CANs

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

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

A novel MRI method for noninvasive imaging of bone quality in type 2 diabetes

ABSTRACT: Type 2 diabetes mellitus (T2DM) affects 500 million of the global population, which is expected to increase to 800 million in 20 years. One of the multiple complications involved with T2DM is the significantly increased bone fracture risk and post-fracture mortality. Dual-energy X-ray absorptiometry (DXA) scans are routinely performed to measure bone mineral density (BMD) and associated fracture risk. However, T2DM patients often show preserved or even elevated BMD despite the significantly increased fracture risk. This mismatch between the BMD measurement and actual fracture risk hampers the accurate assessment of fracture risk and the appropriate treatment of T2DM that considers patient bone health. The lack of an accurate fracture risk assessment tool also confounds the evaluation of the bone health effect of antidiabetic drugs, including recently highlighted glucagon-like peptide-1 receptor agonists (e.g., semaglutide) and sodium-glucose cotransporter-2 inhibitors. Previous studies have suggested that bone quality, rather than bone quantity, as represented by BMD, is a crucial factor contributing to fracture risk in T2DM settings. Collagen crosslinking via advanced glycation end-products (AGEs) in cortical bone has been identified as a distinctive bone quality characteristic of T2DM patients, which explains the increased bone fragility. Although this finding is highly promising for improving the bone health management of T2DM patients, currently, no non-invasive method can monitor collagen crosslinking in the bones. This proposal aims to develop an ultrashort echo time (UTE) MRI-based method for measuring the degree of bone collagen crosslinking by quantifying magnetization transfer between water and collagen in the bone. This method, termed UTE-quantitative magnetization transfer (UTE-qMT) MRI, measures not only the quantity of macromolecules (e.g., collagen) in the bone but also the rates of exchange between water and macromolecular protons, which are related to the degree of collagen crosslinking. The proposal will develop and optimize the accelerated UTE-qMT method for reliably measuring the exchange rate in Aim 1. The optimized technique will be validated by correlating exchange rates with AGE-driven collagen crosslinking and subsequent compromise of bone mechanical properties in Aim 2. Finally, the optimized UTE-qMT MRI method will be translated to animal and human studies to demonstrate its clinical feasibility for investigating the effect of antidiabetic drugs on bone health in patients with T2DM in Aim 3. The successful completion of these aims will enable rapid and accurate assessment of bone fracture risk in patients with T2DM. Furthermore, noninvasively probing bone quality can also accurately assess the effect of antidiabetic drugs on bone health and aid in screening novel T2DM therapeutics for their impact on bone health.

Environmental sampling for the fungal pathogen Coccidioides spp. in New Mexico

PROJECT SUMMARY/ABSTRACT Coccidioidomycosis (also known as Valley fever) is a fungal disease endemic to the arid and semi-arid portions of the United States. Due to its alarming health impacts, it has recently been deemed as one of the fungal diseases of highest concern by the World Health Organization. Disease cases continue to rise, causing increasing concern and warranting further understanding of this disease. Though New Mexico has been considered endemic to the disease since the 1940s, few cases are reported in the state each year, suggesting cases may be going vastly underreported. Indeed, recent epidemiologic models suggest New Mexico is likely underreporting cases, which may be a result of low disease awareness in the state or a lack of understanding what populations are at risk. Meanwhile, the neighboring state of Arizona reports the highest number of cases in the country, despite similarities in climate and ecology to New Mexico. In general, very little is known about the health burden of coccidioidomycosis and the geographical distribution of the causative fungal pathogen, Coccidioides spp., in New Mexico. Interestingly, both species of Coccidioides are likely endemic to New Mexico and hybridization of the species may occur. This, in combination with a variety of different ecosystems across the state, makes New Mexico an ideal location for studying the ecology of Coccidioides spp. The objective of our proposal is to generate preliminary data to gain a better understanding of the geographical distribution of Coccidioides spp. in New Mexico, including any regions where hybridization of the species may be occurring. To achieve this, we will collect soil samples throughout New Mexico to: (1) identify what ecosystems are conducive for the growth of Coccidioides and each Coccidioides species in New Mexico and (2) assess whether locations directly surrounding New Mexico’s five largest population centers (Albuquerque, Las Cruces, Rio Rancho, Santa Fe, and Roswell) are endemic to Coccidioides spp. The positive impacts of our proposal are an understanding of what populations are at risk for contracting this disease, where future disease surveillance efforts should be targeted in the state, and where future soil samples should be collected to further explore the genomics and phenotypes of Coccidioides spp. and potential for hybridization. This will help us achieve our long-term goal: to understand the ecology and endemicity of Coccidioides spp. to increase disease awareness, mitigate the negative health impacts from coccidioidomycosis, and ultimately protect the health of all Americans.

