Search Results (580)

Alzheimer’s disease (AD) is the most common neurodegenerative disorder and a leading cause of dementia worldwide, characterized by progressive cognitive decline, memory impairment, and neuronal loss. The pathological hallmarks of AD include extracellular accumulation of amyloid-β (Aβ) plaques, intracellular neurofibrillary tangles composed of hyperphosphorylated tau protein, chronic neuroinflammation, oxidative stress, mitochondrial dysfunction, and synaptic degeneration. Current symptomatic therapies provide modest clinical benefits, while recently approved amyloid-targeting monoclonal antibodies, such as lecanemab and donanemab, can slow decline in selected early-stage AD patients but do not cure the disease and are associated with safety, access, and cost concerns. This narrative review summarizes mechanistic evidence from in vitro and in vivo studies and distinguishes preclinical promise from validated clinical utility. Phytochemicals, including polyphenols, flavonoids, alkaloids, terpenoids, and carotenoids, demonstrate neuroprotective effects through antioxidant activity, anti-inflammatory modulation, inhibition of amyloid aggregation, regulation of tau phosphorylation, and support of mitochondria and synapses. Evidence from experimental models suggests that several phytochemicals may help slow AD pathology and improve cognitive function, but clinical translation remains limited due to poor bioavailability, inadequate blood–brain barrier (BBB) penetration, and a lack of large-scale clinical trials. This review highlights critical research gaps and emerging strategies to facilitate phytochemical-based preventive and therapeutic approaches in AD. Full article

Background and Objectives: As society ages, the number of patients with cognitive impairment is increasing. Machine learning methods that use structured clinical and cognitive-assessment data during routine diagnostic work-up may support and monitor structured classifications of cognitive status. This kind of approach can improve early screening, reduce physicians’ workload and develop greater support for personalized treatment. To develop an XGBoost-based machine learning model using the National Alzheimer’s Coordinating Center (NACC) dataset and to evaluate the model’s precision with clinician-assigned diagnosis in a Latvian retrospective cohort study. Materials and Methods: The research was designed as a retrospective external validation cohort study that used two data sources. Firstly, the National Alzheimer’s Coordination Center (NACC) longitudinal dataset was used to train the ML model. Secondly, medical records gathered from Pauls Stradins Clinical University Hospital dating from 2020 to May 2025 were used to evaluate the algorithm’s precision. Results: In the NACC study, the weighted four-class model achieved an overall accuracy of 84.0% and a balanced accuracy of 70.9%, but the SCD class remained poorly classified. After reframing the model to a three-class model the performance grew stronger for normal cognition, mild cognitive impairment (MCI) and dementia. Class distribution in the Latvian cohort consisted of dementia (n = 138); MCI (n = 13); and subjective cognitive decline (SCD) (n = 2). Dementia was identified most strongly—124/138 (sensitivity—89.9%). MCI was correct in 9/13 cases (sensitivity—69.2%). SCD cases were excluded. Overall, the model agreed with the neurologist-assigned diagnoses in 88.1% of the cases (133/151). Conclusions: The ML classification model has high precision when comparing with neurologist-assigned diagnoses, but it struggles to separate adjacent early-stage diagnoses, meaning that it did not reliably identify SCD. These findings support further methodological development and the implementation of prospective research. Nevertheless, this technology has high potential for being integrated in the future to aid triage and early screening, especially when advanced diagnostics are limited. Full article

Background: Functional decline emerges early in Alzheimer’s disease (AD) and may support clinical staging. However, criterion-referenced thresholds for interpreting the six-minute walk distance (6MWD) across AD stages are lacking. This study aims to derive sex-specific 6MWD cut-off values to differentiate mild cognitive impairment (MCI) from moderate AD dementia. Methods: In this cross-sectional study, 233 community-dwelling adults (128 women) were consecutively recruited from a neurology department and classified using IWG-2 criteria (MCI: MMSE ≥ 26; moderate AD dementia: MMSE 10–19). All participants completed a standardized 6 min walk test (6MWT) following American Thoracic Society guidelines. Receiver operating characteristic (ROC) analyses were performed overall and by sex, optimal thresholds were selected using Youden’s index, and diagnostic indices such as area under the curve (AUC), sensitivity, specificity, 95% confidence intervals (CI), likelihood ratios (LR) and odds ratio (OR) were computed. Results: Overall, participants with moderate AD dementia exhibited substantially lower 6MWD values than those with MCI (313.7 ± 46.5 m vs. 461.2 ± 60.1 m, p < 0.001). The optimal overall threshold was 390 m, yielding an AUC of 0.97, sensitivity of 98.0%, and specificity of 79.4%. Sex-specific thresholds were 389 m in men (AUC = 0.96, sensitivity = 96.4%, specificity = 79.3%) and 367 m in women (AUC = 0.98, sensitivity = 97.8%, specificity = 87.7%). Conclusions: The 6MWD demonstrates strong discriminatory ability between MCI and moderate AD dementia in this sample. Sex-specific thresholds may support functional staging and monitoring but require internal and external validation before clinical implementation. Full article

