Alzheimer's disease (AD) is a growing public health concern, with neuroinflammation implicated in its pathogenesis. Allergic rhinitis (AR), a prevalent chronic inflammatory disorder, may contribute to systemic inflammation and potentially influence AD risk. This study sought to critically assess the association between a history of AR and subsequent AD development in a large, representative Taiwanese cohort. Leveraging Taiwan's National Health Insurance Research Database (LHID2010), this nationwide case-control study identified 4,681 individuals aged ≥ 65 years with a first-time AD diagnosis (cases) and 14,043 propensity-score-matched controls. A rigorous definition of prior AR required at least two clinical diagnoses, including one by an otolaryngology specialist. Multivariable logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for potential confounders. The prevalence of prior AR was significantly higher in AD patients than in controls (25.29% vs. 21.01%, p < 0.001). Following meticulous adjustment for demographic variables, socioeconomic status, geographic factors, and medical comorbidities (including hyperlipidemia, diabetes, coronary heart disease, hearing loss, and hypertension), prior AR was robustly associated with elevated odds of AD (adjusted OR = 1.279, 95% CI = 1.182 ~ 1.384). This association remained significant for both males (adjusted OR = 1.196, 95% CI = 1.053 ~ 1.358) and females (adjusted OR = 1.339, 95% CI = 1.210 ~ 1.482). This study suggests a significant association between prior AR and an increased odds of developing AD in an elderly Taiwanese population. These findings highlight chronic peripheral inflammation as a factor potentially associated with neurodegeneration.

Neurofibrillary tangles in Alzheimer's disease (AD) stereotypically spread from the medial temporal lobe to association areas and then to idiotypic areas (i.e., primary motor, somatosensory, auditory, and visual). Previous studies have reported variable and clinically relevant tangle densities across the hippocampus and association cortices, but the idiotypic tangle burden is understudied. In this study, we measured tangle density using immunohistochemistry in three idiotypic cortices (primary motor, somatosensory, and visual), three association cortices (middle frontal, superior temporal, and inferior parietal), and two hippocampal sectors (CA1 and subiculum) in 144 cases with a high level of AD neuropathologic change. Clinical diagnoses included late-onset AD (LOAD, n = 50), early-onset AD (EOAD, n = 21), behavioral variant frontotemporal dementia (bvFTD, n = 19), corticobasal syndrome (CBS, n = 18), logopenic primary progressive aphasia (lvPPA, n = 21), and posterior cortical atrophy (PCA, n = 15). We algorithmically assigned cases outside the interquartile ranges of mean tangle ratios of association:hippocampal, idiotypic:association, and idiotypic:hippocampal to mutually exclusive subtypes: idiotypic-susceptible, associative-predominant, limbic-predominant, or typical Braak (for all remaining cases). Regional tangle burdens differentiated subtypes, while female sex, younger ages, and longer disease durations also influenced tangle severity. Compared to typical Braak cases, idiotypic-susceptible and associative-predominant cases exhibited shorter disease duration and younger age at death while limbic-predominant cases were older. The MAPT H1H1 haplotype also differed by subtype, being most prevalent in limbic-predominant and least common in idiotypic-susceptible and associative-predominant subtypes. Clinically, the idiotypic-susceptible subtype associated with CBS (56%), the associative-predominant subtype with bvFTD (53%), and the limbic-predominant subtype with LOAD (14%). The typical Braak subtype characterized 74-76% of amnestic AD cases and 32-53% of non-amnestic AD cases. Moreover, k-means clustering corroborated four clusters including the idiotypic-susceptible and associative-predominant patterns. Our results confirm previously described tau subtypes and describe an idiotypic-predominant subtype with clinical relevance and distinct demographic and genetic characteristics in AD.

