Aggregates of the protein α-synuclein may initially form in the gut before propagating to the brain in Parkinson's disease (PD). Indeed, our prior work supports that enteroendocrine cells, specialized intestinal epithelial cells, could play a key role in the development of this disease. Enteroendocrine cells natively express α-synuclein and form synapses with enteric neurons as well as the vagus nerve. Severing the vagus nerve reduces the load of α-synuclein aggregates in the brain, suggesting that this nerve is a conduit for gut-to-brain spread. Enteroendocrine cells line the gut lumen; as such, they are in constant contact with metabolites of the gut microbiota. We previously found that when enteroendocrine cells are exposed to nitrite─a potent oxidant produced by gut bacterial Enterobacteriaceae─a biochemical pathway is initiated that results in α-synuclein aggregation. Here, we detail the cellular and molecular mechanisms involved. First, we holistically profiled nitrite-exposed enteroendocrine cells through untargeted proteomics. Next, we performed targeted analyses that specifically probed the mechanistic role of dopamine, as our prior findings suggested that dopamine is critical for nitrite-induced α-synuclein aggregation. In dopamine-free HeLa cells treated with nitrite, α-synuclein aggregation was indeed suppressed. Proteomic signatures in dopamine-free cells treated with nitrite were distinct from those in nitrite-treated enteroendocrine cells, highlighting pathways relevant to intestinal development of PD. Intriguingly, we observed that enteroendocrine cells maintain viability upon exposure to nitrite and in the presence of α-synuclein aggregates. This cellular robustness suggests that these cells may be a reservoir of toxic α-synuclein aggregates. As a possible antidote, our findings show that benserazide and α-methyl tyrosine─chemical inhibitors of dopamine biosynthesis─limited aggregation. Curious about mechanisms of disease etiology outside of α-synuclein aggregation, we also profiled the enteroendocrine cell lipidome─an emerging area of interest in PD research─to motivate future targeted studies delineating the roles of dysregulated lipid metabolism in disease onset. Overall, these studies lay a foundation for mechanistically informed therapeutic targets to prevent the intestinal formation of α-synuclein aggregates before they spread to the brain.

The aggregation of tau protein is a central pathological event in Alzheimer’s disease, and this pathology is hypothesized to spread via a prion-like mechanism driven by tau “seeds”. While aggregated tau from Alzheimer’s disease brains is known to contain age-related d-isomerized aspartic acid (d-Asp) residues, it remains unknown how this modification affects the seeding activity that drives disease propagation. Here, we investigated the impact of site-specific d-isomerization within R2 and R3 tau repeat-domain peptides, which form the core of tau fibrils. We demonstrate that the stereochemical integrity of these peptides is critical for their seeding function. d-isomerization at Asp314 within the R3 peptide seed severely impaired its ability to template the fibrillization of full-length tau in vitro. This finding was validated in a cellular model, where R3 seeds containing d-Asp314 were significantly less potent at inducing the formation of phosphorylated tau aggregates compared to wild-type seeds. Our results establish that Asp d-isomerization within tau seeds acts as a potent attenuator of their pathological seeding activity, suggesting this spontaneous modification may intrinsically modulate the progression of Alzheimer’s disease.

Preeclampsia (PE) is the onset of hypertension in pregnancy with systemic involvement; PE poses significant risks of cerebral complications, including eclampsia and long-term cognitive impairment. This review explores the potential of neurological biomarkers—neurofilament light chain (NfL), neuron-specific enolase (NSE), S100 Calcium Binding Protein B (S100B), and tau—as indicators of cerebral injury in PE. A literature search identified studies comparing biomarker levels in preeclamptic and healthy pregnancies. Findings reveal elevated plasma levels of NfL, NSE, S100B, and Tau in PE, with NfL showing the strongest association with blood–brain barrier dysfunction, cognitive symptoms, and disease severity. Variations between plasma and cerebrospinal fluid levels suggest impaired BBB integrity rather than increased central nervous system production. Despite promising correlations, limitations include small sample sizes, lack of standardized thresholds, and limited CSF data. While NfL emerges as a particularly promising marker for risk stratification, further research is needed to validate the clinical utility of these biomarkers in routine PE management.

