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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.

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.

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.

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.

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.

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.

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.

Increasing Lung Cancer Screening Uptake Among High-Risk Emergency Department Patients

PROJECT SUMMARY/ABSTRACT Lung cancer is the leading cause of cancer death in the US. Although lung cancer screening (LCS), using low- dose CT scan, decreases lung cancer mortality through early disease identification, fewer than 1 in 6 eligible individuals get screened, with significant differences based on demographic and socio-economic factors. LCS is a process, not just a test. The critical first steps in this process are (1) identification of high-risk individuals who are eligible for LCS, and (2) recruitment of these individuals into an LCS program. The Emergency Department (ED) setting is optimal for an intervention to promote LCS by accomplishing these steps. Individuals at high risk for lung cancer are over-represented in the ED population, including: individuals that smoke, non-White individuals, patients with lower education levels, and the under-insured. In fact, over 2.3 million high-risk people pass through EDs every year who are eligible for LCS but have never been screened. The investigators’ long-term goal is to develop a low-cost, scalable intervention that increases LCS uptake among ED patients and is deployable in any ED with a regionally referrable LCS program. The objective of the proposed randomized clinical trial is to test the efficacies of text messaging and a facilitated referral strategy to promote uptake of LCS in order to achieve this goal. Step 1 of the approach is to identify participants that are eligible for LCS. Step 2 is to randomize eligible participants, using a 2x2 design, among four study arms: (1) basic referral for LCS (i.e. verbal referral with written materials; comprising an enhanced control arm), (2) basic referral plus a subsequent series of text messages, grounded in behavioral change theory, aimed at generating intention and motivation to get screened, (3) facilitated referral for LCS (i.e. submission of a requisition to LCS program by staff), and (4) facilitated referral plus text messages. The investigators’ pilot work demonstrated the feasibility and efficacy of the proposed approach. A total of 1036 individuals eligible for LCS will be recruited from a high-volume urban ED and a low-volume rural ED, randomized among study arms, and followed-up at 120 days to assess interval LCS uptake. The Specific Aims of the proposed project are, (1) Compare LCS program uptake among study arms that receive text messages to study arms that do not, (2) Compare LCS program uptake among study arms with basic referral to study arms with facilitated referral, (3) Investigate the interaction between receipt of text messages (yes/no) and referral type (basic/facilitated), and (4) Evaluate participant feedback on (a) differential barriers to LCS across sub-groups and (b) acceptability and appropriateness of ED-based promotion of LCS. The study team is at the forefront of developing ED-based interventions to promote cancer screening. This project leverages the universal access setting of the ED to identify individuals at greatest risk for lung cancer and get them screened. A scalable ED-based intervention that increases LCS uptake would save lives.

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.

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.

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.

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.

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.

NeuroASCENT- Advancing Science through Career Enhancement and Neuroscience Training

The NeuroASCENT- Advancing Science through Career Enhancement and Neuroscience Training program will support neuroscience‑focused PhD students across multiple graduate programs by providing comprehensive scientific, professional, and research‑development training during their doctoral education. Strengthening the national neuroscience workforce requires ensuring that trainees have access to high‑quality research preparation, strong mentoring, and structured opportunities that enhance their scientific growth and career readiness. Recent analyses of U.S. doctoral recipients indicate that many talented trainees encounter barriers that limit full participation in research careers, underscoring the need for intentional support mechanisms that promote successful advancement. Over the last five years, CU Anschutz PhD programs have seen a substantial increase in students entering from a broad range of academic backgrounds. NeuroASCENT is designed to help these trainees progress efficiently by 1) promoting research excellence, 2) fostering leadership skills, 3) facilitating career development, and 4) providing individualized guidance. To achieve these goals, the program will provide career‑focused workshops, structured research externship opportunities, enhanced mentoring frameworks, and coordinated access to campus resources that extend beyond those offered by individual graduate programs. In partnership with the Office of Research Education, NeuroASCENT will complement and enhance the scientific training provided across biomedical PhD programs while offering added value to the broader CU Anschutz graduate community. Program Directors Dr. Quillinan and Dr. Hughes will oversee training activities, mentor matching, evaluation, program operations, and dissemination. An Institutional Advisory Board composed of research leaders will guide program oversight, and an External Advisory Board of graduate‑education experts will provide additional evaluation and strategic input. NeuroASCENT scholars will also serve on an Executive Advisory Board to develop leadership experience and contribute directly to program refinement. Trainees will typically enter the program after their second year of graduate training and will participate in activities focused on building a supportive peer/mentor network, strengthening scientific confidence and competence, and preparing for careers in academia, government, industry, or non‑profit research organizations.

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.

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.

Targeting the Molecular Crosstalk Between EZHIP and PRC2 in PFA Ependymoma

Project Summary: PFA ependymoma is a rare and aggressive pediatric brain tumor with a poorly understood molecular mechanism. Unlike many cancers, PFA ependymoma exhibits very few genetic alterations. Instead, it is thought to be driven primarily by epigenetic dysregulation. A key player in this disease is the EZH1/2 inhibitory protein EZHIP, which is normally expressed only in germ cells. EZHIP is aberrantly expressed in PFA ependymoma, where it disrupts the function of Polycomb Repressive Complex 2 (PRC2), a master epigenetic regulator of developmental gene repression through deposition of the trimethylated histone H3 lysine 27 (H3K27me3) repressive histone mark. EZHIP-mediated dysregulation of PRC2 involves both enzymatic inhibition and physical stalling of PRC2 on CpG island (CGI) chromatin, leading to a global loss of H3K27me3 levels, an epigenetic hallmark of PFA ependymoma. PRC2 itself is a highly dynamic and intricate complex that assembles into two functional variants, PRC2.1 and PRC2.2. These two variants share a core composed of the catalytic subunits EZH1/2, along with EED, SUZ12, and RBBP4/7, and differ by incorporating distinct accessory subunits. PRC2.1 includes PHF1/MTF2/PHF19, EPOP, and PALI1/2, while PRC2.2 features AEBP2 and JARID2. Our preliminary data reveal intriguing molecular crosstalk between EZHIP and multiple PRC2 components, suggesting potential competitive or cooperative interplay. The ability of EZHIP to inhibit PRC2 partly stems from its mimicry of the oncohistone H3K27M, which harbors a lysine-to-methionine mutation that causes diffuse midline glioma, another devastating brain tumor in children, where PRC2 activity is also globally suppressed. However, the precise, EZHIP-specific mechanisms behind PRC2 dysregulation in PFA ependymoma remain largely unexplored. Our work aims to uncover these elusive mechanisms using a powerful combination of structural biology, biochemistry, and genomics approaches. Ultimately, we aim to identify therapeutic strategies that disrupt the pathogenic EZHIP–PRC2 crosstalk and restore the normal H3K27me3 epigenetic landscape. Specifically, in Aim 1, we will determine the structural and biochemical mechanisms underlying the enzymatic inhibition of the PRC2 core complex by EZHIP. In Aim 2, we will elucidate the molecular basis of EZHIP-mediated stalling of PRC2 on CGI chromatin, involving PRC2 functional variants. In Aim 3, we will explore an exciting mechanism-based therapeutic strategy to overcome PRC2 enzymatic inhibition and chromatin stalling induced by EZHIP.

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.

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.

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.

Pilot and Feasibility Program

PILOT AND FEASIBILITY PROGRAM: PROJECT SUMMARY The goal of the Cedars-Sinai Digestive Diseases Research Center (CSDDRC) Pilot and Feasibility (P&F) Program is to provide monetary support, expertise, and technical support to advance innovative basic, translational, and clinical research that matches the overall goal and themes of the Center. The central theme of the CSDDRC is mechanisms and measurements of the fibroinflammatory response in gastrointestinal (GI) tissues, which reflects Center members’ research in three subthemes: 1) Gut Microbiome, 2) Gastrointestinal (GI) and Liver Metabolism, and 3) GI and Liver Injury. The mission of CSDDRC P&F Program is to support new investigators, established investigators who are new to digestive and liver disease research, and established digestive and liver disease investigators who want to start new or collaborative research that promises to lead to a paradigm shift in the digestive diseases field. In partnership with the Enrichment Program, we will provide guidance for P&F awardees in the form of mentorship and collaboration opportunities. The CSDDRC Biomedical Research Cores will also support P&F awardees, facilitating rapid progress of their new and collaborative digestive and liver disease research. The P&F Program’s outcome measures will include the number of high-impact research publications, grant applications, and subsequent extramural funding for P&F awardees. We will accomplish our goals through the following three specific aims. Aim 1 will solicit research proposals from P&F candidates whose proposed research aligns with the central theme and the subthemes of the CSDDRC. We will advertise P&F support widely across campuses, in addition to contacting department/institute directors to solicit their recommendations for promising young and established investigators who are interested in working in digestive and liver diseases. Aim 2 will select pilot project applications that meet CSDDRC P&F Program goals using rigorous review criteria. Each year, the P&F Program will select four pilot projects to be funded by the P30 grant and matched by institutional support. Submitted applications will be peer- reviewed and preliminarily scored based on the NIH review format by three local expert reviewers. Subsequently, after oral presentations by the P&F applicants, the External Advisory Board (EAB) members will undertake a second round of review, scoring, and discussion at the P&F Program Review meeting following the CSDDRC Annual Symposium. Funding decisions will be made during the P&F Program Review meeting. Aim 3 will assist P&F project investigators with career development and obtaining extramural funding for digestive disease research. P&F awardees will benefit from the Enrichment Program’s well-organized mentoring structure, led by experienced members of the CSDDRC, which includes the Grants-in-Progress Mentoring Program, Gastrointestinal Research-in-Progress meetings, and grant application workshops. P&F awardees will also be mentored through direct interactions with P&F Program Directors, Core Directors, members of the Internal Advisory Board and EAB, and individual or collaborative mentor teams.