OBJECTIVE: Nationally representative data are essential for understanding the causes, consequences, and costs of dementia and mild cognitive impairment (MCI) and for informing policy and care planning. This study aimed to describe methodological considerations in applying the Health and Retirement Study Harmonised Cognitive Assessment Protocol (HRS-HCAP) cognitive domain structure and diagnostic algorithm to the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA-HCAP), and to generate harmonised estimates of the prevalence of dementia and mild cognitive impairment (MCI) in a nationally representative sample. RESULTS: A total of 1,037 participants aged ≥ 65 years completed NICOLA-HCAP. Five cognitive domains were identified, all loading onto a second-order general cognitive performance factor: orientation (0.903), memory (0.855), executive function (0.893), language-fluency (0.962), and visuospatial ability (0.812). Model fit was acceptable (SRMR = 0.065; RMSEA = 0.047; CFI = 0.916; TLI = 0.906). Following classification, 6.2% of participants were classified with dementia and 15.8% as MCI. Methodological modifications addressed software differences, normative sample derivation, and cohort-specific adjustments. These findings provide preliminary support for HCAP as a framework for producing harmonised estimates of cognitive status. NICOLA-HCAP will facilitate future investigation of modifiable risk factors for dementia in community-dwelling older adults. Validation studies are required to determine whether resulting classifications are fit for purpose.

Neuroinflammation has historically been viewed through a biochemical lens, governed by cytokines and danger signals. While this paradigm has provided foundational insights, integrating the physical dimension of tissue stiffening, hemodynamic shear stress, and compressive forces offers a more complete understanding of the pathological microenvironment of the central nervous system (CNS). In this Review, we examine Piezo1 as an important mechanosensitive channel that can translate such physical cues into neuroinflammatory responses. We synthesize emerging evidence showing that Piezo1-mediated calcium signaling can regulate activation, migration, and metabolic reprogramming in resident CNS cells and infiltrating immune populations. Importantly, the strength of evidence is not uniform across all cell types: genetic studies provide the strongest support in microglia, oligodendrocyte-lineage cells, and endothelial cells, whereas roles in astrocytes, dendritic cells, and T cells remain more context-dependent and emerging.Furthermore, we outline the distinct mechanical signatures across major CNS pathologies and discuss how Piezo1 may shape context-dependent outcomes-from plaque-associated microglial responses in Alzheimer's disease to mechanically restricted remyelination in multiple sclerosis, acute vascular or parenchymal injury in stroke and trauma, and emerging links to seizure-associated swelling and hyperexcitability in epilepsy. Finally, we propose an integrated "Mechanical Alterations-Piezo1-Immune Regulation" framework and discuss how mechano-therapeutic strategies might be used to modulate, rather than uniformly enhance or suppress, neuroinflammatory responses.

