Memory and synaptic plasticity are regulated by cyclic guanosine monophosphate (cGMP) signaling. Phosphodiesterase 5 (PDE5) inhibitors, such as vardenafil (VDF), elevate intracellular cGMP levels and represent potential therapeutics for cognitive disorders, including Alzheimer's disease (AD). However, the signaling pathways linking PDE5 inhibition to excitatory synaptic transmission remain incompletely defined. In particular, whether PDE5 inhibition engages amyloid-β (Aβ)-dependent mechanisms to regulate glutamatergic synapses remains unclear. Using biochemical, immunocytochemical, and electrophysiological approaches in neuronal systems, we show that VDF activates an Aβ-cellular prion protein (PrP)-dependent pathway that enhances presynaptic glutamatergic function. Specifically, VDF increases Aβ levels, leading to a marked reduction in PrP surface exposure, an effect prevented by blocking Aβ production. We further demonstrate that PrP facilitates Aβ internalization, supporting a dynamic coupling between Aβ and PrP trafficking. Functionally, VDF selectively augments presynaptic excitatory transmission, as indicated by increased VGLUT1 puncta density and elevated miniature excitatory postsynaptic current (mEPSC) frequency, without changes in mEPSC amplitude. Disrupting Aβ-PrP interaction abolishes these presynaptic effects, establishing this axis as a required mediator of the synaptic response to VDF. Together, these findings identify a functional link between PDE5 inhibition and Aβ-PrP-dependent modulation of presynaptic glutamatergic transmission, expanding the framework of Aβ-PrP signaling beyond neurotoxicity and highlighting its context-dependent role in synaptic regulation.

BACKGROUND: Evidence linking residential environments to Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains limited. METHODS: We followed 426,220 dementia-free UK Biobank participants for a median 13.6 years. Cox models evaluated associations between green, blue spaces, and natural environment (300 and 1000 m buffers) and AD/MCI risk, alongside exploratory mediation and gene-environment interactions. RESULTS: Incident cases included 3513 AD and 864 MCI. For AD, higher green space, blue space, and natural environment within 300 m lowered risk (decreases of 5.8, 0.8, and 5.7% per IQR, respectively). At 1000 m, only green space (6.7%) and natural environment (5.7%) remained inversely associated. Blue space exhibited a non-linear AD association. For MCI, green and natural spaces consistently lowered risk across both buffers (14.9-22.2% reductions); blue space was non-significant. Analyses showed limited mediation by air pollutants and selective additive gene-environment synergy. CONCLUSION: Higher residential green space and natural environment are observationally associated with reduced AD and MCI risks, whereas blue space associations with MCI remain inconclusive. Underlying mechanisms and exploratory gene-environment synergies require further validation.

PURPOSE: Caring for persons living with dementia (PLwD) involves high levels of physical demands and emotional burden that may undermine caregivers' sleep quality. Few studies have examined sleep among African Americans caregivers of PLwD despite their underrepresentation in dementia research and poorer sleep outcomes compared to other racial and ethnic groups. This study examines the relationships between caregiving stressors and sleep and the moderating effect of resilience on these associations among African American caregivers of PLwD. MATERIALS AND METHODS: Data were drawn from a community study of 88 African American caregivers of PLwD. Caregiving stressors included assistance with daily activities and role overload. Resilience refers to the ability to adapt to or recover from adversity. Sleep outcomes included sleep disturbance and sleep satisfaction. Multiple linear regressions with interaction terms were used. RESULTS: Assistance with daily activities and role overload were positively associated with sleep disturbance. These associations were stronger at higher levels of resilience than at lower levels. DISCUSSION: Findings reveal the nuanced role of resilience among African American caregivers of PLwD; its health benefits may be conditional, particularly as caregiving stressors increase. Heightened resilience may overemphasize self-reliance, increasing individual burden and reducing support network use, and ultimately increasing vulnerability to sleep disturbance. CONCLUSION: Findings highlight implications for social work by underscoring the need to understand how resilience operates within the cultural context of the African American community and to develop culturally responsive practice and policies that address caregiving stressors and strained resilience among African American caregivers of PLwD.

