longitudinal

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

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

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

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

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

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

Neuroinflammation in Cerebral Small Vessel Disease

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

Borrelia burgdorferi genotypic diversity, pathogenesis, and host cellular responses

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

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.

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.

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

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

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

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

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.

Post-diagnosis changes in body composition and renal cell cancer survival

ABSTRACT Significance. Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer and most lethal subtype, and there is great interest in the identification of potentially modifiable prognostic factors. Although weight status seems to be relevant, the relationship between body mass index (BMI) at diagnosis and survival among ccRCC patients indicates that mortality is lowest among those classified as overweight or obese at the time of diagnosis by BMI. This has resulted in confusion in clinical guidance for weight management among ccRCC patients. Recent work involving body composition features (adipose and muscle tissue) has provided some insight, but we do not understand how weight or body composition changes after diagnosis relate to survival, nor how these changes relate to pathological and molecular tumor features— information which is needed to resolve this controversy. Rigorous analytical approaches are further required to accurately address these questions. Innovation. Our study is highly innovative in that 1) we will be the first to leverage a large-scale cohort of ccRCC patients with multiple assessments of weight and body composition from diagnosis onward; 2) we will examine tumor characteristics, including molecular features, as potential drivers of these changes; and 3) we will use a rigorous joint modeling approach to simultaneously model the post-diagnosis trajectories of weight and body composition and their relationships with cancer outcomes in the most statistically sound manner. Our findings will inform clinical management of, and identify modifiable body composition features to improve survival for the growing number of ccRCC patients. Approach. We will use available data from the RESOLVE cohort, an NCI-funded retrospective cohort of 1,239 Stage I-III clear-cell renal cell carcinoma (ccRCC) patients diagnosed between 2000-2020 at Memorial Sloan Kettering Cancer Center. These data include clinical and patient-level factors collected from the medical record, including repeated height and weight assessments, body composition measures from existing computed tomography scans, pathological and molecular tumor characteristics, and overall survival (OS) and disease-free survival (DFS). We will use a joint modeling approach to simultaneously model changes in post-diagnosis body weight (Aim 1) and OS and DFS, as well as post-diagnosis changes in muscle and adipose tissue features (Aim 2) and OS and DFS. Models will include molecular tumor characteristics as predictors of these longitudinal trajectories. Impact. These results will provide crucial insight into the relationship between body composition changes and outcomes among ccRCC patients, and potentially identify tumor-related characteristics driving these associations. These results will resolve apparent paradoxes around the relationship between obesity and ccRCC mortality and identify potential targets for nutrition and physical activity interventions on body composition.

Continued HIV Production From Infected Macrophage In People On ART

PROJECT ABSTRACT After a few weeks of antiretroviral therapy (ART), HIV-1 RNA often decays to undetectable levels in blood. The initial decay is typically rapid due to the loss of short-lived, HIV-infected CD4+ T cells, but despite being adherent to ART, some people experience a subsequent period of slower decay and may require months to years to reach virologic suppression. The clinical significance of ‘slow decay’ of HIV-1 RNA after starting ART is currently unknown. Assessing the clinical significance of ‘slow decay virus’ requires identify the mechanisms generating it and exploring whether there is ongoing inflammation and neuronal damage in these people. There are three potential mechanisms that may generate ‘slow decay virus’ and they may have very different clinical implications. (1) Continued HIV-1 replication due to ineffective ART, poor ART adherence or drug- resistance. (2) Alternatively, ART could stop HIV-1 replication, but HIV-1 virions may continue to be produced by HIV-infected CD4+ T cells or (3) macrophage. Virus production without replication that emerges at the time of ART initiation is called primary nonsuppresible viremia (NSV) and is mechanistically distinct from secondary NSV observed in people who were previously suppressed. We recently examined four people who required approximately a year to become suppressed and found that ART stopped HIV-1 replication, but HIV-infected macrophage continued to produce substantial amounts of virus. These preliminary results are consistent with the long-held belief that after starting ART there is a period of rapid viral decay due to loss of HIV-infected CD4+ T cells, but some people have a subsequent period of slower decay due to continued virus production from long- lived, HIV-infected macrophage. The proposed work will expand on these observations and examine the mechanisms generating ‘slow decay virus’ in a much larger cohort of people on ART and explore the clinical implications of having ‘slow decay virus’ after starting ART (i.e. primary NSV). We will use existing, archived, longitudinal blood samples from 99 people in the MACS/WIHS Combined Cohort Study (MWCCS) who did not suppress HIV-1 RNA to undetectable levels by 6 months on ART (i.e. people with ‘slow decay virus’) and samples from 30 people who suppressed virus with typical, rapid kinetics. The proposed experiments will identify the mechanisms generating ‘slow decay virus’ during ART and the clinical implications of ‘slow decay virus’ (Aim 1). In our previous study, we also observed that ‘slow decay virus’ produced by macrophage often had nonsense/frameshift mutations in the HIV-1 vpr gene that may have promoted continued HIV-1 production from macrophage during ART. Specifically, we will explore whether ‘slow decay virus’ populations produced by macrophage have mutations in vpr or other genes that impact macrophage survival and/or HIV-1 production from infected macrophage (Aim 2). We will accomplish these aims using cutting-edge, but highly rigorous approaches. Accomplishing these aims will address clinical concerns about ‘slow decay virus’, the source of ‘slow decay virus’ as well as the role that Vpr plays in HIV-1 persistence and expression in macrophage during ART.