BACKGROUND: Alzheimer's disease and related dementias (ADRD) are major public health concerns. DNA methylation (DNAm)-based biomarkers such as GrimAge and PhenoAge predict aging and health risk, but were not designed to optimize prediction of cognitive function or decline. Epigenetic g-a DNAm-derived index of general cognitive ability-is a promising marker of cognitive function that has not been assessed in a racially and socioeconomically diverse population. METHODS: We used data from the 2016 Venous Blood Study of the Health and Retirement Study (HRS), a nationally representative cohort of U.S. adults aged ≥ 51 years (N = 3575 with high-quality DNAm). Epigenetic g scores were computed using CpG weights from a BayesR+ model of general cognitive ability developed in Generation Scotland. Cognitive function was measured with a modified version of the Telephone Interview for Cognitive Status (TICS) at each interview wave. Linear regression estimated associations with cognitive scores; mixed-effect growth curve models estimated the association with cognitive change. Models were adjusted sequentially for demographics, education, parental education, APOE ε4 status, and blood-based neurodegeneration markers (NfL, GFAP, Aβ42/40, pTau181). RESULTS: Higher epigenetic g was associated with better baseline cognition (β = 2.55, 95% CI 1.80-3.30)) and cognition at the time DNAm was measured (β = 2.30, 95% CI 1.47-3.13) after demographic adjustment. Associations were attenuated but remained significant with education and parental education (β = 1.23-1.89). In growth curve models, Epigenetic g was associated with higher cognitive performance but did not have a statistically significant association with decline over a 6-year period. Results were robust to adjustment for APOE ε4 and neurodegeneration biomarkers. CONCLUSIONS: Epigenetic g is a scalable, blood-based marker of cognitive function, and potentially or cognitive reserve, that adds predictive value beyond demographics, socioeconomic indicators, APOE, and neuropathology. Its validation in a diverse, nationally representative U.S. cohort underscores its potential for early risk profiling and for research on social determinants of cognitive aging in cross-national samples.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are neurodegenerative diseases with overlapping pathology. Mutations in CCNF, encoding the E3 ubiquitin ligase, Cyclin F, can cause ALS, FTD, or both, even within the same family. Most prior studies of CCNF have relied on overexpression systems, potentially confounding outcomes through disruption of endogenous Cyclin F. Here, we generated the first knock-in mouse model of endogenous Ccnf using CRISPR/Cas9. Heterozygous and homozygous Ccnf mice showed no motor decline or neuronal loss after 18 months, however immunohistochemistry revealed increased hippocampal astrocyte ramification, with sex-, age, and subfield-dependent effects. These data indicate that endogenous Ccnf may prime early astrocyte alterations in the absence of overt neurodegeneration. Similar astrocyte morphological changes were observed in canonically affected regions of sporadic ALS and FTD-ALS patients post mortem, as well as in CCNF iPSC-derived astrocytes following inflammatory stimulation. Proteomics on Ccnf mice identified early dysregulation of pathways related to translation, mitochondrial function, cytoskeletal remodelling, synaptic transmission and neuroinflammation. Correspondingly, CCNF iPSC-derived astrocytes displayed impaired mitochondrial membrane potential and altered network morphology under both basal and inflammatory stimuli. As altered neuronal excitability is a hallmark of ALS, we examined astrocyte-driven changes to neuronal excitability. CCNF iPSC-derived motor neurons cultured alone were hyperexcitable, firing more action potentials than isogenic controls. Remarkably, co-culture with CCNF astrocytes, but not isogenic control astrocytes, abolished repetitive firing, increased the proportion of neurons unable to generate action potentials, and reduced voltage-gated sodium currents in CCNF and isogenic control neurons. Together, these findings identify astrocyte alterations as an early feature of CCNF-mediated disease, in the absence of neuronal loss. Moreover, the combination of astrocytic mitochondrial dysfunction and the ability of CCNF astrocytes to suppress repetitive neuronal firing suggests a critical astrocyte-driven non-cell autonomous mechanism that may contribute to an oligogenic role for CCNF in ALS/FTD pathogenesis.

BACKGROUND: Pain is a hallmark of inflammation and tissue injury, particularly following major surgical procedures. Despite its prevalence and clinical impact, pathological pain, defined as persistent pain that impairs function, remains a major unmet medical need. Human birth tissue, including the amniotic membrane and umbilical cord, has long been recognized for its regenerative properties and its ability to support wound healing. Recent studies have identified heavy chain 1 (HC)-hyaluronic acid (HA)/pentraxin 3 (HC-HA/PTX3) as a key matrix component within these tissues. This complex exhibits anti-inflammatory and anti-scarring activities and helps maintain stem cell quiescence. MAIN BODY: Emerging evidence, including our own findings, indicates that human birth tissue-derived products may also modulate pain responses in certain settings, such as post-surgical pain, potentially through mechanisms involving neuronal inhibition and regenerative healing. We summarize the molecular and cellular mechanisms by which human birth tissue-derived products and HC-HA/PTX3 may exert anti-inflammatory and analgesic effects. We then highlight preclinical and clinical studies evaluating their potential roles in wound healing and pathological pain. Finally, we discuss translational opportunities, current challenges, and future directions for advancing these biologics within the emerging field of regenerative pain medicine. CONCLUSIONS: This review outlines a framework for potential regenerative pain management using birth tissue-derived products, which may serve as a foundation for developing new therapies for certain pathological pain conditions.