INTRODUCTION: Adverse social conditions across the life course influence brain aging and dementia, yet their compounded impact on clinical phenotypes remains underexplored, particularly in Latin America, where social inequality and dementia burden are high. METHODS: We studied 3941 individuals from six Latin American countries, including cognitively unimpaired controls (CU), Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD). A life-course questionnaire captured eight domains of social vulnerability, used to derive a social vulnerability index and latent vulnerability profiles. Brain health was characterized across 37 cognitive, functional, mental health, and dementia severity indicators. RESULTS: Higher vulnerability was mostly associated with executive and memory deficits in CU, cognitive and functional impairment in AD, and social cognition and neuropsychiatric symptoms in FTLD. Multidimensional brain health was affected across groups. DISCUSSION: Compounded social vulnerability is a key determinant of clinical expression in aging and dementia, underscoring the need for life-course-informed and equity-oriented dementia models.

INTRODUCTION: Adults with Down syndrome (DS) are at risk for Alzheimer's disease (AD), yet identifying the preclinical phase remains challenging. Intraindividual cognitive variability (IICV) may be a sensitive marker of early AD-related changes but remains understudied in DS. METHODS: Adults from the Alzheimer's Biomarker Consortium-DS (ABC-DS) study (N = 460, mean age 43.3 years; 45.7% female) were included. Generalized linear models examined whether baseline IICV predicted incident mild cognitive impairment (MCI)/dementia, cognitive decline, and amyloid and tau positron emission tomography outcomes, adjusting for demographics, intellectual disability, apolipoprotein E ε4, site, assessment interval, and mean cognitive performance, with Bonferroni correction. RESULTS: Greater IICV predicted incident MCI/dementia (odds ratio = 4.63 to 5.13, p < 0.05), greater amyloid burden, early tau accumulation, and higher tau across Braak stages, independent of mean cognition. Exploratory analyses suggested sex-specific interactions with tau outcomes. DISCUSSION: IICV is a sensitive marker of dementia risk and cognitive resilience in DS, with potential utility for secondary prevention and trial enrichment.

INTRODUCTION: Imaging-based cerebral small vessel disease (CSVD) summary scores quantify CSVD burden. This study characterized CSVD scores and assessed their cognitive associations in older adults with various neurodegenerative diseases and cognitive profiles. METHODS: Baseline data from 958 Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) study participants were analyzed (19.4% cognitively normal, 14.9% subjective cognitive decline, 40.3% mild cognitive impairment, 25.4% dementia). MRI markers of cerebral vascular injury (lacunes, microbleeds, white matter hyperintensities [WMHs], and enlarged perivascular spaces) were visually rated, and a cumulative CSVD score was generated. Cognition was measured using the Montreal Cognitive Assessment (MoCA), Clinical Dementia Rating-Sum of Boxes (CDR-SB), and a composite neuropsychological battery test z-score. RESULTS: Higher CSVD scores were associated with greater Hachinski ischemic scores, poorer MoCA performance, worse CDR-SB, and lower composite z-scores. Associations were strongest for cognitive domains of executive function, attention, and learning. DISCUSSION: CSVD burden may further contribute to poorer cognition across neurodegenerative conditions and cognitive profiles.

INTRODUCTION: The extent to which non-pathological aging influences plasma biomarkers remains unclear. Here, we investigate factors influencing plasma p-tau217 levels in cognitively unimpaired (CU), amyloid-beta-negative (Aβ-) individuals. METHODS: Plasma p-tau217 was measured in CU Aβ- positron emission tomography-negative (PET-) participants using two immunoassays (ALZpath n = 360 and LUMIPULSE G1200 n = 73). Associations between p-tau217 and age groups (60-69, 70-79, and 80+ years), apolipoprotein E (APOE) genotype, and gender were evaluated. RESULTS: ALZpath plasma p-tau217 showed a non-pathological age-related increase (p < 0.001), and increased percentage within the intermediate zone with age. Lumipulse p-tau217 showed an increase in the percentage of subjects with positive results with age, however, this trend was not significant (p > 0.05). Men had higher levels of p-tau217 only with the ALZpath assay (p = 0.02; Lumipulse: p = 0.81). No significant associations were found between p-tau217 and APOE genotype. DISCUSSION: Our results highlight the importance of incorporating age and sex into the interpretation of plasma p-tau217 particularly in preclinical stages.

