CS1P1 PET as an neuroinflammation imaging biomarker and investigate the role of neuroinflammation in cSVD pathogenesis and progression. It will lay a foundation for developing future therapies in modulating neuroinflammation.

Specificity requirements and functional properties of microbiota-reactive peri-weaning Tregs

PROJECT SUMMARY This application seeks to define the specificity requirements and functional properties of regulatory T cells (Tregs) that maintain tolerance to the microbiota. RORgt+ Tregs generated during an early-life peri-weaning window (from approximately P14 to P28 in mice) are particularly critical for intestinal tolerance. Mice that first encounter their microbiota outside this window still generate Tregs, but these cells are functionally inferior to those induced during the peri-weaning period and fail to maintain tolerance. The features of peri-weaning Tregs that make them so essential for intestinal homeostasis are not well defined. Here we propose to test two non-mutually exclusive hypotheses: 1) that the unique functionality of peri-weaning Tregs requires a distinct functional state; and 2) that reactivity with specific members of the microbiota is required for peri-weaning Tregs to maintain intestinal tolerance to a complex SPF microbiota. We have developed a model of intestinal inflammation based on oral delivery of the non-steroidal anti- inflammatory drug (NSAID) piroxicam that reveals underlying immune dysregulation in mice with defects in peri-weaning Tregs. When we applied this model to gnotobiotic mice colonized with defined microbiota communities we found that one community (OMM12) induced Tregs capable of preventing inflammation while the other community (ASF) did not, despite similar induction of RORgt+ peri-weaning Tregs by both communities. This exciting result suggests a previously unappreciated specificity requirement for induction of peri-weaning Tregs and indicates that differences in the microbes encountered early in life can have lifelong ramifications for immune tolerance. To better understand the basis of this specificity requirement, we developed a pipeline to rapidly screen the reactivity of T cells and applied it to mice colonized with the protective OMM12 community. This analysis revealed that the antigen-specific Treg response is biased toward only a subset of the microbiota. Thus, by tracking and characterizing microbiota-reactive peri-weaning Tregs at unprecedented resolution, we uncovered an unexpected bias in the microbiota-reactivity of Tregs. We are now ideally positioned to examine how the specificities and functional properties of peri-weaning Tregs are linked to their unique role in intestinal tolerance. In Aim 1, we will define the specificity of microbiota- reactive peri-weaning Tregs at homeostasis, using new tools developed through our screening pipeline, and we will determine whether missing the weaning period alters Treg responses to the microbiota. In Aim 2, we will compare the transcriptional programs of peri-weaning and post-weaning Tregs to identify peri-weaning- specific features. We will also build on our analyses from Aim 1 to determine if functional differences are linked to reactivity with specific members of the microbiota. In Aim 3, we will explore why specific members of the microbiota are required for induction of protective peri-weaning Tregs. We will define communities of microbes that do or do not confer protection in our piroxicam model, and we will profile the Tregs in these communities, including microbiota-reactive Tregs with defined specificities, to test the hypothesis that a key aspect of peri- weaning Treg function is specificity for only certain gut microbes.

Research on End-user Acceptability.and Long-term Impacts of HIV Cure Strategies (REALISE)

ABSTRACT Despite remarkable advances in HIV cure science, emerging cure candidates will likely involve trade-offs (e.g., incomplete eradication, monitoring burdens) and must compete with increasingly convenient long-acting ART; without early implementation guidance, even efficacious products may see limited uptake, particularly among the ~30–40% of people with HIV (PWH) in the U.S. who are not durably suppressed. We propose REALISE, a multidisciplinary program to define plausible cure profiles, quantify end-user preferences, and project population-level impact to inform product design and policy before market entry. Aim 1 conducts qualitative interviews with ~30 researchers and developers to delineate credible 10–20-year cure and long-acting treatment scenarios (eradication vs functional control, safety, monitoring, durability), yielding bounded “target product profiles.” Aim 2 elicits patient-centered preferences through a two-stage study: formative interviews (n=60; ≥50% not virally suppressed) to identify salient attributes; best-worst scaling (n=360 across Missouri, Georgia, and San Francisco) to prioritize attributes; and a discrete choice experiment (n=360) to quantify trade-offs versus alternative therapies, with latent class analysis to identify preference segments and estimate potential reach. Aim 3 integrates preference-based uptake from Aim 2 with Aim 1 efficacy and cost inputs in a mathematical model to estimate health impact, QALYs, net QALYs, and incremental cost-effectiveness across heterogeneous populations and Ending the HIV Epidemic jurisdictions. Innovation lies in linking cure R&D horizons to end-user preferences and transmission-dynamic outcomes, an approach that anticipates real-world use rather than retrofitting after approval. Deliverables include ranked cure attributes for product optimization, uptake projections including among unsuppressed PWH, and jurisdiction-specific value assessments to guide public health investment. By aligning cure design with what patients will accept and systems can sustain, REALISE will accelerate effective deployment of future cure strategies and maximize their contribution to Ending the HIV Epidemic. In doing so, this study advances NIH's priorities by connecting implementation science with prevention, treatment, and cure research. Using a multidisciplinary strategy to refine and extend `target product profiles,' REALISE will ensure cure development reflects patient needs and accelerate translation into real-world benefit.

Structural and functional characterization of autoimmune antibodies against NMDAR

Project Summary. The goal of this project is to understand the origins and molecular mechanisms underlying the anti-cancer autoimmune response against the N-methyl-D-aspartate receptor (NMDAR) and its correlation with anti-N-methyl-D-aspartate receptor autoimmune encephalitis (NMDARAE). While anti-cancer immune responses can promote tumor elimination, they may also lead to the production of self-reactive antibodies that trigger autoimmune diseases. NMDARAE is the most common form of immune-mediated encephalitis, which results in prominent neuropsychiatric symptoms, including seizures, psychosis, and memory deficits. NMDARs belong to a family of ligand-gated ion channels expressed exclusively in the central nervous system. They are involved in various aspects of brain development and function, including learning and memory. They respond to the neurotransmitter glutamate and a co-agonist, glycine or D-serine, to mediate excitatory neurotransmission, which plays a central role in synaptic plasticity. NMDARAE is associated with ovarian teratomas, where aberrant NMDAR expression is believed to trigger an autoimmune response. In NMDARAE, anti-NMDAR antibodies, as well as B cells and antibody-secreting cells, cross the blood-brain barrier via unknown mechanisms, resulting in the presence of anti-NMDAR antibodies at high titers within the brain and cerebrospinal fluid (CSF). These antibodies target NMDARs, modulating their function and contributing to disease pathology. Emerging evidence, supported by our preliminary data, suggests that NMDARs are also expressed in triple-negative breast cancer (TNBC), extending the relevance of anti-NMDAR autoimmunity beyond ovarian teratomas. In our TNBC mouse model, which ectopically expresses NMDARs (TNBC-NMDAR), we observed the onset of anti-NMDAR autoimmunity, where the produced antibodies cause both anti-tumor activity and symptoms such as lowered seizure threshold, mirroring key features of NMDARAE. Here, we will establish this TNBC mouse model as we develop molecular methods to characterize it. Aim 1 will focus on establishing and characterizing the TNBC- NMDAR mouse model. We will develop a detection method utilizing the intact tetrameric NMDAR channel proteins and a method to isolate B cells expressing B cell receptors against NMDAR from biological samples by using fluorescently labeled intact NMDAR proteins, followed by single-cell RNA sequencing. Aim 2 will utilize single-particle cryo-electron microscopy (cryo-EM) to investigate the interactions between NMDAR and the cloned antibodies, providing insights into epitope recognition, NMDAR subtype specificity, and conformational changes induced by antibody binding. Aim 3 will assess the impact of the cloned antibodies on NMDAR channel activity using electrophysiology. We will also assess anti-tumor activity and NMDARAE onset by each antibody clone. Together, the proposed research will gain insights into the link between anti-cancer anti-NMDAR autoimmunity and NMDARAE. It will also elucidate which functional properties of the cloned antibodies promote anti-tumor activity while contributing to NMDARAE, thereby informing potential therapeutic strategies.