BACKGROUND: The Health and Social Care Professionals' Knowledge and Attitudes towards Later-Life Intimacy and Sexuality (HSCP-KALLIS) is designed to assess health and social care professionals' knowledge and attitudes toward later-life intimacy and sexuality. Additional care considerations are included for older adults with dementia and those from diverse gender backgrounds. This study aimed to evaluate the reliability and validity of the HSCP-KALLIS scale. METHODS: This methodological study was a subsequent phase of the HSCP-KALLIS scale development undertaken between 2022 and 2023, using an online survey approach with participants who were health and social care professionals. Internal consistency was assessed using McDonald's Omega and Cronbach's alpha, while the underlying factor structure of the scale was examined through exploratory factor analysis. RESULTS: A total of 98 participants were recruited for the study. Participants primarily were females, registered nurses, worked in aged care, and demonstrated high levels of knowledge and positive attitudes towards later-life intimacy and sexuality. The final HSCP-KALLIS Scale consists of 30 knowledge items across two factors and 25 attitude items across three factors, with satisfactory internal consistency demonstrated. CONCLUSIONS: This study provides preliminary evidence that the HSCP-KALLIS scale is a reliable tool for measuring health and social care professionals' knowledge and attitudes towards later-life intimacy and sexuality. This scale shows potential for identifying staff training needs, evaluating training effectiveness, and informing policy and guidelines development. The primary study limitations include methodological constraints and a small sample size. Future research should involve a larger sample size to enable confirmatory factor analysis. TRIAL REGISTRATION: Not applicable.

BACKGROUND: Disability assessment in dementia is important for care planning, but the full World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is time-intensive and may limit clinical use. This study developed machine learning (ML)-based short forms of the WHODAS 2.0 and examined their reliability, concurrent validity, and responsiveness. METHODS: Using data from 51,245 persons with dementia (training set: n = 31,952; validation set: n = 19,293), we developed two ML-based short forms, ML-WHODAS-16 and ML-WHODAS-10, with Extreme Gradient Boosting and bootstrap-based item selection under a lock-down training/validation workflow. Their performance was compared with the full WHODAS-32 and the conventional 12-item short form adapted to 11 items after excluding work-related items (Standard-12). Anchor-based longitudinal validity was also examined using deterioration in official Disability Severity Grade. RESULTS: Both ML short forms showed high internal consistency (α = 0.96 for ML-WHODAS-16 and 0.93 for ML-WHODAS-10) and excellent concurrent validity with the full WHODAS-32 (r = 0.98 for both). Compared with the Standard-12, they showed lower error, negligible Bland-Altman bias, and met predefined equivalence criteria, including ±0.5 points. Anchor-based Responsiveness was broadly comparable to the Disability Severity Grade (anchor) (r = 0.66-0.67; standardized response mean = 0.37-0.40). Anchor-based minimal clinically important differences were 9.26 for ML-WHODAS-16 and 9.95 for ML-WHODAS-10. CONCLUSION: The ML-WHODAS-16 and ML-WHODAS-10 substantially reduced assessment burden while maintaining scores that closely reflected those of the full WHODAS-32, particularly for group-level assessment and longitudinal monitoring. These findings support their use as practical, low-burden alternatives in dementia disability assessment. However, external validation, validation against harder clinical outcomes, formal non-inferiority testing, and clinically anchored longitudinal thresholds remain needed before individual-level interchangeability can be inferred.

Choline is an essential nutrient required for the synthesis of key molecules, such as phosphatidylcholine, sphingomyelin, acetylcholine, and S-adenosylmethionine. Choline metabolism encompasses two phases, namely the postprandial and postabsorptive states. The former enables the digestion, absorption, distribution, and storage of choline derivatives after a meal, while the latter allows the cellular utilization of choline and the mobilization of stored choline-containing molecules during fasting. Understanding choline metabolism is fundamental to the study of lipid disorders such as steatohepatitis or atherosclerosis, as well as neurodegenerative diseases, including Alzheimer's disease, and inflammatory signaling pathways. Members of the alkaline phosphatase (AP) superfamily are prominent contributors to extracellular choline metabolism. Within this family, several APs and ectonucleotide pyrophosphatases/phosphodiesterases (ENPP) members are required for physiological choline metabolism. While intestinal alkaline phosphatase (IAP) and alkaline sphingomyelinase/ENPP7 both participate in the digestion of choline-containing derivatives in the gut during the postprandial phase, circulating ENPP2, ENPP6, and tissue-nonspecific alkaline phosphatase (TNAP) act during the postabsorptive phase to generate choline. In this review we first provide a comprehensive overview of choline metabolism and then describe how APs and ENPPs have functionally and structurally co-evolved to catalyze sequential reactions within this metabolic pathway.

