design

Antibody-guided design of a human astrovirus vaccine

PROJECT SUMMARY Viral diarrheal diseases cause substantial global morbidity and mortality. Diarrheal disease is the second leading cause of childhood mortality in the world, accounting for over 10% of all deaths of children under 5 years old. Gobally, over 1 billion cases of diarrheal diseases occur every year, making prevention of these diseases a public health concern of the highest priority. Human astrovirus (HAstV) infection is a leading cause of viral diarrhea in children and has been shown to cause chronic gastrointestinal disease and fatal neurological disease in immunocompromised patients. There are nearly 4 million cases of HAstV infection each year in the United States alone, and there are no clinically approved HAstV-specific vaccines or therapeutics. Antibody-guided vaccine development leverages a deep understanding of productive antiviral antibody responses in order to design vaccine immunogens that deliberately focus the induced response toward highly conserved epitopes with the goal of reliably inducing broad, durable immunity. Using a cutting-edge monoclonal antibody (mAb) discovery approach based on next-generation antigen barcoding, single cell multi-omics, and sophisticated bioinformatics, we will exhaustively screen the HAstV- specific antibody repertoires of geographically distinct donor cohorts to uncover the structural and immunogenetic features that differentiate broad and potently neutralizing HAstV mAbs. A more complete understanding of these exceptional – and potentially very rare – mAbs will accelerate the development of HAstV vaccines and therapeutics. We have assembled a collaborative, multidisciplinary group of investigators with a long history of productive collaboration and with highly complementary areas of expertise. We expect our work will result in the discovery of thousands of novel anti-HAstV mAbs from cohorts of healthy adult and pediatric participants. Detailed genetic, functional, and structural characterization of these mAbs will reveal conserved sites of viral vulnerability, uncover the precise molecular mechanisms of viral neutralization, and inform our development of a broadly protective HAstV vaccine.

Communication and Hospice Online with Optimal Support and Engagement (CHOOSE)

Abstract Drawing upon the principles of social identity theory, existing literature, and our initial findings from family caregiver (FCG) online support groups (OSGs), our objective is to identify fundamental facilitator communication strategies that promote safe communication engage participants, and strengthen mechanisms of action (MOAs) within OSGs, ultimately enhancing health outcomes for hospice FCGs. Our pioneering initiative, Communication and Hospice Online with Optimal Support and Engagement (CHOOSE) is backed by compelling evidence highlighting the critical role of facilitator communication in reinforcing MOAs (a shared identity, social support, and social networks) in OSGs. Preliminary research underscores the transformative power of these MOAs in improving health outcomes for FCGs, yet current studies lack generalizability and statistical robustness. CHOOSE represents the first major, multisite, rigorously designed, and theoretically informed OSG intervention explicitly tailored for hospice FCGs of cancer patients. We aim to strengthen MOAs to enhance FCG well-being, reduce depression and anxiety, improve quality of life, and diminish loneliness. By advancing this critical research, we seek to provide a well-founded, evidence-based solution to the urgent needs of FCGs, making a significant impact on their health and well-being. We have outlined the following study aims: Aim 1. Determine the effect of the CHOOSE intervention on FCGs’ health outcomes compared to usual OSGs and usual hospice care. Aim 2. Examine direct and mediational relationships between CHOOSE participation, MOAs, and health outcomes. Aim 3. Explore the relationship between facilitator communication strategies and the FCG experience of the MOA to allow for future calibration of the intervention 1

Weak Cell Adhesion is a Prognostic Signature of Invasive Cancer

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

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

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

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.

Mentoring investigators in patient-oriented research on HIV and public health

PROJECT SUMMARY/ABSTRACT Despite marked progress in treatment and prevention, HIV remains a significant public health threat in the US and globally. Innovative strategies are needed to effectively deploy interventions and reduce HIV incidence, which requires a sustained and committed workforce. Dr. Dennis is an infectious disease physician and researcher at the University of North Carolina (UNC) at Chapel Hill, Division of Infectious Diseases. She seeks the protected time of the K24 award to ensure adequate time and effort to provide mentorship in patient- oriented HIV research focused on applied public health strategies. Dr. Dennis has a track record of performing high-quality patient-oriented research supported by independent funding. Her research bridges basic, clinical, and epidemiologic science by using HIV-1 molecular epidemiology and phylogenetics to understand HIV transmission at the population level and to use this information to direct prevention. She has expanded this work to optimize strategies to detect and respond to HIV networks using mixed-methods approaches. The overall goal of this work is to uncover the links between these sub-epidemics - which are overlapping sub- epidemics defined by risk groups, geography, social interaction - to facilitate the design of timely, effective interventions. The research specific aims are 1) Investigate HIV transmission networks using molecular epidemiology and phylodynamics (R01AI135970), 2) Evaluate uptake of HIV treatment and prevention services in public health with social network approaches (supported by R01AI169602), and 3) Pilot a network-based characterization of early syphilis infections to inform strategies to increase the uptake of injectable antiretrovirals for HIV treatment and prevention (supported by K24). With the support of the K24, she will leverage resources at UNC to support mentorship and professional development to strengthen new directions (implementation science, community-engaged research). Dr. Dennis is deeply committed to expanding her mentorship and dedicated to fostering diverse mentees with lived experiences that are critical for sustaining the HIV workforce. Dr. Dennis is Co-Director of the UNC Center for AIDS Research (CFAR) Scientific Working Group which focuses on Ending the HIV Epidemic efforts in North and South Carolina. She has strong institutional support and a multidisciplinary team of advisors, including the UNC CFAR, and is an advisor on the UNC T32 HIV/STI institutional training program. She has collaborated for the past 10 years with NC Division of Public Health and with multiple investigators and trainees at the UNC Gillings School of Public Health. She is active in the UNC Infectious Diseases Fellowship program, providing clinical and research mentorship to numerous ID fellows. Her clinical activity provides practical grounding and relevance in patient-oriented research. The K24 will provide 50% of Dr. Dennis’ salary and additional funds to support mentees’ research. The proposed research is timely and aligned with the National HIV/AIDS Strategy and will support the protected time needed to mentor the next-generation of investigators in HIV patient-oriented research.

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.

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.

FIRE-PF: Developing and Testing a Trauma-Informed Alcohol Intervention to Enhance Mental Health in Firefighters

PROJECT SUMMARY Alcohol use and hazardous drinking are ubiquitous among firefighters in the United states and is associated with significant physical and mental health risks for this population. Due to the nature of their work, firefighters experience substantially higher rates of trauma exposure and are subsequently at greater risk of developing specific mental health conditions compared to the general population, particularly trauma-related psychopathology (e.g., posttraumatic stress). Hazardous drinking and posttraumatic stress frequently co-occur among firefighters, leading to poorer health outcomes compared to either condition alone. Despite this elevated risk, firefighters often lack access to tailored, empirically supported interventions, and no existing mental health interventions address hazardous drinking in a trauma-informed framework for this at-risk population. Personalized feedback interventions (PFIs) are a promising approach that could address this gap. By delivering brief, patient-centered feedback on drinking behaviors and perceptions within the context of trauma and occupational stress, PFIs aim to reduce problematic drinking behaviors and stigma related to coping-orientated drinking and improve stress management strategies. PFIs can be brief, cost-effective, and easily disseminated in a format accessible to large groups, making them a strong candidate for use with firefighters who face critical barriers to engaging in traditional mental health programs. This innovative study aims to develop a single-session, trauma-informed, online PFI tailored specifically for firefighters, using a comprehensive, three-phase approach to address three primary aims. The Development Phase involves developing, adapting, and enhancing a trauma-informed PFI by gathering qualitative feedback from firefighters (N = 45) and using an iterative, rapid user-centered design approach to ensure the intervention is engaging for firefighters as well as relevant and aligned with fire service culture. The Evaluation Phase will assess the feasibility, acceptability, and preliminary impact of the PFI in a mixed-methods longitudinal open trial with firefighters (N = 50), with a focus on the intervention's usability, delivery, and influence on drinking behaviors. The Implementation Planning Phase will involve qualitative and quantitative assessments with fire service leaders (N = 15) to identify implementation barriers and shape future research testing the implementation process for the intervention and inform future strategies for resource integration and fostering sustainable community partnerships. This proposal will equip Dr. Lebeaut with essential training for an independent research career, including training in (1) qualitative methodologies, (2) user-centered design, (3) developing, adapting, and enhancing trauma-informed alcohol interventions, and (4) developing collaborative relationships with community partners in the fire service. The proposed study will directly inform a future R01 to evaluate the intervention’s efficacy and scalability and support the development of a firefighter-focused research program.

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.

Integrins α4β7 in Leukocyte Rolling in Shear Flow, Firm Adhesion, and Therapy

Abstract. Integrin α4β7 facilitates leukocyte migration to sites of infection and autoimmune disease, making it an important therapeutic target for ulcerative colitis and Crohns disease. However, the currently approved antibody drug vedolizumab targeting α4β7 has limited efficacy. This proposal seeks mechanistic understanding of how α4β7 mediates rolling and firm adhesion of leukocytes during extravasation as well as how therapeutically relevant antibodies modulate α4β7 function to improve drug design. Unlike most integrins, α4β7 mediates rolling adhesion on its ligand MAdCAM. α4β7 can also mediate firm adhesion like α5β1. Integrins typically equilibrate between two low-affinity closed conformations and a high-affinity open conformation. Ligand binding is intimately coordinated with conformational change. During rolling adhesion, receptor-ligand bonds must rapidly form beneath rolling cells as cells are torqued by shear flow onto the substrate. Bonds must also rapidly dissociate at the upstream tethers to the substrate due to hydrodynamic force applied to the cell. To enable their function in rolling adhesion, we hypothesize that α4β7 ligand binding and dissociation and conformational change kinetics are faster than those of other integrins like α5β1 and that α4β7's pathways for conformational change may also differ. We propose that activation of the actin cytoskeleton in the transition from rolling to firm adhesion stabilizes α4β7 in a high-affinity state. Aim 1 will determine high-resolution structures of unliganded α4β7 and its complexes with MAdCAM or medically relevant antibodies using cryo- EM. These structures will reveal how these integrins recognize their ligands, the conformational changes due to ligand binding, and potential structural specializations that enable α4β7 to mediate rolling adhesion. The binding epitopes and conformational specificities of activating antibodies to the β7 subunit will also be defined. The structure of α4β7 bound to vedolizumab will resolve the contention around how it blocks MAdCAM binding. Aim 2 will quantitatively define the mechanisms by which α4β7 mediates both rolling and firm adhesion to improve therapies for inflammatory bowel diseases. Ligand affinity and binding kinetics of α4β7 stabilized in different conformations will be measured as well as single-molecule conformational change rates when bound and unbound to ligand. The effect of mutations that stabilize rolling or firm adhesion will be used to identify parameters important for each adhesion type. The tensile force and bond lifetimes during rolling and firm adhesion will be quantified at the single-molecule level. Together, our studies will enhance our structural, biochemical, and mechanical understanding of α4β7-mediated rolling and firm adhesion and will provide structural and functional information that can be utilized in the development of more effective therapies for inflammatory bowel diseases and multiple myeloma.

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.

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.