INTRODUCTION: The WW-FINGERS network has demonstrated the efficacy of multidomain non-pharmaceutical interventions (NPIs) but left their real-world implementation largely unexplored, prompting this study in Changxing County to identify key determinants and develop actionable strategies for community-based delivery. METHODS: An embedded mixed-methods retrospective evaluation using the Consolidated Framework for Implementation Research (CFIR) was conducted. Data from 42 stakeholders across six communities were analyzed via a hybrid deductive-inductive approach and coincidence analysis (CNA). Strategies were matched using the ERIC compendium and refined by a stakeholder panel. RESULTS: We identified 202 determinants, revealing six core facilitator themes (e.g., policy-academia-community synergy) and six barrier themes(e.g., unsustainable funding). CNA delineated potential pathways. Three strategy bundles were finalized: Capacity Building, Collaborative Network Building, and an AI-enabled digital platform. DISCUSSION: This study provides a practical, theory-informed framework for implementing complex NPIs, bridging the science-to-practice gap in dementia prevention. The AI-enabled platform offers a forward-looking approach for sustained delivery.

The accumulation of pathogenic tau protein is linked to cognitive decline and neuronal loss in Alzheimer's disease (AD), with tau oligomers identified as particularly neurotoxic. The 51 kDa FK506-binding protein (FKBP51) stabilizes these toxic tau oligomers and has been identified as a risk factor for several neurodegenerative diseases. FKBP51 levels increase with age and are especially high in AD brains, suggesting its involvement in disease progression. The development of the selective FKBP51 inhibitor, SAFit2, which can cross the blood-brain barrier, has shown promise in reducing stress hormones, improving stress responses, and mitigating protein-related pathologies in other neurodegenerative models. However, the effects of SAFit2 on tauopathies, such as those seen in AD, have not yet been investigated. Here, the effects of the FKBP51-selective inhibitor, SAFit2, were evaluated in PS19 tau transgenic mice. Mice received a 28-day regimen of SAFit2, followed by comprehensive behavioral, neuropathological, and proteomic analyses. SAFit2 demonstrated effective brain penetrance, with sex-dependent pharmacokinetics. Treatment slowed cognitive decline and depressive-like behavior, with pronounced benefits in male PS19 mice, including improved spatial memory and reduced tau oligomer burden. In females, SAFit2 promoted clearance of AT8-positive tau multimers with some benefit to recognition memory. Proteomic profiling revealed distinct molecular signatures underlying these sex-specific responses: males exhibited upregulation of RNA processing and ribosomal proteins, while females showed restoration of calcium signaling and synaptic drivers. Notably, behavioral recovery occurred independently of widespread neuroinflammation reversal. These findings provide the first in vivo evidence that FKBP51 inhibition by SAFit2 induces sex-specific remodeling of the brain proteome. This study also provides further evidence for the therapeutic benefits of targeting FKBP51 for tauopathies.

BACKGROUND: Depression and anxiety are prevalent mental disorders that contribute significantly to global disability. While the MIND diet has demonstrated benefits in preventing Alzheimer's disease, its potential impact on mental health outcomes remains unclear. This study systematically reviews evidence on the association between adherence to the MIND diet and symptoms of depression, anxiety, and stress. METHODS: We conducted a systematic search of PubMed, Web of Science, Scopus, and Google Scholar databases up to August 2025 to identify observational and interventional studies examining the relationship between the MIND diet and depression, anxiety, or stress. Twenty one eligible studies-including eleven cross-sectional designs-were included. RESULTS: Of the 21 studies, twelve reported a significant inverse association between adherence to the MIND diet and depression symptoms, seven found similar associations with anxiety, and three with stress. However, findings were inconsistent, likely due to heterogeneity in study design, assessment tools, and populations. CONCLUSION: Current evidence suggests that greater adherence to the MIND diet may be associated with lower levels of depression and anxiety, but the overall quality and consistency of the evidence are limited. Well-designed longitudinal and clinical trials are needed to confirm these potential benefits.