Multimodal computational models for early prediction of peritoneal recurrence in gastric cancer

ABSTRACT Gastric cancer represents a significant disease burden and is a leading cause of cancer-related deaths in the United States and globally. Approximately 80% of gastric cancer patients are diagnosed at an advanced stage, with the peritoneum being the most common site of relapse (peritoneal recurrence) after radical surgery. Nearly 50% of patients with advanced-stage gastric cancer develop peritoneal recurrence post-surgery, resulting in a median survival of only 3–6 months and a markedly reduced quality of life. Early peritoneal recurrence is primarily characterized by micro-metastasis, which traditional imaging techniques struggle to detect due to the small size of metastatic nodules. Predicting the likelihood and timing of peritoneal recurrence is crucial for identifying at- risk patients, enabling timely interventions that could improve survival rates and quality of life. Unfortunately, reliable predictive biomarkers and models for peritoneal recurrence in gastric cancer are lacking in clinical practice, highlighting an urgent need for innovative predictive tools. This proposal aims to develop and validate novel predictive models for early peritoneal recurrence in gastric cancer, leveraging advanced deep learning techniques and multimodal integration of clinical, radiological (CT), and histopathological (hematoxylin and eosin, H&E) data. In Aim 1, we will develop a rational approach for predicting peritoneal recurrence by creating a novel deep learning multimodal method guided by genomics knowledge. Additionally, we will integrate both deep learning-extracted features and traditional hand-crafted radiomics features with clinical data to improve prediction accuracy. Aim 2 focuses on developing a robust prediction model of peritoneal recurrence utilizing a pre-trained foundation model from large-scale H&E image data. Aim 3 will combine CT, H&E, and clinical data to further enhance predictive capabilities, employing an innovative cross-modal collaborative optimization approach for multimodal data integration. All models will be trained and internally validated using a retrospective cohort from Atrium Health Wake Forest Baptist Comprehensive Cancer Center and externally validated in two independent cohorts from additional institutions to ensure robustness across populations and imaging protocols. Additionally, we will compare our models with existing methods, including clinical staging and alternative fusion strategies. If successful, these models will enhance risk stratification and prediction of peritoneal recurrence in gastric cancer patients, significantly improving survival rates and quality of life by identifying those likely to develop peritoneal recurrence post-surgery and facilitating timely intervention. Furthermore, they can help avoid the risk of complications and extra medical costs associated with overtreatment. Since the information is derived from routinely examined CT, H&E and clinical data, they could be seamlessly integrated into current clinical workflows. The AI technology developed through this project has the potential to benefit underserved populations in low- resource settings and reduce healthcare disparities in the U.S.

Utilizing integrin-targeted PET imaging and therapeutics to predict and treat radiation-induced pulmonary fibrosis

Project Summary/Abstract. Lung cancer is the leading cause of cancer death in the US, with over 125,000 deaths annually. Radiation therapy (RT) is a critical component of curative lung cancer treatment for many patients. However, radiationinduced pulmonary fibrosis (RIPF) is a common side effect that carries a poor prognosis with limited treatment options. Up to 40% of patients with lung cancer who receive RT may experience RIPF. RIPF is a late effect of RT, typically occurring 3 or more months after treatment. The symptoms of RIPF can include shortness of breath, pleural effusions, decreased lung function, and respiratory failure. Cell surface integrin heterodimers play a key role in the pathogenesis of RIPF. In particular, the integrin αvβ6, which is expressed at a low level in the alveolar epithelium at baseline, is significantly upregulated upon RT damage. The key role of integrin αvβ6 in RIPF is illustrated by studies in which mice lacking integrin αvβ6, or treated with an αvβ6-blocking antibody, do not develop RIPF. Here, we propose to translate this mechanistic understanding of RIPF into novel approaches for monitoring and treating RIPF. We hypothesize that non-invasive αvβ6 PET imaging will be safe and can specifically bind to αvβ6 in patients with RIPF. Additionally, we hypothesize that a novel small-molecule integrin antagonist, IDL2965, can mitigate and treat RIPF in mice. In this project, we are utilizing mice to model RIPF, as mice develop RIPF that mimics human disease. In addition, cellular and in vitro models do not approximate the complex biology leading to the development of RIPF. Our data using [64Cu]Cu-DOTA-αvβ6-BP to detect early RIPF in mice are compelling in both single-fraction high-dose RT and lower dose-larger volume RT models (Lo et. al, IJROBP 2025). However, to progress to clinical trials in patients with cancer, we will obtain data to submit an Investigational New Drug (IND) application to the FDA. Importantly, we propose translating [64Cu]Cu-DOTA-αvβ6-BP PET imaging into patients with lung cancer, allowing us to better identify RIPF and develop a tool to determine the efficacy of IDL-2965 in future clinical studies. The specific aims of the proposal are: (1) Characterize the utility of [64Cu]Cu-DOTA-αvβ6-BP in mice with conventionally fractionated RT and identify circulating biomarkers of RIPF, and determine the in vivo toxicology of [64Cu]Cu-DOTA-αvβ6-BP to prepare and submit an exploratory Investigational New Drug (eIND) application to the FDA, (2) Conduct a first-in-human clinical trial of [64Cu]Cu-DOTA-αvβ6-BP to determine its safety and human dosimetry in patients with evidence of RIPF from computed tomography or in healthy controls, and (3) Determine the effect of integrin antagonism using IDL-2965 on mitigating RIPF in preclinical mouse models. The goals of this proposal are two-fold: (1) demonstrate safety and target specificity for [64Cu]Cu-DOTA-αvβ6-BP so that it can be used in future studies to identify RIPF and evaluate the efficacy of anti-fibrotic therapies, and 2) determine the ability of IDL-2965 to prevent RIPF in preclinical mouse models.

Defining Microbial and Host Pathways Driving Asymptomatic C. difficile Colonization Associated with Aging and High-Sugar Diets

SUMMARY Clostridioides difficile infection (CDI) is a leading cause of healthcare-associated diarrhea, with rising incidence in community settings and a growing burden of asymptomatic colonization. Asymptomatic car- riers, particularly among the elderly and individuals consuming high-sugar diets, represent a critical but underexplored reservoir for transmission and disease progression. This proposal introduces novel, anti- biotic-independent mouse models demonstrating that both dietary sugar and aging independently pro- mote asymptomatic C. difficile colonization. We hypothesize that these factors disrupt colonization re- sistance (CR) through distinct but overlapping microbial, metabolic, and immune pathways. In Aim 1, we will define how traditional and emerging dietary sugars alter the gut environment to permit C. difficile colonization using in vitro bioreactors and in vivo models. Aim 2 will identify age-associated changes in microbiota and mucosal immunity that impair CR, using longitudinal studies and fecal micro- biota transfer. Aim 3 will functionally validate C. difficile genes upregulated during asymptomatic carriage using CRISPR-Cas9 mutants in both sugar- and age-induced models. This integrative, multi-omics approach will uncover the mechanisms enabling asymptomatic colonization and identify microbial and host targets for intervention. The findings will inform microbiome-based strat- egies to prevent CDI in vulnerable populations and shift current paradigms in CDI risk assessment and prevention.