Systems Biology of Early Atopy: Role of Human Milk (SunBEAm-Milk)

Surprisingly little is known about the effect of breastfeeding (BF) on infant immune system development besides an effect on the gut microbiome, but its impact on metabolites and Tregs could support protection against food allergy (FA). BF is currently recommended to prevent the development of allergic diseases, especially asthma/recurrent wheezing and AD in early childhood, but firm conclusions could not be drawn regarding FA due to high heterogeneity and low quality of studies. Reverse causation, recall bias and the poor accuracy of outcome assessment are significant limitations. Most are inadequately powered to specific FA; however, a recent study showed that exclusively BF infants had lower odds of egg, sesame, and peanut allergies. Importantly, immunomodulatory composition of HM varies between mothers, which has not been taken into consideration. For over two decades we have been developing methods to assess immunomodulatory factors in the complex matrix of HM and their association with infant FA. We have shown that high levels of HM total and specific IgA are associated with protection against cow’s milk allergy, but it is unclear whether HM IgA is responsible for or is a biomarker of the vertical transfer of protection. Infant fecal and systemic IgA levels during breastfeeding and after weaning are also elevated in infants at low risk for atopic disease raising the question of whether HM factors such as cytokines can promote IgA production in infants. Consistent with this, we showed that HM cytokines, such as APRIL, induce IgA production in naïve infant B cells, and infants receiving HM with higher levels of APRIL had lower incidence of allergic disease. Finally, lower levels of several HM fatty acids including short-chain fatty acids and DHA were associated with FA. While some these factors were are associated with maternal atopic disease, several of them are not and suggest a role for diet instead. The System Biology of Early Atopy (SunBEAm) population-based cohort of 2500 mother-infant pairs is >50% recruited and provides an unprecedented opportunity to assess association of HM feeding and immune factors in HM with development of infant immune system and FA/AD. The Common Sample comprises a subset of 100 dyads with FA, 100 with FA+AD, 100 with AD, 100 with no FA or AD and more extensively profiled biological data. Utilizing all 2-month HM samples available in the Common Sample, we will assess levels of immune factors in HM and their association with maternal/infant characteristics (Aim 1). Utilizing data from the whole cohort, we will assess the association between HM vs formula feeding on well-defined FA/AD further adjusted based on high vs low levels of HM immune components in the Common Sample (Aim 2b). Finally, we will examine the immune cell and epithelial effects of HM on infant immune markers and intestinal organoids (Aim 3). Key findings will be validated in an independent birth cohort. The ultimate goal is to uncover protective properties of BF and HM in FA and subsequent design of policies and prevention strategies to address the increasing rates of FA.

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.

Biostatistics, Ethics, Data Management, Research Design and Community Engagement(BEDRoC) Core

Biostatistics, Ethics, Data Management, Research Design and Community Engagement (BEDRoC) Core Abstract The Biostatistics, Ethics, Data Management, Research Design and Community Engagement (BEDRoC) Core will promote and support aging with serious illness science for the Center for Aging with Serious Illness (CASI). BEDRoC will provide expertise in statistical design and analysis, research ethics, and community engagement for all components of CASI. The Core's services will support the Research Project Leaders (RPLs) and Pilot Project Leaders (PPLs) and build capacity for the broader Dartmouth Health aging research community to conduct rigorous, impactful research to inform and improve care delivery for older adults with serious illness. BEDRoC includes expertise in mixed methods approaches that feature both quantitative and qualitative research methods to provide a comprehensive understanding of the complex issues related to aging with serious illness, ethical approaches to consent in research trials, multidimensional quality of life measurement, and innovative modeling approaches to studying clinical decision making. BEDRoC faculty have actively collaborated in study planning with each RPL, serving as both mentors and experienced collaborators on the three different projects involving decision aids for patients considering carotid revascularization, a patient-reported outcome-directed referral intervention to improve referral rates to palliative care services, and a pilot trial for a virtual/home-based exercise and a weight management osteoarthritis treatment program in older patients with osteoarthritis and multimorbidity. The BEDRoC Core will further support CASI by establishing an innovative training curriculum with workshops, tutorials, resources, and services, offered locally to RPLs and PPLs and extended to regional and national investigators in the IDeA network. In addition to their primary individual project mentors, each RPL will receive training and guidance from BEDRoC leaders through co-mentoring and RPL-focused works-in-progress sessions. BEDRoC will also provide access to a comprehensive inventory of patient-reported outcomes instruments, which are crucial in geriatric research to provide validated measures of health status, quality of life and functional ability outcomes. BEDRoC will coordinate with the Administrative and Mentoring Core to integrate community advisors in guiding their activities in support of the RPLs. BEDRoC will also enable research collaboration with and within the larger Dartmouth and IDeA investigator communities. The BEDRoC Core will build capacity for aging research and disseminate new resources to RPLs and PPLs, including innovative solutions created through robust community engagement. These services, resources, and solutions will ensure all projects operate in a cohesive, complementary, and collaborative manner to study approaches to improving the health of older patients with serious illness.

AI-enabled methods for de novo design of functional peptides

PROJECT SUMMARY Macrocyclic peptides offer unique therapeutic potential, particularly for targeting intracellular protein-protein interactions considered ‘undruggable’ with traditional therapeutic modalities. Additionally, peptides can combine the benefits and bridge the gap between conventional small molecule therapeutics and large biologics. However, developing new peptide-based therapeutics using traditional approaches, such as natural product discovery or high-throughput library screening, has remained slow and challenging. Moreover, these conventional approaches cover a small fraction of the chemical and structural space, are restricted to a few starting peptide scaffolds, and typically fail to optimize for multiple therapeutic properties simultaneously. Our central hypothesis is that structure-guided deep learning methods can rapidly explore the chemical and structural space beyond natural products and enable precise, rapid, and custom design of functional peptides simultaneously optimized for target binding, selectivity, and membrane permeability. In our recent work, we developed physics-based methods for designing constrained peptides and macrocycles and, more recently, introduced deep learning methods for structure prediction, sequence redesign, and de novo design of peptide monomers and targeted binders. Here, we propose to develop a new generation of structure-guided deep learning (DL) tools to address the current limitations of computational and experimental methods and enable accurate, accessible, and broadly applicable design of macrocycles. Specifically, we will pursue the projects focused on: (i) leveraging DL methods to systematically enumerate the chemical and structural space of constrained peptides and membrane-traversing peptides to develop scaffolds and core design principles for functional peptide design; (ii) high-throughput design and data collection to improve design selection, filtering metrics, and sequence design algorithms; (iii) developing generative DL methods that expand beyond current capabilities and allow sequence and structure design with vast chemical space of non-canonical amino acids; and (iv) use those new generative methods to design macrocyclic binders against different therapeutically-relevant targets, including the critical fusion and attachment proteins from viruses of pandemic concern. Our preliminary work in these proposed areas demonstrates the feasibility of this approach. The proposed computational tools, scaffold sets, and designed peptides will significantly advance therapeutic design beyond the state-of-the-art and enable rapid and custom design of drug- like peptides tailored for addressing complex therapeutic, diagnostic and research challenges.

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.

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.

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.

ATPase Chromatin Remodeling Complexes as Modulators of HIV-1 Latency and Therapeutic Targets

Abstract Significance: HIV persists in long-lived CD4⁺ T cell reservoirs despite suppressive ART, as integrated proviruses remain poised for reactivation. Chromatin remodeling is a central barrier to durable silencing, yet most studies have focused on SWI/SNF family members. The roles of non- SWI/SNF remodelers remain poorly defined, limiting our ability to rationally design host-directed “block-and-lock” cure strategies. Our unbiased shRNA screen of all 16 human remodeler ATPases identified EP400, CHD1, and CHD9 as repressors and INO80A, SMARCA5, and CHD2 as activators, establishing chromatin remodeling as a key determinant of HIV latency. Innovation: Our prior studies revealed that the p400 complex regulates HIV transcription through dual mechanisms: directly, by engaging Tat via the DMAP1 subunit to block Tat-TAR RNA interactions and restrict p-TEFb recruitment; and indirectly, by altering host transcriptional programs that control T cell activation states. Building on this mechanistic precedent and methodological platform, we now focus on INO80A, SMARCA5, CHD1, and CHD2, remodelers from distinct ATPase families that govern Tat-independent checkpoints at initiation, pause release, and elongation. Methodologically, we will apply TurboID-ChAP-MS (locus-specific proteomics), BEM-seq (single-nucleosome mapping), and degron-mediated acute depletion with ATPase-dead rescue to interrogate remodeler function with unprecedented resolution. Approach: Aim 1 will define the ATPase requirement and transcriptional checkpoints regulated by INO80A, SMARCA5, CHD1, and CHD2 using degron/CRISPR perturbations, ChIP-seq, nascent RNA profiling, and nucleosome mapping. Aim 2 will characterize remodeler-specific complexes and Tat dependence at the HIV promoter via TurboID proximity labeling integrated with chromatin affinity purification-mass spectrometry. Aim 3 will test combinatorial perturbations in Jurkat and primary CD4⁺ T cell latency models, including ART-suppressed donor cells, to identify synergistic “block-and-lock” strategies that enforce durable proviral silencing. Impact: By defining remodeler-specific mechanisms at discrete transcriptional checkpoints and leveraging their enzymatic, druggable activities, this work will establish chromatin remodeling as a therapeutic axis for durable HIV suppression and functional cure.

Specific Affinity Requirements for Antibody Somatic Hypermutation

PROJECT SUMMARY Antibodies diversify through two distinct pathways. The first involves the combinatorial assembly of immunoglobulin (Ig) heavy and light chain variable region (V) exons, forming the antigen recognition domains of the B cell receptor (BCR), which is initially expressed as IgM on immature B cells. The second diversification pathway is somatic hypermutation (SHM) of V exons in germinal centers (GCs). In this setting, B cells that acquire mutations enhancing affinity for antigen receive limited cognate T cell help and are selected for clonal expansion, leading to affinity maturation. These primary and secondary diversification systems work together to generate protective antibody responses. The primary, or pre-immune, repertoire provides the foundation for initial antigen recognition. SHM and affinity maturation refine these baseline specificities. While it is well established that SHM improves affinities already present in the primary repertoire, this project explores the hypothesis that SHM can also generate new specificities in B cells that initially lack measurable antigen recognition. This process, termed affinity birth, may enable access to otherwise excluded V gene segments and expand the landscape of antibody evolution. This hypothesis will be tested through two specific aims: (i) To elucidate the extent of SHM-mediated Ig diversification in non-specific or bystander B cells. And, (ii) to define parameters that influence SHM-mediated antibody affinity birth. The significance of this work lies in its potential to reveal previously unappreciated flexibility in the antibody diversification process and to uncover modifiable factors that influence the emergence of new specificities. The proposed studies are innovative in suggesting that B cells possess intrinsic capacity to undergo SHM and selection regardless of their initial antigen specificity. This research may advance understanding of how germinal centers support antibody evolution and inform strategies to design vaccines that anticipate emerging pathogens.

Mechanisms of age-related inflammatory dysregulation in the pathogenesis of periodontal disease

Periodontal disease is a chronic inflammatory condition that affects the supporting tissues of the dentition. Similar to other chronic inflammatory conditions, the prevalence of periodontal disease increases with age. Dysregulation of the host inflammatory response is central to the pathogenesis of periodontal disease and other age-related diseases. Therefore, an improved understanding of the pathologic mechanisms that contribute to age-related inflammatory dysregulation is needed to better manage periodontal disease in older adults. Towards understanding a mechanism of age-related inflammatory dysregulation in periodontal disease, we will investigate the role of triggering receptor expressed on myeloid cells 2 (TREM2). TREM2 is a potent immunoregulator expressed on macrophages. Signaling through TREM2 downregulates inflammation, in part, through inhibition of inflammatory cytokine expression. Dysregulation of TREM2 has been implicated in chronic inflammatory disease and age-related conditions, such as Alzheimer’s disease, liver disease, and osteoarthritis. However, the role of TREM2 in periodontal disease is understudied. Therefore, we propose to study TREM2 in the pathogenesis of periodontal disease and age-related inflammatory dysregulation. Our preliminary work has demonstrated that TREM2 is critical in macrophage immunoregulatory processes in the periodontium and TREM2 dysregulation contributes to periodontal disease in mice. We have shown that Trem2 is expressed in macrophages isolated form the periodontium in mice. We demonstrated that old mice expressed less Trem2 in the periodontium compared to young, which was associated with local inflammatory dysregulation and increased periodontal disease severity. Interestingly, Trem2 depletion in young mice resulted in increased inflammatory dysregulation and periodontal disease severity, similar to what is observed in old mice. From the preliminary data, we hypothesize that TREM2 modulates macrophage activity in the periodontium and age-related dysregulation of TREM2 drives a pathologic inflammatory response in periodontal disease. In Aim 1, we will demonstrate the extent to which TREM2 modulates inflammation and periodontal disease severity using old, young, and Trem2-/- mouse models of periodontal disease. In Aim 2, we will develop tissue-specific, single cell map of the immune cells in the periodontium and understand the effect of age and Trem2 on immune cell phenotypes and subpopulations. Findings from this proposal will elucidate a novel mechanism in age-related inflammatory dysregulation in the pathogenesis of periodontal disease and further advance our understanding of the role of TREM2 within oral tissues. This proposal was designed to generate a novel body of work that will be used to develop the independent research program of an early stage investigator and to support an R01 proposal to be submitted at the completion of this project period.