Using home sensors to provide agitation warnings for community-dwelling dementia patients without ongoing clinical supervision can enable their carers to intervene early during the agitation latent period, thereby reducing unnecessary hospital admissions and harmful events. Most existing studies are based on behavioral, sleep, and physiological data from the previous 24 h to predict patients’ agitation events, which fail to fully capture patients’ recent behavioral details. In this study, monitoring data from the previous 8 × 24 h for dementia patients are used to achieve in-depth mining of patients’ living habits. Furthermore, to address the common clinical problem of extreme imbalance between agitation and normal samples (agitation samples often are extremely scarce), we designed a two-stage agitation early warning model based on symmetric autoencoders and a spatio-temporal network, dubbed SAS-Net. In the first stage, we randomly sample 80% of normal samples and employ multiple symmetric autoencoders to perform feature transformation and pseudo-label construction, and then pre-train the spatio-temporal learning network composed of convolutional networks and a gated Multilayer Perceptron. It aims to learn the patient data’s intrinsic structure, underlying patterns, and effective feature extraction methods. In the second stage, we freeze the parameters of the spatio-temporal learning network and use a balanced dataset consisting of the remaining 20% of normal samples and all agitation samples to reconstruct and fine-tune the top fully connected classifier to improve the recognition performance of agitation samples. The two-stage strategy resolves the problem of ineffective training faced by deep learning models on imbalanced datasets. The experimental results demonstrate the effectiveness of the proposed SAS-Net for agitated behavior early warning. Full article

Alzheimer disease (AD) is a neurodegenerative disorder currently recognized as the leading cause of dementia worldwide. It is characterized by a progressive cognitive decline, which can be studied and diagnosed through the use of various brain biomarkers. The retina, being part of the central nervous system, shares numerous structural and functional features with the brain. In this light, a wide range of alterations have been found in the retina with significant potential as biomarkers for AD diagnosis, even at early stages of its manifestation in the brain, and for monitoring disease progression within this organ. Furthermore, the detection of such alterations in the eye and retina is feasible through non-invasive, relatively simple and cost-effective techniques, such as optical coherence tomography, scanning laser ophthalmoscopy and electroretinography. Using these methods, numerous studies have identified molecular, morphological and functional changes associated with AD in the retina and other ocular elements, including the choroid, cornea, lens, intraocular humors and tear fluid. This review addresses the main anomalous changes identified to date in the retina and other eye structures in patients with AD, highlighting their potential utility as biomarkers for the diagnosis of this disease and their possible extrapolation to its prognosis in the brain. Full article

Background/Objectives: Cognitive impairment can compromise toothbrushing and other oral self-care functions, increasing the risk of oral diseases and related complications. However, how toothbrushing ability declines across stages of cognitive impairment remains unclear. This study aimed to describe functional deficits in toothbrushing among older adults with different levels of cognitive function. Method: Sixty-five older adults (14 cognitively healthy and 51 with documented cognitive impairment) were classified into five cognitive levels based on Standardized Mini-Mental State Examination scores. Participants completed a toothbrushing task as they normally would at home. Performance was videotaped, coded, and evaluated across four domains (task initiation, completion, thoroughness, and quality) with total scores reflecting overall toothbrushing ability. Overall performance, functional deficits, and assistance needs were analyzed in relation to cognitive levels. Results: Participants averaged 76.5 years of age. Toothbrushing ability declined gradually with worsening cognitive impairment, followed by a sharp deterioration at the profound stage (e.g., SMMSE ≤ 5). Compared with cognitively healthy participants (n = 14), those with mild cognitive impairment (MCI, n = 20) or mild (n = 10), moderate (n = 10), or severe dementia (n = 11) lost an average of 3%, 8%, 12%, and 37% of overall toothbrushing ability, respectively. Brushing efficiency declined earlier and more rapidly, decreasing by 13% in MCI and up to 46% in severe dementia (p < 0.001). All participants with MCI or mild dementia completed the task independently, whereas 20% with moderate dementia and 80% with severe dementia required assistance to initiate or complete the task. Conclusions: Overall toothbrushing ability remains relatively preserved until the later stages of cognitive impairment, but brushing quality deteriorates much earlier and quicker. These findings highlight the importance of early caregiver–patient partnerships, functionally tailored oral self-care rehabilitation, and personalized caregiver training to support oral hygiene among older adults with cognitive impairment. Full article