Magnetic resonance true temperature imaging with high spatial and temporal resolution

ABSTRACT The knowledge of temperature and temperature distribution within the brain can be critical to understanding the healthy and diseased brain, its response to acute injury, and in monitoring critically important thermal interventions. There are several temperature sensitive properties such relaxation rates and the proton resonance frequency shift (PRFS) that can be measured with magnetic resonance imaging (MRI) methods but these methods can only measure temperature change. The PRFS method, which provides the most accurate measurement of temperature change can only measure true tissue temperature if the starting true temperature distribution is known. Fortunately, MR spectroscopy (MRS) methods have been developed that show great promise in the measurement of true temperature. These methods rely on the detection of a temperature independent spectral peak of protons bound to carbon atoms in high concentration metabolites, such as N- acetylaspartate (NAA), creatine (Cr) and choline (Cho) which can be used as a reference for the temperature dependent spectral peak of water protons. Both single voxel spectroscopy (SVS) methods and MRS imaging (MRSI) methods have been described but are slow because of the long readout time needed to achieve adequate spectral resolution and the need to perform multiple averages due to the low signal being measured. Echo-planar spectroscopic imaging (EPSI) speeds up MRSI by interleaving an oscillating imaging gradient to spatially encode one of the imaging dimensions simultaneously with spectral readout. Unfortunately, SVS, MRSI, and even EPSI are unsuitable for clinical applications because of the low spatial resolution (voxel size 1 cm3) and temporal resolution (multiple minutes). The goal of this project is to develop an MRI technique that can measure true temperature in the whole brain at spatial and temporal resolutions that enable clinical utility for acutely assessing and longitudinally monitoring healthy and diseased brain tissue, and real time monitoring of thermal interventional therapies. This innovative true temperature measurement technique combines EPSI, for low resolution background field measurements, with PRFS for high spatial and temporal resolution water proton measurements. While conventional EPSI methods interleave volumetric acquisitions with and without water suppression, we propose an innovative modification to take advantage of the very strong water signal to obtain a very high resolution, dynamic method for true temperature measurements. The MRI pulse sequence will be refined, validated (Aim 1), applied to healthy subjects and post-surgery patients at risk for infections (Aim 2), and applied to essential tremor (ET) patients during the required delay between repeated focused ultrasound sonications (Aim 3). Successful completion of the aims of this study will result in a clinically practical method to obtain true temperature measurements in the brain with a spatial and temporal resolution sufficiently high to meet the needs of monitoring focal thermal therapy treatments as well as to provide true temperature measurements over the entire brain for assessment of the state of the brain with disease, infection, and injury.

Stability in disrupted maternal representations over the perinatal period: Contributors and consequences

Abstract High-quality mother-infant relationships promote social, emotional, and cognitive development while protecting against poor child behavioral, health, and psychological adaptation that create risk for long- term negative outcomes. As mothers transition to parenthood, their own experiences of being cared for influence their emerging views of parenting and representations of their developing child. Evidence suggests that ‘disrupted’ maternal representations of the child, i.e., representations characterized by mixed communication, role merging, extreme withdrawal, and other unusual psychological processes, are tied to both poor child socioemotional adjustment and both insecure and disorganized attachment. However, it is unclear whether disrupted representations that emerge during pregnancy remain stable across the first several years of the child’s life. In addition, to date, research has not examined how change/stability in these representations may affect maternal caregiving and subsequent child adaptation. Using data from a longitudinal, multi-method study, this proposed project will examine the stability of maternal representations of the child for 99 women living in high risk contexts using the Working Model of the Child Interview during the third trimester and again when the child is two years of age. Mothers’ demographic characteristics (i.e. SES and relationship status), interpersonal violence experiences (i.e. child maltreatment or intimate violence exposure), psychological health (i.e. depressive, anxious, and PTSD symptoms), and parenting stress (i.e. perceptions of the child as difficult and parent-child interactions as dysfunctional) are measured as well to examine influences on representation stability. Finally, the observed quality of maternal caregiving and child adaptation are measured and examined in relation to stability in maternal representations of the child. Findings from this study have the potential to identify which mother-child dyads are at greatest risk for poor adaptation across the perinatal period and to delineate the contributors and consequences of maternal representational stability. These findings will serve as an important step towards informing the development or modification of existing prevention/intervention approaches that are targeted specifically towards mother-child dyads who are most at need.