Addressing C-F bonds and amyloid-formation in biological systems

The ingestion, pulmonary inhalation, and dermal infiltration of C-F bond-containing compounds, most commonly found in the form of per- and polyfluoroalkyl organic acids, causes oxidative stress, inflammation, DNA damage, and developmental defects in infants and adults. These chemicals accumulate in the brain, disrupt neurological function and compromise cognitive and locomotory behavior. Yet, we lack a high-resolution road-map of the interactions between C-F bonds and biomolecular assemblies driving the trajectory towards neurodegenerative outcomes. This gap constitutes a significant barrier to advancing measures designed to mitigate C-F chemistry-associated neurotoxicity. Emerging experimental and computational data from our laboratory reveals that perfluorooctanoic acid, perfluorodecanoic acid and perfluorosulfonic acid corrupt biomolecular structures through C-F:side-chain interactions in tested soluble, globular proteins found in milk and tissues (matrices where C-F chemistries have been detected). Furthermore, they impaired the physiological function in these proteins through displacement of physiological ligands or by compromising the binding of co-factors. The neuroblastoma-derived SHSY-5Y cell line insulted with the said C-F moieties displayed altered gene expression corresponding to reactive oxygen species (ROS), protein ubiquitination, inflammation along with compromised cytoskeletal integrity. C-F bond ingestion ablated dopaminergic (DA) neurons in the nematode C. elegans and induced locomotory deficits in a manner mimicking paraquat. Based on these findings, we propose to gather data towards our hypothesis that C-F bond exposure perturbs biomolecular, cellular and organismal assemblies to onset neurodegeneration-linked trajectories. In Aim 1, we will determine whether organic fluoroacids alter mRNA levels in differentiated SHSY-5Y cells and in neuroprotective gut bacteria (Lactobacillus rhamnosus, Bifidobacterium lactis and Lactobacillus acidophilus). We will examine whether the neuroblastoma cell line exposed to C-F chemistry displays readouts designed to inform the onset of neurodegeneration-associated trajectories (including α-synuclein aggregation). In Aim 2, we will further address in a preclinical model whether C-F burden induces protein aggregation (α-synuclein, amyloid β, mHTT), interferes with dopaminergic neuronal assembles and induces locomotory deficits. Completion of the proposed work will complement ongoing experimental biophysical, structural (crystallographic, NMR) and computational (docking, molecular dynamics simulations) mapping of the interactions between these anthropogenic “forever” chemicals and amyloid-forming proteins potentially resulting in a soluble-to-toxic transformation. It will prepare the stage for vertebrate testing. The findings from this relatively understudied area likely exposes interventional targets for C-F chemistry associated neurotoxicity, spurs therapeutic efforts and can also guide the development of more biocompatible alternatives.

Targeting subtype specification as a driver of PDAC health disparities

PROJECT SUMMARY Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease that is refractory to current treatment strategies due in part to adaptive mechanisms of chemoresistance. Racial health disparities also confound the treatment and care of these patients. Blacks (people with African genetic ancestry) have significantly higher incidence rates of PDAC and decreased survival times compared to Caucasians (White genetic ancestry) even after socioeconomic status and tumor stages are controlled. Therefore, it is possible different racial groups exhibit unique molecular characteristics in PDAC tumors that contribute to these health disparities. The unique molecular characteristics that distinguish PDAC tumors between racial groups exhibiting disparities have the potential to identify new therapeutic targets. In a previous study, we identified 4 distinct subtypes of PDAC (Metabolic, Progenitor-like, Proliferative, and Inflammatory) that can be distinguished using multivariate analysis of quantitative proteomic data. While these PDAC subtypes are predictive of therapeutic response, this has not yet been analyzed in disparity factor balanced studies. We have examined the proteomes of primary PDAC tumors using quantitative mass spectrometry and identified unique protein signatures for Blacks and Whites. PDAC tumors from Black patients display features consistent with the Inflammatory subtype of PDAC, which is characterized by an inflamed microenvironment expressing complement proteins that can promote resistance to chemotherapy. Therefore, it is possible that race influences subtype and Blacks could preferentially develop the more aggressive and treatment refractory Inflammatory subtype. Strategies are needed to modulate subtype to improve response to chemotherapy. Toward this goal, our proteomic analysis identified polycomb repressor complex 1 (PRC1) protein RNF2 as being upregulated in PDACs from Blacks compared to Whites. We have also discovered that RNF2 regulates mRNA expression of the PDAC subtype specification factor GATA6 and inhibiting RNF2 promotes a molecular shift toward the more chemosensitive Classical subtype of PDAC. Therapeutic targeting can be achieved with Tazemetostat that inhibits the upstream PRC2 to prevent RNF2 binding the GATA6 promoter leading to its increased expression. Additionally, the Inflammatory subtype characterized by innate immune complement protein activation could be targeted with another FDA approved drug, Avacopan, which has not previously been studied in PDAC. Therefore, the Specific Aims of this proposal are designed to: 1) Evaluate the extent to which Tazemetostat treatment impacts chemotherapy-induced subtype plasticity in patient derived organoids; and 2) To determine the extent to which strategies targeting pathways associated with PDAC disparities affect progression and subtype characteristics in vivo. The successful completion of these aims has the potential to be moved quickly into phase I clinical trials since both Tazemetostat and Avacopan are FDA approved drugs. Furthermore, if successful, this project has the potential to mitigate health disparities in PDAC and broadly improve patient outcomes by implementing new precision interventions. The mouse models we propose faithfully recapitulate pancreatic cancer's clinical syndrome, histopathology and molecular properties, including the often-unique features of the stromal and immune responses that constitute the complex desmoplasia of this disease, which cannot be addressed using in vitro model systems

Optimizing gamma-delta T cell receptor-mediated signaling to improve cancer immunotherapy

PROJECT SUMMARY The recent development of T cell-based cancer immunotherapies, including checkpoint blockade (anti-PD-1, anti-CTLA-4 and others) or adoptive cell therapy (ACT) using modified patient T cells, has led to improved patient outcomes for a variety of cancers. However, durable responses are observed in only a fraction of patients. Further progress can be made by studying and targeting different T cell subpopulations, such as the gd T cells which are known to possess antitumor activities. Further, gd T cells are mostly independent of MHC-restriction, unconstrained by neoantigen burden, preferential homing to peripheral tissues and possess unique properties of T cells as well as natural killer cells making them an extremely attractive cancer immunotherapy target. One way of gd T cell activation involves the gd T cell receptor (gdTCR)-CD3 signaling pathway. gd T cell recognition of antigen by the gdTCR and the resulting proximal signaling through surrounding CD3 subunits are key steps of gd T cell activation. Even though the individual components of the gdTCR-CD3 and abTCR-CD3 complexes remain the same except for the TCRs, the complete gdTCR-CD3 complex extracellular structure is unknown. Identification of the specific extracellular interactions between the gdTCR and CD3 subunits could offer precise guidance for the development of immunotherapeutic strategies that modulate gdT cell immunity by targeting signaling through the gdTCR-CD3 complex. Our previous data showed that mutating residues in the constant domain of the abTCR resulted in altered ab T cell cytokine responses. Based on this data, our hypothesis is that gdTCR-CD3 signaling can also be modulated by targeting specific regions of the gdTCR by mutagenesis to improve gd T cell antitumor activities. To test our hypothesis, in Aim 1, we will use a novel photo-crosslinking and computational docking methodology to solve the complete extracellular structure of a gdTCR-CD3 complex. Further, we will use an in silico structure-based TCR design approach to identify gdTCR mutants that enhance signaling. In Aim 2, we will use an in vitro retroviral TCR display method using degenerate primers to create gdTCR mutant libraries at specific gdTCR sites such as Cg helix 3 and connecting peptide (CP) regions. In both instances, identified mutants will be tested for improved functionalities in an MHC-independent gd TCR (G115 Vg9Vd2 TCR) using in vitro cytokine and tumor-killing assays. Overall, the newly identified enhanced gd T cell clones could potentially lead to a new wave of effective cancer immunotherapy strategy by leaning into the largely untapped potential of gd T cells.

Uncovering genetic determinants of carbapenem resistance in Klebsiella pneumoniae

Carbapenem-resistant Klebsiella pneumoniae represents an urgent global health threat due to its increasing prevalence and high mortality rates, necessitating a comprehensive understanding of its resistance mechanisms. While key resistance mechanisms and their genetic determinants are known, such as beta- lactamases and porin mutations, the cause of resistance in many strains remains elusive. Moreover, other strains that carry known genetic carbapenem-resistance factors have been found to still be susceptible to carbapenems for unclear reasons. Further, strains can carry genetic elements which, while not conferring resistance directly, can promote resistance indirectly by accelerating its acquisition, such as through mutations in DNA repair systems or mobile genetic elements. To address these knowledge gaps, we propose a genome-wide association study (GWAS), with the aim of maximizing the discovery of gene variants associated with meropenem resistance, with experimental validation of candidates to identify true causal variants. We will overcome limitations of prior studies in the following ways: 1) We have compiled an expanded data set of publicly available K. pneumoniae genomes from strains isolated across a wide distribution of countries, with in hand access to >100 isolates upon which experimental validation studies will be performed. 2) We will perform comprehensive capture of genetic variants by employing a reference-free GWAS, utilizing unitigs, stretches of DNA sequence that represent the entire spectrum of genetic variation. 3) We will enhance statistical power to detect genetic variants with even subtle effects on resistance by using a quantitative, continuous minimum inhibitory concentration (MIC) phenotype to meropenem rather than a binary designation of resistant or susceptible. 4) We will reduce the number of false positives arising from correlation, or linkage disequilibrium (LD), with known carbapenemase and other known resistance factors by performing a conditional GWAS, where known factors are included as covariates. 5) We will further mitigate confounding effects due to population structure and LD, which cause non-random relationships between variants, by utilizing a pangenome-wide regression with an elastic net penalty. 6) Crucially, we will functionally validate our findings, which will include genetic variants associated with increased resistance, whether through direct or indirect mechanisms, as well as those that may restore susceptibility in strains already possessing known resistance factors. We will bridge the gap between GWAS findings and functional validation by leveraging our high-throughput experimental capabilities. This integrated approach promises to uncover novel mechanisms of carbapenem resistance, its acquisition, and susceptibility in K. pneumoniae, with the potential to inform the development of future diagnostics or therapeutic strategies.

Bacterial ferrous iron sensing via the BqsRS (CarRS) two-component system

Project Summary Pseudomonas aeruginosa (Pa) is an opportunistic and increasingly antibiotic resistant Gram-negative bacterium that is one of the major causes of chronic nosocomial infections in the United States. The colonization of Pa within a host is often linked to the bioavailability of nutrients, such as iron, and Pa has multiple iron acquisition pathways that allow it to adapt readily to the variety of environments it may encounter within a human host. Pa responds to these dynamic environments commonly through the use of two-component signal transduction systems (TCSs) that are important mediators of signal transduction and allow pathogens to detect chemical and/or physical changes in the environment in order to control basic cellular processes. Previous studies have identified a biofilm and quorum sensing TCS known as BqsRS (also known as CarRS) that regulates biofilm formation and decay in Pa through the sensing of extracytoplasmic Fe2+ and Ca2+. Among its targets, the BqsRS TCS is known to regulate rhlAB and rhlC, critical genes for rhamnolipid production and biofilm formation that are also known to be connected to iron homeostasis and antibiotic resistance. Moreover, the deletion of either bqsR or bqsS in PAO1 results in a significant increase in biofilm formation but reduced biofilm dispersion, the latter of which is important for downstream infections. These observations highlight the importance of the BqsRS TCS to Pa virulence, but there is a foundational lack of understanding regarding the structure, the selectivity, and the mechanism of this system. The ultimate goal of this proposal is to generate a mechanistic and functional understanding of BqsRS at atomic, molecular, and organismal levels in order to exploit this system as a means of reducing or stemming the virulence of opportunistic pathogens such as Pa. The objectives of this exploratory grant are to determine the structural and molecular characteristics of BqsRS, to define how these properties govern BqsRS metal selectivity and function, and to examine a new role of the BqsRS system in regulating the Feo system in P. aeruginosa. Ultimately, the accomplishment of this exploratory grant will deliver fundamental mechanistic insight into a critical metal-sensing TCS and lay the groundwork for future studies that may be designed to target this system and its homologs for additional bacterial exploits.