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.

Factors Driving Wear and Implant Failure in Total Shoulder Arthroplasty

Polyethylene (PE) wear and implant-related failure remain leading causes of revision in total shoulder arthroplasty (TSA), a procedure which now surpasses the growth rate of hip and knee arthroplasty. Both anatomic (aTSA) and reverse (rTSA) TSA outcomes are heavily influenced by complex interactions between rotator cuff function, scapular motion, implant design, and patient-specific loading—factors not adequately captured in current preclinical implant testing standards. Emerging evidence suggests that PE wear progression in TSA is highly dependent on shoulder kinematics, joint loading, implant positioning, and individual patient factors. Nonetheless, data on in vivo motion and load profiles remain sparse, and few tools exist to link these profiles to clinically relevant wear patterns or associated periprosthetic inflammatory tissue responses. Accordingly, the primary objective of this project is to develop validated, patient-specific models that predict PE wear in TSA and identify modifiable surgical, design, and rehabilitation targets to improve implant longevity and restore patient mobility. Additionally, we will establish histopathological hallmarks that indicate TSA failure caused by PE wear debris. Our central hypothesis is that specific shoulder kinematics and joint loading drive distinct PE wear patterns in TSA associated with mechanical failure or inflammatory-mediated osteolysis, depending on implant design and positioning. To achieve the overall objective of this work, shoulder motions and muscle excitations across 25 activities of daily living will be collected at pre-op and post-op (>6 months) in both aTSA and rTSA patients, with long-term follow-up of patient-reported outcomes via validated surveys (5 years). Unsupervised machine learning will categorize patients into movement-based phenotypes, which will then inform a multi-scale modeling framework to estimate in vivo shoulder joint loads and implant wear across the varying movement strategies. Predicted wear patterns will be validated using state-of-the-art preclinical wear simulators. Simultaneously, we will quantify how patient, surgical, and implant factors contribute to wear in retrieved TSA components (>400 samples), correlating imaging-based wear patterns with clinical outcomes, patient-reported function, inflammatory tissue responses, and radiographic indications of loosening. For that purpose, we will establish benchmarks of TSA wear rates and introduce a new histopathological approach augmented by infrared spectroscopic imaging. This work is innovative because we are linking patient-specific movement patterns following TSA with multi-scale computational models to predict PE wear, breaking the current approaches of using generic motions and loads in existing testing standards. This work will produce the first integrated, publicly available database of TSA kinematics, joint loading, and PE wear patterns and rates, along with validated computational tools to inform implant design, surgical planning, rehabilitation strategies, and personalized risk assessment. Ultimately, these advances will improve functional outcomes and long-term success for TSA patients and enable better preclinical testing methods and standards.

Behavioral, Implementation & Community Sciences Core

PROJECT SUMMARY: BEHAVIORAL, IMPLEMENTATION, AND COMMUNITY SCIENCES (BICS) CORE Like many US jurisdictions, New York City (NYC) is not on track to achieve 2030 End the Epidemic (EHE) 95- 95-95 goals. By the end of 2023, 95% of people with HIV (PWH) in NYC had been diagnosed with HIV, but only 88% of those were in HIV care, and of those, only 80% were virally suppressed. Further, in 2022, only 40% of individuals estimated to need PrEP were prescribed it. Highly efficacious biomedical HIV treatment and prevention interventions have the potential to end the HIV epidemic, but only if they are accessed and used. Yet, behavioral, social, and structural determinants of real-world adoption as well as population-level impact of HIV prevention, care, and treatment innovations have not been addressed adequately for individuals or communities. Meeting EHE goals will depend on behavioral, implementation, and community sciences research that identifies factors contributing to these outcomes, informs interventions to address them, and ensures that communities affected by HIV are engaged throughout the research process. The Behavioral, Implementation, and Community Sciences (BICS) Core will facilitate such rigorous, innovative research by Columbia University (CU) and Weill Cornell Medicine (WCM) investigators – particularly early career investigators (ECIs) and those new to HIV research – to help achieve EHE 2030 goals. The BICS Core will support the use of relevant theories, methods, and analytic approaches to advance the integration of context-specific behavioral, implementation, and community sciences perspectives across the research continuum – from basic research through scale-up and sustainment of evidence-based interventions. The Core has three Aims: (1) Behavioral science: To support CFAR users in developing, selecting, and integrating behavioral science methodologies across the research continuum; (2) Implementation science: To support CFAR users in designing and conducting implementation studies and related health services research and (3) Community science: To facilitate rigorous community-based participatory research across the research continuum to strengthen and sustain stakeholder engagement that will optimize research translation and impact. Led by Core Co-Directors Robert Remien and Bruce Schackman and Core Associate Directors Delivette Castor, Shashi Kapadia, and Justin Knox, the BICS Core will use multiple approaches to achieve each of these aims, including substantive scientific consultations on proposed or ongoing research; access to resources and tools; and seminars and educational activities that promote integration of these methods into EHE research. The Core, thus, will support CU-WCM CFAR investigators and outside collaborators – including ECIs and investigators new to HIV research – to advance local and national EHE goals.

Characterization and functional impact of somatic numtogenesis in the human cortex

Project Summary This project focuses on studying nuclear mitochondrial insertions (numts), which are fragments of mitochondrial DNA that get integrated into the nuclear DNA of human cells. While this process, called numtogenesis, occurs naturally and can be passed down to future generations, it has also been observed to occur somatically in our bodies. Historically the function of numts has been difficult to study because they are repetitive and difficult to map with short read sequencing technologies, but there is emerging evidence that they can influence cell function and play a role in diseases, aging, and even complicate genetic studies. Our recent research discovered numts in the human brain’s cortex, and their presence appeared to be linked with earlier death, suggesting they may play a role in aging. However, due to limitations in the data we used, we could not fully explore the extent or impact of these insertions across different tissues or individuals. This project aims to map and study numts in more detail, especially in the human cortex, to further explore this ongoing transfer of DNA from the mitochondria to the nuclear genome and their potential to impact aging and brain function. We will accomplish this by 1) improving sequencing methods to detect numts, 2) comparing their presence across different tissues, and 3) investigating how they affect gene expression and DNA structure. By the end of the project, we aim to provide a model for how such somatic variation may occur and impact cellular function at the tissue level.

Linking Single-Cell Transcriptomic, Morphological, and Temporal Signatures of Vulnerability in Neurodegeneration

Neurodegeneration involves complex cellular phenotypes and molecular changes that vary widely among the cells of the nervous system. Current methodologies permit either detailed molecular profiling (e.g., single-cell transcriptomics) or functional phenotyping (e.g., live imaging of neuronal activity), but not both in the same cells. Thus, it is difficult to directly link a neuron's functional state or fate with its gene expression profile. To address this limitation, we developed an innovative technology, VISTA-FISH (Video Imaging with Spatial- Temporal Analysis by FISH), that couples prospective live-cell imaging with high-resolution spatial transcriptomic profiling of the same cells. This approach enables in situ comparisons of gene expression in neurons that exhibit divergent behaviors or outcomes. Using VISTA-FISH, we will profile iPS-derived human neurons to link single-cell gene expression, morphology, and temporal phenotypes to study molecular pathways driving resilience as well as susceptibility. After exposing neurons carrying TDP43 and C9orf72 mutations to a stimulus inducing TDP43 aggregation, we will jointly record TDP43 localization and neuron activity using live-cell microscopy, then measure single-cell gene expression of the same cells (Aim 1). We will also combine live-cell measurements of TDP43 half-life with CRISPR screening and single-cell gene expression (Aim 2). These rich datasets will enable us to determine transcriptomic changes associated with differences in protein aggregation, protein synthesis, and protein degradation in individual cells, providing an unprecedented molecular perspective on factors responsible for vulnerability and resilience to neurodegeneration.

COCHLEAR SIGNALING MEDIATED BY HENSEN’S CELLS

PROJECT SUMMARY/ABSTRACT The organ of Corti has two types of auditory sensory cells (inner and outer hair cells) surrounded by nearly a dozen different types of supporting cells organized in a very meticulous pattern. Hair cells mediate the mechano-electrical transduction process of the organ of Corti and thus most cochlear auditory research has focused on these sensory cells. In contrast, much less is known about the different types of cochlear supporting cells, even though they likely impact hair cell function. Hensen’s cells are located laterally to the outer hair cell rows and appear to be the only cell type in the cochlear epithelium that expresses TRPA1 channels. These channels are widely known for their role as sensors of tissue damage and inflammation in nociceptive neurons. Not surprisingly, we recently found that Hensen’s cells are main sensors of tissue damage in the cochlear epithelium via the activation of TRPA1 channels (Velez-Ortega et al., Nat Commn, 2023). Additionally, our preliminary data also supports the role of Hensen’s cells in signaling pathways important for the proper innervation of the organ of Corti (aim 1), for the transmission of cochlear damage signals to the brain (aim 2), and for the regulation of hearing sensitivity after acoustic trauma (aim 3). Thus, here we will explore the hypothesis that TRPA1- mediated signaling pathways in the Hensen’s cells are required for the proper innervation and auditory function of the organ of Corti. In Aim 1 we will perform a detailed comparison of the morphology and synapses of afferent cochlear neurons of wild-type and Trpa1-/- mice at several developmental stages (using immunolabeling, confocal microscopy, STED microscopy, and electron microscopy) to assess the role of TRPA1 activity on the postnatal refinement of the cochlear innervation. Aim 2 will evaluate whether the afferent type II spiral ganglion neurons (SGN) can be activated downstream of TRPA1 channel gating in Hensen’s cells by testing responses of neonate and adult type II SGN to TRPA1 agonists (via live-cell time-lapse calcium imaging and patch clamp recordings of type II SGN dendrites). Aim 3 will test the impact of TRPA1 signaling in Hensen’s cells to the operating point of the cochlear transducer (via the recording of cochlear microphonics) and to cochlear tuning (via the recording of ABR tuning curves). This study is significant because it will contribute to our understanding of the cellular (Hensen’s cells plus type II SGN) and molecular (TRPA1 channels) mechanisms of the elusive cochlear nociceptive pathway. In addition, given that the loss of TRPA1 channels does not affect hearing thresholds in mice, we believe that undiagnosed deficits in TRPA1-dependent responses in the human population could represent a hidden susceptibility for cochlear damage after noise exposure or other insults.