Understanding reward-guided learning using large-scale datasets

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

Understanding reward-guided learning using large-scale datasets

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

Learning produces a hippocampal cognitive map in the form of an orthogonalized state machine

Cognitive maps confer animals with flexible intelligence by representing spatial, temporal, and abstract relationships that can be used to shape thought, planning, and behavior. Cognitive maps have been observed in the hippocampus, but their algorithmic form and the processes by which they are learned remain obscure. Here, we employed large-scale, longitudinal two-photon calcium imaging to record activity from thousands of neurons in the CA1 region of the hippocampus while mice learned to efficiently collect rewards from two subtly different versions of linear tracks in virtual reality. The results provide a detailed view of the formation of a cognitive map in the hippocampus. Throughout learning, both the animal behavior and hippocampal neural activity progressed through multiple intermediate stages, gradually revealing improved task representation that mirrored improved behavioral efficiency. The learning process led to progressive decorrelations in initially similar hippocampal neural activity within and across tracks, ultimately resulting in orthogonalized representations resembling a state machine capturing the inherent struture of the task. We show that a Hidden Markov Model (HMM) and a biologically plausible recurrent neural network trained using Hebbian learning can both capture core aspects of the learning dynamics and the orthogonalized representational structure in neural activity. In contrast, we show that gradient-based learning of sequence models such as Long Short-Term Memory networks (LSTMs) and Transformers do not naturally produce such orthogonalized representations. We further demonstrate that mice exhibited adaptive behavior in novel task settings, with neural activity reflecting flexible deployment of the state machine. These findings shed light on the mathematical form of cognitive maps, the learning rules that sculpt them, and the algorithms that promote adaptive behavior in animals. The work thus charts a course toward a deeper understanding of biological intelligence and offers insights toward developing more robust learning algorithms in artificial intelligence.

Learning through the eyes and ears of a child

Young children have sophisticated representations of their visual and linguistic environment. Where do these representations come from? How much knowledge arises through generic learning mechanisms applied to sensory data, and how much requires more substantive (possibly innate) inductive biases? We examine these questions by training neural networks solely on longitudinal data collected from a single child (Sullivan et al., 2020), consisting of egocentric video and audio streams. Our principal findings are as follows: 1) Based on visual only training, neural networks can acquire high-level visual features that are broadly useful across categorization and segmentation tasks. 2) Based on language only training, networks can acquire meaningful clusters of words and sentence-level syntactic sensitivity. 3) Based on paired visual and language training, networks can acquire word-referent mappings from tens of noisy examples and align their multi-modal conceptual systems. Taken together, our results show how sophisticated visual and linguistic representations can arise through data-driven learning applied to one child’s first-person experience.

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.

Early life adversity, inflammation, and depression-onset: Results from the Teen Resilience Project

My research focuses broadly on the lifelong health disparities associated with experiences of adversity early in life. In this talk I will present the results of our recently completed Teen Resilience Project, a prospective and longitudinal study of first onset depression during adolescence. First, I will present the results on whether and how inflammatory processes may be shaped by early life adversity. Second, I will present data on the role of stress-induced inflammation in reward-related psychological processes. Finally, I will discuss the biobehavioral predictors of first-onset depression in this sample.

At the nexus of genes, aging and environment: Understanding transcriptomic and epigenomic regulation in Parkinson's disease

Parkinson’s Disease (PD), the most common neurodegenerative movement disorder, is based on a complex interplay between genetic predispositions, aging processes, and environmental influences. In order to better understand the gene-environment axis in PD, we pursue a multi-omics approach to comprehensively interrogate genome-wide changes in histone modifications, DNA methylation, and hydroxymethylation, accompanied by transcriptomic profiling in cell and animal models of PD as well as large patient cohorts. Furthermore, we assess the plasticity of epigenomic modifications under influence of environmental factors using longitudinal cohorts of sporadic PD cases as well as mouse models exposed to specific environmental factors. Here, we present gene expression changes in PD mouse models in context of aging as well as environmental enrichment and high-fat diet.

How Children Discover Mathematical Structure through Relational Mapping

A core question in human development is how we bring meaning to conventional symbols. This question is deeply connected to understanding how children learn mathematics—a symbol system with unique vocabularies, syntaxes, and written forms. In this talk, I will present findings from a program of research focused on children’s acquisition of place value symbols (i.e., multidigit number meanings). The base-10 symbol system presents a variety of obstacles to children, particularly in English. Children who cannot overcome these obstacles face years of struggle as they progress through the mathematics curriculum of the upper elementary and middle school grades. Through a combination of longitudinal, cross-sectional, and pretest-training-posttest approaches, I aim to illuminate relational learning mechanisms by which children sometimes succeed in mastering the place value system, as well as instructional techniques we might use to help those who do not.

Co-allocation to overlapping dendritic branches in the retrosplenial cortex integrates memories across time

Events occurring close in time are often linked in memory, providing an episodic timeline and a framework for those memories. Recent studies suggest that memories acquired close in time are encoded by overlapping neuronal ensembles, but whether dendritic plasticity plays a role in linking memories is unknown. Using activity-dependent labeling and manipulation, as well as longitudinal one- and two-photon imaging of RSC somatic and dendritic compartments, we show that memory linking is not only dependent on ensemble overlap in the retrosplenial cortex, but also on branch-specific dendritic allocation mechanisms. These results demonstrate a causal role for dendritic mechanisms in memory integration and reveal a novel set of rules that govern how linked, and independent memories are allocated to dendritic compartments.