Structure-Based Development of Nucleotide-Competing Inhibitors Against HIV-1 and LINE-1 Reverse Transcriptases

PROJECT SUMMARY Reverse transcriptases (RTs) from retroviruses and endogenous retroelements are essential polymerases that catalyze RNA- and DNA-dependent DNA synthesis. Nucleoside inhibitors (NIs) remain central to HIV-1 therapy and are also used against other viral infections and in cancer, but toxicity, limited selectivity, pharmacokinetic (PK) liabilities, and the emergence of drug resistance highlight the need for alternative RT inhibitor mechanisms. In contrast to NIs, nucleotide-competing inhibitors (NCIs) block the polymerase active site without requiring incorporation into nucleic acids. Structural studies by PI Ruiz have defined the NCI mechanism of action for HIV- 1 RT and revealed conserved binding modules shared across multiple polymerase families. These advances now enable rational discovery of improved NCIs. LINE-1 (L1) ORF2 RT is an emerging therapeutic target in cancer, autoimmunity, and aging, yet NIs are the only inhibitors known to act against L1 RT. Notably, the NCI-binding region is structurally similar between HIV-1 RT and L1 RT, suggesting that NCI recognition principles may extend across these two biologically distinct polymerases. This R21 seeks to establish proof-of-concept for NCI development against both enzymes. Aim 1 will discover and structurally optimize NCIs targeting HIV-1 RT by combining binding modules from known NCI chemotypes and determining their biochemical activity and co-crystal structures. Aim 2 will determine whether HIV-1 RT NCI principles translate to L1 RT by solving L1 RT/nucleic acid/NCI structures, evaluating enzymatic inhibition, and applying AI-based structure prediction and generative design to propose L1-specific NCI candidates. Cellular retrotransposition assays will test mechanism of action. Aim 3 will develop a fragment library tailored to protein–nucleic acid interfaces and perform fragment screening of HIV-1 and L1 RT/nucleic acid complexes to identify additional chemotypes that engage the NCI binding region. Successful completion will yield NCI scaffolds and mechanistic insights applicable to HIV-1 RT and L1 RT, define structural principles governing NCI recognition across two evolutionarily related polymerases, and establish new avenues for RT inhibitor development. The PI is highly qualified to lead this work, with extensive expertise in RT structural biology, drug design, and fragment-based discovery.

RECONJOINT: A Preference Elicitation Tool to Improve Shared Decision Making for Breast Reconstruction Surgery

PROJECT SUMMARY/ABSTRACT Breast reconstruction is a critical component of comprehensive breast cancer care, offering physical and emotional restoration after mastectomy. However, 40% of women undergoing breast reconstruction report dissatisfaction and decisional regret due to low involvement with treatment decisions and poor alignment between treatment preferences and the chosen reconstructive technique. Current approaches to shared decision-making (SDM) often fail to elicit and integrate individual-level preferences into treatment planning. This serves as a barrier to effective SDM and patient-centered care. To address this gap, we developed a web- based decision tool that uses adaptive choice–based conjoint (ACBC) analysis to elicit patient-level preferences for breast reconstruction. Preliminary studies indicate that the decision tool is acceptable and usable; patients wanted to view their results and use the tool in clinic, which we could not accommodate at the time because the decision tool currently lacks a structured method for clinical integration. We propose to develop an implementation toolkit for the decision tool to facilitate clinical integration and then test the feasibility, acceptability, and implementation of the intervention, RECONJOINT (decision tool and toolkit). In Aim 1, we will design an implementation toolkit informed by focus groups and developed with input from key partners, including patients, providers, and patient advocates. Candidate elements for the implementation toolkit include components developed for site-level implementation: treatment preferences report, video introducing the tool and existing evidence, and recommendations for patients and providers to incorporate preferences into SDM. In Aim 2, we will evaluate the feasibility, acceptability, and preliminary efficacy of the intervention in a pilot cluster-randomized hybrid type 1 trial conducted at two cancer centers (Memorial Sloan Kettering and Duke University). Our primary outcome of interest is the feasibility of the intervention. Secondary outcomes include acceptability and preliminary efficacy. Using a hybrid design, we will simultaneously evaluate facilitators, barriers, and strategies to implementation and how these factors influence the feasibility and acceptability of the intervention. The Consolidated Framework for Implementation Research and the Theoretical Domains Framework will serve as conceptual frameworks. This study is innovative as it leverages ACBC analysis to elicit patient preferences, designs an intervention with multilevel input from clinical and community partners, and uses a hybrid trial design to simultaneously evaluate feasibility, acceptability, preliminary efficacy, and implementation. By addressing critical barriers to SDM and enhancing patient–provider communication, this research aligns with the goals of PA-25-253 and the National Cancer Plan to deliver high quality, patient-centered cancer care. Findings from this study will inform a full-scale multi-site trial to evaluate the efficacy of the intervention and implementation outcomes (e.g., reach).

Structure-function and mechanistic studies of a specific glycosyltransferase complex in fusion-driven pediatric gliomas

Abstract Glycosylation is a co/post-translational modification involved in cell-matrix interactions, antigen-antibody interactions, tumor invasion, and cell motility. Abnormal glycosylation is a hallmark of cancer, with various glycosylation-related genes linked to glioma prognosis and tumor heterogeneity. Pediatric low-grade gliomas (pLGGs) stand as the most common childhood central nervous system tumor, accounting for 30%-40% of all CNS tumors in children. Despite its relatively low mortality rate, pLGGs are associated with devastating lifelong morbidity. The most common alteration found in 75% of tumors is the KIAA1549:BRAF fusion, causing an aberrant activation of the MAPK/ERK signaling pathway. Current treatments, such as traditional chemotherapies and targeted therapies, have limitations such as resistance, lack of specificity, toxicity and paradoxical activation of the MAPK pathway. This highlights the urgent need for novel therapeutic approaches. Investigations into KIAA1549:BRAF-driven pLGGs identified their dependency on the protein-O-mannosyl transferase (POMT) complex for survival. In contrast, BRAFV600E-mutant cells did not show dependency, suggesting the POMT complex as a vulnerability and promising target in KIAA1549:BRAF-driven pLGGs. Therefore, our goal is to characterize the POMT complex structurally and biochemically and study its roles in KIAA1549:BRAF-driven pLGGs. In this proposal, we aim to 1) determine the high-resolution structures of the complex in its unbound, substrate-bound, and inhibitor-bound forms and 2) elucidate the POMT complex mechanisms in KIAA1549:BRAF-driven pLGGs. We will define the critical functional domains, active sites, interaction interfaces and translational modifications crucial for enzymatic activity using cryo-EM techniques, mutagenesis, and functional studies. To study biological pathways and molecular events modulated by the POMT complex, we will implement global proteomics and transcriptomics analysis in well-characterized disease models. In parallel, we will assess the effect of the POMT complex on the MAPK/ERK signaling pathway. This study will guide the structure-based design of probes and drugs targeting the POMT complex and will unveil glycosylation-mediated oncogenesis in pediatric gliomas. It will aid in the development of new targeted therapies and the identification of new biomarkers for pLGGs harboring the KIAA1549:BRAF fusion. The research will be conducted in the Fischer lab at Dana-Farber Cancer Institute, which provides a collaborative and resource-rich environment. The career development plan includes training in scientific writing, mentoring, and presentation skills, as well as interdisciplinary networking with experts in structural biology and pediatric oncology. The candidate’s career goal is to establish an independent research laboratory focused on developing new therapeutic modalities for pediatric neurooncology. The training provided through this fellowship represents a critical step toward achieving this goal.

Dual mRNA Therapeutics for Liver Metastatic Uveal Melanoma

Abstract Uveal melanoma (UM) is the most common primary intraocular cancer in adults, accounting for approximately 70% of all ocular malignancies. Current treatments for primary UM include surgical tumor removal, transpupillary thermotherapy, and radiotherapy. Unfortunately, both surgical enucleation and brachytherapy have shown similar survival outcomes and carry an equivalent risk of metastasis. While the survival rate for patients with primary, non-metastatic UM is relatively high, metastatic uveal melanoma (MUM), especially when it spreads to the liver, remains universally fatal. The liver is the first site of metastasis in 80 to 90 percent of cases, and about 50 percent of UM patients develop liver metastases within 15 years of initial diagnosis. Median survival following liver metastasis is only 5 to 7 months, with an almost zero percent five-year survival rate. Currently, no available therapy significantly improves outcomes for patients with liver MUM. This R21 project addresses this urgent unmet need by developing liver-tropic mRNA therapeutics targeting two key drivers of MUM progression and metastasis: (1) constitutive activation of Gαq/11 caused by single-point mutations, and (2) loss-of-function mutations in BAP1. Both alterations occur in over 80 percent of UM patients and are associated with poor prognosis. We hypothesize that inhibition of constitutively active Gαq/11 and/or restoration of BAP1 tumor suppressor function will significantly suppress MUM progression and improve survival outcomes. Aim 1 focuses on delivering mRNA encoding a novel protein trap designed to specifically inhibit constitutively active Gαq/11 and its downstream oncogenic signaling pathways. Aim 2 seeks to restore wild-type BAP1, which is mutated or lost in approximately 84 percent of MUM cases, through liver-tropic mRNA delivery using a liver MUM model established via splenic inoculation. We will also evaluate the potential synergy between Gαq/11 inhibition and BAP1 restoration. The success of this project will not only advance our understanding of the disease mechanisms underlying MUM but also provide clinically viable strategies for treating liver metastases in uveal melanoma.

2-Deoxyglucose Therapy for Organophosphate Intoxication

Project Summary The main goal of this project is to determine the therapeutic potential of glycolysis inhibition as an adjunct to midazolam therapy in mitigating the long-term neurological effects from acute organophosphate pesticide and nerve agent (OPNA) exposure. Novel countermeasures are desperately needed for effective mitigation of morbidity and long-term effects of OPNAs. A variety of agents targeting glutamate, GABA and oxidative stress have been proposed, but glycolysis inhibitors have not been widely studied in OPNA intoxication. Dysregulated glucose metabolism plays a key role in seizures and neuronal injury following OPNA exposure. 2-Deoxyglucose (2-DG), a selective glycolysis inhibitor, has anticonvulsant and neuroprotection effects and hence can effectively mitigate acute and long-term OPNA neurotoxicity. In this project, we seek to identify the glycolysis inhibition as novel adjunct neuroprotection to midazolam therapy for OPNA exposure, with the goal of identifying 2-DG or related drugs as medical countermeasures. The glycolytic pathway represents a logical target for such intervention because glycolysis controls seizures and neuronal injury by regulating glucose utilization and activity in neurons and astrocytes in the brain. The proposed therapy is based on the hypothesis that acute OPNA neurotoxicity imparts sustained activation of the glycolysis pathway in the brain and therefore, 2- DG and selective glycolysis inhibitors prevents long-term neuronal damage neurological dysfunction. This hypothesis will be tested by using the FDA-approved (2-DG) or clinical-stage glycolytic inhibitors in two distinct OPNA models in rats: (Aim 1) To investigate the protective efficacy of 2-DG and novel glycolysis inhibitors against DFP-induced acute and long-term neuronal damage and neurological dysfunction. (Aim 2) Aim 2 (Year 2). To determine brain penetration, pilot toxicity and pharmacokinetic of 2-DG or other lead drug in naïve and DFP-exposed animals. Test drugs will be evaluated as per the NIH rigor criteria in a dose-related design in male and female rats and behavior/neuropathology will be checked for 3 months post-exposure. 2-DG and test drugs will be given starting 40-min after exposure to ONAs. Three primary outcome measures will be addressed for therapy effectiveness: (i) acute adjunct neuroprotection; (ii) chronic neuroprotectant efficacy; and (iii) prevention of neurological and behavioral deficits. The primary measures of neuroprotection include longitudinal MRI scanning, and extent of neurodegeneration, neuroinflammation, aberrant neurogenesis, and mossy fiber sprouting. Key neurological outcomes include memory deficits, depression, anxiety behavior, and neurological/motor deficits. The outcome of this project will provide “proof-of-efficacy” of a novel glycolytic therapy with FDA-approvable, repurposed drugs with promising potential to limit long-term effects of OPNAs in humans. Thus, the overall impact of the outcome is enormous for civilians, especially in developing a highly effective and safe post-exposure medical countermeasure for chemical nerve agents.