Background and Objectives: To quantify behavioral complexity in probable Alzheimer’s disease (AD), compare complexity phenotypes, and determine whether behavioral complexity provides clinically meaningful information beyond total neuropsychiatric burden. We also explored whether global amyloid extent and lobar amyloid topography added explanatory value. Methods: In this cross-sectional retrospective study, we analyzed 245 psychotropic drug-naïve patients with probable AD, positive ¹⁸F-FC119S amyloid positron emission tomography (PET), and complete neuropsychiatric, cognitive, functional, and regional PET data. Behavioral complexity was derived from 12 Korean Neuropsychiatric Inventory domains using symptom count, normalized Shannon entropy of the frequency × severity profile, and a composite index. Patients were classified into tertiles. Multivariable regression and burden-stratified analyses examined associations with cognition, dementia severity, function, and amyloid measures. Results: Higher behavioral complexity was associated with lower Korean Mini-Mental State Examination (K-MMSE) scores and higher Clinical Dementia Rating (CDR) and Global Deterioration Scale (GDS) stages. In multivariable analysis, higher CDR, higher GDS, and lower Barthel Index independently predicted greater complexity, whereas amyloid extent did not. After adjustment for total neuropsychiatric burden, higher CDR remained independently associated with the composite complexity index and normalized entropy, while amyloid extent remained non-significant. Complexity-related clinical differences were most evident in the lowest burden stratum and attenuated at higher burden levels. Regional amyloid analyses yielded only selective signals. Conclusions: Behavioral complexity is a clinically meaningful neuropsychiatric phenotype in AD. Although strongly related to total neuropsychiatric burden, it is not fully reducible to it, with its clearest independent association seen for global dementia severity, particularly at lower overall burden. Full article

Accumulation of aggregated amyloid beta (Aβ) species is a defining pathological hallmark of Alzheimer’s disease and is associated with extensive neuronal structural abnormalities. Mild cognitive impairment (MCI), a transitional stage between normal aging and the onset of dementia, is thought to represent an early phase of this pathological continuum. Studies at the cellular level suggest that the conditions impair the maintenance of established neuronal processes/networks and restrict their capacity for elongation or re-elongation. They may also attenuate the activation and process extension of quiescent neural progenitor or stem-like cells. These early cellular changes precede overt neurodegeneration in neural tissue and are likely to contribute to cognitive decline. They highlight the importance of in vitro models for identifying molecular targets involved in recovery from disease. In this study, we investigated the effects of aggregated Aβ (25–35) on neuronal process elongation and associated intracellular events in the N1E-115 cell line, a widely used model of neuronal differentiation. Addition of aggregated Aβ to cultured N1E-115 cells attenuated process elongation in a concentration-dependent manner. This morphological impairment was accompanied by decreased expression of neuronal differentiation markers. In contrast, at the half-maximal inhibitory concentration for process elongation, long-term cultured cells did not exhibit apparent process retraction or degenerative morphology. This mild but progressive impairment, without extensive cell death, is consistent with the cellular features of early-stage conditions rather than advanced Alzheimer’s pathologies. Similar results were observed in primary cortical neurons. Aβ also decreased the level of GTP-bound Ras and phosphorylation of the downstream mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK). Furthermore, treatment with hesperetin, a bioactive flavonoid compound, recovered the Aβ-induced inhibition of neuronal process elongation. Hesperetin also restored Ras and MAPK/ERK states, suggesting that its effects are associated, at least in part, with modulation of signaling through Ras and MAPK/ERK. Our findings suggest that hesperetin may serve as a useful molecular probe for modulating early cellular responses associated with Alzheimer’s disease-related pathology. This in vitro model might serve as a useful platform for investigating the molecular target candidates involved in recovery from nervous system disorders. Full article