Brain and behavioural impacts of early life adversity

Abuse, neglect, and other forms of uncontrollable stress during childhood and early adolescence can lead to adverse outcomes later in life, including especially perturbations in the regulation of mood and emotional states, and specifically anxiety disorders and depression. However, stress experiences vary from one individual to the next, meaning that causal relationships and mechanistic accounts are often difficult to establish in humans. This interdisciplinary talk considers the value of research in experimental animals where stressor experiences can be tightly controlled and detailed investigations of molecular, cellular, and circuit-level mechanisms can be carried out. The talk will focus on the widely used repeated maternal separation procedure in rats where rat offspring are repeatedly separated from maternal care during early postnatal life. This early life stress has remarkably persistent effects on behaviour with a general recognition that maternally-deprived animals are susceptible to depressive-like phenotypes. The validity of this conclusion will be critically appraised with convergent insights from a recent longitudinal study in maternally separated rats involving translational brain imaging, transcriptomics, and behavioural assessment.

Learning binds novel inputs into functional synaptic clusters via spinogenesis

Learning is known to induce the formation of new dendritic spines, but despite decades of effort, the functional properties of new spines in vivo remain unknown. Here, using a combination of longitudinal in vivo 2-photon imaging of the glutamate reporter, iGluSnFR, and correlated electron microscopy (CLEM) of dendritic spines on the apical dendrites of L2/3 excitatory neurons in the motor cortex during motor learning, we describe a framework of new spines' formation, survival, and resulting function. Specifically, our data indicate that the potentiation of a subset of clustered, pre-existing spines showing task-related activity in early sessions of learning creates a micro-environment of plasticity within dendrites, wherein multiple filopodia sample the nearby neuropil, form connections with pre-existing boutons connected to allodendritic spines, and are then selected for survival based on co-activity with nearby task-related spines. Thus, the formation and survival of new spines is determined by the functional micro-environment of dendrites. After formation, new spines show preferential co-activation with nearby task-related spines. This synchronous activity is more specific to movements than activation of the individual spines in isolation, and further, is coincident with movements that are more similar to the learned pattern. Thus, new spines functionally engage with their parent clusters to signal the learned movement. Finally, by reconstructing the axons associated with new spines, we found that they synapse with axons previously unrepresented in these dendritic domains, suggesting that the strong local co-activity structure exhibited by new spines is likely not due to axon sharing. Thus, learning involves the binding of new information streams into functional synaptic clusters to subserve the learned behavior.

Mapping Individual Trajectories of Structural and Cognitive Decline in Mild Cognitive Impairment

The US has an aging population. For the first time in US history, the number of older adults is projected to outnumber that of children by 2034. This combined with the fact that the prevalence of Alzheimer's Disease increases exponentially with age makes for a worrying combination. Mild cognitive impairment (MCI) is an intermediate stage of cognitive decline between being cognitively normal and having full-blown Dementia, with every third person with MCI progressing to dementia of the Alzheimer's Type (DAT). While there is no known way to reverse symptoms once they begin, early prediction of disease can help stall its progression and help with early financial planning. While grey matter volume loss in the Hippocampus and Entorhinal Cortex (EC) are characteristic biomarkers of DAT, little is known about the rates of decrease of these volumes within individuals in MCI state across time. We used longitudinal growth curve models to map individual trajectories of volume loss in subjects with MCI. We then looked at whether these rates of volume decrease could predict progression to DAT right in the MCI stage. Finally, we evaluated whether these rates of Hippocampal and EC volume loss were correlated with individual rates of decline of episodic memory, visuospatial ability, and executive function.

Biopsychosocial pathways in dementia inequalities

In the United States, racial/ethnic inequalities in Alzheimer's disease and related dementias persist even after controlling for socioeconomic factors and physical health. These persistent and unexplained disparities suggest: (1) there are unrecognized dementia risk factors that are socially patterned and/or (2) known dementia risk factors exhibit differential impact across social groups. Pursuing these research directions with data from multiple longitudinal studies of brain and cognitive aging has revealed several challenges to the study of late-life health inequalities, highlighted evidence for both risk and resilience within marginalized communities, and inspired new data collection efforts to advance the field.

Multimodal imaging in Dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is a synucleinopathy but more than half of patients with DLB also have varying degrees of tau and amyloid-β co-pathology. Identifying and tracking the pathologic heterogeneity of DLB with multi-modal biomarkers is critical for the design of clinical trials that target each pathology early in the disease at a time when prevention or delaying the transition to dementia is possible. Furthermore, longitudinal evaluation of multi-modal biomarkers contributes to our understanding of the type and extent of the pathologic progression and serves to characterize the temporal emergence of the associated phenotypic expression. This talk will focus on the utility of multi-modal imaging in DLB.

Brain chart for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight. Here, we built an interactive resource to benchmark brain morphology, www.brainchart.io, derived from any current or future sample of magnetic resonance imaging (MRI) data. With the goal of basing these reference charts on the largest and most inclusive dataset available, we aggregated 123,984 MRI scans from 101,457 participants aged from 115 days post-conception through 100 postnatal years, across more than 100 primary research studies. Cerebrum tissue volumes and other global or regional MRI metrics were quantified by centile scores, relative to non-linear trajectories of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones; showed high stability of individual centile scores over longitudinal assessments; and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes, and provided a standardised measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In sum, brain charts are an essential first step towards robust quantification of individual deviations from normative trajectories in multiple, commonly-used neuroimaging phenotypes. Our collaborative study proves the principle that brain charts are achievable on a global scale over the entire lifespan, and applicable to analysis of diverse developmental and clinical effects on human brain structure.