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.

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.

Trends in NeuroAI - SwiFT: Swin 4D fMRI Transformer

Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). Title: SwiFT: Swin 4D fMRI Transformer Abstract: Modeling spatiotemporal brain dynamics from high-dimensional data, such as functional Magnetic Resonance Imaging (fMRI), is a formidable task in neuroscience. Existing approaches for fMRI analysis utilize hand-crafted features, but the process of feature extraction risks losing essential information in fMRI scans. To address this challenge, we present SwiFT (Swin 4D fMRI Transformer), a Swin Transformer architecture that can learn brain dynamics directly from fMRI volumes in a memory and computation-efficient manner. SwiFT achieves this by implementing a 4D window multi-head self-attention mechanism and absolute positional embeddings. We evaluate SwiFT using multiple large-scale resting-state fMRI datasets, including the Human Connectome Project (HCP), Adolescent Brain Cognitive Development (ABCD), and UK Biobank (UKB) datasets, to predict sex, age, and cognitive intelligence. Our experimental outcomes reveal that SwiFT consistently outperforms recent state-of-the-art models. Furthermore, by leveraging its end-to-end learning capability, we show that contrastive loss-based self-supervised pre-training of SwiFT can enhance performance on downstream tasks. Additionally, we employ an explainable AI method to identify the brain regions associated with sex classification. To our knowledge, SwiFT is the first Swin Transformer architecture to process dimensional spatiotemporal brain functional data in an end-to-end fashion. Our work holds substantial potential in facilitating scalable learning of functional brain imaging in neuroscience research by reducing the hurdles associated with applying Transformer models to high-dimensional fMRI. Speaker: Junbeom Kwon is a research associate working in Prof. Jiook Cha’s lab at Seoul National University. Paper link: https://arxiv.org/abs/2307.05916

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.

Networking—the key to success… especially in the brain

In our everyday lives, we form connections and build up social networks that allow us to function successfully as individuals and as a society. Our social networks tend to include well-connected individuals who link us to other groups of people that we might otherwise have limited access to. In addition, we are more likely to befriend individuals who a) live nearby and b) have mutual friends. Interestingly, neurons tend to do the same…until development is perturbed. Just like social networks, neuronal networks require highly connected hubs to elicit efficient communication at minimal cost (you can’t befriend everybody you meet, nor can every neuron wire with every other!). This talk will cover some of Alex’s work showing that microscopic (cellular scale) brain networks inferred from spontaneous activity show similar complex topology to that previously described in macroscopic human brain scans. The talk will also discuss what happens when neurodevelopment is disrupted in the case of a monogenic disorder called Rett Syndrome. This will include simulations of neuronal activity and the effects of manipulation of model parameters as well as what happens when we manipulate real developing networks using optogenetics. If functional development can be restored in atypical networks, this may have implications for treatment of neurodevelopmental disorders like Rett Syndrome.

The Impact of Racism-related Stress on Neurobiological Systems in Black Americans”

Black Americans experience diverse racism-related stressors throughout the lifespan. Disproportionately high trauma exposure, economic disadvantage, explicit racism and inequitable treatment are stressors faced by many Black Americans. These experiences have a cumulative negative impact on psychological and physical health. However, little is understood about how experiences of racism, such as discrimination, can mediate health outcomes via their effects on neurobiology. I will present clinical, behavioral, physiological and neurobiological data from Black American participants in the Grady Trauma Project, a longstanding study of trauma conducted in inner-city Atlanta. These data will be discussed in the context of both risk and resilience/adaptation perspectives. Finally, recommendations for future clinical neuroscience research and targets for intervention in marginalized populations will be discussed.