CONTEXT: . Feasible, person-centered advance care planning (ACP) approaches for persons with dementia and their care partners are needed, and the optimal approach may differ depending on the situation. Two contrasting approaches involve a highly scripted medical order-setting approach to decide on specific treatments in advance versus a flexible goal-eliciting, more psychosocially-oriented coping-based approach. OBJECTIVES: . To distinguish situations in which either approach is preferred in dementia from the perspective of general practitioners. METHODS: . We interviewed thirteen practitioners participating in the CONT-END program in the Netherlands. Seven were trained in the order-setting approach and six in the goal-eliciting approach for an ACP trial. Twelve other practitioners participated in a video vignette study showing the two approaches, and we triangulated findings. Inductive qualitative content analyses of interviews aimed at elucidating for whom and when an approach was preferred. RESULTS: . Four attributes distinguished situations in which either approach is preferred: understanding, trust, readiness and momentum. For the order-setting approach, understanding, trust, and readiness of person and care partner were prerequisites for momentum (time right to express preferences), when not triggered for urgent medical reasons. In contrast, the goal-eliciting approach would help understand the person, foster trust and create readiness from a first conversation. Without a clear trigger, however, momentum would need to be created. CONCLUSION: . Skill in employing various approaches to ACP conversations each with specific benefits could help tailor ACP to the individual and their situation. Further theoretical and empirical research including in other populations and settings may inform person-centered ACP.

Ferritins are vital macromolecules that have been widely used in a number of biotechnological fields. Ferritin-based hybrid nanoparticles, composed of different types of subunits and conjugates, represent a next generation of tools, which can significantly enhance their efficiency and expand the range of existing applications. This review outlines the application landscape of these hybrids in developing recombinant vaccines, drug delivery and imaging systems. We highlight the increasing trend towards the development of ferritin-based mosaic vaccines and some of them are already in the first or second phases of clinical studies. In comparison, drug delivery research, which is mostly focused on cancer theranostics, to our knowledge, has not progressed beyond the preclinical stage. Herein, we describe the key limitations and challenges of ferritin-based drug delivery systems development, suggest strategies that address these limitations and discuss promising future research directions. We conclude that engineered ferritin hybrids hold significant potential as useful tools for immunology, theranostics and other biomedical applications.

Spatial transcriptomics extends traditional transcriptomic methods by quantifying gene expression within intact tissues while preserving each cell's precise spatial context. This technology also captures gene expression under physiological conditions, including interactions with the surrounding microenvironment, thereby enhancing our understanding of cellular states in both health and disease. Rapid recent advances have improved throughput, transcript capture, accuracy, and overall data quality. In this review, we summarize the major spatial transcriptomics platforms and outline their strengths and limitations. We also highlight key applications in neuroscience, including brain cell-type identification, structure-function relationships, and developmental processes. Additionally, we examine spatial gene-expression patterns in psychiatric and neurodegenerative disorders such as Alzheimer's disease and depression. Finally, we discuss emerging directions, including spatial multi-omics integration and the potential for artificial intelligence to advance brain research. Collectively, this work provides a foundation for future studies in neuroscience and brain disorders.

BACKGROUND: Survival estimates for frontotemporal lobar degeneration (FTLD)-related syndromes by incorporating fluid biomarkers are essential to better assess their prognostic value and explore how they might inform long-term outcomes in FTLD. Population-based registries provide valuable data for these predictions. The aim of the present study was to assess whether NfL and GFAP levels correlate with mortality risk in a population-based registry of incident FTLD. METHODS: Incident cases with FTLD-spectrum, occurring between 2018 and 2020, were followed for up to six years. Survival and hazard analysis according to biomarkers levels were conducted. RESULTS: Median survival was 6 years from symptom onset and 3 years from diagnosis. While FTD-ALS phenotype showed significantly shorter survival, no differences were observed among bvFTD, PPAs, and CBS/PSP. Biomarkers were significantly associated with survival. Higher plasma GFAP (HR = 1.006, 95%CIs 1.001-1.012; p = 0.026) and plasma NfL (HR = 1.027, 95%CIs 1.003-1.053; p = 0.025) were associated with increased mortality risk in bvFTD, PPAs, and CBS/PSP. CONCLUSIONS: These results highlight the potential of NfL and GFAP as valuable biomarkers for assessing prognosis in FTLD and underscore the importance of incorporating biomarker analysis into clinical practice for more accurate patient management. Further studies are needed to refine prognostic models for FTLD.