Linear diribonucleotides regulation of bacterial physiology and infections

RNA degradation was thought to proceed through endonucleolytic fragmentation, followed by exo- ribonuclease trimming which generate short RNA fragments that are turned over into mononucleotides by oligoribonuclease (Orn). In the last funding period, we published data supporting that only specific enzymes (Orn, NrnA, NrnB, and NrnC) cleave diribonucleotides into monoribonucleotides, and that prokaryotic organisms need to encode at least one diribonuclease to fulfill this specific function. These results support a new perspective on RNA degradation in which the short oligoribonucleotides are processed through a sequence of discrete steps involving distinct enzymes. In addition, linear diribonucleotides appear to be biologically active molecules since we reported that mutants lacking these enzymes accumulate diribonucleotides and have altered cell growth, biofilm formation, motility, and sporulation. Here we present additional preliminary data supporting diribonucleotides as active signaling molecules in the cell including: 1. Specific enzymes act trinucleases to generate diribonucleotides, 2. RNase AM of Pseudomonas aeruginosa ∆orn is a cryptic diribonuclease, 3. Two enzymes in central metabolism are diribonucleotide- binding proteins, and 4. P. aeruginosa ∆orn has virulence defects in an animal model of catheter-associated urinary tract infection. Our past publications and preliminary data provide the scientific premise for our hypothesis that cells generate linear dinucleotides from RNA degradation and linearization of cyclic dinucleotides, which can bind target proteins to alter cell physiology and pathogenesis. To test these aims, we will perform the following specific aims: In Aim 1, we will characterize the generation and degradation of diribonucleotides by characterizing how diribonucleases and triribonucleases bind their respective substrates through molecular biology, biochemistry, and computational docking. In Aim 2, we will identify effects of dinucleotides on bacterial metabolism and physiology by characterizing the binding proteins that specifically interact with linear diribonucleotides. Building on our success of identifying cellular diribonucleotide receptors, we will screen for additional proteins from open reading libraries of P. aeruginosa and Bacillus anthracis. We will exploit the strains available to us that lack all diguanylate cyclases to reveal whether the effect of linear diribonucleotides is independent of c-di-GMP signaling. In Aim 3, we will characterize the effect of expression levels of dinucleases and the effect of dinucleotide accumulation on bacterial physiology and pathogenesis. We will develop mass spectrometry methods to detect di- and triribonucleotides. We will employ existing mutants lacking diribonucleases, including P. aeruginosa ∆orn to study the defects in chronic infection in a murine model of catheter-associated urinary tract infection. Results from these studies will advance our understanding of RNA degradation and open a new area of signaling by linear diribonucleotides with the potential to be applied to novel antibacterial strategies.

Perturbation of mammary immunoglobulins during maternal antibiotic administration

Project Summary Prescribed in up to 40% of pregnancies, antibiotics represent the most commonly used class of medication during pregnancy. Although this practice is often necessary for maternal health, accumulating evidence suggests that antibiotic exposure may have unintended consequences for the mother-infant dyad. Epidemiologic studies associate maternal antibiotic exposure, especially in the absence of infection, with increased risk of neonatal complications including late-onset sepsis (LOS) and necrotizing enterocolitis (NEC), yet the mechanisms driving these associations remain poorly understood. Secretory IgA (sIgA) in milk is an essential component of neonatal mucosal immunity, shaping early gut microbial colonization and providing protection against enteric pathogens. The mechanisms by which maternal physiology regulates the abundance and microbial specificity of these antibodies in milk remain poorly understood. In animal models, the maternal gut–mammary axis governs the generation of milk IgA: IgA-committed lymphocytes from the maternal intestine migrate to the mammary gland during advancing pregnancy via CCL- 28/CCR10 signaling. Our preliminary data suggest that maternal antibiotic exposure disrupts this process leading to a decrease in milk IgA. However, the timing and extent of antibody dysbiosis are undefined; the downstream effects on neonatal intestinal health are unknown; and the underlying mechanisms—whether due to altered microbial stimulation, impaired recruitment of IgA⁺ cells to the mammary gland, or both—remain to be elucidated. Our central hypothesis is that maternal antibiotic exposure reduces pathogen-reactive IgA in milk by impairing gut-to-mammary immune cell trafficking thereby compromising neonatal mucosal immunity and increasing infection susceptibility. We will address this hypothesis through three integrated aims: (1) Determine the magnitude and duration of antibiotic-mediated mammary antibody dysbiosis in women who deliver preterm and at term; (2) Identify microbial targets of mammary antibodies diminished by maternal antibiotic exposure and (3 Determine the role of maternal antibiotics in the disruption of mammary resident IgA+ plasma cells in animal models. This integrative human and animal study will uncover critical mechanisms by which maternal antibiotic use alters the maternal-infant immune axis. The results will provide mechanistic insight into the risks associated with perinatal antibiotic exposure and inform clinical strategies to mitigate risk to neonatal health.

Transcriptional control of activation induced deaminase (AID) function

SUMMARY Somatic hypermutation (SHM) and class switch recombination (CSR) are vital for the generation of high affinity antibodies with appropriate effector function, protection against infection, and vaccine efficiency. They are initiated when the activation induced deaminase (AID) deaminates cytidines in single-stranded DNA in the context of transcription by RNA polymerase 2 (Pol2). Aberrant DNA deamination by AID is an important driver of genetic instability and the development of B cell malignancies. Understanding the factors and mechanisms that coordinate AID-mediated deamination with Pol2 transcription is an important objective in the study of humoral immunity and the central goal of research under this grant. Our preliminary data demonstrate that Pol2 pause factor NELF, Super Elongation Complex (SEC) components MLLT1/3, and the phosphatase module of the Integrator-protein phosphatase complex (INT-PP2A) are required for SHM, with MLLT1/3 but not NELF being required for AID binding to its chromatin targets. Our findings yield a new conceptual framework and model for AID-Pol2 collaboration in which NELF and a balance between kinase and phosphatase activities of SEC and INT-PP2A regulate Pol2 pausing/elongation to generate the critical stalled Pol2 complex on which AID acts. Further, our work has yielded major methodological advances that allow us to overcome obstacles that have stymied progress in the field. In this proposal, we take advantage of these conceptual and technical advances to pursue our central goal through the following two aims: Aim 1: Determine the molecular mechanisms by which NELF and other Pol2 regulatory factors enable AID-Pol2 collaboration and SHM/CSR. It has previously been very difficult to assess the role of cell-essential factors in SHM. By combining our new Rapid Assay for SHM (RASH) cells with degron technology, we will determine the mechanism of action of our newly discovered regulators of SHM using genomic, transcriptomic, and interaction assays that assess Pol2 distribution, phosphorylation, and activity, and the chromatin binding profiles of and interactions between AID and components of NELF, SEC, and INT-PP2A. AID and MLLT1 appear to co-associate in a complex and we will test for a direct interaction between AID and MLLT1/3. Factors will be tested for roles in CSR and validated in human cell line and germinal center B cell models and in mice. Aim 2: Hypothesis testing and deep mechanistic analysis through perturbation of the balance between Pol2 pause/arrest and elongation. We will rigorously test our new model for AID-Pol2 collaboration using degron, reconstitution, mutagenesis, and small molecular inhibitor approaches to perturb the balance between Pol2 pausing and elongation, revealing how altering NELF-Pol2 interactions and the balance between SEC kinase and INT-PP2A phosphatase activities influences SHM efficiencies and AID binding. Together, our proposed studies are significant for the development of new technologies and for understanding mechanisms of antibody gene diversification and causes of genome instability and cancer.