Examining the foundations of reading comprehension: a longitudinal study of brain and behavior starting in infancy

SUMMARY Reading comprehension (RC) is one of the most complex skills that we utilize daily and is crucial for functioning in modern society, but despite its significance for academic achievement, employment prospects, and mental health, many children and adults do not exhibit proficient RC abilities. New theoretical models aiming to explain variability in RC suggest a dynamic interplay and co-development among ‘precursor’ foundational and cognitive- linguistic skills, interacting with environmental and socio-ecological factors across the developmental timeline of learning to read. Behavioral and neuroimaging studies in school-age children have demonstrated critical mechanistic support for these multifactorial RC models by identifying the developmental trajectories of precursor skills and further showing that brain areas, tracts, and networks typically underlying language and cognitive skills are also involved in RC. Nevertheless, the precursor skills that support RC start developing in infancy and the brain correlates underlying these precursors begin to develop in utero, which suggests that typical and atypical RC developmental trajectories could diverge long before school age. As such, examining RC development using a multifactorial, longitudinal approach that includes brain and behavior starting in infancy is critical for developing theoretical frameworks that can inform early preventative and intervention strategies. Here, we propose a comprehensive longitudinal study of RC development in which we examine direct and indirect effects on RC from brain, behavioral, familial risk, and environmental data from infancy to adolescence. To achieve this goal, we will combine two existing longitudinal cohorts, one ranging from infancy to late childhood (n = 174) and the other from preschool to early adolescence (n = 137). By applying state-of-the-art pediatric neuroimaging analyses, multiple indicator growth model structural equation models, and an innovative behavior- brain co-development measurement index to this unique, combined dataset, we will be able to identify brain and behavioral measures in infancy that directly and indirectly support subsequent RC development (Aim1). We will further characterize how longitudinal trajectories of behavioral measures as well as brain structure, function, and white matter organization contribute to RC development and how familial risk and environmental factors shape these trajectories (Aim 2). Finally, we will examine how the co-development of brain and behavior, as measured with an innovative co-development index, relates to subsequent RC (Aim 3). If successful, we will contribute the first multifactorial longitudinal model of RC development comprising direct and indirect effects from brain, behavior, brain-behavior co-development, familial risk, and environmental measures beginning in infancy. Understanding RC development using a multifactorial longitudinal lens will be crucial for building theoretical models and developing experimental designs focused on early preventative and intervention approaches long before the start of formal schooling.

Circulating extracellular vesicles as functional indicators of maternal mental and physical health in pregnancy and postpartum

Women with high levels of adverse childhood experiences (ACEs) are at significantly greater risk for negative health outcomes in pregnancy and postpartum, including gestational diabetes, PTB, and depressed mood. However, we still lack biomarkers or a sufficient understanding of causal mechanisms. Extracellular vesicles (EVs) are one of the most dynamic and abundant biological signals secreted into maternal circulation, largely produced by the placenta – where levels increase 4-5-fold during pregnancy. Similarly, removal of the placenta at delivery produces a dramatic drop in maternal EV concentration. Across species, we and others have identified significant EV changes during pregnancy associated with homeostatic regulation, including glucose and glucocorticoid levels, supporting key roles for EVs in maternal health. However, longitudinal studies in human pregnancy and postpartum have not been conducted. We know little as to the mechanisms controlling EV secretion or the roles for EVs in maternal pregnancy and postpartum health. Our decade’s long work identified the X-linked gene, O-glycosyltransferase (OGT), in mouse and human placenta as a master gage of the maternal milieu, where OGT regulation of annexin A1 (AA1) is key to EV cargo loading and secretion from the placenta. We recently reported that placental OGT levels positively correlate with maternal EV concentration. How this association may contribute toward postpartum health, including regulating maternal stress physiology and mood in humans is not known. We hypothesize that increased ACEs, similar to stress in preclinical models, are negatively associated with a cell’s ability to secrete EVs important to maintain homeostasis in the face of the challenges of pregnancy and postpartum, producing an increasingly unhealthy state. Therefore, the goals of these proposed studies in both mice and humans are as follows: 1) To identify cellular mechanisms involved in EV secretion important to maternal health outcomes utilizing the placenta as a tool to genetically target OGT in mice and examine maternal homeostatic control related to EV concentration and composition during pregnancy; 2) To examine the functional ability for a dynamic elevation in maternal EV concentration to improve homeostatic regulation in pregnancy and postpartum using chemogenetic activation (DREADDs) of placenta trophoblast cells in pregnancy, and by EV transfer by tail vein injection postpartum; and 3) To examine in women changes in maternal EVs in a longitudinal pregnancy and postpartum study in association with maternal glucose and cortisol changes, we will examine markers of physical (glucose challenge test), HPA stress (hair cortisol & stress- stimulated salivary cortisol) and psychological (Hamilton Rating Scale for Depression, Perceived Stress Scale) health across pregnancy and the postpartum period in 150 healthy women with varying degrees of exposure to ACEs as measured using the ACE Questionnaire (ACE-Q).

Maternal Depression and Antidepressant Effects on Fetal Brain Structure and Function (FABMOMS)

PROJECT ABSTRACT Major depressive disorder (MDD) is one of the most common diseases in childbearing women, with a prevalence of 12.7% in pregnancy and 21.9% the year after birth. Exposure to maternal stress and depressive symptoms alters fetal/infant neurodevelopment, functional brain connectivity, and networks implicated in stress processing. About 5% of pregnant women are prescribed a serotonin selective or serotonin norepinephrine reuptake inhibitor (collectively, SRI). Remission of maternal MDD is crucial to the health and functioning of the mother and family. In observational studies typical of this field, differentiating the effects of drug exposure on offspring from the sequelae of the underlying psychiatric disease, both physiological and psychosocial, is challenging. Substantial progress has been made using sophisticated study designs and analytic approaches with large pregnancy cohorts that reduce the risk of spurious associations. Increased rates of overall and cardiac defects, stillbirth, preterm birth, and fetal growth have been largely explained by confounding by factors associated with both MDD and these outcomes rather than SRI exposure. Assessing the neurobehavioral development of children exposed in utero to SRI is the current research priority in this field. Our team pioneered the development of novel and safe fetal and neonatal quantitative magnetic resonance imaging (qMRI) tools, which will be combined with an evaluation of maternal heart rate variability to explore associations between exposures to stress, psychiatric symptoms and SRI on fetal and neonatal brain structure and function. The overarching goal of this project is to evaluate the separate and interactive effects of exposure to antidepressants in utero and maternal MDD on fetal and infant brain structure and function, with a specific focus on the hippocampus. We will accomplish this by evaluating four groups of pregnant women who have: 1) MDD treated with SRI to remission), 2) MDD treated with SRI (non-remitted, with both depressive symptom and SRI exposure), 3) MDD untreated with antidepressants, and 4) no current MDD or SRI treatment. Maternal assessments will occur at intake and in the early third trimesters and in then newborn period (at the time of fetal/newborn MRI) after birth. Maternal and infant evaluations will continue at 6 and 12 months postpartum. Maternal psychosocial and psychiatric status will provide extensive data on the context in which mothers experience pregnancy and infant care and allow adjustment for factors that will inevitably differ across groups. Lastly, we will explore the effects of maternal choline on MDD and offspring brain development. As these exposures and neurodevelopmental studies are conducted, exploring primary preventive strategies is a public health imperative. We will explore a potential mediator, poor maternal choline intake, a modifiable risk factor for both maternal MDD and altered fetal hippocampal growth and infant neurobehavior.