BACKGROUND: Pain may be linked to neuropsychiatric symptoms in dementia but the nature of these associations is unclear. The aims of this study were to examine the concurrent validity of pain scales and to investigate the relationship between pain and neuropsychiatric symptoms in community-dwelling people with dementia. METHODS: This study recruited dyads of people with dementia and their caregivers. Questionnaires measuring pain (Numeric Rating Scale, Brief Pain Inventory Short Form, EQ5D3L) and cognition (Mini- Addenbrookes Cognition Examination) were completed by people with dementia. Dyad partners completed the Neuropsychiatric Inventory Questionnaire (NPI-Q). We examined the degree of agreement between different measures of pain and compared the NPI-Q score and items between people with dementia with and without troublesome pain (NRS ≥ 4, NRS < 4), and between those with single and multisite pain. RESULTS: The study recruited 35 individuals with dementia (49% female, mean age 80 with a range of 65-91 years, mean Mini-ACE 13.6/30) and 35 dyad partners. 66% of people with dementia had troublesome pain and compared to those without troublesome pain they were not significantly different in terms of age, sex, frailty, or other demographic variables, but were more likely to take regular paracetamol. Agreement between the NRS and EQ5D3L pain score was good (Cohen's kappa 0.70, p<0.001), as was agreement between the NRS and BPI-SF with a close to 0 mean difference between the scores on a Bland-Altman plot. The total NPI-Q score was not significantly associated with the presence of troublesome pain. Of all NPI-Q symptoms, only disinhibition showed associations with both painseverity and multisite pain (44% vs 0% and 38% vs 0% respectively, both p<0.05). CONCLUSION: Community-dwelling people living with dementia can self-report pain using a range of pain scales. Certain neuropsychiatric symptoms may be more common in the presence of pain but requires further study with larger cohorts.

BACKGROUND: Delirium is a frequent manifestation of acute brain dysfunction in critically ill patients with bloodstream infections (BSI). While the association between sepsis and delirium is well-established, pathogen-specific neurotoxic effects, particularly those induced by Staphylococcus aureus (S. aureus), remain inadequately elucidated. This study aimed to evaluate the independent association between S. aureus BSI and the risk of 7-day incident delirium in critically ill adults. METHODS: A retrospective cohort study was conducted using the MIMIC-IV database, including 3,226 adult patients with confirmed BSI. To minimize confounding bias, a "doubly robust" estimation approach was employed, combining Inverse Probability of Treatment Weighting based on Covariate Balancing Propensity Scores (IPTW-CBPS) with multivariable adjustment. Fine-Gray proportional subdistribution hazard models were utilized to assess the association between pathogen status and 7-day delirium, accounting for death as a competing risk. Explainable machine learning using the eXtreme Gradient Boosting (XGBoost) algorithm and Shapley Additive exPlanations (SHAP) value analysis was performed to identify feature importance. Sensitivity analyses for the 3-day acute risk and methicillin-resistant Staphylococcus aureus (MRSA) phenotype were also conducted. RESULTS: Among 3,226 patients, 618 (19.2%) were identified with S. aureus BSI. In the fully adjusted Fine-Gray model, compared with Gram-negative infections, S. aureus BSI was robustly and independently associated with an increased risk of 7-day incident delirium (sHR 1.39; 95% CI 1.11-1.74; p = 0.005). This association was even more pronounced within the 3-day acute window (sHR 1.60; 95% CI 1.27-2.02; p < 0.001). Conversely, compared with Gram-negative BSI, the MRSA phenotype showed no significant independent association with delirium risk (sHR 1.12; 95% CI 0.81-1.55; p = 0.488). SHAP analysis identified S. aureus infection as the fourth most influential feature for delirium, surpassing age and sedative exposure. Subgroup analyses revealed that the pathogen-specific impact was significantly more prominent in patients with lower baseline illness severity (SOFA < 5) and those without a history of dementia (P for interaction < 0.001 and 0.004, respectively). SHAP value analysis further confirmed this finding by demonstrating a higher risk contribution of S. aureus in patients with lower SOFA scores. CONCLUSIONS: S. aureus BSI is a robust independent risk factor for 7-day incident delirium compared with Gram-negative BSI, with the hazard being more pronounced within the first 3 days of infection. Notably, compared with Gram-negative BSI, the MRSA phenotype was not independently associated with delirium risk. Identifying S. aureus as a critical driver of early brain dysfunction provides a pathogen-specific framework for risk stratification. Consequently, clinicians should prioritize early neurocognitive monitoring and targeted neuroprotection (e.g. the ABCDEF bundle) for all patients with S. aureus infection.