Investigating the nonlinear complex dynamics of the tuft cell-microbiome cross-talk: the impact of feedback loops on immune regulation, microbial modulation and response to tissue insults

Project Abstract Tuft cells (TCs) are specialized chemosensory epithelial cells that are emerging as critical regulators of intestinal homeostasis. Named over 70 years ago based on their distinct morphology, a defined function for TCs was only elucidated in the last decade. TCs in the small intestine sense succinate from helminths to initiate type 2 immune responses that mediate parasite expulsion. Recently, we discovered a novel physiologic function for TCs in the colon, where their role had been considered minimal. Succinate, a key microbial metabolite, is produced by colonic microbiota as both a precursor to other metabolites and a cross-feeding fuel source for pathogens. TCs respond to succinate by secreting interleukin-25 (IL-25), which activates type 2 cytokine- producing lymphocytes (T2Ls), amplifying TC expansion and reinforcing barrier function. We recently demonstrated that this SPB–TC–IL-25–T2L feedback loop is essential for protection against pathogen-induced colitis. Our preliminary data further suggest that TCs actively promote colonization by succinate-producing bacteria (SPBs), establishing positive feedback on TC-supporting microbes, while other epithelial cells such as goblet cells (GCs) and Paneth cells (PCs) may exert complementary or counterbalancing influences. Supported by new modeling insights, we hypothesize that these epithelial–immune–microbiome interactions form coordinated feedback loops that collectively optimize intestinal resilience. These loops may create a dynamic, multi-stable system that flexibly transitions between homeostatic and hyperplastic states, buffering against microbial fluctuations and pathogenic insults while preventing uncontrolled type 2 inflammation. Using a combination of mathematical modeling and experimental validation, we will develop a multi- layered systems framework to explore how epithelial–immune–microbial feedbacks shape resilience or breakdown in clinically relevant models of colonic infection and inflammation. Our three Aims will (1) develop, calibrate, and validate a mathematical model that integrates TCs, GCs, PCs, SPBs, and SCBs; (2) define the immunological circuits governing epithelial–microbiome equilibrium; and (3) determine how epithelial feedbacks regulate microbial community structure and resilience. In line with NIH’s new initiative to prioritize human-based research, our proposal combines computational modeling, human colonic organoids, and complementary mouse models. Organoid experiments will provide human-relevant data for model calibration, while in vivo studies validate systemic predictions, ensuring both rigor and translational relevance while minimizing reliance on animal models. This work will generate interoperable models that integrate epithelial, microbial, and immune networks, providing predictive insight into intestinal outcomes under homeostatic, infectious, and inflammatory conditions and informing therapeutic strategies for microbiome-targeted interventions.

Computational Mechanisms of Predictive Processing in Brains and Machines

Predictive processing offers a unifying view of neural computation, proposing that brains continuously anticipate sensory input and update internal models based on prediction errors. In this talk, I will present converging evidence for the computational mechanisms underlying this framework across human neuroscience and deep neural networks. I will begin with recent work showing that large-scale distributed prediction-error encoding in the human brain directly predicts how sensory representations reorganize through predictive learning. I will then turn to PredNet, a popular predictive coding inspired deep network that has been widely used to model real-world biological vision systems. Using dynamic stimuli generated with our Spatiotemporal Style Transfer algorithm, we demonstrate that PredNet relies primarily on low-level spatiotemporal structure and remains insensitive to high-level content, revealing limits in its generalization capacity. Finally, I will discuss new recurrent vision models that integrate top-down feedback connections with intrinsic neural variability, uncovering a dual mechanism for robust sensory coding in which neural variability decorrelates unit responses, while top-down feedback stabilizes network dynamics. Together, these results outline how prediction error signaling and top-down feedback pathways shape adaptive sensory processing in biological and artificial systems.

A human stem cell-derived organoid model of the trigeminal ganglion

MRI investigation of orientation-dependent changes in microstructure and function in a mouse model of mild traumatic brain injury

Organization of thalamic networks and mechanisms of dysfunction in schizophrenia and autism

Thalamic networks, at the core of thalamocortical and thalamosubcortical communications, underlie processes of perception, attention, memory, emotions, and the sleep-wake cycle, and are disrupted in mental disorders, including schizophrenia and autism. However, the underlying mechanisms of pathology are unknown. I will present novel evidence on key organizational principles, structural, and molecular features of thalamocortical networks, as well as critical thalamic pathway interactions that are likely affected in disorders. This data can facilitate modeling typical and abnormal brain function and can provide the foundation to understand heterogeneous disruption of these networks in sleep disorders, attention deficits, and cognitive and affective impairments in schizophrenia and autism, with important implications for the design of targeted therapeutic interventions

Generation and use of internal models of the world to guide flexible behavior

Cellular Crosstalk in Brain Development, Evolution and Disease

Cellular crosstalk is an essential process during brain development and is influenced by numerous factors, including cell morphology, adhesion, the local extracellular matrix and secreted vesicles. Inspired by mutations associated with neurodevelopmental disorders, we focus on understanding the role of extracellular mechanisms essential for the proper development of the human brain. Therefore, we combine 2D and 3D in vitro human models to better understand the molecular and cellular mechanisms involved in progenitor proliferation and fate, migration and maturation of excitatory and inhibitory neurons during human brain development and tackle the causes of neurodevelopmental disorders.

AutoMIND: Deep inverse models for revealing neural circuit invariances

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

OpenNeuro FitLins GLM: An Accessible, Semi-Automated Pipeline for OpenNeuro Task fMRI Analysis

In this talk, I will discuss the OpenNeuro Fitlins GLM package and provide an illustration of the analytic workflow. OpenNeuro FitLins GLM is a semi-automated pipeline that reduces barriers to analyzing task-based fMRI data from OpenNeuro's 600+ task datasets. Created for psychology, psychiatry and cognitive neuroscience researchers without extensive computational expertise, this tool automates what is largely a manual process and compilation of in-house scripts for data retrieval, validation, quality control, statistical modeling and reporting that, in some cases, may require weeks of effort. The workflow abides by open-science practices, enhancing reproducibility and incorporates community feedback for model improvement. The pipeline integrates BIDS-compliant datasets and fMRIPrep preprocessed derivatives, and dynamically creates BIDS Statistical Model specifications (with Fitlins) to perform common mass univariate [GLM] analyses. To enhance and standardize reporting, it generates comprehensive reports which includes design matrices, statistical maps and COBIDAS-aligned reporting that is fully reproducible from the model specifications and derivatives. OpenNeuro Fitlins GLM has been tested on over 30 datasets spanning 50+ unique fMRI tasks (e.g., working memory, social processing, emotion regulation, decision-making, motor paradigms), reducing analysis times from weeks to hours when using high-performance computers, thereby enabling researchers to conduct robust single-study, meta- and mega-analyses of task fMRI data with significantly improved accessibility, standardized reporting and reproducibility.

Understanding reward-guided learning using large-scale datasets

Understanding the neural mechanisms of reward-guided learning is a long-standing goal of computational neuroscience. Recent methodological innovations enable us to collect ever larger neural and behavioral datasets. This presents opportunities to achieve greater understanding of learning in the brain at scale, as well as methodological challenges. In the first part of the talk, I will discuss our recent insights into the mechanisms by which zebra finch songbirds learn to sing. Dopamine has been long thought to guide reward-based trial-and-error learning by encoding reward prediction errors. However, it is unknown whether the learning of natural behaviours, such as developmental vocal learning, occurs through dopamine-based reinforcement. Longitudinal recordings of dopamine and bird songs reveal that dopamine activity is indeed consistent with encoding a reward prediction error during naturalistic learning. In the second part of the talk, I will talk about recent work we are doing at DeepMind to develop tools for automatically discovering interpretable models of behavior directly from animal choice data. Our method, dubbed CogFunSearch, uses LLMs within an evolutionary search process in order to "discover" novel models in the form of Python programs that excel at accurately predicting animal behavior during reward-guided learning. The discovered programs reveal novel patterns of learning and choice behavior that update our understanding of how the brain solves reinforcement learning problems.