Breaking Tolerance: Trichloroethylene Provides Survival Signals to Autoreactive CD4s in the Liver

PROJECT SUMMARY The industrial solvent and widespread environmental contaminant, trichloroethylene (TCE) has been linked to autoimmune disease in humans. How TCE impairs tolerance (i.e., unresponsiveness) to self-antigens leading to autoimmunity has not been explored. Autoimmune diseases (ADs) are a class of disorders that affect many different organs and tissues. However, all autoimmune diseases share a feature in common which is the ability of potentially pathogenic autoreactive cells to evade deletion. During early life, peripheral CD4+ cells are primarily comprised of recent thymic emigrants (RTE) which home to the liver. The liver is known to efficiently retain and tolerize self-reactive CD4s to where they are functionally unresponsive to their antigen. Thus, the liver is the first checkpoint in the periphery to filter, retain, and enforce tolerance to autoreactive CD4+ RTEs. The liver is also the site of TCE metabolism. Our Aims are designed to test the hypothesis that TCE, through its metabolite TCAH, delivers costimulatory signals to liver CD4 RTEs via CD28, thereby overriding inhibitory CTLA-4 signaling. This disruption promotes the survival of self-reactive CD4 RTEs by impairing CTLA-4-dependent tolerance mechanisms contributing to the development of ADs. This research will significantly advance the fields of toxicology and autoimmunity, where the origins of environmentally induced AD remain poorly understood. Aim 1 will assess TCE’s effects on RTE migration patterns in real-time in transgenic mice. Aim 2 will investigate TCAH-mediated costimulatory signaling in CD4 RTEs in vitro. Successful completion of these studies will determine how TCE alters key tolerance pathways in the liver resulting in a greater proportion of self-reactive effector memory (EM) peripheral CD4s capable of promoting AD.

A PROTAC Strategy to Combat Botulinum Neurotoxicity

PROJECT SUMMARY/ABSTRACT Botulinum neurotoxin (BoNT), the causative agent of botulism, is the most potent toxin known to humans. While BoNTs are widely recognized for their therapeutic and cosmetic applications, such as Botox™, their increasing use has raised concerns about iatrogenic botulism. Due to their extreme lethality, ease of production, and history of weaponization, the Centers for Disease Control and Prevention (CDC) classifies BoNTs as a Category A bioterrorism threat. Among the seven major serotypes (A-G), BoNT/A, BoNT/B, and BoNT/E account for over 95% of human botulism cases with A being the most prevalent. Despite the severity of botulism, no approved therapeutic exists to rescue intoxicated neurons. The current treatment, a heptavalent antitoxin, can only slow disease progression and requires early administration and prolonged hospitalization due to the inability of antibodies to penetrate infected cells. In the field of small- molecule inhibitors (SMIs), promising scaffolds targeting BoNT/A have been discovered, offering opportunities for further derivatization to incorporate bifunctional approaches. Developing a clinically viable therapeutic requires inhibiting the zinc (Zn2+) metalloprotease light chain (LC) as well as addressing toxin persistence. Through extensive inhibitor screening, we have identified two classes of small molecules that inhibit BoNT/A with submicromolar affinity and demonstrate efficacy in both cellular and animal models. However, the transient nature of these inhibitors necessitates the need of a sustained clearance approach. To achieve this, we propose integrating our previously identified BoNT/A LC SMIs with a targeted protein degradation (TPD) technology for toxin elimination. Based upon the background outlined, vide supra, our research strategy for the ablation of BoNT/A will be focused upon the following three specific objectives: 1) Structural Optimization – Utilize molecular docking, and structure-activity relationship (SAR) analysis to modify inhibitors for TPD ligand attachment. 2) Degrader Design – Development of ubiquitin-protease system (UPS)-based proteolysis-targeting chimeras (PROTACs) and autophagy-targeting chimeras to enhance degradation efficiency. 3) Cellular Evaluation – Assess enzyme inhibition, toxin clearance, degradation kinetics in cells.

Implementing a New Paradigm for Antifungal Drug Development

About 30% of the drugs currently in clinical use function through covalent modification of their target. Yet, until recently, none of these covalent drugs were specifically designed to utilize this irreversible mode of action. It is our hypothesis that the production of a new class of covalent inactivators, designed to selectively modify new drug targets, will lead to novel agents with efficacy against both native and drug-resistant pathogenic fungal species. Because of their novelty these agents will also offer a greater opportunity to bypass the existing mechanisms of drug resistance. Pathogenic fungal infections remain among the leading causes of human mortality, and this threat is rising due to the increasing prevalence of drug- resistance strains and the paucity of effective antifungal drugs against the more virulent fungal species. Our proposed new drug target is an enzyme that plays a critical role in a uniquely microbial pathway that is essential for the survival of fungal organisms. To test our hypothesis and achieve the goals of this project we plan to complete the following specific aims during the initial R21 phase of this project: (1) Optimization of the potency of novel enzyme inactivators. Our goals here are to use our strong preliminary results to address critical barriers that must be overcome to convert potent enzyme inactivators into advanced drug candidates, thereby achieving higher target selectivity and increasing compound reactivity once bound to the target; (2) Enhance the antifungal capability of these enzyme inactivators. Our strategy for this aim is focused on the incorporation of conjugate partners into this new class of covalent inactivators, enabling them to potentially utilize the existing nutrient uptake systems to achieve toxic levels in Candida species; (3) Examine the target selectivity of our new antifungal agents. Results from fungal growth inhibition and fungal killing assays will be used to evaluate and rank the efficacy of our compounds against both wild-type and drug-resistant Candida strains. Specific milestones are presented to evaluate our achievement of these initial aims. Once accomplished we will immediately proceed to the R33 phase of this project, with the aims of: (4) Pharmacological evaluation of lead candidates, though ranking the drug candidates based on their ADME, pharmacokinetic and toxicity properties; and then (5) Evaluate the efficacy of our candidates against pathogenic fungal infections. A systematic infection animal model will be utilized for candidate screening to identify the best agents against disseminated fungal infections, followed by further efficacy screening in an oral infection model. Completion of these aims will produce, refine and evaluate a new class of antifungal agents with a novel mode of action against an unexplored but essential fungal target. The agents with the most promising drug profiles will then be moved into advanced preclinical trials used to select the most effective new antifungal agents.

Noninvasive Neuromodulation to Improve Hand Motor Function in Multiple Sclerosis

Project Summary/Abstract Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating, and degenerative disease that affects nearly one million Americans. Although more than 75% of persons with MS (PwMS) experience hand motor impairments that reduce independence and quality of life, current treatments primarily aim to slow disease progression through pharmacological approaches and rehabilitation and often do not improve motor function. Recent evidence shows that reduced corticospinal transmission is strongly associated with motor impairment severity in PwMS, highlighting the need for targeted strategies to strengthen residual corticospinal pathways. Therefore, this project aims to evaluate the therapeutic potential of paired corticospinal-motoneuronal stimulation (PCMS) in improving hand dexterity in PwMS. PCMS, a noninvasive mechanism-driven neuromodulation approach, enhances corticospinal transmission by producing long-term potentiation-like effects at the corticospinal-motoneuronal synapse by precisely pairing transcranial magnetic stimulation (TMS) with peripheral nerve stimulation (PNS). This project first aims to examine the effects of a single PCMS session on corticospinal transmission and hand motor function in PwMS. Using a randomized, crossover design, 25 PwMS will complete two sessions: (1) PCMS and (2) sham-PCMS. Each session will deliver 180 paired TMS-PNS stimuli over 30 minutes. The primary outcome is performance on the 9-Hole Peg Test (9HPT). Secondary outcomes include pinch grip force, maximal voluntary contraction (MVC), MEP amplitude and latency, F-wave parameters, and M- max amplitude. It is hypothesized that PCMS will enhance corticospinal transmission and improve hand motor performance compared to sham stimulation. Second, this project will examine the effects of PCMS combined with hand motor training in PwMS. Forty-eight PwMS will be randomized to receive either PCMS or sham-PCMS combined with motor training over 10 sessions in 3–4 weeks. Outcomes will be assessed at baseline, post- intervention, and one-month follow-up. It is hypothesized that PCMS participants receiving PCMS with motor training to show greater functional gains than those receiving sham-PCMS with motor training and the functional gains will be better maintained in the PCMS with motor training group at follow-up. This project is the first to apply PCMS in PwMS, leveraging a noninvasive neuromodulation strategy to specifically enhance corticospinal output for improving manual dexterity. Findings will establish proof-of-concept for this intervention in PwMS and guide future studies optimizing stimulation protocols and evaluating clinical efficacy on a larger scale. Ultimately, this work may lead to a new therapeutic approach to improve dexterity, independence, and quality of life for people living with MS.

Glycoengineering core a(1,3)-fucose motifs to enhance HIV-1 envelope vaccine immunogenicity

Project Summary The HIV-1 envelope glycoprotein (Env) is the sole target of neutralizing antibodies (NAbs). We previously developed a vaccine platform integrating three innovations: (1) the uncleaved prefusion-optimized (UFO) trimer design to stabilize Env; (2) multilayered single-component self-assembling protein nanoparticles (1c-SApNPs) for multivalent trimer display; and (3) enzymatic trimming of oligomannose glycans on CHO cell-produced Env immunogens. Glycan trimming substantially improved Env immunogenicity by enhancing tier 2 NAb elicitation, reducing off-target responses to immunodominant glycan sites, and increasing responder rates. These vaccine candidates are now in phase 1 clinical trials (NCT06541093; NCT06905275). Building on this foundation, we propose a novel strategy to enhance immunogenicity by incorporating core α(1,3)-fucose into HIV-1 Env. Core α(1,3)-fucose, a key allergenic epitope in many plant and insect glycoproteins, is highly immunogenic in humans and other mammals. Our central hypothesis is that the targeted introduction of core α(1,3)-fucose will convert the glycan shield from an immune-evasive barrier into an immunogenic trigger that promotes NAb induction. Glycoengineered cell lines expressing α(1,3)-fucose will enable production of highly immunogenic Env vaccines suitable for preclinical and clinical testing. Importantly, particulate display of these Env trimers on 1c-SApNPs can suppress IgE-mediated allergic pathways by inducing high-affinity protective IgGs, ensuring vaccine safety. Aim 1 will focus on producing core α(1,3)-fucosylated HIV-1 Env immunogens. We will begin by developing a transient insect cell expression system using BTI-TN-5B1-4 (“High Five” or Hi5) cells to produce Env with short paucimannose glycans bearing native α(1,3)-fucose. To further enhance α(1,3)-fucosylation, we will co-express exogenous core α(1,3)-fucosyltransferases in insect and CHO cells. We will validate glycan profiles and characterize the biochemical, biophysical, structural, and antigenic properties of the resulting immunogens. Aim 2 will assess the immunogenicity of these glycoengineered HIV-1 Env immunogens. Using our previously established glycan-trimmed Env immunogens as benchmarks, we will immunize mice, rabbits, and nonhuman primates (NHPs). Mice will be used for early-stage immunogen and adjuvant screening; rabbits to evaluate glycan hole-targeting NAb responses; and key vaccine formulations will advance to NHP studies. We will assess autologous and heterologous tier 2 NAb responses and vaccine responder rates. Aim 3 will elucidate the functional, structural, repertoire, and mechanistic basis of vaccine-induced immunity. We will isolate NAbs via Env-specific single-cell sorting and antibody cloning, map epitopes by electron microscopy (EM) and X-ray crystallography, perform next-generation sequencing (NGS) of B-cell repertoires, and trace NAb lineages. Finally, we will investigate antigen trafficking, retention, presentation, and germinal center (GC) reactions in lymph nodes. Together, these studies will define a new class of glycoengineered HIV-1 vaccines and establish core α(1,3)-fucose as a novel immunomodulatory tool to overcome glycan shield-mediated immune evasion.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

Enhancing Real-World Event Memory

Memory is essential for shaping how we interpret the world, plan for the future, and understand ourselves, yet effective cognitive interventions for real-world episodic memory loss remain scarce. This talk introduces HippoCamera, a smartphone-based intervention inspired by how the brain supports memory, designed to enhance real-world episodic recollection by replaying high-fidelity autobiographical cues. It will showcase how our approach improves memory, mood, and hippocampal activity while uncovering links between memory distinctiveness, well-being, and the perception of time.