Understanding the molecular composition of the brain at cellular level is essential for deciphering the metabolic alterations associated with brain diseases. Furthermore, the different prevalence of some neurological diseases between males and females highlight the importance of incorporating gender factor in such studies. Here, we demonstrate that using imaging mass spectrometry in negative polarity it is possible to isolate and characterize the lipidome of specific neuronal populations in the mouse brain, including the locus coeruleus (LC), mesencephalic neurons and the substantia nigra pars compacta (SNc). Neuronal identity was validated through immunofluorescence on adjacent serial sections. Comparative analysis revealed that each neuronal population presents a distinct and well-defined lipidic profile, with differences extending across all lipid classes analyzed. Regarding sex-based differences, we found discrete differences in phosphatidylcholine/phosphatidylethanolamine-ether, phosphatidylinositol and sphingomyelin LC neurons. Lipidomic differences were more pronounced in mesencephalic neurons, whereas no significant sex-dependant differences were observed in SNc lipid composition. These findings lay the groundwork for future studies aimed at identifying lipid metabolic dysregulations in the context of neurodegenerative diseases.

Characterizing spinal cord atrophy in multiple sclerosis patients without disease activity or brain atrophy progression.

A causal bidirectional selective state space model for imaging genetics in neurodegenerative diseases.

Gallyas silver staining and AT8 immunostaining are frequently used to stage tau pathology in post-mortem Alzheimer disease (AD) brains. Because of differential labeling of tau aggregation types, however, these methods result in strikingly different patterns of pathology when used in adjacent sections of the same brain. How Gallyas versus AT8 staining impacts the quantification of tau pathology distribution across brain areas and affect analysis of tau and cognitive impairment is unknown. We performed a side-by-side comparison of AT8 versus Gallyas-stained hippocampal sections from 34 patients from the University of Southern California (USC) Alzheimer's Disease Research Center (ADRC). Using images of Gallyas and AT8 stained sections, we computed overall tau density in hippocampal subregions as well as manual tangle counts and compared each of them to cognitive variables like Clinical Dementia Rating and Mini Mental State Exam in the patients. We found that AT8 had a much higher density of staining overall, and the two stains had differing distributions, with increased AT8 in Brodmann area 35 and CA1. Both stains related to cognition differentially, and Gallyas density was significantly related to post-mortem interval. These findings contribute to our understanding of how tau pathology stain choice might influence the characterization of AD.

Evidence linking modifiable risk factors to age-related brain diseases, such as dementia, stroke, and depression (DSD), is robust, yet limited regarding long-term change in modifiable risk factors in association with these conditions, particularly in real-world settings. This study aimed to assess whether longitudinal changes in modifiable brain health risk factors were associated with reduced risk of DSD. We analyzed UK Biobank data (2006-2019) from 155,469 participants with general practitioner-linked data. The Brain Care Score (BCS) assesses 12 modifiable risk factors across lifestyle, physical, and social-emotional domains. Longitudinal BCS measurements were derived from repeated general practitioner (GP)-recorded measurements. Changes in the BCS were modeled using linear mixed-effects models, and associations with DSD were evaluated using multivariable Cox models, adjusting for baseline BCS and genetic risk (polygenic risk scores for stroke and depression, and APOE genotype for dementia). Among 155,469 participants (median age = 51 years, 54.3% women), the median annual BCS change was 0.14 (Q1-Q3 = 0.008-0.30) points over a median follow-up of 12.3 years (Q1-Q3 = 11.5-13.1 years). Over time, 82.1% improved their BCS, 12.9% remained stable, and 5.0% worsened over time. Each 1-point annual increase in the BCS was associated with 4% lower risk of incident age-related brain diseases (hazard ratio [HR] = 0.96, 95% confidence interval [CI] = 0.95-0.97). In this large real-world cohort, improvements in modifiable risk factor profiles were associated with lower incidence of DSD, regardless of genetic risk or baseline BCS. Our results provide important information for communicating with patients about the brain health benefits of improving risk factor profiles. ANN NEUROL 2026.