Dementia affects approximately 55 million people worldwide, yet the psychological experience of diagnosis and the determinants of post-diagnostic well-being remain underexplored relative to biomedical research priorities. The existing literature has been predominantly deficit-oriented, focusing on cognitive decline, neuropsychiatric symptoms, and carer burden, with limited attention to preserved psychological capacities and what supports flourishing following diagnosis. This narrative review applies a positive psychology framework to synthesise evidence on meaning, purpose, hope, and post-diagnostic adjustment in early-stage dementia. A central empirical observation motivating the review: the well-being paradox—subjective well-being in early-to-moderate dementia is frequently higher than carers and clinicians predict. It is also more strongly associated with psychosocial variables than with objective cognitive status. Evidence from the IDEAL (Improving the experience of Dementia and Enhancing Active Life) cohort and related longitudinal research demonstrates that emotional responsiveness, need satisfaction, and capacity for meaning-making are preserved in early-stage dementia and constitute clinically relevant assets. Four positive psychology constructs are identified as evidence-based targets for intervention: hope, self-compassion, social identity, and meaningful engagement. Clinical implications include integrating strengths-based assessment, meaning-centred group interventions, structured peer support, and validated positive outcome measures into post-diagnostic care pathways. Health equity considerations and research priorities are addressed, including the underrepresentation of minority ethnic communities and people with young-onset dementia in existing research. The review argues that meaningful progress requires deliberate reorientation of clinical, commissioning, and research priorities toward a positive psychology framework for dementia care. Full article

Alzheimer’s disease (AD), the leading cause of dementia, is characterized by progressive cognitive decline along with hallmark brain pathologies including amyloid-beta accumulation, hyperphosphorylated tau, neuroinflammation and neuronal mitochondrial dysfunction. As current pharmaceutical treatments only provide modest symptomatic improvement, there is an urgent need for effective non-pharmaceutical treatment options for the prevention or slowing down of this disease. This review synthesizes results from randomized controlled trials, observational studies, and animal model research on the ability of exercise to influence cognitive functions, brain structural changes, inflammatory processes, and neuroplasticity-related pathways. Exercise has demonstrated the capacity to enhance neurotrophic signaling, improve the regulation of mitochondria, improve cerebrovascular function and reduce pro-inflammatory cytokine levels in preclinical and mild cognitive impairment (MCI) subjects. Additionally, aerobic and resistance training has been shown to enhance physical performance and functional capacity. Furthermore, mind–body, dual-task and multimodal types of interventions may also provide additional cognitive and psychological benefits. Although the overall cognitive effect of exercise in individuals with established AD is generally small, it has been demonstrated that exercise can contribute to maintaining brain health through multiple interconnected metabolic, vascular and molecular pathways, thereby preserving cognitive reserve and slowing disease progression, particularly when initiated during early to midlife prior to the onset of AD symptoms. Therefore, future research will require establishing stage-specific exercise recommendations based on modality type, intensity and duration to achieve optimal clinical outcomes. Full article

(1) Background: Alzheimer’s disease is a common neurodegenerative disease which mainly affects the elderly. The aim of the study is to investigate the relationship between handgrip strength and cognitive ability in a geriatric population with early-stage dementia. There are only a few studies that associate handgrip strength with cognitive ability in a population with early-stage dementia. (2) Methods: The present study consists of a sample of 60 individuals with early-stage dementia and was conducted at the Alzheimer’s Association of Athens. Participants’ ages ranged from 65 to 93 years (M = 80 years, SD = 6.05). Specific inclusion and exclusion criteria of the sample were defined. Handgrip strength was assessed using a digital handheld dynamometer, while cognitive ability was measured using the Mini-Mental State Examination Test (MMSE). (3) Results: Descriptive statistics showed that the mean handgrip strength of the dominant upper limb was 144.45 ± 50.47 Newtons, and the mean cognitive score was M = 21.75 (SD = 1.97) (0–30 points). In a multivariable regression analysis adjusted for age, sex, and education, handgrip strength was not significantly associated with MMSE score (B = 0.056, 95% CI: −0.054 to 0.166, p = 0.314). (4) Discussion: There are few studies that correlate cognitive ability with handgrip strength in a population with early-stage dementia; thus, further studies are needed to investigate the present results, possibly with a larger sample size or using different cognitive function measurement tools. (5) Conclusions: Handgrip strength may appear not to be associated with cognitive ability when elderly patients are in early-stage dementia. More research should be conducted to confirm the present findings. Full article