Clinical Trial Readiness of MEG Biomarkers in Children Across the Autism Spectrum

PROJECT SUMMARY Biological and phenotypic heterogeneity of autism spectrum disorder (ASD) poses a major challenge for clinically focused research and interventions. Brain electrophysiological phenotyping holds promise for parsing this heterogeneity. Using magnetoencephalography (MEG), findings of diminished and delayed auditory evoked responses (e.g. the ~50ms component, M50 and, specifically, its latency: M50L) have reproducibly been shown in ASD, with correlation to behavior. Additionally, abnormal resting state activity and network functional connectivity has been identified as an electrophysiological hallmark. Such passively-acquired signatures may serve as objective biomarkers in subtyping autistic individuals, including stratifying patients for inclusion in clinical trials according to biology, rather than behavior alone. However, despite their abundant promise, these measures are not yet permeating clinical trial design, nor being utilized in clinical practice, in part because of their lack of standardized implementation and analysis. This proposal seeks to remedy this by using rigorous and standardized, scalable and sharable methods with two leading MEG measures to determine their measurement- reliability as well as their sensitivity to inter-individual differences in clinically-relevant aspects of autism features, general cognitive ability and language and communication. Specifically adopting a 12-week repeated scanning design, mimicking the duration of a typical pharmaceutical trial or behavioral intervention, we will acquire each of these two MEG metrics at baseline and 12-week follow-up to assess interval change. Additionally, we will evaluate test-retest variability with an intermediate measurement point 4-weeks after baseline. As such we will characterize both intra-subject variability (measurement precision) and inter-subject variability which will be correlated with dimension axes of autism features, general cognitive ability and language skills, as well as major co-occurring condition confounds. These studies will recruit a broad range of 240 autistic children, paralleling the CDC’s prevalence data on intellectual ability and encompassing the group considered as having “profound autism”. This is enabled by our adoption of MEG-PLAN, a strategy developed over the last decade in our group and demonstrated to enhance inclusive participation in MEG scanning studies, even in non-verbal participants. Data will be compared to a control group of age-matched typically-developing peers. The two MEG measures will also be assessed for their ability to identify clusters of less heterogeneous neurophysiological phenotype as a novel basis for stratification or subtyping of the heterogeneous autism population. In culmination, this study addresses key “clinical readiness” aspects of utilization of MEG biomarkers for ASD including profound autism, for both stratification (inclusion/trial selection) and monitoring of response to intervention, and will, ultimately, pave the way for the adoption of such biomarkers as adjunctive tests in increasingly-routine clinical practice.

Hepatotoxicity of Legacy and Replacement PFAS: Role of BRUCE-Mitochondrial Interactions

Epidemiological studies have shown a strong association between exposure to PFAS (Per- and Poly- fluoroalkyl Substances) and liver toxicity. Particularly, legacy C8-PFAS members, PFOS (perfluorooctane sulfonate) and PFOA (perfluorooctanoic acid), are highly toxic, with PFOS estimated to be approximately 10 times more toxic than PFOA in ecotoxicity models. Consequently, PFAS replacements such as GenX and PFBS are marketed as safe alternatives, although growing evidence indicates that these substitutes also exhibit toxic effects. Lab animal model studies have shown hepatotoxic effects of both legacy and replacement PFAS members, characterized by Metabolic dysfunction-associated steatotic liver disease (MASLD) and its severe form Metabolic dysfunction- associated steatohepatitis (MASH), the two chronic liver diseases affecting an estimated 80-100 million Americans. The broader objective of this project is to understand the underlying mechanisms of PFAS hepatotoxicity in MASLD/MASH. In this context, our initial studies have shown that PFAS exposure of mice downregulates hepatic BRUCE, an autophagy inhibitor, resulting in development of MASLD in WT, and more severe MASLD and even progression to MASH in BRUCE liver-knockdown (BKO) mice. Using primary hepatocytes, we found PFAS-induced BRUCE reduction compromised mitochondrial (mt) functions (respiration, fatty acid oxidation/FAO, and ATP production) and suppressed mitophagy in WT and more so in BKO mice. Pharmacological restoration of mt function in mice prevented PFAS-induced MASLD/MASH. Guided by these compelling preliminary data and scientific premise, we hypothesize that PFAS degradation of BRUCE in hepatocytes induces excessive autophagy (resulting in cytotoxicity) and inhibits mitophagy (resulting in accumulation of damaged mitochondria), leading to release of mtDAMPs to activate inflammation/ fibrosis, thereby facilitating progression from MASLD to MASH. We will test this by three specific aims. Aim 1 (ex vivo) is to determine the human-relevant PFAS doses that modulate BRUCE levels for homeostatic vs cytotoxic autophagy and how BRUCE in turn regulates autophagy. Aim 2 (ex vivo) will investigate BRUCE-driven mitophagy pathway specific to PFAS exposure at human-relevant doses. Aim 3 (ex vivo and in vivo) will involve ex vivo simulation experiments to characterize the role of PFAS-induced, BRUCE-dependent hepatocyte- released mt DAMPs in activation of immune and fibrogenic cells using co-culture assays. Next, we will perform in vivo intervention to validate the role of PFAS-damaged mitochondria in driving MASH progression in mouse models. Furthermore, human relevance of the delineated mechanisms will be ascertained and validated using iPSC-derived human liver organoid system. Impact: This project will advance our understanding of autophagy/mitophagy-centric mechanisms with therapeutic potential in the context of PFAS-induced liver disease MASLD/MASH.

Protective efficacy and immunogenicity of a live attenuated Chlamydia strain

PROJECT SUMMARY The main goal of this project is to rigorously evaluate the immunogenicity and protective efficacy of a mutant, live attenuated Chlamydia trachomatis (CT) vaccine strain in an established nonhuman primate (NHP) model that accurately mimics many aspects of human CT infection. This work is highly significant, as CT is the leading cause of bacterial sexually transmitted infection and an important causative agent of morbidity in women. Although the development of an effective CT vaccine is an urgent medical priority, no approved vaccines exist and it is imperative to pursue new candidates. Historical evidence supports the vaccine efficacy of whole Chlamydia organisms in protecting the reproductive tract from reinfection, primarily using C. muridarum infections in a mouse model. Recent advances in Chlamydia genetic engineering now allow for the development of genetically attenuated strains which can be evaluated as live vaccines in preclinical models. We recently characterized a human-tropic CT mutant with a disruption in garD (CT∆garD); this mutant is sensitive to an intracellular, IFNγ activated defense mechanism and we demonstrated that this strain was attenuated in the female NHP genital tract. In a pilot vaccine efficacy study, we further demonstrated that immunization of macaques with CT∆garD was safe and elicited protection against subsequent challenge with wildtype CT. A unique feature of this strain is that it arrests at an intracellular stage and thus presents a broad array of desirable T and B cell antigens that are broadly conserved across circulating CT strains. We will first generate an improved genetically attenuated CT strain that harbors a clean deletion of garD, and we will subsequently genetically and phenotypically validate its attenuation phenotype. We will then conduct an immunogenicity and efficacy study in female macaques to determine the optimal dosing regimen of live attenuated CT for eliciting protective cellular and humoral immune responses, and also protective efficacy, against challenge with a wild type circulating clinical CT strain. These studies will investigate the potential for a live attenuated human tropic vaccine candidate in a macaque preclinical model and pave the way for greater understanding of immune correlates of protection against CT.

Improving Disease-Modifying Therapy Uptake among Patients with Multiple Sclerosis

Project Summary/Abstract Recent advances in the epidemiology of multiple sclerosis (MS) indicate that its prevalence is similar among White (238 per 100,000) and Black (226 per 100,000) populations. These data challenge historic assumptions about individuals with northern European heritage having higher risk and prevalence of MS. Evidence also suggests that MS incidence may be higher than previously recognized in the United States and increasing over time with more individuals identified and diagnosed year over year. MS continues to impose significant and growing burden on patients, healthcare systems and society. These health differences in the diagnosis, treatment and symptom management of MS in light of the increasing prevalence of MS in the US are an important public health issue that requires broader urgent research and policy attention to reduce the overall disease burden. In this study, we will use real-world data derived from the electronic health records (EHR) from four large academic medical centers (University of Kentucky, University of Virginia, Virginia Commonwealth University, and University of Southern California). Extracted EHR data from these four medical centers will be deidentified, combined, and harmonized. We will use this combined data set to examine (1) whether there are any differences in the timely treatment of disease modifying therapy (DMT) among different MS populations, (2) any disparities in the management of symptoms and comorbidities, (3) how non-medical factors of health such as income, education, and health insurance status (patientlevel), linguistically appropriate care provision (provider-level), and neighborhood factors (system-level) affect these outcomes and influence disparities across populations, and (4) assess whether disparities exist in the risks of cardiovascular disease CVD and mortality in MS subgroups and examine if these disparities can be reduced with improved treatment of MS and vascular comorbidities. In pursuing these objectives, we will identify clinical solutions (e.g., optimal DMT sequences) and non-medical factors such as neighborhood factors such as poverty, educational achievement, crime rates, civic participation, and housing quality, access to care factors, and cultural and linguistic match between providers and patients that substantially contribute to health disparities. For actionable solutions, we will rank-order these factors by their relative importance in addressing disparities, which will guide decision-making at the policy, system, and provider level. Our long-term objective is to develop public health strategies and scalable solutions to reduce overall burden in the management of MS. This project is expected to help policy makers and health system administrators in prioritizing interventions and to have implications for clinical practice in improving care of all patients with MS in neurology clinics, at the healthcare system level, and for national health policy.

Bridging Local and System-Wide Autoreactive, Extrafollicular B Cell Signatures in a TLR7-Driven Model

Project Summary A substantial body of literature has described the development of autoreactive humoral responses in the context of autoimmune disease and recently discerned an exciting new avenue for investigation. While early work focused on canonical mechanisms of activation through the germinal center (GC) response, recent studies have found GC infrastructure to be dispensable for the onset of chronic autoimmunity. It has become clear that an alternative pathway of B cell activation, the extrafollicular (EF) pathway, can drive the onset of new autoreactivity in multiple human disorders including rheumatoid arthritis and systemic lupus erythematosus (SLE). In comparison to the GC pathway, the EF pathway represents a less stringent method for B cell activation, leads to accelerated antibody-secreting cell (ASC) formation, and thus has a higher propensity for the production of autoreactive B cell effectors and ASCs. Recently, our group has identified a similar skew toward the EF response in the context of severe viral infection, tied to acute tolerance loss, increased disease severity, and complicated recovery from infection. These findings highlight how further study of the EF response is crucial to our understanding of autoimmune induction across multiple areas of disease. Toll-like receptor 7 (TLR7) stimulation has been identified as a key contributor to EF B cell development in SLE, and several studies have now linked TLR7 overstimulation to chronic autoimmune disease. While EF effector B cell populations have now been identified in both murine models and humans, substantial gaps in our knowledge remain to be answered concerning i) the origins of these cells and ii) the system-wide and microenvironmental signaling and organization that drive this differentiation pathway. We propose to address these gaps, here, by utilizing a TLR7 agonist (R848) in a murine model to characterize the autoreactive response within the blood and draining lymph node through innovative high-throughput analytical techniques. Systemic shifts in proteomic signatures and immune cell phenotype will be monitored in the blood throughout the induction of autoreactivity, using novel applications of machine-learning based classification. These signatures will then be connected to developing inflammatory microenvironments identified within the draining lymph node by applying a customized set of software tools to spatial transcriptomic data. This work will deepen our understanding of the immunologic mechanisms by which the EF pathway can lead to “run-away” autoreactive B cell development, with the added potential for identification of early blood-based biomarkers for this developing autoreactivity. The above proposed work will provide an ideal training opportunity for the candidate to develop experience with advanced immunologic laboratory techniques, rigorous bioinformatic analysis, a systems-level view of immunology, and scientific communication. The Woodruff and Sanz Labs are highly experienced within the autoimmune disease space with extensive experience with the required techniques and established routes for clinical collaboration to act on these findings.