“Brain theory, what is it or what should it be?”

n the neurosciences the need for some 'overarching' theory is sometimes expressed, but it is not always obvious what is meant by this. One can perhaps agree that in modern science observation and experimentation is normally complemented by 'theory', i.e. the development of theoretical concepts that help guiding and evaluating experiments and measurements. A deeper discussion of 'brain theory' will require the clarification of some further distictions, in particular: theory vs. model and brain research (and its theory) vs. neuroscience. Other questions are: Does a theory require mathematics? Or even differential equations? Today it is often taken for granted that the whole universe including everything in it, for example humans, animals, and plants, can be adequately treated by physics and therefore theoretical physics is the overarching theory. Even if this is the case, it has turned out that in some particular parts of physics (the historical example is thermodynamics) it may be useful to simplify the theory by introducing additional theoretical concepts that can in principle be 'reduced' to more complex descriptions on the 'microscopic' level of basic physical particals and forces. In this sense, brain theory may be regarded as part of theoretical neuroscience, which is inside biophysics and therefore inside physics, or theoretical physics. Still, in neuroscience and brain research, additional concepts are typically used to describe results and help guiding experimentation that are 'outside' physics, beginning with neurons and synapses, names of brain parts and areas, up to concepts like 'learning', 'motivation', 'attention'. Certainly, we do not yet have one theory that includes all these concepts. So 'brain theory' is still in a 'pre-newtonian' state. However, it may still be useful to understand in general the relations between a larger theory and its 'parts', or between microscopic and macroscopic theories, or between theories at different 'levels' of description. This is what I plan to do.

From Spiking Predictive Coding to Learning Abstract Object Representation

In a first part of the talk, I will present Predictive Coding Light (PCL), a novel unsupervised learning architecture for spiking neural networks. In contrast to conventional predictive coding approaches, which only transmit prediction errors to higher processing stages, PCL learns inhibitory lateral and top-down connectivity to suppress the most predictable spikes and passes a compressed representation of the input to higher processing stages. We show that PCL reproduces a range of biological findings and exhibits a favorable tradeoff between energy consumption and downstream classification performance on challenging benchmarks. A second part of the talk will feature our lab’s efforts to explain how infants and toddlers might learn abstract object representations without supervision. I will present deep learning models that exploit the temporal and multimodal structure of their sensory inputs to learn representations of individual objects, object categories, or abstract super-categories such as „kitchen object“ in a fully unsupervised fashion. These models offer a parsimonious account of how abstract semantic knowledge may be rooted in children's embodied first-person experiences.

“Development and application of gaze control models for active perception”

Gaze shifts in humans serve to direct high-resolution vision provided by the fovea towards areas in the environment. Gaze can be considered a proxy for attention or indicator of the relative importance of different parts of the environment. In this talk, we discuss the development of generative models of human gaze in response to visual input. We discuss how such models can be learned, both using supervised learning and using implicit feedback as an agent interacts with the environment, the latter being more plausible in biological agents. We also discuss two ways such models can be used. First, they can be used to improve the performance of artificial autonomous systems, in applications such as autonomous navigation. Second, because these models are contingent on the human’s task, goals, and/or state in the context of the environment, observations of gaze can be used to infer information about user intent. This information can be used to improve human-machine and human robot interaction, by making interfaces more anticipative. We discuss example applications in gaze-typing, robotic tele-operation and human-robot interaction.

Developmental and evolutionary perspectives on thalamic function

Brain organization and function is a complex topic. We are good at establishing correlates of perception and behavior across forebrain circuits, as well as manipulating activity in these circuits to affect behavior. However, we still lack good models for the large-scale organization and function of the forebrain. What are the contributions of the cortex, basal ganglia, and thalamus to behavior? In addressing these questions, we often ascribe function to each area as if it were an independent processing unit. However, we know from the anatomy that the cortex, basal ganglia, and thalamus, are massively interconnected in a large network. One way to generate insight into these questions is to consider the evolution and development of forebrain systems. In this talk, I will discuss the developmental and evolutionary (comparative anatomy) data on the thalamus, and how it fits within forebrain networks. I will address questions including, when did the thalamus appear in evolution, how is the thalamus organized across the vertebrate lineage, and how can the change in the organization of forebrain networks affect behavioral repertoires.

Neurobiological constraints on learning: bug or feature?

Understanding how brains learn requires bridging evidence across scales—from behaviour and neural circuits to cells, synapses, and molecules. In our work, we use computational modelling and data analysis to explore how the physical properties of neurons and neural circuits constrain learning. These include limits imposed by brain wiring, energy availability, molecular noise, and the 3D structure of dendritic spines. In this talk I will describe one such project testing if wiring motifs from fly brain connectomes can improve performance of reservoir computers, a type of recurrent neural network. The hope is that these insights into brain learning will lead to improved learning algorithms for artificial systems.

Investigating the Neurobiology and Neurophysiology of Psilocybin Using Drosophila melanogaster as a Model System

Neural mechanisms of optimal performance

When we attend a demanding task, our performance is poor at low arousal (when drowsy) or high arousal (when anxious), but we achieve optimal performance at intermediate arousal. This celebrated Yerkes-Dodson inverted-U law relating performance and arousal is colloquially referred to as being "in the zone." In this talk, I will elucidate the behavioral and neural mechanisms linking arousal and performance under the Yerkes-Dodson law in a mouse model. During decision-making tasks, mice express an array of discrete strategies, whereby the optimal strategy occurs at intermediate arousal, measured by pupil, consistent with the inverted-U law. Population recordings from the auditory cortex (A1) further revealed that sound encoding is optimal at intermediate arousal. To explain the computational principle underlying this inverted-U law, we modeled the A1 circuit as a spiking network with excitatory/inhibitory clusters, based on the observed functional clusters in A1. Arousal induced a transition from a multi-attractor (low arousal) to a single attractor phase (high arousal), and performance is optimized at the transition point. The model also predicts stimulus- and arousal-induced modulations of neural variability, which we confirmed in the data. Our theory suggests that a single unifying dynamical principle, phase transitions in metastable dynamics, underlies both the inverted-U law of optimal performance and state-dependent modulations of neural variability.

Neural mechanisms of rhythmic motor control in Drosophila

All animal locomotion is rhythmic,whether it is achieved through undulatory movement of the whole body or the coordination of articulated limbs. Neurobiologists have long studied locomotor circuits that produce rhythmic activity with non-rhythmic input, also called central pattern generators (CPGs). However, the cellular and microcircuit implementation of a walking CPG has not been described for any limbed animal. New comprehensive connectomes of the fruit fly ventral nerve cord (VNC) provide an opportunity to study rhythmogenic walking circuits at a synaptic scale.We use a data-driven network modeling approach to identify and characterize a putative walking CPG in the Drosophila leg motor system.