Artificial intelligence (AI) is reshaping drug repurposing by integrating systems biology with molecular design. Here, we present a unified framework combining AI-enhanced Kinase Enrichment Analysis (KEA), geometric deep learning, and federated learning to enable scalable and privacy-preserving therapeutic discovery. KEA prioritizes disease-relevant kinases from multi-omics data, while geometric deep learning captures structure-activity relationships (SARs) at atomic resolution. Federated learning facilitates secure, multi-institutional model training across heterogeneous datasets. This integrative pipeline enhances identification of repurposable kinase inhibitors and supports emerging modalities, such as proteolysis-targeting chimeras (PROTACs). A case study in Alzheimer's disease (AD) highlights improved target prioritization and predictive performance. By bridging kinase signaling networks with AI-driven modeling, this framework provides a robust strategy for accelerating precision drug discovery and repurposing.

The sodium leak channel non-selective (NALCN) is a key regulator of resting membrane potential and cellular excitability in neurons and endocrine cells. Gain-of-function de novo pathogenic variants in NALCN cause severe neurodevelopmental disorders with a broad and heterogeneous clinical spectrum. Partial inhibition of NALCN has been proposed as a therapeutic strategy; however, progress has been limited by the absence of selective pharmacological modulators. This gap largely reflects the lack of a robust heterologous expression system suitable for high-throughput screening, as functional NALCN requires multiple ancillary subunits and its constitutive expression is toxic in commonly used cell lines such as HEK293. To address these challenges, we developed a multitransposon-based approach to generate inducible HEK293 cell lines that stably express the complete NALCN channelosome, including wild-type and disease-associated variants. We further demonstrate that NALCN current expression is cell cycle-dependent, enabling the definition of optimized conditions for consistent and reproducible electrophysiological recordings. Using these cell lines, we conducted a systematic pharmacological characterization of the NALCN channelosome by patch-clamp electrophysiology and identified several candidate modulators that are currently under evaluation. Notably, we revisited NALCN modulation by N-benzhydryl quinuclidine compounds and found that these compounds can restore locomotor phenotypes in an animal model of NALCN gain-of-function. Together, this work establishes a foundational platform for the discovery of NALCN-targeting compounds and opens new therapeutic avenues not only for NALCN-associated neurodevelopmental diseases, but also potentially for psychiatric disorders, chronic pain, and cancer.

A growing body of evidence suggests that reduced metabolic activity in astrocytes may compromise their normal supportive role for neurons and trigger pathophysiological pathways that contribute to the progression of Alzheimer's disease (AD). Due to the complexity of AD pathophysiology, it is crucial to study the disease not only within those contexts traditionally viewed from a neuron-centric perspective. In this study, we settled up a new model of AD by exposing primary rat cortical astrocytes to glyceraldehyde (GA), an inhibitor of glycolytic pathway able to induce a significant hypometabolism and recapitulate several AD pathomechanisms. Accordingly, GA-induced hypometabolism produced (a) astrocytosis, as revealed by the increase in GFAP and Glutamine Synthase (GS) immunosignals, (b) mitochondrial dysfunction, detected as reduced ATP level, mitochondrial ROS hyperproduction and Ca dyshomeostasis at both cytosolic and mitochondrial level (c) inflammation, measured as NF-κB activation, TNFα release, AGEs hyperproduction/RAGE hyperexpression and increase in S100β immunosignal, and, finally (d) autophagy impairment, characterized by the p62 and LC3II protein accumulation. By virtue of glutamate ability to stimulate cell metabolism, we examined the effect of the neurotransmitter supplementation on cell damage and those correlated mechanisms in the proposed AD model. Of interest, metabolic, inflammatory and autophagy defects were mitigated when astrocytes were exposed to glutamate as metabolic boosting substrate. The protective effect of glutamate was counteracted by the pharmacological inhibition of astrocytic glutamate transporters, thus highlighting the relevance of glutamate intracellular action. Collectively, these results highlight the importance of considering astrocyte-targeted therapies as potential strategy in AD.