Multiplex single-cell chemical genomics to identify small molecule modulators of tumor cell-intrinsic immunogenicity in glioblastoma

PROJECT SUMMARY/ABSTRACT Glioblastoma multiforme is the most common and aggressive primary brain cancer. Despite a multimodal treatment regimen of surgical resection, chemotherapy, radiotherapy, and tumor-treating fields, most patients succumb to the disease within two years of diagnosis. Cancer immunotherapy strategies have emerged as a powerful tool for treating aggressive solid tumors such as melanoma and non-small cell lung cancer. However, current strategies have led to low response rates in glioblastoma, resulting from its low immunogenicity. The proposed research program aims to identify small molecules capable of increasing the immunogenicity of glioblastoma cells, focusing on altering gene expression programs associated with recognition by the immune system and the ability of cytotoxic immune cells to target glioblastoma for destruction. We will use highly multiplex chemical transcriptomic profiling to determine the molecular consequence of exposing glioblastoma neurosphere models to 3,792 small molecules, targeting the majority of cellular activities and clinically relevant drug targets as well as a collection of previously identified immunomodulators. We will then determine how each exposure alters the expression of gene programs associated with tumor cell immunogenicity and response to therapy, including the expression of genes associated with the recognition by the immune system and those associated with immune checkpoints, as well as programs more broadly correlated with resistance to anti-cancer therapies. Chemical hits that meet specific criteria will be subjected to a medicinal chemistry review to further classify compounds by their suitability for treating malignancies in the brain. We will then screen chemical hits to determine their ability to modulate immune-mediated tumor cell killing using tumor- immune cell co-culture. Lastly, we will leverage gene editing and flow cytometry to validate hits based on on- target molecular effects and further refine the mechanism of action by inspecting the ability of drugs to modulate immunogenic programs at the protein level. Our chemical genomics screens aim to provide crucial information regarding the link between pathway activity and immunomodulation in GBM, a critical step to guide future efforts in GBM immunotherapy. More broadly, our study will establish single-cell chemical genomics as a scalable platform for phenotype-based screening for preclinical prioritization of chemical modulators of complex transcriptional phenotypes and provide a framework for hit prioritization, establishment of pipeline robustness and hit validation in the context of single- cell chemical genomics screens.

From Evidence to Scale: Implementation Science and Simulation Modeling to Transform HIV-Hypertension Care Integration

Project Summary As HIV programs mature, cardiovascular disease (CVD) is becoming a leading contributor to morbidity and mortality. Integration of HIV and CVD prevention, with a focus on hypertension–the most prevalent and impactful modifiable CVD risk factor, presents an opportunity to build more robust primary health systems that improve health outcomes and advance health system sustainability–a key priority for the U.S. PEPFAR program. Using an expanded version of the HIV Synthesis microsimulation model—which incorporates hypertension and CVD outcomes—and data from the NHLBI-funded HLB-SIMPLe consortium’s cluster randomized trials in six African countries, we will evaluate the health effects, cost-effectiveness, and scalability of implementation strategies to promote HIV-hypertension integration to improve health outcomes for people with and without HIV under a range of health system constraints. Our first aim is to develop and validate an additional layer to HIV Synthesis model that accounts for health system constraints and implementation strategies for integration of HIV and hypertension care. This will include parameterization using data from the WHO Health System Building Blocks framework and empiric data from trials in the HLB-SIMPLe consortium. Our second aim is to evaluate the health effects and cost-effectiveness of implementation strategies for HIV-hypertension integration to identify the most effective and scalable approaches for settings with varying health system constraints representative of conditions in west, east, and southern Africa. Analyses will include scenarios targeting people with HIV and scaling up to the broader population. Our third aim focuses on engaging policymakers and program managers to promote uptake of findings through dissemination workshops and interactive modeling tools, with tailored model outputs to specific health system contexts. Using qualitative interviews with policymakers, we will use the Weiss schema for conceptualizing research utilization to assess model impact on decision-making. We will use the Translational Science Benefits Model, to capture, classify and conceptualize the clinical, policy, economic, and operational impacts and identify barriers and facilitators to use in country programs focused on HIV, hypertension, and related NCDs. The overarching project goal is to inform evidence-based, cost-effective implementation strategies for integrating NCD care into HIV platforms, improving population health outcomes in Africa and advancing implementation science through generalizable knowledge about the intersection of implementation strategies, health system strength, and service integration.

SUPPORT SERVICES FOR THE PREVENTION AND TREATMENT THROUGH A COMPREHENSIVE CARE CONTINUUM FOR HIV-AFFECTED ADOLESCENTS IN RESOURCE CONSTRAINED SETTINGS IMPLEMENTATION SCIENCE NETWORK

Support Services for the Prevention and Treatment through a Comprehensive Care Continuum for HIV-affected Adolescents in Resource Constrained Settings Implementation Science Network (PATC3H-IN) (UG1/UM2) Program The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) requires support for logistical and operational coordination, website and communication management, analytic and data management, infrastructure for emerging research, regulatory, and monitoring of research activities for the Prevention and Treatment through a Comprehensive Care Continuum for HIV-affected Adolescents in Resource Constrained Settings Implementation Science Network (PATC3H-IN) (UG1/UM2) Program. The NICHD and partner NIH Institutes anticipate funding 8 PATC3H-IN UG1 awards in Asia and throughout sub-Saharan Africa in 2023 through a cooperative agreement mechanism for interventions of high public health significance: The prevention of new HIV infections among adolescents at risk, and the identification of, linkage to and retention in care of, and long-term viral suppression among youth living with HIV in low-to-middle income countries with high HIV burden. The PATC3H-IN network will expand and/or improve on successes achieved by its predecessor, PATC3H, to new geographic settings and/or risk populations and stimulate much needed implementation science (IS) research in the prevention of new HIV infections among adolescents at risk and the identification of, and linkage and retention to care of and long-term viral suppression among youth living with HIV in low-to-middle income countries (LMICs). PATC3H-IN will establish a network of investigators with multidisciplinary expertise on the youth-specific PHCC and in IS research, whose mission will be to evaluate promising prevention innovations contextually and developmentally tailored for HIV uninfected at-risk youth, and treatment and care interventions for youth living with HIV which have demonstrated efficacy and/or effectiveness in adolescent or adult populations and to translate them into public health practices. The structure of PATC3H-IN will consist of multiple interdependent functional components: (1) Five Clinical Research Centers (CRC) awarded through the UG1 grant mechanism; (2) one Implementation Science Coordinating Center (ISCC) to be awarded through a UM2 grant mechanism in 2024; and (3) a Scientific Leadership Committee (SLC). The CRCs will conduct clinical research and clinical trials, including implementation, effectiveness, and hybrid implementation-effectiveness studies at their 8-or more participating Clinical Research Performance Sites (CRPS). The ISCC will establish infrastructure to support research education and capacity building across PATC3H-IN, as well as infrastructure for stakeholder engagement in and dissemination of findings from PATC3H-IN and advanced statistical modeling support across PATC3H-IN. The ISCC will also provide infrastructure for conducting foundational research to support the work of clinical sites, including possible modeling studies and translation projects, as well as national surveys, and/or systematic collection and analysis of relevant policies and laws. Lastly, the SLC will be responsible for PATC3H-IN governance, oversight, and coordination, and will develop and implement the network research agenda, convening working groups as needed, prioritizing emerging research projects, efficiently managing the development of clinical protocols, implementing and completing clinical trials, and ensuring timely publication and communication of results.