Understanding reward-guided learning using large-scale datasets

Understanding the neural mechanisms of reward-guided learning is a long-standing goal of computational neuroscience. Recent methodological innovations enable us to collect ever larger neural and behavioral datasets. This presents opportunities to achieve greater understanding of learning in the brain at scale, as well as methodological challenges. In the first part of the talk, I will discuss our recent insights into the mechanisms by which zebra finch songbirds learn to sing. Dopamine has been long thought to guide reward-based trial-and-error learning by encoding reward prediction errors. However, it is unknown whether the learning of natural behaviours, such as developmental vocal learning, occurs through dopamine-based reinforcement. Longitudinal recordings of dopamine and bird songs reveal that dopamine activity is indeed consistent with encoding a reward prediction error during naturalistic learning. In the second part of the talk, I will talk about recent work we are doing at DeepMind to develop tools for automatically discovering interpretable models of behavior directly from animal choice data. Our method, dubbed CogFunSearch, uses LLMs within an evolutionary search process in order to "discover" novel models in the form of Python programs that excel at accurately predicting animal behavior during reward-guided learning. The discovered programs reveal novel patterns of learning and choice behavior that update our understanding of how the brain solves reinforcement learning problems.

Harnessing Big Data in Neuroscience: From Mapping Brain Connectivity to Predicting Traumatic Brain Injury

Neuroscience is experiencing unprecedented growth in dataset size both within individual brains and across populations. Large-scale, multimodal datasets are transforming our understanding of brain structure and function, creating opportunities to address previously unexplored questions. However, managing this increasing data volume requires new training and technology approaches. Modern data technologies are reshaping neuroscience by enabling researchers to tackle complex questions within a Ph.D. or postdoctoral timeframe. I will discuss cloud-based platforms such as brainlife.io, that provide scalable, reproducible, and accessible computational infrastructure. Modern data technology can democratize neuroscience, accelerate discovery and foster scientific transparency and collaboration. Concrete examples will illustrate how these technologies can be applied to mapping brain connectivity, studying human learning and development, and developing predictive models for traumatic brain injury (TBI). By integrating cloud computing and scalable data-sharing frameworks, neuroscience can become more impactful, inclusive, and data-driven..

Simulating Thought Disorder: Fine-Tuning Llama-2 for Synthetic Speech in Schizophrenia

Unlocking the Secrets of Microglia in Neurodegenerative diseases: Mechanisms of resilience to AD pathologies

An inconvenient truth: pathophysiological remodeling of the inner retina in photoreceptor degeneration

Photoreceptor loss is the primary cause behind vision impairment and blindness in diseases such as retinitis pigmentosa and age-related macular degeneration. However, the death of rods and cones allows retinoids to permeate the inner retina, causing retinal ganglion cells to become spontaneously hyperactive, severely reducing the signal-to-noise ratio, and creating interference in the communication between the surviving retina and the brain. Treatments aimed at blocking or reducing hyperactivity improve vision initiated from surviving photoreceptors and could enhance the signal fidelity generated by vision restoration methodologies.

Impact of High Fat Diet on Central Cardiac Circuits: When The Wanderer is Lost

Cardiac vagal motor drive originates in the brainstem's cardiac vagal motor neurons (CVNs). Despite well-established cardioinhibitory functions in health, our understanding of CVNs in disease is limited. There is a clear connection of cardiovascular regulation with metabolic and energy expenditure systems. Using high fat diet as a model, this talk will explore how metabolic dysfunction impacts the regulation of cardiac tissue through robust inhibition of CVNs. Specifically, it will present an often overlooked modality of inhibition, tonic gamma-aminobuytric acid (GABA) A-type neurotransmission using an array of techniques from single cell patch clamp electrophysiology to transgenic in vivo whole animal physiology. It also will highlight a unique interaction with the delta isoform of protein kinase C to facilitate GABA A-type receptor expression.

Cognitive maps as expectations learned across episodes – a model of the two dentate gyrus blades

How can the hippocampal system transition from episodic one-shot learning to a multi-shot learning regime and what is the utility of the resultant neural representations? This talk will explore the role of the dentate gyrus (DG) anatomy in this context. The canonical DG model suggests it performs pattern separation. More recent experimental results challenge this standard model, suggesting DG function is more complex and also supports the precise binding of objects and events to space and the integration of information across episodes. Very recent studies attribute pattern separation and pattern integration to anatomically distinct parts of the DG (the suprapyramidal blade vs the infrapyramidal blade). We propose a computational model that investigates this distinction. In the model the two processing streams (potentially localized in separate blades) contribute to the storage of distinct episodic memories, and the integration of information across episodes, respectively. The latter forms generalized expectations across episodes, eventually forming a cognitive map. We train the model with two data sets, MNIST and plausible entorhinal cortex inputs. The comparison between the two streams allows for the calculation of a prediction error, which can drive the storage of poorly predicted memories and the forgetting of well-predicted memories. We suggest that differential processing across the DG aids in the iterative construction of spatial cognitive maps to serve the generation of location-dependent expectations, while at the same time preserving episodic memory traces of idiosyncratic events.

Neural architectures: what are they good for anyway?

The brain has a highly complex structure in terms of cell types and wiring between different regions. What is it for, if anything? I'll start this talk by asking what might an answer to this question even look like given that we can't run an alternative universe where our brains are structured differently. (Preview: we can do this with models!) I'll then talk about some of our work in two areas: (1) does the modular structure of the brain contribute to specialisation of function? (2) how do different cell types and architectures contribute to multimodal sensory processing?

Memory formation in hippocampal microcircuit

The centre of memory is the medial temporal lobe (MTL) and especially the hippocampus. In our research, a more flexible brain-inspired computational microcircuit of the CA1 region of the mammalian hippocampus was upgraded and used to examine how information retrieval could be affected under different conditions. Six models (1-6) were created by modulating different excitatory and inhibitory pathways. The results showed that the increase in the strength of the feedforward excitation was the most effective way to recall memories. In other words, that allows the system to access stored memories more accurately.

Analyzing Network-Level Brain Processing and Plasticity Using Molecular Neuroimaging

Behavior and cognition depend on the integrated action of neural structures and populations distributed throughout the brain. We recently developed a set of molecular imaging tools that enable multiregional processing and plasticity in neural networks to be studied at a brain-wide scale in rodents and nonhuman primates. Here we will describe how a novel genetically encoded activity reporter enables information flow in virally labeled neural circuitry to be monitored by fMRI. Using the reporter to perform functional imaging of synaptically defined neural populations in the rat somatosensory system, we show how activity is transformed within brain regions to yield characteristics specific to distinct output projections. We also show how this approach enables regional activity to be modeled in terms of inputs, in a paradigm that we are extending to address circuit-level origins of functional specialization in marmoset brains. In the second part of the talk, we will discuss how another genetic tool for MRI enables systematic studies of the relationship between anatomical and functional connectivity in the mouse brain. We show that variations in physical and functional connectivity can be dissociated both across individual subjects and over experience. We also use the tool to examine brain-wide relationships between plasticity and activity during an opioid treatment. This work demonstrates the possibility of studying diverse brain-wide processing phenomena using molecular neuroimaging.

Rethinking Attention: Dynamic Prioritization

Decades of research on understanding the mechanisms of attentional selection have focused on identifying the units (representations) on which attention operates in order to guide prioritized sensory processing. These attentional units fit neatly to accommodate our understanding of how attention is allocated in a top-down, bottom-up, or historical fashion. In this talk, I will focus on attentional phenomena that are not easily accommodated within current theories of attentional selection – the “attentional platypuses,” as they allude to an observation that within biological taxonomies the platypus does not fit into either mammal or bird categories. Similarly, attentional phenomena that do not fit neatly within current attentional models suggest that current models need to be revised. I list a few instances of the ‘attentional platypuses” and then offer a new approach, the Dynamically Weighted Prioritization, stipulating that multiple factors impinge onto the attentional priority map, each with a corresponding weight. The interaction between factors and their corresponding weights determines the current state of the priority map which subsequently constrains/guides attention allocation. I propose that this new approach should be considered as a supplement to existing models of attention, especially those that emphasize categorical organizations.