Whether individual-level cognitive trajectories in Parkinson's disease are predictable remains unresolved. Here, we provide convergent evidence that measurement fidelity, rather than model complexity, governs the prediction ceiling. We evaluated ten machine learning paradigm families across 26 configurations in two independent cohorts-the Parkinson's Progression Markers Initiative (PPMI, N = 1018) and the National Alzheimer's Coordinating Center (NACC, N = 523). Motor subtype classification succeeded as a positive control (AUROC = 0.869), while cognitive trajectory prediction from the Montreal Cognitive Assessment remained uninformative (AUROC = 0.581) across all methods, including 42 genetic features. Synthetic experiments confirmed that models recover trajectories at high signal-to-noise ratios but collapse uniformly at levels present in clinical screening data. Replacing coarse screening with detailed neuropsychological tests improved prediction in both cohorts (PPMI: Symbol Digit Modalities Test AUROC = 0.725 vs. MoCA 0.596; NACC: Logical Memory AUROC = 0.684 vs. MMSE 0.648). Within-patient trajectory R² = 0.20 for MoCA domains confirmed that approximately 80% of score variance represents non-signal variance. These findings redirect the clinical AI agenda from algorithm development toward measurement innovation: higher-frequency, higher-fidelity cognitive instruments are necessary before individual-level prediction becomes feasible.

Interventions targeting social and health-related risk factors are thought to reduce the risk of cognitive decline and dementia in older age. Despite well-known social, economic, and cultural differences across European countries, little is known about how these factors influence associations with memory function in different geographical contexts. This study examined the relationship between five social and health-related risk factors, namely living alone, physical inactivity, obesity, depression, and cardiometabolic and cardiovascular conditions, and memory function across Europe. Data came from the Survey of Health, Ageing, and Retirement in Europe (SHARE), a cross-national study of older adults. The sample included cross-sectional data for 102,851 adults aged 50-102 years from 20 European countries, grouped into four regions: Northern, Western, Eastern, and Southern Europe. Memory function was assessed using a sum score of immediate and delayed recall tests. A flexible Bayesian machine learning approach for multilevel data was applied to assess heterogeneity of associations in the total sample and in analyses stratified by education and age. All five social and health-related risk factors were negatively associated with memory overall, but the strength and, for some factors, the direction of these associations varied across regions. In particular, the associations for living alone, obesity, and physical inactivity differed between Eastern and Southern Europe compared with Northern and Western Europe. These findings highlight substantial geographical heterogeneity in the associations between social and health-related risk factors and memory, which should be considered when designing and implementing public health interventions.

Monkeys, chimpanzees and humans share dorsomedial and ventrolateral frontal regions for vocalization, yet only humans have speech. These regions are interconnected by the frontal aslant tract (FAT), a pathway increasingly recognized as central to speech production. Using spherical deconvolution tractography, we compared the FAT across primate species. In humans, the FAT is left-lateralized and enlarged, predominantly in its anterior parts connecting prefrontal areas. This expansion parallels the enlargement of the arcuate fasciculus, which conveys auditory input to the ventrolateral frontal region. To probe the functional significance of these anatomical modifications, we measured correlations between degeneration of FAT subsegments and language deficits in patients with primary progressive aphasia. Posterior FAT degeneration correlated with impaired verbal fluency whereas anterior FAT degeneration disrupted syntactic processing. Together, these findings support the view that an ancestral vocalization network was exapted in humans to sequence speech sounds, providing a neural substrate for the emergence of language.