Impact of environmental toxicants on frontal cortical circuits

Abstract: Human mercury (Hg) exposure has been known for many decades to produce cognitive impairment and mood disorder symptoms. Hg is a global pollutant that poses widespread potential for neurotoxic exposure, earning it a position on the WHO’s list of the top 10 chemicals of major public health concern. However, little is known about the neural mechanisms that lead to neuropsychiatric symptoms from Hg exposure. The objective of this application is to identify specific mechanisms, within the neocortical circuits that control emotion and cognition, that are disrupted by the neurotoxicant, methylmercury (MeHg). The neocortex exhibits especially strong bioaccumulation of Hg, magnifying the risk to these circuits. Therefore, we hypothesize that chronic MeHg exposure leads to persistent circuit dysfunction in prefrontal and insular cortices (mPFC and aIC) – two brain regions critical in control of emotion and cognition. Our recent work showed that mPFC neurons in brain slices are negatively affected by acute MeHg exposure, resulting in hyperexcitability and altered synaptic transmission. Currently, it unknown how these acute effects on synaptic transmission translate to altered neuronal function in vivo. This proposal applies an integrative approach to determine the in vivo effects of MeHg on mPFC and aIC circuits, at the systems neurophysiology, synaptic and molecular levels. We will compare the effects of MeHg exposure on in vivo spiking activity patterns in brain regions of the mPFC-aIC circuit, using multiunit electrophysiological recordings in awake animals. Action potentials will be recorded simultaneously from multiple neurons, distributed across cortical layers, to evaluate effects on spike frequency, temporal patterning and correlation. Using acute brain slices derived from animals chronically treated with MeHg in vivo, electrophysiologically recorded synaptic estimates will be made to compare the effects of MeHg exposure on synaptic transmission and EI-balance within brain regions of the mPFC-aIC circuit. Based on previous evidence, we hypothesize that TDP-43 hyper-phosphorylation and aggregation link MeHg exposure to mPFC and aIC dysfunction. Therefore, immunohistochemistry will be used to measure TDP-43 hyper-phosphorylation and nuclear redistribution from animals treated in vivo +/- MeHg. In addition, tissue will be co-labeled with antibodies for nPAS4, a well-stablished molecular marker of activity, to determine whether TDP-43 hallmarks correlate with MeHg-induced hyper-excitability. The results of our study will substantively improve our mechanistic understanding of how Hg disrupts frontal cortical function and contribute to our understanding of the biological basis of emotional and cognitive sympoms. Identifying specific actions of MeHg at the functional microcircuitry level and cellular/molecular level will help significantly in finding novel targets for therapeutic interventions. If our hypothesis is correct, this will also raise the question of the extent to which chronic low-level environmental mercury exposure contributes to the etiology of fronto-cortical disorders with symptoms that overlap mercury exposure but do not have definitive genetic origins. This is particularly important because fronto-cortical disorders are predominantly sporadic in nature.

FENS Forum 2026

Europe’s leading neuroscience conference, bringing together researchers, clinicians, and innovators across molecular, cellular, systems, cognitive, and clinical neuroscience.

Adventures in Spin Labeling: Clinical Perfusion Imaging and the Path to Technical Innovation

Arterial spin labeling (ASL) MRI has become a vital tool in clinical neuroimaging, enabling noninvasive assessment of cerebral perfusion across a range of conditions including stroke, vascular malformations, and brain tumors. With broader clinical adoption, its practical strengths — as well as important limitations — have become increasingly clear.

Consciousness at the edge of chaos

Over the last 20 years, neuroimaging and electrophysiology techniques have become central to understanding the mechanisms that accompany loss and recovery of consciousness. Much of this research is performed in the context of healthy individuals with neurotypical brain dynamics. Yet, a true understanding of how consciousness emerges from the joint action of neurons has to account for how severely pathological brains, often showing phenotypes typical of unconsciousness, can nonetheless generate a subjective viewpoint. In this presentation, I will start from the context of Disorders of Consciousness and will discuss recent work aimed at finding generalizable signatures of consciousness that are reliable across a spectrum of brain electrophysiological phenotypes focusing in particular on the notion of edge-of-chaos criticality.

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.

Developmental emergence of personality

The Nature versus Nurture debate has generally been considered from the lens of genome versus experience dichotomy and has dominated our thinking about behavioral individuality and personality traits. In contrast, the role of nonheritable noise during brain development in behavioral variation is understudied. Using the Drosophila melanogaster visual system, I will discuss our efforts to dissect how individuality in circuit wiring emerges during development, and how that helps generate individual behavioral variation.

High Stakes in the Adolescent Brain: Glia Ignite Under THC’s Influence

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

Convergent large-scale network and local vulnerabilities underlie brain atrophy across Parkinson’s disease stages

The tubulin code in neuron health and disease : focus on detyrosination

Astrocytes: From Metabolism to Cognition

Different brain cell types exhibit distinct metabolic signatures that link energy economy to cellular function. Astrocytes and neurons, for instance, diverge dramatically in their reliance on glycolysis versus oxidative phosphorylation, underscoring that metabolic fuel efficiency is not uniform across cell types. A key factor shaping this divergence is the structural organization of the mitochondrial respiratory chain into supercomplexes. Specifically, complexes I (CI) and III (CIII) form a CI–CIII supercomplex, but the degree of this assembly varies by cell type. In neurons, CI is predominantly integrated into supercomplexes, resulting in highly efficient mitochondrial respiration and minimal reactive oxygen species (ROS) generation. Conversely, in astrocytes, a larger fraction of CI remains unassembled, freely existing apart from CIII, leading to reduced respiratory efficiency and elevated mitochondrial ROS production. Despite this apparent inefficiency, astrocytes boast a highly adaptable metabolism capable of responding to diverse stressors. Their looser CI–CIII organization allows for flexible ROS signaling, which activates antioxidant programs via transcription factors like Nrf2. This modular architecture enables astrocytes not only to balance energy production but also to support neuronal health and influence complex organismal behaviors.

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

Endocannabinoid System Dysregulations in Binge Eating Disorder and Obesity

Memory Decoding Journal Club: Distinct synaptic plasticity rules operate across dendritic compartments in vivo during learning

Distinct synaptic plasticity rules operate across dendritic compartments in vivo during learning

Go with the visual flow: circuit mechanisms for gaze control during locomotion

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.

Seeing a changing world through the eyes of coral fishes

Neural control of internal affective states”

Neural circuits underlying sleep structure and functions

Sleep is an active state critical for processing emotional memories encoded during waking in both humans and animals. There is a remarkable overlap between the brain structures and circuits active during sleep, particularly rapid eye-movement (REM) sleep, and the those encoding emotions. Accordingly, disruptions in sleep quality or quantity, including REM sleep, are often associated with, and precede the onset of, nearly all affective psychiatric and mood disorders. In this context, a major biomedical challenge is to better understand the underlying mechanisms of the relationship between (REM) sleep and emotion encoding to improve treatments for mental health. This lecture will summarize our investigation of the cellular and circuit mechanisms underlying sleep architecture, sleep oscillations, and local brain dynamics across sleep-wake states using electrophysiological recordings combined with single-cell calcium imaging or optogenetics. The presentation will detail the discovery of a 'somato-dendritic decoupling'in prefrontal cortex pyramidal neurons underlying REM sleep-dependent stabilization of optimal emotional memory traces. This decoupling reflects a tonic inhibition at the somas of pyramidal cells, occurring simultaneously with a selective disinhibition of their dendritic arbors selectively during REM sleep. Recent findings on REM sleep-dependent subcortical inputs and neuromodulation of this decoupling will be discussed in the context of synaptic plasticity and the optimization of emotional responses in the maintenance of mental health.

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.

Astrocytes release glutamate by regulated exocytosis in health and disease

Astrocytes release glutamate by regulated exocytosis in health and disease Vladimir Parpura, International Translational Neuroscience Research Institute, Zhejiang Chinese Medical University, Hangzhou, P.R. China Parpura will present you with the evidence that astrocytes, a subtype of glial cells in the brain, can exocytotically release the neurotransmitter glutamate and how this release is regulated. Spatiotemporal characteristic of vesicular fusion that underlie glutamate release in astrocytes will be discussed. He will also present data on a translational project in which this release pathway can be targeted for the treatment of glioblastoma, the deadliest brain cancer.

Expanding mechanisms and therapeutic targets for neurodegenerative disease

A hallmark pathological feature of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is the depletion of RNA-binding protein TDP-43 from the nucleus of neurons in the brain and spinal cord. A major function of TDP-43 is as a repressor of cryptic exon inclusion during RNA splicing. By re-analyzing RNA-sequencing datasets from human FTD/ALS brains, we discovered dozens of novel cryptic splicing events in important neuronal genes. Single nucleotide polymorphisms in UNC13A are among the strongest hits associated with FTD and ALS in human genome-wide association studies, but how those variants increase risk for disease is unknown. We discovered that TDP-43 represses a cryptic exon-splicing event in UNC13A. Loss of TDP-43 from the nucleus in human brain, neuronal cell lines and motor neurons derived from induced pluripotent stem cells resulted in the inclusion of a cryptic exon in UNC13A mRNA and reduced UNC13A protein expression. The top variants associated with FTD or ALS risk in humans are located in the intron harboring the cryptic exon, and we show that they increase UNC13A cryptic exon splicing in the face of TDP-43 dysfunction. Together, our data provide a direct functional link between one of the strongest genetic risk factors for FTD and ALS (UNC13A genetic variants), and loss of TDP-43 function. Recent analyses have revealed even further changes in TDP-43 target genes, including widespread changes in alternative polyadenylation, impacting expression of disease-relevant genes (e.g., ELP1, NEFL, and TMEM106B) and providing evidence that alternative polyadenylation is a new facet of TDP-43 pathology.

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

Restoring Sight to the Blind: Effects of Structural and Functional Plasticity

Visual restoration after decades of blindness is now becoming possible by means of retinal and cortical prostheses, as well as emerging stem cell and gene therapeutic approaches. After restoring visual perception, however, a key question remains. Are there optimal means and methods for retraining the visual cortex to process visual inputs, and for learning or relearning to “see”? Up to this point, it has been largely assumed that if the sensory loss is visual, then the rehabilitation focus should also be primarily visual. However, the other senses play a key role in visual rehabilitation due to the plastic repurposing of visual cortex during blindness by audition and somatosensation, and also to the reintegration of restored vision with the other senses. I will present multisensory neuroimaging results, cortical thickness changes, as well as behavioral outcomes for patients with Retinitis Pigmentosa (RP), which causes blindness by destroying photoreceptors in the retina. These patients have had their vision partially restored by the implantation of a retinal prosthesis, which electrically stimulates still viable retinal ganglion cells in the eye. Our multisensory and structural neuroimaging and behavioral results suggest a new, holistic concept of visual rehabilitation that leverages rather than neglects audition, somatosensation, and other sensory modalities.