Kamala Harris and the Construction of Complex Ethnolinguistic Political Identity

Over the past 50 years, sociolinguistic studies on black Americans have expanded in both theoretical and technical scope, and newer research has moved beyond seeing speakers, especially black speakers, as a monolithic sociolinguistic community (Wolfram 2007, Blake 2014). Yet there remains a dearth of critical work on complex identities existing within black American communities as well as how these identities are reflected and perceived in linguistic practice. At the same time, linguists have begun to take greater interest in the ways in which public figures, such as politicians, may illuminate the wider social meaning of specific linguistic variables. In this talk, I will present results from analyses of multiple aspects of ethnolinguistic variation in the speech of Vice President Kamala Harris during the 2019-2020 Democratic Party Primary debates. Together, these results show how VP Harris expertly employs both enregistered and subtle linguistic variables, including aspects of African American Language morphosyntax, vowels, and intonational phonology in the construction and performance of a highly specific sociolinguistic identity that reflects her unique positions politically, socially, and racially. The results of this study expand our knowledge about how the complexities of speaker identity are reflected in sociolinguistic variation, as well as press on the boundaries of what we know about how speakers in the public sphere use variation to reflect both who they are and who we want them to be.

What is serially-dependent perception good for?

Perception can be strongly serially-dependent (i.e. biased toward previously seen stimuli). Recently, serial dependencies in perception were proposed as a mechanism for perceptual stability, increasing the apparent continuity of the complex environments we experience in everyday life. For example, stable scene perception can be actively achieved by the visual system through global serial dependencies, a special kind of serial dependence between summary statistical representations. Serial dependence occurs also between emotional expressions, but it is highly selective for the same identity. Overall, these results further support the notion of serial dependence as a global, highly specialized, and purposeful mechanism. However, serial dependence could also be a deleterious phenomenon in unnatural or unpredictable situations, such as visual search in radiological scans, biasing current judgments toward previous ones even when accurate and unbiased perception is needed. For example, observers make consistent perceptual errors when classifying a tumor- like shape on the current trial, seeing it as more similar to the shape presented on the previous trial. In a separate localization test, observers make consistent errors when reporting the perceived position of an objects on the current trial, mislocalizing it toward the position in the preceding trial. Taken together, these results show two opposite sides of serial dependence; it can be a beneficial mechanism which promotes perceptual stability, but at the same time a deleterious mechanism which impairs our percept when fine recognition is needed.

Linking neural representations of space by multiple attractor networks in the entorhinal cortex and the hippocampus

In the past decade evidence has accumulated in favor of the hypothesis that multiple sub-networks in the medial entorhinal cortex (MEC) are characterized by low-dimensional, continuous attractor dynamics. Much has been learned about the joint activity of grid cells within a module (a module consists of grid cells that share a common grid spacing), but little is known about the interactions between them. Under typical conditions of spatial exploration in which sensory cues are abundant, all grid-cells in the MEC represent the animal’s position in space and their joint activity lies on a two-dimensional manifold. However, if the grid cells in a single module mechanistically constitute independent attractor networks, then under conditions in which salient sensory cues are absent, errors could accumulate in the different modules in an uncoordinated manner. Such uncoordinated errors would give rise to catastrophic readout errors when attempting to decode position from the joint grid-cell activity. I will discuss recent theoretical works from our group, in which we explored different mechanisms that could impose coordination in the different modules. One of these mechanisms involves coordination with the hippocampus and must be set up such that it operates across multiple spatial maps that represent different environments. The other mechanism is internal to the entorhinal cortex and independent of the hippocampus.

Bacterial Peptidoglycans from Microbiota in Neurodevelopment and Behavior

Epigenetics and Dementia: Lessons From the 20-Year Indianapolis-Ibadan Dementia Study

Dementia is of global interest because of the rapid increase in both the number of individuals affected and the population at risk. It is essential that the risk factors be carefully delineated for the formulation of preventive strategies. Epigenetics refers to external modifications that turn genes "on" or "off”, and cross-cultural studies of migrant populations provide information on the interplay of environmental factors on genetic predisposition. The Indianapolis-Ibadan Dementia Study compared the prevalence, incidence and risk factors of dementia in African Americans and Yoruba to tease out the role of epigenetics in dementia. The presentation will provide details on biomarkers of dementia, vascular risk factors and the association with apolipoprotein E in the Yoruba. The purpose will be to inspire early career researchers on possibilities and research strategies applicable in African populations

Chondroitin Sulphate Proteoglycans Potentially Induces Reactive Astrogliosis

Inhibition of Chondroitin Sulfate Proteoglycans (CSPGs) to Promote Regeneration in the CNS in Multiple Sclerosis

Environment for precise EEG electrode localization on data from low-cost structured light projector cameras or MRI head scans

FENS Forum 2024

In vitro modelling of immune effector cell-associated neurotoxicity syndrome (ICANS) resulting from CAR T-cell therapy treating haematological cancer

FENS Forum 2024