Artificial Intelligence (AI) has become integral to the research of neurological diseases due to the rapid expansion of neuroimaging, clinical, physiological, and wearable data. However, the concise synthesis of recent machine learning (ML) and deep learning (DL) remains limited. This systematic review analyzes studies published between January 2021 and March 2026 on five major conditions- Alzheimer's disease, stroke, Parkinson's disease, brain tumors, and traumatic brain injury (TBI)-following the PRISMA 2020 guidelines and a structured search of PubMed, Scopus, and Web of Science, yielding 206 eligible articles. The results show that convolutional and encoder-decoder architectures dominate imaging tasks, whereas hybrid and multimodal approaches increasingly combine imaging with clinical and sensor data. Emerging paradigms, including federated learning, self-supervised learning, and foundation models, address data scarcity, privacy, and cross-institutional variability. Key advances include high-performing transformer-based models for Alzheimer's diagnosis, real-time stroke detection by CT/MRI, improved Parkinson's detection by multimodal fusion, hybrid models for brain tumor classification, and outcome prediction in TBI. Despite these gains, challenges in generalizability, interpretability, and clinical translation persist, underscoring the need for more robust and clinically reliable AI systems to address these issues.

Semi-quantitative positron emission tomography (PET) analysis, particularly Centiloid and CenTauRz scaling, is essential for Alzheimer's disease (AD) research and diagnosis. However, standard quantification workflows often depend on structural MRI for spatial normalization (SN) or rely on computationally intensive software, limiting clinical accessibility. In this retrospective, multi-center study (3,539 patients; 6,531 scans; 2005-2025), we compiled data across 7 modalities and 13 tracers to develop and validate the Deep Cascaded Cerebral Calculator (DCCC). This fully automated, PET-only framework employs cascaded CNN-based rigid/affine and VoxelMorph-based elastic registration modules for rapid SN. We benchmarked DCCC against the standard MRI-guided SPM12 pipeline and other PET-only tools using meta region-of-interest (ROI) Standard Uptake Value ratio (SUVr) and correlation analyses. DCCC achieved a mean absolute relative SUVr error of 1.34±0.59% and a Pearson correlation of 0.96±0.02, demonstrating robust generalization to unseen tracers and modalities including neuroinflammation and methionine metabolism imaging, with superior consistency compared to conventional template-based PET-only methods. Centiloid and CenTauRz estimates were highly accurate (R²>0.97) with a processing speed of 1.22±0.64 s per image. We further demonstrated DCCC's utility across 3 scenarios: (1) longitudinal tracking, where it identified a distinct low-Centiloid AD subgroup; (2) deep learning preprocessing, yielding classification AUCs comparable to standard methods (P=0.36); and (3) exploratory clinical support, where DCCC-derived metrics were adopted in 79% Aβ and 61% tau cases and were associated with changes in interpretation and increased agreement with reference labels in a multi-reader survey. Collectively, DCCC provides accurate, PET-only standardization, facilitating harmonized biomarker estimation without MRI and enabling large-scale, tracer-agnostic analyses in AD neuroimaging. A free standalone command-line interface program and a 3D Slicer plugin are provided.

Alzheimer's disease (AD) is characterized by mitochondrial dysfunction and oxidative stress, which drive synaptic damage. Proteomic analysis in an AD mouse model identified significant downregulation of Nicotinamide Nucleotide Transhydrogenase (NNT), a mitochondrial enzyme crucial for maintaining redox balance by regenerating NADPH. This loss created a pro-oxidant shift, sensitizing neurons to amyloid-β (Aβ) toxicity and triggering mitochondrial collapse-evidenced by loss of membrane potential and depletion of energy and antioxidants. NNT deficiency alone was sufficient to induce AD-like synaptic loss and cognitive deficits, independent of amyloid or tau pathology. Functionally, NNT acted as a metabolic-transcriptional hub, promoting pro-synaptic gene expression and synaptic protein homeostasis. It supported synaptic resilience through dual mechanisms: preserving redox balance to protect synaptic components and facilitating clearance of toxic Aβ accumulation. These findings could position NNT dysfunction as a critical, non-amyloid factor in AD pathogenesis, linking mitochondrial bioenergetics to synaptic integrity. Enhancing NNT activity thus represents a promising therapeutic strategy to bolster metabolic resilience and cognitive function in AD.