SummaryThe human neocortex underlies higher cognition and is the engine of complex thought. Yet our understanding of its neuronal diversity is limited by sparse access to tissue, inconsistent sampling across studies, and a lack of multiple modality data. Although single-cell transcriptomic taxonomies are an important framework for characterizing cell type diversity, transcriptomic information alone cannot reveal the cellular properties that define neuronal computations. To address this, we performed Patch-seq, a method for collecting Morphology, Electrophysiology, and Transcriptomic data from a single neuron. We focused on glutamatergic, neocortical, excitatory neurons, the principal long-range projecting neurons of the cortex, and systematically integrated their morphoelectric features with transcriptomic identity. In combination with spatial transcriptomic data, we interrogated 39 of 42 transcriptomically-defined neuron types with a layer-centric perspective. Morphoelectric properties, such as cortical depth, apical dendrite structure, and excitability clearly distinguish transcriptomic subclasses and support many finer transcriptomic types. Morphoelectric properties are influenced by spatial location in supragranular layers, while deeper layers exhibit greater heterogeneity. Cross-species comparisons reveal conserved subclass organization but pronounced differences in apical dendrite arborization between mouse and human, and surprising similarities between human and macaque. Together, these datasets provide a unified multimodal reference that advances our understanding of human cortical circuitry and establishes a foundation for experimental and computational studies of human brain function and disease.

Grey matter structure is central to neuroscience, as cellular morphology varies by type and is influenced by neurological conditions. Understanding these variations is essential for studying brain function and disease mechanisms. Diffusion-weighted MRI (dMRI) offers a non-invasive way to examine cellular microstructure, but its accuracy depends on identifying which morphological features influence its measurements. Despite increasing interest, no systematic study has defined the key neural cell features relevant to dMRI interpretation. Here, we analyzed over 11,800 three-dimensional cellular reconstructions across three species and nine cell types, establishing reference values for critical traits grouped into structural, shape, and topological categories. We also identified which of these traits are most relevant to dMRI sensitivity. In addition, we provide high-resolution 3D surface meshes representative of each cell type and species. These meshes, compatible with Monte Carlo simulators, offer a valuable resource for modeling and interpreting gray matter microstructure Carlo simulators, offering a valuable resource for the modelling community.

BackgroundNeuroinflammation is a key pathological driver of neurodegenerative diseases, including Alzheimer's disease (AD). Positron emission tomography (PET) with tracers targeting the translocator protein (TSPO) enables the in vivo quantification of microglial activation. Currently, direct comparison between TSPO‐PET tracers in AD have not been performed. Here, we tested a pipeline to quantitatively compare different TSPO‐PET tracers in clinically‐matched cohorts of patients with AD across multi‐centre data.Method32 people with AD and 15 controls underwent [11C]PK11195‐PET at the University of Cambridge, 45 people with AD and 19 controls underwent [18F]GE180‐PET at Ludwig‐Maximilians‐University of Munich, and 25 people with AD and 25 controls underwent [11C]PBR28‐PET at McGill University. Participants across the centres were matched for age, sex, and clinical severity. Pre‐processing of scans was harmonised across centres, and regional SUVr of tracers were obtained using a shared reference region and atlas. Z‐scores of regional SUVr values for each participant were calculated based on centre‐specific controls. Dissimilarity and clustering analyses were performed to assess the effectiveness of the standardisation pipeline. Figure 1 outlines the methodology.ResultClustering analyses identified no tracer‐specific patterns in the distribution of z‐scores following standardisation. Across all tracers, regional z‐scores of the AD groups were significantly different between tracers in 7 of 41 brain regions, while no differences were found for controls (Figure 2). Full factorial analysis found a main effect of tracer; however, these were due to interaction effects with disease group, sex, age, and brain region and explained very little of the variance. Pattern similarity between representational similarity matrices found moderate correlations between the three tracers in patient and control groups.ConclusionThese results suggest that our pipeline is effective at harmonising TSPO‐PET tracers and standardising the regional quantification of microglial activation in the context of different AD cohorts. Dissimilarity analyses identified small tracer‐specific effects, however. Ongoing work aims to optimize this pipeline in order to compare and combine TSPO‐PET tracers in other tauopathies (ie PSP) and to identify thresholds of “inflammation severity” related to clinical outcomes.