What happens to our ability to perceive multisensory information as we age?

Our ability to perceive the world around us can be affected by a number of factors including the nature of the external information, prior experience of the environment, and the integrity of the underlying perceptual system. A particular challenge for the brain is to maintain a coherent perception from information encoded by the peripheral sensory organs whose function is affected by typical, developmental changes across the lifespan. Yet, how the brain adapts to the maturation of the senses, as well as experiential changes in the multisensory environment, is poorly understood. Over the past few years, we have used a range of multisensory tasks to investigate the role of ageing on the brain’s ability to merge sensory inputs. In particular, we have embedded an audio-visual task based on the sound-induced flash illusion (SIFI) into a large-scale, longitudinal study of ageing. Our findings support the idea that the temporal binding window (TBW) is modulated by age and reveal important individual differences in this TBW that may have clinical implications. However, our investigations also suggest the TWB is experience-dependent with evidence for both long and short term behavioural plasticity. An overview of these findings, including recent evidence on how multisensory integration may be associated with higher order functions, will be discussed.

Mechanisms of sleep-seizure interactions in tuberous sclerosis and other mTORpathies

An intriguing, relatively unexplored therapeutic avenue to investigate epilepsy is the interaction of sleep mechanisms and seizures. Multiple lines of clinical observations suggest a strong, bi-directional relationship between epilepsy and sleep. Epilepsy and sleep disorders are common comorbidities. Seizures occur more commonly in sleep in many types of epilepsy, and in turn, seizures can cause disrupted sleep. Sudden unexplained death in epilepsy (SUDEP) is strongly associated with sleep. The biological mechanisms underlying this relationship between seizures and sleep are poorly understood, but if better delineated, could offer novel therapeutic approaches to treating both epilepsy and sleep disorders. In this presentation, I will explore this sleep-seizure relationship in mouse models of epilepsy. First, I will present general approaches for performing detailed longitudinal sleep and vigilance state analysis in mice, including pre-weanling neonatal mice. I will then discuss recent data from my laboratory demonstrating an abnormal sleep phenotype in a mouse model of the genetic epilepsy, tuberous sclerosis complex (TSC), and its relationship to seizures. The potential mechanistic basis of sleep abnormalities and sleep-seizure interactions in this TSC model will be investigated, focusing on the role of the mechanistic target of rapamycin (mTOR) pathway and hypothalamic orexin, with potential therapeutic applications of mTOR inhibitors and orexin antagonists. Finally, similar sleep-seizure interactions and mechanisms will be extended to models of acquired epilepsy due to status epilepticus-related brain injury.

Opponent processing in the expanded retinal mosaic of Nymphalid butterflies

In many butterflies, the ancestral trichromatic insect colour vision, based on UV-, blue- and green-sensitive photoreceptors, is extended with red-sensitive cells. Physiological evidence for red receptors has been missing in nymphalid butterflies, although some species can discriminate red hues well. In eight species from genera Archaeoprepona, Argynnis, Charaxes, Danaus, Melitaea, Morpho, Heliconius and Speyeria, we found a novel class of green-sensitive photoreceptors that have hyperpolarizing responses to stimulation with red light. These green-positive, red-negative (G+R–) cells are allocated to positions R1/2, normally occupied by UV and blue-sensitive cells. Spectral sensitivity, polarization sensitivity and temporal dynamics suggest that the red opponent units (R–) are the basal photoreceptors R9, interacting with R1/2 in the same ommatidia via direct inhibitory synapses. We found the G+R– cells exclusively in butterflies with red-shining ommatidia, which contain longitudinal screening pigments. The implementation of the red colour channel with R9 is different from pierid and papilionid butterflies, where cells R5–8 are the red receptors. The nymphalid red-green opponent channel and the potential for tetrachromacy seem to have been switched on several times during evolution, balancing between the cost of neural processing and the value of extended colour information.

Evidence for the role of glymphatic dysfunction in the development of Alzheimer’s disease

Glymphatic perivascular exchange is supported by the astroglial water channel aquaporin-4 (AQP4), which localizes to perivascular astrocytic endfeet surrounding the cerebral vasculature. In aging mice, impairment of glymphatic function is associated with reduced perivascular AQP4 localization, yet whether these changes contribute to the development of neurodegenerative disease, such as Alzheimer’s disease (AD), remains unknown. Using post mortem human tissue, we evaluated perivascular AQP4 localization in the frontal cortical gray matter, white matter, and hippocampus of cognitively normal subjects and those with AD. Loss of perivascular and increasing cellular localization of AQP4 in the frontal gray matter was specifically associated with AD status, amyloid β (Aβ) and tau pathology, and cognitive decline in the early stages of disease. Using AAV-PHP.B to drive expression on non-perivascular AQP4 in wild type and Tg2576 (APPSwe, mouse model of Aβ deposition) mice, increased cellular AQP4 localization did not slow glymphatic function or change Aβ deposition. Using the Snta1 knockout line (which lacks perivascular AQP4 localization), we observed that loss AQP4 from perivascular endfeet slowed glymphatic function in wild type mice and accelerated Aβ plaque deposition in Tg2576 mice. These findings demonstrate that loss of perivascular AQP4 localization, and not increased cellular AQP4 localization, slows glymphatic function and promotes the development of AD pathology. To evaluate whether naturally occurring variation in the human AQP4 gene, or the alpha syntrophin (SNTA1), dystrobrevin (DTNA) or dystroglycan (DAG1) genes (whose products maintain perivascular AQP4 localization) confer risk for or protection from AD pathology or clinical progression, we evaluated 56 tag single nucleotide polymorphisms (SNPs) across these genes for association with CSF AD biomarkers, MRI measures of cortical and hippocampal atrophy, and longitudinal cognitive decline in the Alzheimer’s Disease Neuroimaging Initiative I (ADNI I) cohort. We identify 25 different significant associations between AQP4, SNTA1, DTNA, and DAG1 tag SNPs and phenotypic measures of AD pathology and progression. These findings provide complimentary human genetic evidence for the contribution of perivascular glymphatic dysfunction to the development of AD in human populations.