BACKGROUND: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are neurodegenerative syndromes associated with progressive disruption of functional brain networks. This pilot study evaluated whether a stacked set of resting-state EEG-derived centrality measures could characterize functional network alterations across AD, FTD, and healthy control groups. METHODOLOGY: Scalp EEG data from 45 participants, comprising 15 AD, 15 FTD, and 15 controls, were analysed using a 19-channel 10-20 montage. After standardized preprocessing, functional connectivity networks were constructed for each participant, with the 19 EEG electrodes treated as network nodes. Four centrality measures were computed: leverage centrality, weighted leverage measure, betweenness centrality, and closeness centrality. Group differences were assessed across anatomical regions, hemispheres, and anterior-posterior-central divisions, with Benjamini-Hochberg false discovery rate correction applied. RESULTS: Closeness centrality provided the strongest corrected evidence of disease-related functional network alteration, with FDR-significant regional effects retained in frontal, occipital, and temporal regions. Hemispheric analyses showed bilateral closeness-centrality alterations, particularly in AD, while betweenness centrality showed a corrected left-hemisphere effect for AD versus controls. Temporal-region findings across multiple metrics were biologically consistent with known AD and FTD alteration patterns but remained partly exploratory after correction. Leverage-based measures showed a strong negative association with age in FTD, whereas betweenness and closeness centrality demonstrated moderate associations with MMSE. CONCLUSION: EEG-derived stacked centrality analysis may provide a useful pilot framework for characterizing dementia-related functional network disruption in AD and FTD, with closeness centrality showing the strongest corrected evidence of disease-related network alteration. Larger, longitudinal, and clinically stratified studies are required to validate its diagnostic, prognostic, and disease-monitoring utility.

INTRODUCTION: Copper homeostasis disturbance has been implicated in Alzheimer's disease (AD), and excess copper exacerbates oxidative damage, protein aggregation and cognitive deficits. Cuproptosis is a new form of cell death mainly related to mitochondrial impairment which caused by intracellular copper overload. However, the involvement of cuproptosis in the pathogenesis of AD remains elusive. OBJECTIVES: The copper chaperone ATOX1 is crucial for copper homeostasis. This study aimed to investigate the role of ATOX1 and cuproptosis in the progression of Alzheimer's disease and to identify the underlying regulatory mechanism. METHODS: We analyzed human AD brain databases and tissue, alongside APP/PS1 mouse models and Aβ-treated HT22 cells. Techniques included proteomics, immunofluorescence, Western blot, electron microscopy, and behavioral tests. ATOX1 was manipulated using AAV vectors and shRNA in vivo and in vitro. Chromatin immunoprecipitation (ChIP) and luciferase assays were used to study transcriptional regulation. RESULTS: ATOX1 was significantly decreased in human AD brains, APP/PS1 mice, and Aβ-treated cells. ATOX1 downregulation in mice induced copper accumulation, mitochondrial damage, and molecular features of cuproptosis, including lipoylated protein aggregation and Fe-S cluster protein loss, leading to neuronal death and memory impairment. These cuproptosis markers were also confirmed in human AD brains and APP/PS1 mice. Critically, ATOX1 up-regulation reversed cuproptosis, ameliorated synaptic deficits, and rescued memory impairments in APP/PS1 mice and Aβ-treated cells. Furthermore, we identify Runx1 as a transcriptional repressor of ATOX1 under Aβ exposure, revealing a novel mechanism that couples amyloid pathology directly to copper dysregulation. CONCLUSION: Our findings demonstrate that Aβ-induced Runx1 repression of ATOX1 drives copper overload and cuproptosis, contributing to neurodegeneration and cognitive deficits in AD. ATOX1 represents a promising therapeutic target for AD.