Screen Savers : Protecting adolescent mental health in a digital world

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

Using Adversarial Collaboration to Harness Collective Intelligence

There are many mysteries in the universe. One of the most significant, often considered the final frontier in science, is understanding how our subjective experience, or consciousness, emerges from the collective action of neurons in biological systems. While substantial progress has been made over the past decades, a unified and widely accepted explanation of the neural mechanisms underpinning consciousness remains elusive. The field is rife with theories that frequently provide contradictory explanations of the phenomenon. To accelerate progress, we have adopted a new model of science: adversarial collaboration in team science. Our goal is to test theories of consciousness in an adversarial setting. Adversarial collaboration offers a unique way to bolster creativity and rigor in scientific research by merging the expertise of teams with diverse viewpoints. Ideally, we aim to harness collective intelligence, embracing various perspectives, to expedite the uncovering of scientific truths. In this talk, I will highlight the effectiveness (and challenges) of this approach using selected case studies, showcasing its potential to counter biases, challenge traditional viewpoints, and foster innovative thought. Through the joint design of experiments, teams incorporate a competitive aspect, ensuring comprehensive exploration of problems. This method underscores the importance of structured conflict and diversity in propelling scientific advancement and innovation.

Neuronal population interactions between brain areas

Most brain functions involve interactions among multiple, distinct areas or nuclei. Yet our understanding of how populations of neurons in interconnected brain areas communicate is in its infancy. Using a population approach, we found that interactions between early visual cortical areas (V1 and V2) occur through a low-dimensional bottleneck, termed a communication subspace. In this talk, I will focus on the statistical methods we have developed for studying interactions between brain areas. First, I will describe Delayed Latents Across Groups (DLAG), designed to disentangle concurrent, bi-directional (i.e., feedforward and feedback) interactions between areas. Second, I will describe an extension of DLAG applicable to three or more areas, and demonstrate its utility for studying simultaneous Neuropixels recordings in areas V1, V2, and V3. Our results provide a framework for understanding how neuronal population activity is gated and selectively routed across brain areas.

Current and future trends in neuroimaging

With the advent of several different fMRI analysis tools and packages outside of the established ones (i.e., SPM, AFNI, and FSL), today's researcher may wonder what the best practices are for fMRI analysis. This talk will discuss some of the recent trends in neuroimaging, including design optimization and power analysis, standardized analysis pipelines such as fMRIPrep, and an overview of current recommendations for how to present neuroimaging results. Along the way we will discuss the balance between Type I and Type II errors with different correction mechanisms (e.g., Threshold-Free Cluster Enhancement and Equitable Thresholding and Clustering), as well as considerations for working with large open-access databases.

Doubting the neurofeedback double-blind do participants have residual awareness of experimental purposes in neurofeedback studies?

Neurofeedback provides a feedback display which is linked with on-going brain activity and thus allows self-regulation of neural activity in specific brain regions associated with certain cognitive functions and is considered a promising tool for clinical interventions. Recent reviews of neurofeedback have stressed the importance of applying the “double-blind” experimental design where critically the patient is unaware of the neurofeedback treatment condition. An important question then becomes; is double-blind even possible? Or are subjects aware of the purposes of the neurofeedback experiment? – this question is related to the issue of how we assess awareness or the absence of awareness to certain information in human subjects. Fortunately, methods have been developed which employ neurofeedback implicitly, where the subject is claimed to have no awareness of experimental purposes when performing the neurofeedback. Implicit neurofeedback is intriguing and controversial because it runs counter to the first neurofeedback study, which showed a link between awareness of being in a certain brain state and control of the neurofeedback-derived brain activity. Claiming that humans are unaware of a specific type of mental content is a notoriously difficult endeavor. For instance, what was long held as wholly unconscious phenomena, such as dreams or subliminal perception, have been overturned by more sensitive measures which show that degrees of awareness can be detected. In this talk, I will discuss whether we will critically examine the claim that we can know for certain that a neurofeedback experiment was performed in an unconscious manner. I will present evidence that in certain neurofeedback experiments such as manipulations of attention, participants display residual degrees of awareness of experimental contingencies to alter their cognition.

Bernstein Student Workshop Series

The Bernstein Student Workshop Series is an initiative of the student members of the Bernstein Network. It provides a unique opportunity to enhance the technical exchange on a peer-to-peer basis. The series is motivated by the idea of bridging the gap between theoretical and experimental neuroscience by bringing together methodological expertise in the network. Unlike conventional workshops, a talented junior scientist will first give a tutorial about a specific theoretical or experimental technique, and then give a talk about their own research to demonstrate how the technique helps to address neuroscience questions. The workshop series is designed to cover a wide range of theoretical and experimental techniques and to elucidate how different techniques can be applied to answer different types of neuroscience questions. Combining the technical tutorial and the research talk, the workshop series aims to promote knowledge sharing in the community and enhance in-depth discussions among students from diverse backgrounds.

Walk the talk: concrete actions to promote diversity in neuroscience in Latin America

Building upon the webinar "What are the main barriers to succeed in brain sciences in Latin America?" (February 2021) and the paper "Addressing the opportunity gap in the Latin American neuroscience community" (Silva, A., Iyer, K., Cirulli, F. et al. Nat Neurosci August 2022), this ALBA-IBRO Webinar is the next chapter in our journey towards fostering inclusivity and diversity in neuroscience in Latin America. The webinar is designed to go beyond theoretical discussions and provide tangible solutions. We will showcase 3-4 best practice case studies, shining a spotlight on real-life actions and campaigns implemented at the institutional level, be it within government bodies, universities, or other organisations. Our goal is to empower neuroscientists across Latin America by equipping them with practical knowledge they can apply in their own institutions and countries.

Bernstein Student Workshop Series

The Bernstein Student Workshop Series is an initiative of the student members of the Bernstein Network. It provides a unique opportunity to enhance the technical exchange on a peer-to-peer basis. The series is motivated by the idea of bridging the gap between theoretical and experimental neuroscience by bringing together methodological expertise in the network. Unlike conventional workshops, a talented junior scientist will first give a tutorial about a specific theoretical or experimental technique, and then give a talk about their own research to demonstrate how the technique helps to address neuroscience questions. The workshop series is designed to cover a wide range of theoretical and experimental techniques and to elucidate how different techniques can be applied to answer different types of neuroscience questions. Combining the technical tutorial and the research talk, the workshop series aims to promote knowledge sharing in the community and enhance in-depth discussions among students from diverse backgrounds.

Dynamic endocrine modulation of the nervous system

Sex hormones are powerful neuromodulators of learning and memory. In rodents and nonhuman primates estrogen and progesterone influence the central nervous system across a range of spatiotemporal scales. Yet, their influence on the structural and functional architecture of the human brain is largely unknown. Here, I highlight findings from a series of dense-sampling neuroimaging studies from my laboratory designed to probe the dynamic interplay between the nervous and endocrine systems. Individuals underwent brain imaging and venipuncture every 12-24 hours for 30 consecutive days. These procedures were carried out under freely cycling conditions and again under a pharmacological regimen that chronically suppresses sex hormone production. First, resting state fMRI evidence suggests that transient increases in estrogen drive robust increases in functional connectivity across the brain. Time-lagged methods from dynamical systems analysis further reveals that these transient changes in estrogen enhance within-network integration (i.e. global efficiency) in several large-scale brain networks, particularly Default Mode and Dorsal Attention Networks. Next, using high-resolution hippocampal subfield imaging, we found that intrinsic hormone fluctuations and exogenous hormone manipulations can rapidly and dynamically shape medial temporal lobe morphology. Together, these findings suggest that neuroendocrine factors influence the brain over short and protracted timescales.

Bernstein Student Workshop Series

The Bernstein Student Workshop Series is an initiative of the student members of the Bernstein Network. It provides a unique opportunity to enhance the technical exchange on a peer-to-peer basis. The series is motivated by the idea of bridging the gap between theoretical and experimental neuroscience by bringing together methodological expertise in the network. Unlike conventional workshops, a talented junior scientist will first give a tutorial about a specific theoretical or experimental technique, and then give a talk about their own research to demonstrate how the technique helps to address neuroscience questions. The workshop series is designed to cover a wide range of theoretical and experimental techniques and to elucidate how different techniques can be applied to answer different types of neuroscience questions. Combining the technical tutorial and the research talk, the workshop series aims to promote knowledge sharing in the community and enhance in-depth discussions among students from diverse backgrounds.

Relations and Predictions in Brains and Machines

Humans and animals learn and plan with flexibility and efficiency well beyond that of modern Machine Learning methods. This is hypothesized to owe in part to the ability of animals to build structured representations of their environments, and modulate these representations to rapidly adapt to new settings. In the first part of this talk, I will discuss theoretical work describing how learned representations in hippocampus enable rapid adaptation to new goals by learning predictive representations, while entorhinal cortex compresses these predictive representations with spectral methods that support smooth generalization among related states. I will also cover recent work extending this account, in which we show how the predictive model can be adapted to the probabilistic setting to describe a broader array of generalization results in humans and animals, and how entorhinal representations can be modulated to support sample generation optimized for different behavioral states. In the second part of the talk, I will overview some of the ways in which we have combined many of the same mathematical concepts with state-of-the-art deep learning methods to improve efficiency and performance in machine learning applications like physical simulation, relational reasoning, and design.

Analogical Reasoning and Generalization for Interactive Task Learning in Physical Machines

Humans are natural teachers; learning through instruction is one of the most fundamental ways that we learn. Interactive Task Learning (ITL) is an emerging research agenda that studies the design of complex intelligent robots that can acquire new knowledge through natural human teacher-robot learner interactions. ITL methods are particularly useful for designing intelligent robots whose behavior can be adapted by humans collaborating with them. In this talk, I will summarize our recent findings on the structure that human instruction naturally has and motivate an intelligent system design that can exploit their structure. The system – AILEEN – is being developed using the common model of cognition. Architectures that implement the Common Model of Cognition - Soar, ACT-R, and Sigma - have a prominent place in research on cognitive modeling as well as on designing complex intelligent agents. However, they miss a critical piece of intelligent behavior – analogical reasoning and generalization. I will introduce a new memory – concept memory – that integrates with a common model of cognition architecture and supports ITL.