Mapping the neural dynamics of dominance and defeat

Social experiences can have lasting changes on behavior and affective state. In particular, repeated wins and losses during fighting can facilitate and suppress future aggressive behavior, leading to persistent high aggression or low aggression states. We use a combination of techniques for multi-region neural recording, perturbation, behavioral analysis, and modeling to understand how nodes in the brain’s subcortical “social decision-making network” encode and transform aggressive motivation into action, and how these circuits change following social experience.

Genetic and epigenetic underpinnings of neurodegenerative disorders

Pluripotent cells, including embryonic stem (ES) and induced pluripotent stem (iPS) cells, are used to investigate the genetic and epigenetic underpinnings of human diseases such as Parkinson’s, Alzheimer’s, autism, and cancer. Mechanisms of somatic cell reprogramming to an embryonic pluripotent state are explored, utilizing patient-specific pluripotent cells to model and analyze neurodegenerative diseases.

Rett syndrome, MECP2 and therapeutic strategies

The development of the iPS cell technology has revolutionized our ability to study development and diseases in defined in vitro cell culture systems. The talk will focus on Rett Syndrome and discuss two topics: (i) the use of gene editing as an approach to therapy and (ii) the role of MECP2 in gene expression (i) The mutation of the X-linked MECP2 gene is causative for the disease. In a female patient, every cell has a wt copy that is, however, in 50% of the cells located on the inactive X chromosome. We have used epigenetic gene editing tools to activate the wt MECP2 allele on the inactive X chromosome. (ii) MECP2 is thought to act as repressor of gene expression. I will present data which show that MECP2 binds to Pol II and acts as an activator for thousands of genes. The target genes are significantly enriched for Autism related genes. Our data challenge the established model of MECP2’s role in gene expression and suggest novel therapeutic approaches.

Screen Savers : Protecting adolescent mental health in a digital world

In our rapidly evolving digital world, there is increasing concern about the impact of digital technologies and social media on the mental health of young people. Policymakers and the public are nervous. Psychologists are facing mounting pressures to deliver evidence that can inform policies and practices to safeguard both young people and society at large. However, research progress is slow while technological change is accelerating.My talk will reflect on this, both as a question of psychological science and metascience. Digital companies have designed highly popular environments that differ in important ways from traditional offline spaces. By revisiting the foundations of psychology (e.g. development and cognition) and considering digital changes' impact on theories and findings, we gain deeper insights into questions such as the following. (1) How do digital environments exacerbate developmental vulnerabilities that predispose young people to mental health conditions? (2) How do digital designs interact with cognitive and learning processes, formalised through computational approaches such as reinforcement learning or Bayesian modelling?However, we also need to face deeper questions about what it means to do science about new technologies and the challenge of keeping pace with technological advancements. Therefore, I discuss the concept of ‘fast science’, where, during crises, scientists might lower their standards of evidence to come to conclusions quicker. Might psychologists want to take this approach in the face of technological change and looming concerns? The talk concludes with a discussion of such strategies for 21st-century psychology research in the era of digitalization.

The Brain Prize winners' webinar

This webinar brings together three leaders in theoretical and computational neuroscience—Larry Abbott, Haim Sompolinsky, and Terry Sejnowski—to discuss how neural circuits generate fundamental aspects of the mind. Abbott illustrates mechanisms in electric fish that differentiate self-generated electric signals from external sensory cues, showing how predictive plasticity and two-stage signal cancellation mediate a sense of self. Sompolinsky explores attractor networks, revealing how discrete and continuous attractors can stabilize activity patterns, enable working memory, and incorporate chaotic dynamics underlying spontaneous behaviors. He further highlights the concept of object manifolds in high-level sensory representations and raises open questions on integrating connectomics with theoretical frameworks. Sejnowski bridges these motifs with modern artificial intelligence, demonstrating how large-scale neural networks capture language structures through distributed representations that parallel biological coding. Together, their presentations emphasize the synergy between empirical data, computational modeling, and connectomics in explaining the neural basis of cognition—offering insights into perception, memory, language, and the emergence of mind-like processes.

Decision and Behavior

This webinar addressed computational perspectives on how animals and humans make decisions, spanning normative, descriptive, and mechanistic models. Sam Gershman (Harvard) presented a capacity-limited reinforcement learning framework in which policies are compressed under an information bottleneck constraint. This approach predicts pervasive perseveration, stimulus‐independent “default” actions, and trade-offs between complexity and reward. Such policy compression reconciles observed action stochasticity and response time patterns with an optimal balance between learning capacity and performance. Jonathan Pillow (Princeton) discussed flexible descriptive models for tracking time-varying policies in animals. He introduced dynamic Generalized Linear Models (Sidetrack) and hidden Markov models (GLM-HMMs) that capture day-to-day and trial-to-trial fluctuations in choice behavior, including abrupt switches between “engaged” and “disengaged” states. These models provide new insights into how animals’ strategies evolve under learning. Finally, Kenji Doya (OIST) highlighted the importance of unifying reinforcement learning with Bayesian inference, exploring how cortical-basal ganglia networks might implement model-based and model-free strategies. He also described Japan’s Brain/MINDS 2.0 and Digital Brain initiatives, aiming to integrate multimodal data and computational principles into cohesive “digital brains.”

Sensory cognition

This webinar features presentations from SueYeon Chung (New York University) and Srinivas Turaga (HHMI Janelia Research Campus) on theoretical and computational approaches to sensory cognition. Chung introduced a “neural manifold” framework to capture how high-dimensional neural activity is structured into meaningful manifolds reflecting object representations. She demonstrated that manifold geometry—shaped by radius, dimensionality, and correlations—directly governs a population’s capacity for classifying or separating stimuli under nuisance variations. Applying these ideas as a data analysis tool, she showed how measuring object-manifold geometry can explain transformations along the ventral visual stream and suggested that manifold principles also yield better self-supervised neural network models resembling mammalian visual cortex. Turaga described simulating the entire fruit fly visual pathway using its connectome, modeling 64 key cell types in the optic lobe. His team’s systematic approach—combining sparse connectivity from electron microscopy with simple dynamical parameters—recapitulated known motion-selective responses and produced novel testable predictions. Together, these studies underscore the power of combining connectomic detail, task objectives, and geometric theories to unravel neural computations bridging from stimuli to cognitive functions.

LLMs and Human Language Processing

This webinar convened researchers at the intersection of Artificial Intelligence and Neuroscience to investigate how large language models (LLMs) can serve as valuable “model organisms” for understanding human language processing. Presenters showcased evidence that brain recordings (fMRI, MEG, ECoG) acquired while participants read or listened to unconstrained speech can be predicted by representations extracted from state-of-the-art text- and speech-based LLMs. In particular, text-based LLMs tend to align better with higher-level language regions, capturing more semantic aspects, while speech-based LLMs excel at explaining early auditory cortical responses. However, purely low-level features can drive part of these alignments, complicating interpretations. New methods, including perturbation analyses, highlight which linguistic variables matter for each cortical area and time scale. Further, “brain tuning” of LLMs—fine-tuning on measured neural signals—can improve semantic representations and downstream language tasks. Despite open questions about interpretability and exact neural mechanisms, these results demonstrate that LLMs provide a promising framework for probing the computations underlying human language comprehension and production at multiple spatiotemporal scales.