Rapid eye movement (REM) sleep behaviour disorder (RBD), particularly its idiopathic/isolated form (iRBD), is a prodromal marker for α-synucleinopathies, including Parkinson's disease, dementia with Lewy bodies and multiple system atrophy. Machine learning (ML) offers opportunities to improve diagnosis and risk stratification in this high-risk group. We conducted a systematic review of PubMed, Embase (Ovid) and Medline (Ovid) from 2014 to September 2025, following PRISMA guidelines. From 335 records identified, 202 remained after duplicate removal and 75 studies on adult humans with clinically diagnosed RBD or iRBD that applied and validated an ML model were included. Fifty-eight studies addressed diagnosis, four studied RBD phenotypes, and thirteen evaluated prediction of phenoconversion to overt α-synucleinopathy. Across diagnostic studies, reported accuracies ranged from ∼63% to ∼99.7%, with median values around 90%, using polysomnography, EEG, neuroimaging, molecular and behavioural markers. Phenoconversion models (often using dopaminergic imaging or multimodal features) achieved AUCs up to ∼0.94, but frequently relied on small, single-centre cohorts with heterogeneous definitions of phenoconversion and limited external validation. A wide variety of ML algorithms was used (n ~ 30), most commonly support vector machines, random forests and logistic regression. Overall, ML approaches show promise for scalable diagnosis and risk stratification in iRBD, but progress is constrained by methodological bias, inconsistent endpoints, data imbalance and a lack of explainable, externally validated models. We outline methodological priorities to make future ML tools clinically interpretable and translatable.

Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder that significantly predisposes individuals to delirium and dementia through multifaceted neurobiological pathways. The essence of this neurocognitive decline involves mechanisms such as central insulin resistance, chronic low-grade inflammation, and mitochondrial dysfunction. While metformin remains the cornerstone of T2DM management, its impact on the central nervous system exhibits a "double-edged sword" nature, balancing intrinsic neuroprotective properties against the potential neurotoxicity associated with vitamin B12 deficiency. This review aims to systematically synthesize epidemiological and clinical evidence linking metformin to neurocognitive outcomes, contrasting its efficacy with newer glucose-lowering agents such as GLP-1 receptor agonists and SGLT2 inhibitors. In addition, it sheds light on the reciprocal connectivity between systemic metabolic regulation and direct CNS modulation, specifically elucidating AMPK activation, the autophagy-lysosome axis, and the gut-brain and liver-brain axes. We review these molecular mechanisms to delineate the delicate trade-off between neuroprotection and risk, providing a framework for precision pharmacotherapy and biomarker-guided stratification in high-risk T2DM populations.

γ-Secretase (GS) is a key therapeutic target in Alzheimer's disease because it catalyzes amyloid-β production. To reduce toxic amyloid-β species, several γ-secretase modulators (GSMs) have been developed. Among these, GSM-1, a piperidine carboxylic acid-based modulator, has shown potent activity in preclinical studies; however, its binding site and molecular mechanism remain unclear. Here, a molecular dynamics protocol inspired by the Wrap-'N'-Shake approach was used to investigate how the axial and equatorial conformations of the piperidine nitrogen in GSM-1 interact with GS's presenilin subunit. Both conformations formed stable interactions with presenilin TM1 and TM5. The carboxylate group established persistent interactions with R220 in TM5, while the trifluoromethylphenyl group engaged residues K76, K80, V87, and L91 in TM1. These findings provide the first model of GSM-1 engagement with GS, identify the key GSM-1 chemical groups involved in recognition, and establish a mechanistic foundation for the rational design of next-generation GSM analogs.