Unpacking Nature from Nurture: Understanding how Family Processes Affect Child and Adolescent Mental Health

Mental Health problems among youth constitutes an area of significant social, educational, clinical, policy and public health concern. Understanding processes and mechanisms that underlie the development of mental health problems during childhood and adolescence requires theoretical and methodological integration across multiple scientific domains, including developmental science, neuroscience, genetics, education and prevention science. The primary focus of this presentation is to examine the relative role of genetic and family environmental influences on children’s emotional and behavioural development. Specifically, a complementary array of genetically sensitive and longitudinal research designs will be employed to examine the role of early environmental adversity (e.g. inter-parental conflict, negative parenting practices) relative to inherited factors in accounting for individual differences in children’s symptoms of psychopathology (e.g. depression, aggression, ADHD ). Examples of recent applications of this research to the development of evidence-based intervention programmes aimed at reducing psychopathology in the context of high-risk family settings will also be presented.

Early constipation predicts faster dementia onset in Parkinson’s disease

Constipation is a common but not a universal feature in early PD, suggesting that gut involvement is heterogeneous and may be part of a distinct PD subtype with prognostic implications. We analysed data from the Parkinson’s Incidence Cohorts Collaboration, composed of incident community-based cohorts of PD patients assessed longitudinally over 8 years. Constipation was assessed with the MDS-UPDRS constipation item or a comparable categorical scale. Primary PD outcomes of interest were dementia, postural instability and death. PD patients were stratified according to constipation severity at diagnosis: none (n=313, 67.3%), minor (n=97, 20.9%) and major (n=55, 11.8%). Clinical progression to all 3 outcomes was more rapid in those with more severe constipation at baseline (Kaplan Meier survival analysis). Cox regression analysis, adjusting for relevant confounders, confirmed a significant relationship between constipation severity and progression to dementia, but not postural instability or death. Early constipation may predict an accelerated progression of neurodegenerative pathology. Conclusions: We show widespread cortical and subcortical grey matter micro-structure associations with schizophrenia PRS. Across all investigated phenotypes NDI, a measure of the density of myelinated axons and dendrites, showed the most robust associations with schizophrenia PRS. We interpret these results as indicative of reduced density of myelinated axons and dendritic arborization in large-scale cortico-subcortical networks mediating the genetic risk for schizophrenia.

Data-driven Artificial Social Intelligence: From Social Appropriateness to Fairness

Designing artificially intelligent systems and interfaces with socio-emotional skills is a challenging task. Progress in industry and developments in academia provide us a positive outlook, however, the artificial social and emotional intelligence of the current technology is still limited. My lab’s research has been pushing the state of the art in a wide spectrum of research topics in this area, including the design and creation of new datasets; novel feature representations and learning algorithms for sensing and understanding human nonverbal behaviours in solo, dyadic and group settings; designing longitudinal human-robot interaction studies for wellbeing; and investigating how to mitigate the bias that creeps into these systems. In this talk, I will present some of my research team’s explorations in these areas including social appropriateness of robot actions, virtual reality based cognitive training with affective adaptation, and bias and fairness in data-driven emotionally intelligent systems.

The time of chromatin: emerging insights from longitudinal modelling of neurodevelopmental disorders

CURE-ND Neurotechnology Workshop - Innovative models of neurodegenerative diseases

One of the major roadblocks to medical progress in the field of neurodegeneration is the absence of animal models that fully recapitulate features of the human diseases. Unprecedented opportunities to tackle this challenge are emerging e.g. from genome engineering and stem cell technologies, and there are intense efforts to develop models with a high translational value. Simultaneously, single-cell, multi-omics and optogenetics technologies now allow longitudinal, molecular and functional analysis of human disease processes in these models at high resolution. During this workshop, 12 experts will present recent progress in the field and discuss: - What are the most advanced disease models available to date? - Which aspects of the human disease do these accurately models, which ones do they fail to replicate? - How should models be validated? Against which reference, which standards? - What are currently the best methods to analyse these models? - What is the field still missing in terms of modelling, and of technologies to analyse disease models? CURE-ND stands for 'Catalysing a United Response in Europe to Neurodegenerative Diseases'. It is a new alliance between the German Center for Neurodegenerative Diseases (DZNE), the Paris Brain Institute (ICM), Mission Lucidity (ML, a partnership between imec, KU Leuven, UZ Leuven and VIB in Belgium) and the UK Dementia Research Institute (UK DRI). Together, these partners embrace a joint effort to accelerate the pace of scientific discovery and nurture breakthroughs in the field of neurodegenerative diseases. This Neurotechnology Workshop is the first in a series of joint events aiming at exchanging expertise, promoting scientific collaboration and building a strong community of neurodegeneration researchers in Europe and beyond.