Multi-infarct dementia (MID) is a major subtype of vascular cognitive impairment, second only to Alzheimer's disease as a leading cause of dementia worldwide. Unlike neurodegenerative dementias, MID results from recurrent vascular insults, producing stepwise cognitive decline. Animal models have become indispensable for understanding MID mechanisms and testing therapies, yet no single model fully captures human disease complexity. This review synthesizes current knowledge of embolic, chronic cerebral hypoperfusion, hypertensive, and large animal models of MID. We compare methodological strategies, neuropathological features (including white matter injury, neuroinflammation, and blood-brain barrier disruption), and behavioral outcomes. Key limitations include poor replication of infarct heterogeneity, absence of comorbidities, and translational failures. Emerging directions such as multi-hit paradigms and mixed dementia models are discussed. We conclude that integrative, multifactorial models are essential for improving translational relevance and developing effective therapies.

BACKGROUND: Type 2 chronic inflammatory diseases such as chronic urticaria (CU), chronic sinusitis (CS), and allergic rhinitis (AR) are commonly treated with second-generation H1-antihistamines (sgAH). Although considered safe, concerns exist about a possible association with dementia risk. OBJECTIVE: To determine whether sgAH are associated with increased dementia risk in patients with CU, CS, or AR. METHODS: We conducted a target trial emulation using real-world data from the TriNetX electronic health record network. Patients aged ≥50 years with CU, CS, or AR and no prior dementia diagnosis were included. Treatment groups comprised users of sgAH, first-generation H1-antihistamines (fgAH), or non-antihistamine alternatives (intranasal steroids for AR/CS, oral steroids for CU). Propensity-score matching was applied across 38 covariates. Dementia incidence was assessed over 5 years using Kaplan-Meier survival analysis and Cox proportional hazards models. RESULTS: After matching, 48,238 patients with CU, 21,611 with CS, and 36,802 with AR were analyzed alongside equal-sized control groups. Across all comparisons, no increased dementia risk was observed for users of any antihistamine versus non-antihistamine controls. No differences were found between sgAH and fgAH or steroid users. Intranasal steroids use in patients with AR was associated with a slight decrease in dementia risk (p=0.007). CONCLUSION: Overall, our findings do not support increased dementia risk associated with sgAH use. Lower dementia rates in patients with AR treated with corticosteroids might be associated with the protective effects of corticosteroids rather than harmful effects of sgAH.

BACKGROUND: Anxiety disorders and insomnia are common modifiable conditions in older adults, but their independent and combined effects on the risk of incident Alzheimer's disease and related dementias (ADRD) remain unclear. OBJECTIVES: To estimate the independent and combined associations of anxiety disorders and insomnia with the risk of incident ADRD. DESIGN: Retrospective cohort study using an intention-to-treat approach with a 10-year follow-up period (2014-2023). SETTING: De-identified electronic health record (EHR) data from 70 participating healthcare organizations within the TriNetX Research Network. PARTICIPANTS: Adults aged ≥50 years without prior dementia who had regular ambulatory care during a three-year baseline period (n = 1,868,790). MEASUREMENTS: Anxiety and insomnia were identified using ICD-based algorithms and categorized into four exposure groups: neither condition, anxiety only, insomnia only, and both. Incident ADRD was defined by two or more diagnostic codes within 12 months. Entropy balancing controlled for confounding, and weighted Cox proportional hazards models estimated hazard ratios (HRs). RESULTS: At baseline, 4.1% had anxiety only, 3.8% had insomnia only, and 1.1% had both. Over follow-up, 2.3% developed ADRD. In weighted models, insomnia alone (HR: 1.12; 95% CI: 1.06-1.19), anxiety alone (HR: 1.49; 95% CI: 1.39-1.60), and co-occurring anxiety and insomnia (HR: 1.31; 95% CI: 1.06-1.62) were each associated with higher ADRD risk compared with neither condition. No significant effect modification by age, sex, or race was observed. CONCLUSIONS: Anxiety and insomnia independently increase ADRD risk, though insomnia's contribution is very modest compared to the primary association demonstrated by anxiety. Co-occurrence does not confer additional risk beyond anxiety alone. Clinically, routine screening and treatment of anxiety and sleep disturbances represent actionable, broadly applicable strategies for ADRD prevention and healthy cognitive aging.