BackgroundDysfunctional allostatic‐interoception, altered processing of bodily signals in response to environmental demands, occurs in behavioural‐variant frontotemporal dementia (bvFTD) patients. Previous research, however, has focused on static measures of interoception (e.g., heart‐evoked potential, HEP). These measures do not capture the dynamic nature of interoception, unlike intrinsic neural timescales. Intrinsic neural timescales refers to the temporal durations over which information is processed within the spatiotemporal hierarchy of the brain, with shorter timescales representing more rapid processing. We hypothesised that longer intrinsic neural timescales of interoception would occur in bvFTD patients, evidencing dysfunctional allostatic‐interoception.MethodOne‐hundred and twelve participants (31 bvFTD patients, 35 Alzheimer's disease patients, AD and 46 healthy controls) completed a well‐validated task measuring cardiac‐interoception and exteroception. Simultaneous EEG and ECG were recorded. Intrinsic neural timescales were measured via the autocorrelation window (ACW) of broadband EEG signals from each heartbeat and a time‐lagged version of itself. Spatiotemporal clustering analyses identified clusters with significant between‐group differences in each condition. HEP modulation analyses were also conducted and covaried for to investigate potential relationships between HEP and ACW. Voxel‐based morphometry was used to target the allostatic‐interoceptive network. Neuropsychological tests of cognition and social cognition were assessed.ResultIn bvFTD patients, longer interoceptive‐ACWs than controls were observed in the bilateral fronto‐temporal and parietal regions (Figure 1). In AD patients, longer interoceptive‐ACWs than controls were observed in central and occipitoparietal brain regions (Figure 1). No differences were observed during exteroception. In bvFTD patients only, longer interoceptive‐ACW was linked to worse sociocognitive performance. Our interoceptive‐ACW results, remained the same when accounting for HEP modulation. Structural neural correlates of interoceptive‐ACW in bvFTD involved the anterior cingulate, insula, orbitofrontal cortex, hippocampus, and angular gyrus (Figure 2). No structural differences emerging in AD.ConclusionOur findings suggest a core allostatic‐interoceptive deficit occurs in people with bvFTD, captured by altered brain dynamics of intrinsic neural timescales. In AD, it is possible that a more generalised disruption of brain oscillation occurs. Altered interoceptive intrinsic neural timescales may provide a neurobiological mechanism underpinning the complex behaviours observed in bvFTD patients. Our findings support synergistic models of brain disease and can inform clinical practice.

The blood-brain barrier (BBB) renders the delivery of nanomedicine in the brain ineffective and the detection of circulating disease-related DNA from the brain unreliable. Here, we demonstrate that microbubble-enhanced focused ultrasound (MB-FUS) mediated BBB opening, supported by large-data models predict sonication regimens for safe and effective BBB opening. Importantly, a closed-loop MB-FUS controller augmented by machine learning (ML-CL) expands the treatment window, as compared to conventional controllers, by persistently and proactively maximizing the BBB permeability while preventing tissue damage. By successfully scaling up from mice to rats and from healthy to diseased brains (glioma), ML-CL rendered the BBB permeable to large nanoparticles and markedly improved the release and detection of reporter gene DNA from tumors in blood. Together, our findings reveal the potential of data-driven feedback to support the development of next-generation AI-powered ultrasound systems for safe, robust, and efficient nanotheranostic targeting and treatment of brain diseases.

Over the past decade, increasing attention has been paid to neurofluid (NF) drainage in the brain, particularly to the glymphatic system and intramural periarterial drainage (IPAD) pathway, which are responsible for substance transport in the brain and are highly dependent on astrocyte function. The dysfunction of these drainage pathways can lead to the accumulation of toxic substances and fluids, and contribute to various brain diseases, such as stroke and Alzheimer's disease. Since astrocytes in the brain closely connect to the microvascular system with their endfeet, in this work, the roles of astrocytes in regulating the glymphatic system and IPAD pathway and their dysfunction in neurodegenerative diseases have been comprehensively reviewed. Additionally, the effects of aquaporin 4, a water channel protein located on astrocytic endfeet, on these two pathways are explored. Furthermore, the possible therapeutic strategies for brain diseases targeting the NF drainage systems have also been proposed and thoroughly discussed.

The risk allele rs10191329*A is associated with disease severity and brain atrophy in people with multiple sclerosis (MS). We investigated the association of rs10191329 with age-related brain atrophy in a population-based cohort using 10,308 magnetic resonance imaging (MRI) scans of 4,815 participants aged ≥ 45 years without MS in cross-sectional and longitudinal analyses. We observed associations between the rs10191329*A allele and lower total brain volume and gray matter volume in middle-aged (< 55 years of age), but not in older participants. These data suggest that rs10191329*A contributes to earlier onset of atrophy in the general population, and that mediating mechanisms of accelerated neurodegeneration extend beyond MS. ANN NEUROL 2026.

T-cell immunoglobulin and mucin-domain containing-3 orchestrates myeloid dysfunction across brain aging and disease.