Functional Plasticity in the Language Network – evidence from Neuroimaging and Neurostimulation

Efficient cognition requires flexible interactions between distributed neural networks in the human brain. These networks adapt to challenges by flexibly recruiting different regions and connections. In this talk, I will discuss how we study functional network plasticity and reorganization with combined neurostimulation and neuroimaging across the adult life span. I will argue that short-term plasticity enables flexible adaptation to challenges, via functional reorganization. My key hypothesis is that disruption of higher-level cognitive functions such as language can be compensated for by the recruitment of domain-general networks in our brain. Examples from healthy young brains illustrate how neurostimulation can be used to temporarily interfere with efficient processing, probing short-term network plasticity at the systems level. Examples from people with dyslexia help to better understand network disorders in the language domain and outline the potential of facilitatory neurostimulation for treatment. I will also discuss examples from aging brains where plasticity helps to compensate for loss of function. Finally, examples from lesioned brains after stroke provide insight into the brain’s potential for long-term reorganization and recovery of function. Collectively, these results challenge the view of a modular organization of the human brain and argue for a flexible redistribution of function via systems plasticity.

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..

Rejuvenating the Alzheimer’s brain: Challenges & Opportunities

Motor learning selectively strengthens cortical and striatal synapses of motor engram neurons

Join Us for the Memory Decoding Journal Club! A collaboration of the Carboncopies Foundation and BPF Aspirational Neuroscience. This time, we’re diving into a groundbreaking paper: "Motor learning selectively strengthens cortical and striatal synapses of motor engram neurons

Recent views on pre-registration

A discussion on some recent perspectives on pre-registration, which has become a growing trend in the past few years. This is not just limited to neuroimaging, and it applies to most scientific fields. We will start with this overview editorial by Simmons et al. (2021): https://faculty.wharton.upenn.edu/wp-content/uploads/2016/11/34-Simmons-Nelson-Simonsohn-2021a.pdf, and also talk about a more critical perspective by Pham & Oh (2021): https://www.researchgate.net/profile/Michel-Pham/publication/349545600_Preregistration_Is_Neither_Sufficient_nor_Necessary_for_Good_Science/links/60fb311e2bf3553b29096aa7/Preregistration-Is-Neither-Sufficient-nor-Necessary-for-Good-Science.pdf. I would like us to discuss the pros and cons of pre-registration, and if we have time, I may do a demonstration of how to perform a pre-registration through the Open Science Framework.

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

Relating circuit dynamics to computation: robustness and dimension-specific computation in cortical dynamics

Neural dynamics represent the hard-to-interpret substrate of circuit computations. Advances in large-scale recordings have highlighted the sheer spatiotemporal complexity of circuit dynamics within and across circuits, portraying in detail the difficulty of interpreting such dynamics and relating it to computation. Indeed, even in extremely simplified experimental conditions, one observes high-dimensional temporal dynamics in the relevant circuits. This complexity can be potentially addressed by the notion that not all changes in population activity have equal meaning, i.e., a small change in the evolution of activity along a particular dimension may have a bigger effect on a given computation than a large change in another. We term such conditions dimension-specific computation. Considering motor preparatory activity in a delayed response task we utilized neural recordings performed simultaneously with optogenetic perturbations to probe circuit dynamics. First, we revealed a remarkable robustness in the detailed evolution of certain dimensions of the population activity, beyond what was thought to be the case experimentally and theoretically. Second, the robust dimension in activity space carries nearly all of the decodable behavioral information whereas other non-robust dimensions contained nearly no decodable information, as if the circuit was setup to make informative dimensions stiff, i.e., resistive to perturbations, leaving uninformative dimensions sloppy, i.e., sensitive to perturbations. Third, we show that this robustness can be achieved by a modular organization of circuitry, whereby modules whose dynamics normally evolve independently can correct each other’s dynamics when an individual module is perturbed, a common design feature in robust systems engineering. Finally, we will recent work extending this framework to understanding the neural dynamics underlying preparation of speech.

Fear learning induces synaptic potentiation between engram neurons in the rat lateral amygdala

Fear learning induces synaptic potentiation between engram neurons in the rat lateral amygdala. This study by Marios Abatis et al. demonstrates how fear conditioning strengthens synaptic connections between engram cells in the lateral amygdala, revealed through optogenetic identification of neuronal ensembles and electrophysiological measurements. The work provides crucial insights into memory formation mechanisms at the synaptic level, with implications for understanding anxiety disorders and developing targeted interventions. Presented by Dr. Kenneth Hayworth, this journal club will explore the paper's methodology linking engram cell reactivation with synaptic plasticity measurements, and discuss implications for memory decoding research.

Neurosurgery & Consciousness: Bridging Science and Philosophy in the Age of AI

Overview of neurosurgery specialty interplay between neurology, psychiatry and neurosurgery. Discussion on benefits and disadvantages of classifications. Presentation of sub-specialties: trauma, oncology, functional, pediatric, vascular and spine. How does an ordinary day of a neurosurgeon look like; outpatient clinic, emergencies, pre/intra/post operative patient care. An ordinary operation. Myth-busting and practical insights of every day practice. An ordinary operation. Hint for research on clinical problems to be solved. The coming ethical frontiers of neuroprosthetics. In part two we will explore the explanatory gap and its significance. We will review the more than 200 theories of the hard problem of consciousness, from the prevailing to the unconventional. Finally, we are going to reflect on the AI advancements and the claims of LLMs becoming conscious

Memory Decoding Journal Club: Reconstructing a new hippocampal engram for systems reconsolidation and remote memory updating

Join us for the Memory Decoding Journal Club, a collaboration between the Carboncopies Foundation and BPF Aspirational Neuroscience. This month, we're diving into a groundbreaking paper: 'Reconstructing a new hippocampal engram for systems reconsolidation and remote memory updating' by Bo Lei, Bilin Kang, Yuejun Hao, Haoyu Yang, Zihan Zhong, Zihan Zhai, and Yi Zhong from Tsinghua University, Beijing Academy of Artificial Intelligence, IDG/McGovern Institute of Brain Research, and Peking Union Medical College. Dr. Randal Koene will guide us through an engaging discussion on these exciting findings and their implications for neuroscience and memory research.

Decoding ketamine: Neurobiological mechanisms underlying its rapid antidepressant efficacy

Unlike traditional monoamine-based antidepressants that require weeks to exert effects, ketamine alleviates depression within hours, though its clinical use is limited by side effects. While ketamine was initially thought to work primarily through NMDA receptor (NMDAR) inhibition, our research reveals a more complex mechanism. We demonstrate that NMDAR inhibition alone cannot explain ketamine's sustained antidepressant effects, as other NMDAR antagonists like MK-801 lack similar efficacy. Instead, the (2R,6R)-hydroxynorketamine (HNK) metabolite appears critical, exhibiting antidepressant effects without ketamine's side effects. Paradoxically, our findings suggest an inverted U-shaped dose-response relationship where excessive NMDAR inhibition may actually impede antidepressant efficacy, while some level of NMDAR activation is necessary. The antidepressant actions of ketamine and (2R,6R)-HNK require AMPA receptor activation, leading to synaptic potentiation and upregulation of AMPA receptor subunits GluA1 and GluA2. Furthermore, NMDAR subunit GluN2A appears necessary and possibly sufficient for these effects. This research establishes NMDAR-GluN2A activation as a common downstream effector for rapid-acting antidepressants, regardless of their initial targets, offering promising directions for developing next-generation antidepressants with improved efficacy and reduced side effects.

COSYNE 2025

The COSYNE 2025 conference was held in Montreal with post-conference workshops in Mont-Tremblant, continuing to provide a premier forum for computational and systems neuroscience. Attendees exchanged cutting-edge research in a single-track main meeting and in-depth specialized workshops, reflecting Cosyne’s mission to understand how neural systems function.

Pain in the Brain: A Drink a Day Could Bring More Than You Bargain

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.

What it’s like is all there is: The value of Consciousness

Over the past thirty years or so, cognitive neuroscience has made spectacular progress understanding the biological mechanisms of consciousness. Consciousness science, as this field is now sometimes called, was not only inexistent thirty years ago, but its very name seemed like an oxymoron: how can there be a science of consciousness? And yet, despite this scepticism, we are now equipped with a rich set of sophisticated behavioural paradigms, with an impressive array of techniques making it possible to see the brain in action, and with an ever-growing collection of theories and speculations about the putative biological mechanisms through which information processing becomes conscious. This is all good and fine, even promising, but we also seem to have thrown the baby out with the bathwater, or at least to have forgotten it in the crib: consciousness is not just mechanisms, it’s what it feels like. In other words, while we know thousands of informative studies about access-consciousness, we have little in the way of phenomenal consciousness. But that — what it feels like — is truly what “consciousness” is about. Understanding why it feels like something to be me and nothing (panpsychists notwithstanding) for a stone to be a stone is what the field has always been after. However, while it is relatively easy to study access-consciousness through the contrastive approach applied to reports, it is much less clear how to study phenomenology, its structure and its function. Here, I first overview work on what consciousness does (the "how"). Next, I ask what difference feeling things makes and what function phenomenology might play. I argue that subjective experience has intrinsic value and plays a functional role in everything that we do.