Two pathways to self-harm in adolescence

The behavioural and emotional profiles underlying adolescent self-harm, and its developmental risk factors, are relatively unknown. The authors of this paper aimed to identify sub-groups of young people who self-harm (YPSH) and longitudinal predictors leading to self-harm using the Millennium Cohort Study. (Pre-print: https://www.medrxiv.org/content/10.1101/2020.07.10.20150789v1)

Mapping early brain network changes in neurodegenerative and cerebrovascular disorders: a longitudinal perspective

The spatial patterning of each neurodegenerative disease relates closely to a distinct structural and functional network in the human brain. This talk will mainly describe how brain network-sensitive neuroimaging methods such as resting-state fMRI and diffusion MRI can shed light on brain network dysfunctions associated with pathology and cognitive decline from preclinical to clinical dementia. I will first present our findings from two independent datasets on how amyloid and cerebrovascular pathology influence brain functional networks cross-sectionally and longitudinally in individuals with mild cognitive impairment and dementia. Evidence on longitudinal functional network organizational changes in healthy older adults and the influence of APOE genotype will be presented. In the second part, I will describe our work on how different pathology influences brain structural network and white matter microstructure. I will also touch on some new data on how brain network integrity contributes to behavior and disease progression using multivariate or machine learning approaches. These findings underscore the importance of studying selective brain network vulnerability instead of individual region and longitudinal design. Further developed with machine learning approaches, multimodal network-specific imaging signatures will help reveal disease mechanisms and facilitate early detection, prognosis and treatment search of neuropsychiatric disorders.

Multimodal brain imaging to predict progression of Alzheimer’s disease

Cross-sectional and longitudinal multimodal brain imaging studies using positron emission tomography (PET) and magnetic resonance imaging (MRI) have provided detailed insight into the pathophysiological progression of Alzheimer’s disease. It starts at an asymptomatic stage with widespread gradual accumulation of beta-amyloid and spread of pathological tau deposits. Subsequently changes of functional connectivity and glucose metabolism associated with mild cognitive impairment and brain atrophy may develop. However, the rate of progression to a symptomatic stage and ultimately dementia varies considerably between individuals. Mathematical models have been developed to describe disease progression, which may be used to identify markers that determine the current stage and likely rate of progression. Both are very important to improve the efficacy of clinical trials. In this lecture, I will provide an overview on current research and future perspectives in this area.

Generation Covid-19: Should the fetus be worried?

Historically pregnant women and their unborn baby have been amongst those with the poorest outcomes in previous epidemics, most notably the Zika virus. For much of 2020, with the emergence of the novel coronavirus, the effect on the fetus remains unclear. While initial reports suggest that vertical transmission with SARS-CoV2 is reassuringly rare, the complex socioeconomic, domestic and broader maternal lifestyle factors which can influence a child’s lifelong well-being have been modulated during the experience of this pandemic. The developing brain is particularly susceptible to maternal stress, resulting in permanent structural changes and increased incidence of behavioural and mental health illness later in childhood. A large international longitudinal survey is being undertaken by the Department of Psychology to better understand the impact of the pandemic on those yet to be born.