Neuroinflammation is evident in Alzheimer's disease (AD) brains, exacerbating the pathology and ensuing cognitive deficits in patients. The prostaglandin-E2 receptor EP2 emerged as a neuroinflammatory target in several neurodegenerative diseases, including AD. Antagonism of EP2 mitigates neuroinflammation and cognitive deficits in status epilepticus and stroke models. Here, we investigated the efficacy of a potent and selective EP2 antagonist TG11-77.HCl on the cognitive behavior and neuroinflammation in a two-hit 5xFAD mouse model of AD. We exposed adult 5xFAD mice on B6SJL genetic background and their nontransgenic littermates to a low dose of lipopolysaccharide and administered TG11-77.HCl or the vehicle in the drinking water for 12 weeks. Mice were subjected to Morris water maze and Y-maze testing during their last week of drug treatment. Blood samples were subjected to complete blood count (CBC) analysis and brain tissues were processed to examine the levels of inflammatory transcripts and glial marker expression (mRNA), followed by the quantification of congophilic amyloid deposition and microglial activation (IBA+) in the brain by immunohistochemistry. TG11-77.HCl treatment enhanced the spatial memory performance and ameliorated mRNA expression of proinflammatory mediators, chemokines, and cytokines in the neocortex of 5xFAD males only and attenuated astroglia and microglia activation in both male and female 5xFAD mice and the congophilic amyloid load in 5xFAD males only. CBC analysis revealed no changes in peripheral inflammation, irrespective of sex, on treatment with TG11-77.HCl. This study reveals sex-specific protection of selective EP2 antagonism in a two-hit mouse model of AD and supports a prudent therapeutic strategy against neuroinflammation and associated cognitive impairment in AD.

Multi-modal learning is extensively applied to diagnose brain diseases such as epilepsy and Alzheimer's disease. However, incomplete multi-modal data, where some modalities are unavailable or difficult to collect, limits the effectiveness of conventional methods. Additionally, existing approaches often overlook semantic relationships between neighbors with the same-label and latent information in missing modalities. To address these challenges, we propose an adjacent-aware distillation recovery framework designed for incomplete multi-modal learning, with a focus on diagnosing representative brain diseases, i.e. epilepsy and Alzheimer's disease. The key novelty of our framework lies in its joint design of adjacent-aware modality recovery and multi-modal representation learning in a single end-to-end pipeline. Specifically, we introduce a label-guided adjacent-aware recovery module that uses a self-attention mechanism to exploit neighbor semantics and generate distribution-consistent features for high-quality modality reconstruction. The recovered features are then refined through a knowledge distillation pathway into a modality generator, enhancing generalization under severe data incompleteness. For multi-modal representation learning, the recovered modality information is fused with the original incomplete information to enhance feature extraction and representation. Extensive experiments demonstrate the effectiveness of our method in diagnosing epilepsy and Alzheimer's disease.

Qualitative and quantitative analysis of microplastics and nanoplastics in healthy human central nervous system and its blood-brain barrier transmission efficiency-A pilot study.

Currently, single-target therapy and difficulty in brain drug delivery gravely impede the treatment of Alzheimer's disease (AD). The promising development of microRNA-124-3p (miR-124-3p) serves as a possibility for multiple therapeutic approaches for AD. However, the effective delivery of miR-124-3p to AD-affected brain regions remains a major challenge, primarily due to the blood-brain barrier (BBB) and the inherent instability of therapeutic miR-124-3p. Herein, we engineered miR-124-3p-enriched microglial exosomes (Exo-124-3p) as a biomimetic nanomedicine for the multifunctional treatment of AD. Exo-124-3p can traverse the BBB and facilitate activated-microglia targeting. Subsequently, the on-demand release of miR-124-3p from Exo-124-3p decreased the aggregation of β-amyloid (Aβ) plaques, attenuated the activation of microglia/astrocytes, and exhibited a valuable neuroprotective effect, thereby remolding the AD focal microenvironment. Notably, the in vivo results demonstrated that Exo-124-3p significantly improved the cognitive function in an AD mouse model. Mechanistically, it was elucidated that Exo-124-3p can bind to the 3'UTR region of MEKK3, ultimately inhibiting the MEKK3/NF-κB signaling pathway, thereby ameliorating AD neuroinflammation. Consequently, this study not only provides a promising therapeutic approach for AD combinational therapy, but also advances the development of miRNA delivery in other brain diseases.