Various comorbidities have been associated with psoriasis. Most clinical studies support the hypothesis that psoriasis may be a risk factor for dementia. Meanwhile, some evidence indicates that certain immunomodulatory agents, many of which are widely used in psoriatic disease management, exert neuroprotective effects and may attenuate dementia progression. In view of the lack of existing studies that specifically investigate the effects of systemic treatments for psoriatic disease on dementia or cognitive impairment, in this narrative review, we focus on Alzheimer's disease, as a model to explore whether systemic psoriasis treatments influence dementia risk and severity. Our findings suggest that some systemic treatments for psoriasis may also provide potential neuroprotective benefits.

IMPORTANCE: Delirium is common among hospitalized adults, prevalence estimates ranging from 33% to 50% of hospitalized patients over age 65. Yet, little is known about the association between social determinants of health (SDOH) and delirium. OBJECTIVE: To describe neighborhood-level risk factors for hospitalization with delirium. We examined the association between hospitalization with delirium and neighborhood disadvantage, measured by the Area Deprivation Index (ADI)-a tool that measures SDOH by assessing socioeconomic conditions and disadvantages within a geographic area. METHODS: The Atherosclerosis Risk in Communities (ARIC) study is a community-based prospective cohort of adults recruited from four US communities. This analysis included ARIC participants that attended visit 5 (2011-2013) and had at least one hospitalization before visit 7 (2018-2019). Delirium was identified and quantified using hospital claim records. The association between ADI quartiles and incidence and number of delirium events was estimated with offset Poisson regression models for the time participants were observed. Associations were also examined by cognitive status. RESULTS: In this analytic cohort of 4130 participants, 486 (11.8%) experienced at least one hospitalization with delirium. Unadjusted regression analyses showed a higher incidence of delirium (proportion ratio, PR = 1.32; and 95% CI = 1.03, 1.69) and number of delirium events (incidence rate ratio, IRR = 1.30; 95% CI = 1.05, 1.63) among participants from the highest ADI quartile compared to the lowest quartile. In fully adjusted models, this association was attenuated. Among participants with mild cognitive impairment (MCI) and dementia, those from the most disadvantaged neighborhoods experienced a higher incidence and number of delirium events. CONCLUSION: In this cohort of hospitalized older adults, participants from more disadvantaged neighborhoods had a higher incidence of delirium; this association was attenuated in adjusted analyses. This suggests that neighborhood-level social disadvantage may be meaningful in studies on prevention and management of delirium, though overlapping demographic and clinical characteristics likely confound this relationship.

BACKGROUND: Parkinson's disease (PD) causes progressive motor and non-motor disability. Although pharmacotherapy is first-line, responses diminish over time. Deep brain stimulation (DBS) effectively treats advanced PD, and recent data suggest benefits when applied earlier. OBJECTIVES: To systematically review studies and meta-analyze randomized controlled trials comparing subthalamic DBS plus best medical therapy (BMT) with BMT alone in early PD. METHODS: We conducted a systematic review and meta-analysis according to PRISMA, with a protocol registered in PROSPERO (CRD420251014105). MEDLINE, Embase, and the Cochrane Library (2002-2025) were searched for studies comparing early DBS with BMT in "early" PD. "Early" was variably defined, commonly disease duration 4-8 years or onset of motor complications without significant disability. We included RCTs, secondary analyses, observational studies, and unpublished trials; meta-analyses were restricted to randomized comparisons of early DBS plus BMT versus BMT alone. RESULTS: Studies included younger patients with ≤8 years' PD duration and early motor complications. Pooled RCT data showed a consistent quality-of-life benefit, while motor and medication outcomes directionally favored early STN-DBS but remained heterogeneous and imprecise. Studies suggest safety is broadly comparable to standard-indication DBS. CONCLUSIONS: Offering DBS before advanced disability-particularly in patients <60 years, <10 years from diagnosis, Hoehn-Yahr stage ≤3, early motor complications, and no dementia-may help delay loss of quality of life versus BMT alone. Given few trials and substantial heterogeneity, further large-scale randomized studies are needed to confirm safety, define optimal timing in early PD, and clarify which subgroups benefit most.