Brain-on-a-Chip: Advanced In Vitro Platforms for Drug Screening and Disease Modeling

Brain-Wide Compositionality and Learning Dynamics in Biological Agents

Biological agents continually reconcile the internal states of their brain circuits with incoming sensory and environmental evidence to evaluate when and how to act. The brains of biological agents, including animals and humans, exploit many evolutionary innovations, chiefly modularity—observable at the level of anatomically-defined brain regions, cortical layers, and cell types among others—that can be repurposed in a compositional manner to endow the animal with a highly flexible behavioral repertoire. Accordingly, their behaviors show their own modularity, yet such behavioral modules seldom correspond directly to traditional notions of modularity in brains. It remains unclear how to link neural and behavioral modularity in a compositional manner. We propose a comprehensive framework—compositional modes—to identify overarching compositionality spanning specialized submodules, such as brain regions. Our framework directly links the behavioral repertoire with distributed patterns of population activity, brain-wide, at multiple concurrent spatial and temporal scales. Using whole-brain recordings of zebrafish brains, we introduce an unsupervised pipeline based on neural network models, constrained by biological data, to reveal highly conserved compositional modes across individuals despite the naturalistic (spontaneous or task-independent) nature of their behaviors. These modes provided a scaffolding for other modes that account for the idiosyncratic behavior of each fish. We then demonstrate experimentally that compositional modes can be manipulated in a consistent manner by behavioral and pharmacological perturbations. Our results demonstrate that even natural behavior in different individuals can be decomposed and understood using a relatively small number of neurobehavioral modules—the compositional modes—and elucidate a compositional neural basis of behavior. This approach aligns with recent progress in understanding how reasoning capabilities and internal representational structures develop over the course of learning or training, offering insights into the modularity and flexibility in artificial and biological agents.

Unmotivated bias

In this talk, I will explore how social affective biases arise even in the absence of motivational factors as an emergent outcome of the basic structure of social learning. In several studies, we found that initial negative interactions with some members of a group can cause subsequent avoidance of the entire group, and that this avoidance perpetuates stereotypes. Additional cognitive modeling discovered that approach and avoidance behavior based on biased beliefs not only influences the evaluative (positive or negative) impressions of group members, but also shapes the depth of the cognitive representations available to learn about individuals. In other words, people have richer cognitive representations of members of groups that are not avoided, akin to individualized vs group level categories. I will end presenting a series of multi-agent reinforcement learning simulations that demonstrate the emergence of these social-structural feedback loops in the development and maintenance of affective biases.

Contribution of computational models of reinforcement learning to neurosciences/ computational modeling, reward, learning, decision-making, conditioning, navigation, dopamine, basal ganglia, prefrontal cortex, hippocampus

PROTEOMIC SIGNATURES IN A RAT MODEL OF SUCCESSFUL BRAIN AGING

FENS Forum 2026

BEHAVIORAL AND SPECTRAL EEG BIOMARKERS OF EPILEPTOGENESIS AND PHARMACORESISTANCE IN A LONGITUDINAL PILOCARPINE MODEL OF TEMPORAL LOBE EPILEPSY

FENS Forum 2026

INTEGRATING GENETICS, PROTEOMICS, AND <EM>IN VITRO</EM> MODELING TO ELUCIDATE <EM>SLCO1A2</EM>-MEDIATED CEREBROSPINAL FLUID CLEARANCE IN IDIOPATHIC NORMAL PRESSURE HYDROCEPHALUS

FENS Forum 2026

A biological model of nonlinear dimensionality reduction

Bernstein Conference 2024

Building mechanistic models of neural computations with simulation-based machine learning

Bernstein Conference 2024

Computational modelling of dentate granule cells reveals Pareto optimal trade-off between pattern separation and energy efficiency (economy)

Bernstein Conference 2024

Building internal models during periods of rest and sleep

Bernstein Conference 2024

Computing mutual-information rates by maximum-entropy-inspired models

Bernstein Conference 2024

Conditions for sequence replay in recurrent network models of CA3

Bernstein Conference 2024

Contrast-invariant orientation selectivity in a synthetic biology model of the early visual pathway

Bernstein Conference 2024

Controlled sampling of non-equilibrium brain dynamics: modeling and estimation from neuroimaging signals

Bernstein Conference 2024

Controversial Opinions on Model Based and Model Free Reinforcement Learning in the Brain

Bernstein Conference 2024

The cost of behavioral flexibility: a modeling study of reversal learning using a spiking neural network

Bernstein Conference 2024

cuBNM: GPU-Accelerated Biophysical Network Modeling

Bernstein Conference 2024

Deep generative networks as a computational approach for global non-linear control modeling in the nematode C. elegans

Bernstein Conference 2024

Inhibition-controlled Hebbian learning unifies phenomenological and normative models of plasticity

Bernstein Conference 2024

Deep inverse modeling reveals dynamic-dependent invariances in neural circuits mechanisms

Bernstein Conference 2024

Deep non-linear mixed effects modelling of voltage-gated potassium channels

Bernstein Conference 2024

Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Hodgkin Huxley Models

Bernstein Conference 2024

Dual role, single pathway: A pyramidal cell model of feedback integration in function and learning

Bernstein Conference 2024

Effects of global inhibition on models of neural dynamics

Bernstein Conference 2024

Evolutionary algorithms support recurrent plasticity in spiking neural network models of neocortical task learning

Bernstein Conference 2024

Excitatory and inhibitory neurons exhibit distinct roles for task learning, temporal scaling, and working memory in recurrent spiking neural network models of neocortex.

Bernstein Conference 2024

Experiment-based Models to Study Local Learning Rules for Spiking Neural Networks

Bernstein Conference 2024

Feature-based letter perception – A neurocognitive plausible, transparent model approach

Bernstein Conference 2024

Forecasting motor cortex activity with a nonlinear latent dynamical system model

Bernstein Conference 2024

A new framework for modeling innate capabilities in network with diverse types of spiking neurons: Probabilistic Skeleton

Bernstein Conference 2024

From sky to compass: a model of the desert locust sky-compass circuit

Bernstein Conference 2024

Exploring the neuroprotective effect of auditory enhanced slow-wave sleep in a mouse model of Alzheimer’s disease

FENS Forum 2024

Generalizing deep neural network model captures the functional organization of feature selective retinal ganglion cell axonal boutons in the superior colliculus

Bernstein Conference 2024

Human-like Behavior and Neural Representations Emerge in a Goal-driven Model of Overt Visual Search for Natural Objects

Bernstein Conference 2024

Neurovascular dysfunction and cognitive impairment in a model of heart failure with preserved ejection fraction

Integrating activity measurements into connectome-constrained and task-optimized models

Bernstein Conference 2024

Intracortical microstimulation in a spiking neural network model of the primary visual cortex

Bernstein Conference 2024

Investigating the role of recurrent connectivity in connectome-constrained and task-optimized models of the fruit fly’s motion pathway

Bernstein Conference 2024

Learning an environment model in real-time with core knowledge and closed-loop behaviours

Bernstein Conference 2024

Mean Field Analysis of a Stochastic STDP model

Bernstein Conference 2024

Migraine mutation of a Na+ channel induces a switch in excitability type and energetically expensive spikes in an experimentally-constrained model of fast-spiking neurons

Bernstein Conference 2024

A Model of Activation of Cortical Cell Populations through TMS

Bernstein Conference 2024

A computationally efficient simplification of the Brunel-Wang NMDA model: Numerical approach and first results

Bernstein Conference 2024