Brain Emulation Challenge Workshop

Brain Emulation Challenge workshop will tackle cutting-edge topics such as ground-truthing for validation, leveraging artificial datasets generated from virtual brain tissue, and the transformative potential of virtual brain platforms, such as applied to the forthcoming Brain Emulation Challenge.

Brain Emulation Challenge Workshop

Brain Emulation Challenge workshop will tackle cutting-edge topics such as ground-truthing for validation, leveraging artificial datasets generated from virtual brain tissue, and the transformative potential of virtual brain platforms, such as applied to the forthcoming Brain Emulation Challenge.

Brain Emulation Challenge Workshop

Brain Emulation Challenge workshop will tackle cutting-edge topics such as ground-truthing for validation, leveraging artificial datasets generated from virtual brain tissue, and the transformative potential of virtual brain platforms, such as applied to the forthcoming Brain Emulation Challenge.

Vision for perception versus vision for action: dissociable contributions of visual sensory drives from primary visual cortex and superior colliculus neurons to orienting behaviors

The primary visual cortex (V1) directly projects to the superior colliculus (SC) and is believed to provide sensory drive for eye movements. Consistent with this, a majority of saccade-related SC neurons also exhibit short-latency, stimulus-driven visual responses, which are additionally feature-tuned. However, direct neurophysiological comparisons of the visual response properties of the two anatomically-connected brain areas are surprisingly lacking, especially with respect to active looking behaviors. I will describe a series of experiments characterizing visual response properties in primate V1 and SC neurons, exploring feature dimensions like visual field location, spatial frequency, orientation, contrast, and luminance polarity. The results suggest a substantial, qualitative reformatting of SC visual responses when compared to V1. For example, SC visual response latencies are actively delayed, independent of individual neuron tuning preferences, as a function of increasing spatial frequency, and this phenomenon is directly correlated with saccadic reaction times. Such “coarse-to-fine” rank ordering of SC visual response latencies as a function of spatial frequency is much weaker in V1, suggesting a dissociation of V1 responses from saccade timing. Consistent with this, when we next explored trial-by-trial correlations of individual neurons’ visual response strengths and visual response latencies with saccadic reaction times, we found that most SC neurons exhibited, on a trial-by-trial basis, stronger and earlier visual responses for faster saccadic reaction times. Moreover, these correlations were substantially higher for visual-motor neurons in the intermediate and deep layers than for more superficial visual-only neurons. No such correlations existed systematically in V1. Thus, visual responses in SC and V1 serve fundamentally different roles in active vision: V1 jumpstarts sensing and image analysis, but SC jumpstarts moving. I will finish by demonstrating, using V1 reversible inactivation, that, despite reformatting of signals from V1 to the brainstem, V1 is still a necessary gateway for visually-driven oculomotor responses to occur, even for the most reflexive of eye movement phenomena. This is a fundamental difference from rodent studies demonstrating clear V1-independent processing in afferent visual pathways bypassing the geniculostriate one, and it demonstrates the importance of multi-species comparisons in the study of oculomotor control.

Circuit Mechanisms of Remote Memory

Memories of emotionally-salient events are long-lasting, guiding behavior from minutes to years after learning. The prelimbic cortex (PL) is required for fear memory retrieval across time and is densely interconnected with many subcortical and cortical areas involved in recent and remote memory recall, including the temporal association area (TeA). While the behavioral expression of a memory may remain constant over time, the neural activity mediating memory-guided behavior is dynamic. In PL, different neurons underlie recent and remote memory retrieval and remote memory-encoding neurons have preferential functional connectivity with cortical association areas, including TeA. TeA plays a preferential role in remote compared to recent memory retrieval, yet how TeA circuits drive remote memory retrieval remains poorly understood. Here we used a combination of activity-dependent neuronal tagging, viral circuit mapping and miniscope imaging to investigate the role of the PL-TeA circuit in fear memory retrieval across time in mice. We show that PL memory ensembles recruit PL-TeA neurons across time, and that PL-TeA neurons have enhanced encoding of salient cues and behaviors at remote timepoints. This recruitment depends upon ongoing synaptic activity in the learning-activated PL ensemble. Our results reveal a novel circuit encoding remote memory and provide insight into the principles of memory circuit reorganization across time.

Predicting traveling waves: a new mathematical technique to link the structure of a network to the specific patterns of neural activity

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.

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.

Bernstein Conference 2024

Each year the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange. Bernstein Conference 2024, held in Frankfurt am Main, featured discussions, keynote lectures, and poster sessions, and has established itself as one of the most renowned conferences worldwide in this field.

FENS Forum 2024

Organised by FENS in partnership with the Austrian Neuroscience Association and the Hungarian Neuroscience Society, the FENS Forum 2024 will take place on 25–29 June 2024 in Vienna, Austria. The FENS Forum is Europe’s largest neuroscience congress, covering all areas of neuroscience from basic to translational research.

COSYNE 2023

The COSYNE 2023 conference provided an inclusive forum for exchanging experimental and theoretical approaches to problems in systems neuroscience, continuing the tradition of bringing together the computational neuroscience community. The main meeting was held in Montreal followed by post-conference workshops in Mont-Tremblant, fostering intensive discussions and collaboration.

Neuromatch 5

Neuromatch 5 (Neuromatch Conference 2022) was a fully virtual conference focused on computational neuroscience broadly construed, including machine learning work with explicit biological links. After four successful Neuromatch conferences, the fifth edition consolidated proven innovations from past events, featuring a series of talks hosted on Crowdcast and flash talk sessions (pre-recorded videos) with dedicated discussion times on Reddit.

COSYNE 2022

The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The main meeting is single-track, with invited talks selected by the Executive Committee and additional talks and posters selected by the Program Committee based on submitted abstracts. The workshops feature in-depth discussion of current topics of interest in a small group setting.

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

THE CEREBROSPINAL FLUID AND PLASMA PROTEOMICS OF IDIOPATHIC NORMAL PRESSURE HYDROCEPHALUS

FENS Forum 2026

Cross-correlation--response relation for spike-driven neurons

Bernstein Conference 2024

Efficient nonlinear receptive field estimation across processing stages of sensory systems

Bernstein Conference 2024

Estimating flexible across-area communication with neurally-constrained RNNs

Bernstein Conference 2024

Homeostatic regulation of synaptic connectivity across connectomes

Bernstein Conference 2024

Increase in dimensionality and sparsification of neural activity over development across diverse cortical areas

Bernstein Conference 2024

Unstructured representations in a structured brain: a cross-region analysis of the neural code

Bernstein Conference 2024

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

Bernstein Conference 2024

Open-source solutions for research data management in neuroscience collaborations

Bernstein Conference 2024

Optimising local diameters across entire dendritic trees

Bernstein Conference 2024

Quantitative modeling of the emergence of macroscopic grid-like representations

Bernstein Conference 2024

Role of local Kenyon cell – Kenyon Cell interactions in the γ lobe of Drosophila melanogaster for specificity in olfactory learning

Bernstein Conference 2024

Set-based Fitness Comparisons - Could Neuroscientists Benefit from Engineering Studies on Conceptual Design?

Bernstein Conference 2024

Flygenvectors: The spatial and temporal structure of neural activity across the fly brain

COSYNE 2022

Flygenvectors: The spatial and temporal structure of neural activity across the fly brain

COSYNE 2022

Utilizing Random Forest for Multivariate Analysis: Exploring the Influence of Dopaminergic Neurons on Drosophila Larvae Locomotion

Bernstein Conference 2024

Accurate Engagement of the Drosophila Central-Complex Compass During Head-Fixed Path-Constrained Navigation

COSYNE 2022

Chromatic contrast and angle of polarization signals are integrated in the Drosophila central complex

COSYNE 2022

A circuit library for exploring the functional logic of massive feedback loops in Drosophila brain

COSYNE 2022

Label-free biomolecular spectroscopy with vibrational fiber photometry deep in the mouse brain

FENS Forum 2024

Conjunctive theta- and ripple-frequency oscillations across hippocampal strata of foraging rats

COSYNE 2022

Coordinated cortico-cerebellar neural dynamics underlying neuroprosthetic learning

COSYNE 2022

Cross-Frequency Coupling Increases Memory Capacity in Oscillatory Neural Networks

COSYNE 2022

Dendritic integration of thalamic HD signals and retrosplenial input in presubicular neurons

COSYNE 2022

Differential encoding of temporal context and expectation across the visual hierarchy

COSYNE 2022

Environment-dependent firing in rigidly organized head-direction cells is stable across weeks

COSYNE 2022

Evaluating Noise Tolerance in Drosophila Vision

COSYNE 2022

Experience early in auditory conditioning impacts across-animal variability in neural tuning

COSYNE 2022

Exploiting color space geometry for visual stimulus design across animals

COSYNE 2022

Stable cortical coding for a dexterous reach-to-grasp task across motor cortical laminae

Bernstein Conference 2024

Identifying patterns across brains from 10 years of human single-neuron recordings

Bernstein Conference 2024

Hierarchical modularity in Drosophila brain reveals novel organizational principles

COSYNE 2022

Hierarchical modularity in Drosophila brain reveals novel organizational principles

COSYNE 2022

Inter-areal patterned microstimulation selectively drives PFC activity and behavior in a memory task

COSYNE 2022

Inter-areal patterned microstimulation selectively drives PFC activity and behavior in a memory task

COSYNE 2022

Interpretable behavioral features have conserved neural representations across mice

COSYNE 2022

Interpretable behavioral features have conserved neural representations across mice

COSYNE 2022

Investigation of a multilevel multisensory circuit underlying female decision making in Drosophila

COSYNE 2022

Population Dynamics and Network Behaviour of ON- and OFF-cells in the Rostral Ventral Medulla

Bernstein Conference 2024