How Children Design by Analogy: The Role of Spatial Thinking

Analogical reasoning is a common reasoning tool for learning and problem-solving. Existing research has extensively studied children’s reasoning when comparing, or choosing from ready-made analogies. Relatively less is known about how children come up with analogies in authentic learning environments. Design education provides a suitable context to investigate how children generate analogies for creative learning purposes. Meanwhile, the frequent use of visual analogies in design provides an additional opportunity to understand the role of spatial reasoning in design-by-analogy. Spatial reasoning is one of the most studied human cognitive factors and is critical to the learning of science, technology, engineering, arts, and mathematics (STEAM). There is growing interest in exploring the interplay between analogical reasoning and spatial reasoning. In this talk, I will share qualitative findings from a case study, where a class of 11-to-12-year-olds in the Netherlands participated in a biomimicry design project. These findings illustrate (1) practical ways to support children’s analogical reasoning in the ideation process and (2) the potential role of spatial reasoning as seen in children mapping form-function relationships in nature analogically and adaptively to those in human designs.

A specialized role for entorhinal attractor dynamics in combining path integration and landmarks during navigation

During navigation, animals estimate their position using path integration and landmarks. In a series of two studies, we used virtual reality and electrophysiology to dissect how these inputs combine to generate the brain’s spatial representations. In the first study (Campbell et al., 2018), we focused on the medial entorhinal cortex (MEC) and its set of navigationally-relevant cell types, including grid cells, border cells, and speed cells. We discovered that attractor dynamics could explain an array of initially puzzling MEC responses to virtual reality manipulations. This theoretical framework successfully predicted both MEC grid cell responses to additional virtual reality manipulations, as well as mouse behavior in a virtual path integration task. In the second study (Campbell*, Attinger* et al., 2021), we asked whether these principles generalize to other navigationally-relevant brain regions. We used Neuropixels probes to record thousands of neurons from MEC, primary visual cortex (V1), and retrosplenial cortex (RSC). In contrast to the prevailing view that “everything is everywhere all at once,” we identified a unique population of MEC neurons, overlapping with grid cells, that became active with striking spatial periodicity while head-fixed mice ran on a treadmill in darkness. These neurons exhibited unique cue-integration properties compared to other MEC, V1, or RSC neurons: they remapped more readily in response to conflicts between path integration and landmarks; they coded position prospectively as opposed to retrospectively; they upweighted path integration relative to landmarks in conditions of low visual contrast; and as a population, they exhibited a lower-dimensional activity structure. Based on these results, our current view is that MEC attractor dynamics play a privileged role in resolving conflicts between path integration and landmarks during navigation. Future work should include carefully designed causal manipulations to rigorously test this idea, and expand the theoretical framework to incorporate notions of uncertainty and optimality.

Children-Agent Interaction For Assessment and Rehabilitation: From Linguistic Skills To Mental Well-being

Socially Assistive Robots (SARs) have shown great potential to help children in therapeutic and healthcare contexts. SARs have been used for companionship, learning enhancement, social and communication skills rehabilitation for children with special needs (e.g., autism), and mood improvement. Robots can be used as novel tools to assess and rehabilitate children’s communication skills and mental well-being by providing affordable and accessible therapeutic and mental health services. In this talk, I will present the various studies I have conducted during my PhD and at the Cambridge Affective Intelligence and Robotics Lab to explore how robots can help assess and rehabilitate children’s communication skills and mental well-being. More specifically, I will provide both quantitative and qualitative results and findings from (i) an exploratory study with children with autism and global developmental disorders to investigate the use of intelligent personal assistants in therapy; (ii) an empirical study involving children with and without language disorders interacting with a physical robot, a virtual agent, and a human counterpart to assess their linguistic skills; (iii) an 8-week longitudinal study involving children with autism and language disorders who interacted either with a physical or a virtual robot to rehabilitate their linguistic skills; and (iv) an empirical study to aid the assessment of mental well-being in children. These findings can inform and help the child-robot interaction community design and develop new adaptive robots to help assess and rehabilitate linguistic skills and mental well-being in children.

When to stop immune checkpoint inhibitor for malignant melanoma? Challenges in emulating target trials

Observational data have become a popular source of evidence for causal effects when no randomized controlled trial exists, or to supplement information provided by those. In practice, a wide range of designs and analytical choices exist, and one recent approach relies on the target trial emulation framework. This framework is particularly well suited to mimic what could be obtained in a specific randomized controlled trial, while avoiding time-related selection biases. In this abstract, we present how this framework could be useful to emulate trials in malignant melanoma, and the challenges faced when planning such a study using longitudinal observational data from a cohort study. More specifically, two questions are envisaged: duration of immune checkpoint inhibitors, and trials comparing treatment strategies for BRAF V600-mutant patients (targeted therapy as 1st line, followed by immunotherapy as 2nd line, vs. immunotherapy as 2nd line followed by targeted therapy as 1st line). Using data from 1027 participants to the MELBASE cohort, we detail the results for the emulation of a trial where immune checkpoint inhibitor would be stopped at 6 months vs. continued, in patients in response or with stable disease.

Meta-learning functional plasticity rules in neural networks

Synaptic plasticity is known to be a key player in the brain’s life-long learning abilities. However, due to experimental limitations, the nature of the local changes at individual synapses and their link with emerging network-level computations remain unclear. I will present a numerical, meta-learning approach to deduce plasticity rules from either neuronal activity data and/or prior knowledge about the network's computation. I will first show how to recover known rules, given a human-designed loss function in rate networks, or directly from data, using an adversarial approach. Then I will present how to scale-up this approach to recurrent spiking networks using simulation-based inference.

Maths, AI and Neuroscience Meeting Stockholm

To understand brain function and develop artificial general intelligence it has become abundantly clear that there should be a close interaction among Neuroscience, machine learning and mathematics. There is a general hope that understanding the brain function will provide us with more powerful machine learning algorithms. On the other hand advances in machine learning are now providing the much needed tools to not only analyse brain activity data but also to design better experiments to expose brain function. Both neuroscience and machine learning explicitly or implicitly deal with high dimensional data and systems. Mathematics can provide powerful new tools to understand and quantify the dynamics of biological and artificial systems as they generate behavior that may be perceived as intelligent.

Experimental Neuroscience Bootcamp

This course provides a fundamental foundation in the modern techniques of experimental neuroscience. It introduces the essentials of sensors, motor control, microcontrollers, programming, data analysis, and machine learning by guiding students through the “hands on” construction of an increasingly capable robot. In parallel, related concepts in neuroscience are introduced as nature’s solution to the challenges students encounter while designing and building their own intelligent system.

Self-direction in daily stress management: the solution for mental health issues

In the lecture Yvette Roke and Jamie Hoefakker will discuss the positive and negative effects of daily stress on mental health. They will also highlight which characteristics are likely to cause more stress related issues, and why recovery time is very important. They will give an understanding of autism spectrum disorder (ASD) in relation to daily stress and they will discuss the app, SAM the stress autism mate, developed and investigated (SCED design) in co-creation with their patients with ASD.

Learning by Analogy in Mathematics

Analogies between old and new concepts are common during classroom instruction. While previous studies of transfer focus on how features of initial learning guide later transfer to new problem solving, less is known about how to best support analogical transfer from previous learning while children are engaged in new learning episodes. Such research may have important implications for teaching and learning in mathematics, which often includes analogies between old and new information. Some existing research promotes supporting learners' explicit connections across old and new information within an analogy. In this talk, I will present evidence that instructors can invite implicit analogical reasoning through warm-up activities designed to activate relevant prior knowledge. Warm-up activities "close the transfer space" between old and new learning without additional direct instruction.

Beyond Biologically Plausible Spiking Networks for Neuromorphic Computing

Biologically plausible spiking neural networks (SNNs) are an emerging architecture for deep learning tasks due to their energy efficiency when implemented on neuromorphic hardware. However, many of the biological features are at best irrelevant and at worst counterproductive when evaluated in the context of task performance and suitability for neuromorphic hardware. In this talk, I will present an alternative paradigm to design deep learning architectures with good task performance in real-world benchmarks while maintaining all the advantages of SNNs. We do this by focusing on two main features – event-based computation and activity sparsity. Starting from the performant gated recurrent unit (GRU) deep learning architecture, we modify it to make it event-based and activity-sparse. The resulting event-based GRU (EGRU) is extremely efficient for both training and inference. At the same time, it achieves performance close to conventional deep learning architectures in challenging tasks such as language modelling, gesture recognition and sequential MNIST.

Algorithm-Hardware Co-design for Efficient and Robust Spiking Neural Networks

Real-world scene perception and search from foveal to peripheral vision

A high-resolution central fovea is a prominent design feature of human vision. But how important is the fovea for information processing and gaze guidance in everyday visual-cognitive tasks? Following on from classic findings for sentence reading, I will present key results from a series of eye-tracking experiments in which observers had to search for a target object within static or dynamic images of real-world scenes. Gaze-contingent scotomas were used to selectively deny information processing in the fovea, parafovea, or periphery. Overall, the results suggest that foveal vision is less important and peripheral vision is more important for scene perception and search than previously thought. The importance of foveal vision was found to depend on the specific requirements of the task. Moreover, the data support a central-peripheral dichotomy in which peripheral vision selects and central vision recognizes.

Designing the BEARS (Both Ears) Virtual Reality Training Package to Improve Spatial Hearing in Young People with Bilateral Cochlear Implant

Results: the main areas which were modified based on participatory feedback were the variety of immersive scenarios to cover a range of ages and interests, the number of levels of complexity to ensure small improvements were measured, the feedback and reward schemes to ensure positive reinforcement, and specific provision for participants with balance issues, who had difficulties when using head-mounted displays. The effectiveness of the finalised BEARS suite will be evaluated in a large-scale clinical trial. We have added in additional login options for other members of the family and based on patient feedback we have improved the accompanying reward schemes. Conclusions: Through participatory design we have developed a training package (BEARS) for young people with bilateral cochlear implants. The training games are appropriate for use by the study population and ultimately should lead to patients taking control of their own management and reducing the reliance upon outpatient-based rehabilitation programmes. Virtual reality training provides a more relevant and engaging approach to rehabilitation for young people.

Setting network states via the dynamics of action potential generation

To understand neural computation and the dynamics in the brain, we usually focus on the connectivity among neurons. In contrast, the properties of single neurons are often thought to be negligible, at least as far as the activity of networks is concerned. In this talk, I will contradict this notion and demonstrate how the biophysics of action-potential generation can have a decisive impact on network behaviour. Our recent theoretical work shows that, among regularly firing neurons, the somewhat unattended homoclinic type (characterized by a spike onset via a saddle homoclinic orbit bifurcation) particularly stands out: First, spikes of this type foster specific network states - synchronization in inhibitory and splayed-out/frustrated states in excitatory networks. Second, homoclinic spikes can easily be induced by changes in a variety of physiological parameters (like temperature, extracellular potassium, or dendritic morphology). As a consequence, such parameter changes can even induce switches in network states, solely based on a modification of cellular voltage dynamics. I will provide first experimental evidence and discuss functional consequences of homoclinic spikes for the design of efficient pattern-generating motor circuits in insects as well as for mammalian pathologies like febrile seizures. Our analysis predicts an interesting role for homoclinic action potentials as an integral part of brain dynamics in both health and disease.