Emergent scientists discuss Alzheimer's disease

This seminar is part of our “Emergent Scientists” series, an initiative that provides a platform for scientists at the critical PhD/postdoc transition period to share their work with a broad audience and network. Summary: These talks cover Alzheimer’s disease (AD) research in both mice and humans. Christiana will discuss in particular the translational aspects of applying mouse work to humans and the importance of timing in disease pathology and intervention (e.g. timing between AD biomarkers vs. symptom onset, timing of therapy, etc.). Siddharth will discuss a rare variant of Alzheimer’s disease called “Logopenic Progressive Aphasia”, which presents with temporo-parietal atrophy yet relative sparing of hippocampal circuitry. Siddharth will discuss how, despite the unusual anatomical basis underlying this AD variant, degeneration of the angular gyrus in the left inferior parietal lobule contributes to memory deficits similar to those of typical amnesic Alzheimer’s disease. Christiana’s abstract: Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder that causes severe deterioration of memory, cognition, behavior, and the ability to perform daily activities. The disease is characterized by the accumulation of two proteins in fibrillar form; Amyloid-β forms fibrils that accumulate as extracellular plaques while tau fibrils form intracellular tangles. Here we aim to translate findings from a commonly used AD mouse model to AD patients. Here we initiate and chronically inhibit neuropathology in lateral entorhinal cortex (LEC) layer two neurons in an AD mouse model. This is achieved by over-expressing P301L tau virally and chronically activating hM4Di DREADDs intracranially using the ligand dechloroclozapine. Biomarkers in cerebrospinal fluid (CSF) is measured longitudinally in the model using microdialysis, and we use this same system to intracranially administer drugs aimed at halting AD-related neuropathology. The models are additionally tested in a novel contextual memory task. Preliminary findings indicate that viral injections of P301L tau into LEC layer two reveal direct projections between this region and the outer molecular layer of dentate gyrus and the rest of hippocampus. Additionally, phosphorylated tau co-localize with ‘starter cells’ and appear to spread from the injection site. Preliminary microdialysis results suggest that the concentrations of CSF amyloid-β and tau proteins mirror changes observed along the disease cascade in patients. The disease-modifying drugs appear to halt neuropathological development in this preclincial model. These findings will lead to a novel platform for translational AD research, linking the extensive research done in rodents to clinical applications. Siddharth’s abstract: A distributed brain network supports our ability to remember past events. The parietal cortex is a critical member of this network, yet, its exact contributions to episodic remembering remain unclear. Neurodegenerative syndromes affecting the posterior neocortex offer a unique opportunity to understand the importance and role of parietal regions to episodic memory. In this talk, I introduce and explore the rare neurodegenerative syndrome of Logopenic Progressive Aphasia (LPA), an aphasic variant of Alzheimer’s disease presenting with early, left-lateralized temporo-parietal atrophy, amidst relatively spared hippocampal integrity. I then discuss two key studies from my recent Ph.D. work showcasing pervasive episodic and autobiographical memory dysfunction in LPA, to a level comparable to typical, amnesic Alzheimer’s disease. Using multimodal neuroimaging, I demonstrate how degeneration of the angular gyrus in the left inferior parietal lobule, and its structural connections to the hippocampus, contribute to amnesic profiles in this syndrome. I finally evaluate these findings in the context of memory profiles in other posterior cortical neurodegenerative syndromes as well as recent theoretical models underscoring the importance of the parietal cortex in the integration and representation of episodic contextual information.

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

FENS Forum 2026

Assessing functional networks dynamic through high-density longitudinal EEG recordings in a new mouse model of early Alzheimer’s disease

Auditory brainstem responses in the Nrxn1 rat and Cntnap2 mouse models for neurodevelopmental disorders: A longitudinal and pharmacological study

Exploring the association between brain-derived neurotrophic factor (BDNF) levels and longitudinal psychopathological and cognitive changes in Sardinian psychotic patients

Hemispheric versus whole-brain irradiation induced neurotoxicity: longitudinal studies in the rat

Implicit reading in tactile domain - a longitudinal fMRI study of sighted participants learning Braille alphabet

Intracerebral longitudinal characterization of large-scale epileptogenesis in the kainate mouse model of focal temporal lobe epilepsy

Longitudinal Change in Interhemispheric Connectivity Predicts Recovery from Vestibular Agnosia

Longitudinal cognitive decline and blood-brain barrier permeability in a population cohort

Longitudinal effect of psychiatric medication on suicidal ideation: A prospective cohort study

Longitudinal imaging of electrical synapses in the awake mouse brain using a novel, customizable, 3D-printed holding system

Longitudinal multielectrode recordings of Purkinje cell activity during accelerated eyeblink conditioning in mice

Longitudinal tracking of synaptic structural homeostatic mechanisms in the hippocampal CA1 region of live mice using two-photon imaging

Longitudinal Volume Loss after Traumatic Brain Injury Predicts Vestibular Dysfunction

Resting state functional connectivity networks in twins with autism: Towards the Turkish Longitudinal Neuroimaging Autism Project (TURK-NAP) using the ABİDE Database

Sex-biased RNA populations along the hippocampal longitudinal axis and their putative transcriptional and post-transcriptional regulatory networks

Cognitive improvement up to 4 years after cochlear implantation in older adults: A prospective longitudinal study using the RBANS-H

FENS Forum 2024

Exploring the effects of incarceration on decision-making processes: A longitudinal EEG study on current and former prisoners

FENS Forum 2024

Investigating risk factors associated with longitudinal changes in brain structure in UK Biobank

FENS Forum 2024

Longitudinal assessment of behaviour and neuronal activity in the lateral habenula in a mouse model of depression

FENS Forum 2024

Longitudinal assessment of neurodegeneration in a mouse model of tauopathy using multiparametric magnetic resonance imaging

FENS Forum 2024

Longitudinal assessment of ALS patient-derived motor neurons reveals altered network dynamics and synaptic impairment

FENS Forum 2024

Longitudinal autophagy profiling of mammalian brain circuits reveals dynamic and sustained mitophagy throughout healthy aging

FENS Forum 2024

Longitudinal single-cell and brain transcriptomic characterization of microglia signatures during experimental demyelination and remyelination

FENS Forum 2024

Longitudinal study of delayed cerebral ischemia in mice using daily functional ultrasound (fUS) imaging and gait analysis

FENS Forum 2024

Longitudinal tracking of hippocampal activity with the InSplorer endoscope in freely moving mice

FENS Forum 2024

Normative brain development in male and female rats: A longitudinal neuroimaging study

FENS Forum 2024

Association of insulin-like growth factor 1 with post-traumatic brain injury sleep disorders: A longitudinal study

FENS Forum 2024

Protective effects of intracranial stimulation on spatial memory and changes in miRNA serum levels in a sporadic rat model of Alzheimer disease: A longitudinal study

FENS Forum 2024