General purpose event-based architectures for deep learning

Biologically plausible spiking neural networks (SNNs) are an emerging architecture for deep learning tasks due to their energy efficiency when implemented on neuromorphic hardware. However, many of the biological features are at best irrelevant and at worst counterproductive when evaluated in the context of task performance and suitability for neuromorphic hardware. In this talk, I will present an alternative paradigm to design deep learning architectures with good task performance in real-world benchmarks while maintaining all the advantages of SNNs. We do this by focusing on two main features -- event-based computation and activity sparsity. Starting from the performant gated recurrent unit (GRU) deep learning architecture, we modify it to make it event-based and activity-sparse. The resulting event-based GRU (EGRU) is extremely efficient for both training and inference. At the same time, it achieves performance close to conventional deep learning architectures in challenging tasks such as language modelling, gesture recognition and sequential MNIST

The Secret Bayesian Life of Ring Attractor Networks

Efficient navigation requires animals to track their position, velocity and heading direction (HD). Some animals’ behavior suggests that they also track uncertainties about these navigational variables, and make strategic use of these uncertainties, in line with a Bayesian computation. Ring-attractor networks have been proposed to estimate and track these navigational variables, for instance in the HD system of the fruit fly Drosophila. However, such networks are not designed to incorporate a notion of uncertainty, and therefore seem unsuited to implement dynamic Bayesian inference. Here, we close this gap by showing that specifically tuned ring-attractor networks can track both a HD estimate and its associated uncertainty, thereby approximating a circular Kalman filter. We identified the network motifs required to integrate angular velocity observations, e.g., through self-initiated turns, and absolute HD observations, e.g., visual landmark inputs, according to their respective reliabilities, and show that these network motifs are present in the connectome of the Drosophila HD system. Specifically, our network encodes uncertainty in the amplitude of a localized bump of neural activity, thereby generalizing standard ring attractor models. In contrast to such standard attractors, however, proper Bayesian inference requires the network dynamics to operate in a regime away from the attractor state. More generally, we show that near-Bayesian integration is inherent in generic ring attractor networks, and that their amplitude dynamics can account for close-to-optimal reliability weighting of external evidence for a wide range of network parameters. This only holds, however, if their connection strengths allow the network to sufficiently deviate from the attractor state. Overall, our work offers a novel interpretation of ring attractor networks as implementing dynamic Bayesian integrators. We further provide a principled theoretical foundation for the suggestion that the Drosophila HD system may implement Bayesian HD tracking via ring attractor dynamics.

Learning with less labels for medical image segmentation

Accurate segmentation of medical images is a key step in developing Computer-Aided Diagnosis (CAD) and automating various clinical tasks such as image-guided interventions. The success of state-of-the-art methods for medical image segmentation is heavily reliant upon the availability of a sizable amount of labelled data. If the required quantity of labelled data for learning cannot be reached, the technology turns out to be fragile. The principle of consensus tells us that as humans, when we are uncertain how to act in a situation, we tend to look to others to determine how to respond. In this webinar, Dr Mehrtash Harandi will show how to model the principle of consensus to learn to segment medical data with limited labelled data. In doing so, we design multiple segmentation models that collaborate with each other to learn from labelled and unlabelled data collectively.

Exploration-Based Approach for Computationally Supported Design-by-Analogy

Engineering designers practice design-by-analogy (DbA) during concept generation to retrieve knowledge from external sources or memory as inspiration to solve design problems. DbA is a tool for innovation that involves retrieving analogies from a source domain and transferring the knowledge to a target domain. While DbA produces innovative results, designers often come up with analogies by themselves or through serendipitous, random encounters. Computational support systems for searching analogies have been developed to facilitate DbA in systematic design practice. However, many systems have focused on a query-based approach, in which a designer inputs a keyword or a query function and is returned a set of algorithmically determined stimuli. In this presentation, a new analogical retrieval process that leverages a visual interaction technique is introduced. It enables designers to explore a space of analogies, rather than be constrained by what’s retrieved by a query-based algorithm. With an exploration-based DbA tool, designers have the potential to uncover more useful and unexpected inspiration for innovative design solutions.

Pynapple: a light-weight python package for neural data analysis - webinar + tutorial

In systems neuroscience, datasets are multimodal and include data-streams of various origins: multichannel electrophysiology, 1- or 2-p calcium imaging, behavior, etc. Often, the exact nature of data streams are unique to each lab, if not each project. Analyzing these datasets in an efficient and open way is crucial for collaboration and reproducibility. In this combined webinar and tutorial, Adrien Peyrache and Guillaume Viejo will present Pynapple, a Python-based data analysis pipeline for systems neuroscience. Designed for flexibility and versatility, Pynapple allows users to perform cross-modal neural data analysis via a common programming approach which facilitates easy sharing of both analysis code and data.

Pynapple: a light-weight python package for neural data analysis - webinar + tutorial

In systems neuroscience, datasets are multimodal and include data-streams of various origins: multichannel electrophysiology, 1- or 2-p calcium imaging, behavior, etc. Often, the exact nature of data streams are unique to each lab, if not each project. Analyzing these datasets in an efficient and open way is crucial for collaboration and reproducibility. In this combined webinar and tutorial, Adrien Peyrache and Guillaume Viejo will present Pynapple, a Python-based data analysis pipeline for systems neuroscience. Designed for flexibility and versatility, Pynapple allows users to perform cross-modal neural data analysis via a common programming approach which facilitates easy sharing of both analysis code and data.

Where do problem spaces come from? On metaphors and representational change

The challenges of problem solving do not exclusively lie in how to perform heuristic search, but they begin with how we understand a given task: How to cognitively represent the task domain and its components can determine how quickly someone is able to progress towards a solution, whether advanced strategies can be discovered, or even whether a solution is found at all. While this challenge of constructing and changing representations has been acknowledged early on in problem solving research, for the most part it has been sidestepped by focussing on simple, well-defined problems whose representation is almost fully determined by the task instructions. Thus, the established theory of problem solving as heuristic search in problem spaces has little to say on this. In this talk, I will present a study designed to explore this issue, by virtue of finding and refining an adequate problem representation being its main challenge. In this exploratory case study, it was investigated how pairs of participants acquaint themselves with a complex spatial transformation task in the domain of iterated mental paper folding over the course of several days. Participants have to understand the geometry of edges which occurs when repeatedly mentally folding a sheet of paper in alternating directions without the use of external aids. Faced with the difficulty of handling increasingly complex folds in light of limited cognitive capacity, participants are forced to look for ways in which to represent folds more efficiently. In a qualitative analysis of video recordings of the participants' behaviour, the development of their conceptualisation of the task domain was traced over the course of the study, focussing especially on their use of gesture and the spontaneous occurrence and use of metaphors in the construction of new representations. Based on these observations, I will conclude the talk with several theoretical speculations regarding the roles of metaphor and cognitive capacity in representational change.

Canonical neural networks perform active inference

The free-energy principle and active inference have received a significant attention in the fields of neuroscience and machine learning. However, it remains to be established whether active inference is an apt explanation for any given neural network that actively exchanges with its environment. To address this issue, we show that a class of canonical neural networks of rate coding models implicitly performs variational Bayesian inference under a well-known form of partially observed Markov decision process model (Isomura, Shimazaki, Friston, Commun Biol, 2022). Based on the proposed theory, we demonstrate that canonical neural networks—featuring delayed modulation of Hebbian plasticity—can perform planning and adaptive behavioural control in the Bayes optimal manner, through postdiction of their previous decisions. This scheme enables us to estimate implicit priors under which the agent’s neural network operates and identify a specific form of the generative model. The proposed equivalence is crucial for rendering brain activity explainable to better understand basic neuropsychology and psychiatric disorders. Moreover, this notion can dramatically reduce the complexity of designing self-learning neuromorphic hardware to perform various types of tasks.

PET imaging in brain diseases

Talk 1. PET based biomarkers of treatment efficacy in temporal lobe epilepsy A critical aspect of drug development involves identifying robust biomarkers of treatment response for use as surrogate endpoints in clinical trials. However, these biomarkers also have the capacity to inform mechanisms of disease pathogenesis and therapeutic efficacy. In this webinar, Dr Bianca Jupp will report on a series of studies using the GABAA PET ligand, [18F]-Flumazenil, to establish biomarkers of treatment response to a novel therapeutic for temporal lobe epilepsy, identifying affinity at this receptor as a key predictor of treatment outcome. Dr Bianca Jupp is a Research Fellow in the Department of Neuroscience, Monash University and Lead PET/CT Scientist at the Alfred Research Alliance–Monash Biomedical Imaging facility. Her research focuses on neuroimaging and its capacity to inform the neurobiology underlying neurological and neuropsychiatric disorders. Talk 2. The development of a PET radiotracer for reparative microglia Imaging of neuroinflammation is currently hindered by the technical limitations associated with TSPO imaging. In this webinar, Dr Lucy Vivash will discuss the development of PET radiotracers that specifically image reparative microglia through targeting the receptor kinase MerTK. This includes medicinal chemistry design and testing, radiochemistry, and in vitro and in vivo testing of lead tracers. Dr Lucy Vivash is a Research Fellow in the Department of Neuroscience, Monash University. Her research focuses on the preclinical development and clinical translation of novel PET radiotracers for the imaging of neurodegenerative diseases.

How communication networks promote cross-cultural similarities: The case of category formation

Individuals vary widely in how they categorize novel phenomena. This individual variation has led canonical theories in cognitive and social science to suggest that communication in large social networks leads populations to construct divergent category systems. Yet, anthropological data indicates that large, independent societies consistently arrive at similar categories across a range of topics. How is it possible for diverse populations, consisting of individuals with significant variation in how they view the world, to independently construct similar categories? Through a series of online experiments, I show how large communication networks within cultures can promote the formation of similar categories across cultures. For this investigation, I designed an online “Grouping Game” to observe how people construct categories in both small and large populations when tasked with grouping together the same novel and ambiguous images. I replicated this design for English-speaking subjects in the U.S. and Mandarin-speaking subjects in China. In both cultures, solitary individuals and small social groups produced highly divergent category systems. Yet, large social groups separately and consistently arrived at highly similar categories both within and across cultures. These findings are accurately predicted by a simple mathematical model of critical mass dynamics. Altogether, I show how large communication networks can filter lexical diversity among individuals to produce replicable society-level patterns, yielding unexpected implications for cultural evolution. In particular, I discuss how participants in both cultures readily harnessed analogies when categorizing novel stimuli, and I examine the role of communication networks in promoting cross-cultural similarities in analogy-making as the key engine of category formation.

Co-Design of Analog Neuromorphic Systems and Cortical Motifs with Local Dendritic Learning Rules

Bernstein Conference 2024

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

Bernstein Conference 2024

Variability in Self-Organizing Networks of Neurons: Between Chance and Design

Bernstein Conference 2024

What should a neuron aim for? Designing local objective functions based on information theory

Bernstein Conference 2024

Exploiting color space geometry for visual stimulus design across animals

COSYNE 2022

Optimization of error distributions as a design principle for neural representations

COSYNE 2022

Optimization of error distributions as a design principle for neural representations

COSYNE 2022

Design principles for memory storage and recall in noisy intracellular networks

COSYNE 2025

Beyond retigabine: design, synthesis, and pharmacological characterization of a potent and chemically-stable neuronal Kv7 channels activator with anticonvulsant activity

Decision-making in dynamic, continuously evolving environments: a novel task design to reliably quantify the flexibility of decision formation and its neural signatures

Design and implementation of an at-home EEG-neurofeedback protocol for decreasing visual motion sensitivity

Design of an Ultrapotent Genetically Encoded Blocker of the Potassium Channel Kv4.2 for Gating Neural Plasticity

Designing viral tools to classify subpopulations of tanycytes along the third ventricle

The effect of nanostructuration of semi-conductor or polymer materials in neural cell cultures: implications for neural implant design

Evaluation of the effectiveness of an executive function training program coupled with transcranial stimulation in brain-injured patients: Preliminary results of a Single Case Experimental Design

In vitro microfluidic design to study mitochondria-microtubules interactions after an axonal traumatic injury

Design and development of nanoliposomes based on soy lecithin for the delivery of molecules to the CNS as strategy for the treatment of neurodegenerative diseases

FENS Forum 2024

Design, synthesis and pharmacological evaluation of pyrazole/tacrine derivatives as potential acetylcholinesterase inhibitors

FENS Forum 2024

Designing a third place in urban underground space

FENS Forum 2024

Designing a transmodal technology to feel sound through touch: The multichannel vibrotactile gloves

FENS Forum 2024

Differences of designer receptor exclusively activated by designer drugs (DREADD) signaling preferences compared to wild type receptors

FENS Forum 2024

From action observation to brain-to-brain social interaction: An EEG µ rhythms scalable design

FENS Forum 2024

Investigating design parameters for improved tissue integration in brain-computer-interface technology

FENS Forum 2024

Microglial depletion strategies as a promising tool to design potential therapies for Alzheimer’s disease

FENS Forum 2024

Modulation of brain activity by environmental design: A study using EEG and virtual reality

FENS Forum 2024

Recording cortico-hypothalamic projection neuron activity in mice living in an automated naturalistic open-design maze

FENS Forum 2024