Alzheimer’s Disease (AD), the most common form of dementia, is pathologically defined by extracellular beta-amyloid (Aβ) plaques and intraneuronal neurofibrillary tangles (NFTs), accompanied by chronic neuroinflammation. Recent advances in single-cell RNA sequencing (scRNA-seq/snRNA-seq) and spatial transcriptomics have provided unprecedented resolution for unraveling the cellular and molecular landscape of neuroinflammation in AD. While scRNA-seq enables high-throughput profiling of cellular heterogeneity across brain regions, spatial transcriptomics preserves tissue architecture to map cell-type-specific gene expression within its anatomical context. This review synthesizes the neuroinflammatory mechanisms of AD, outlines the technical evolution and comparative capabilities of single-cell and spatial omics platforms, including resolution, throughput, and compatibility with multiple sample types, and critically evaluates findings from studies in both animal models and human brain tissues. These approaches have revealed state-specific transitions in microglia and astrocytes, including shifts in transcriptional programs, metabolic reprogramming, and pro-inflammatory polarization across disease stages. Notably, spatial transcriptomic analyses demonstrate pronounced regional heterogeneity: periplaque microenvironments exhibit distinct immune-cell compositions and gene expression signatures. Collectively, these omics technologies are redefining the cellular basis of AD progression and hold the potential to impact the discovery of early diagnostic biomarkers and precision therapeutic targets. Full article

Effective dementia care is often hindered by fragmented communication among patients, informal caregivers, and clinicians. To address this, we introduce an ambient assisted living (AAL) framework designed to establish a continuous, virtual, and unobtrusive connection between an elder’s home and external guardians or medical staff (virtual rounds). The system enables guardians to communicate directly within the home environment, without requiring the older adult to manually accept calls or activate the connection using wearable devices, buttons, or other interfaces. The elders can activate the connection verbally. The structural core of this system relies on three novel hardware configurations designed for zero-interface operation: a remote audio announcement device, a bidirectional intercom, and a “zero-interface mirror” enabling stream-only, real-time video co-presence between patients and guardians. Crucially, the system utilizes a privacy-preserving, staged edge-AI architecture to process data. By default, it operates without long-term persistent storage, selectively transmitting abstracted audio-based behavioral metrics to a secure dashboard. For advanced dementia stages, the system employs ephemeral data retention—specifically a highly restricted, 24 h rolling audio buffer—allowing authorized guardians to verify acute events without permanently exfiltrating raw data. We evaluate this infrastructure through a 10-month longitudinal, single-home feasibility deployment, augmented with historical verified fall data to rigorously test the detection of rare acute events. The study validates the framework’s technical viability, system uptime, and privacy-first architecture in continuously tracking long-term proxy behavioral indicators under real-world conditions. Rather than asserting generalized clinical efficacy, this work demonstrates the operational feasibility of a novel, affordable, technical blueprint for dignified, remote digital care coordination. Full article

Background: Behavioral and psychological symptoms of dementia (BPSD) substantially impair quality of life in individuals with dementia and increase caregiver burden. Conventional non-pharmacological interventions may be limited in terms of engagement and individualized support. This study evaluated the effects of an augmented reality (AR)-integrated aromatherapy intervention on BPSD and psychosocial well-being among older adults with early-stage dementia. Methods: A randomized controlled trial was conducted with 160 participants in Taiwan, including an experimental group (n = 80) and a comparison group (n = 80). The experimental group received a 6-week intervention comprising 12 AR-based aromatherapy sessions delivered twice weekly, whereas the comparison group received routine care. Generalized estimating equations (GEEs) were used to examine group-by-time interaction effects while controlling for baseline gender. Results: Significant group-by-time interaction effects were observed across all outcome measures (all p < 0.001). Compared with the comparison group, the experimental group showed greater reductions in NPI-Q symptom frequency (β = −0.775), symptom severity (β = −2.575), and caregiver distress (β = −4.800). In addition, the intervention group demonstrated significant improvements in pain (β = −2.625), insomnia severity (β = −4.425), psychological well-being (β = 7.675), and life satisfaction (β = 6.913). Baseline gender differences did not significantly affect intervention outcomes. Conclusions: The AR-integrated aromatherapy intervention appears to be an effective non-pharmacological approach for reducing BPSD and improving physical and psychosocial well-being among older adults with early-stage dementia. This technology-enhanced intervention may offer a promising care model for dementia management in geriatric care settings. Full article

The hallmarks of allergic diseases are Type 2 immunity, including IL-4 and IL-13 production, IgE antibody generation, mast cell and basophil activation, histamine release, and eosinophil activation. There are many routes by which such mediators can influence CNS biology, including cytokine entry or signaling via brain barrier receptors; leukocyte trafficking across activated barriers; cytokine signaling via circumventricular organ sites or dural immune compartments; vagus nerve afferent signaling; mast cell degranulation; and histamine neuromodulation. Neuroinflammation is a common hallmark of many neurodegenerative diseases, but whether and to what degree allergic/type 2 immune biology may be involved depends on the specific disease stage and pathology. Here, we assess studies connecting the roles of IL-4/IL-13 signaling, IgE/mast cell activation, eosinophil-attractive chemokines, and histamines in Parkinson’s disease, Alzheimer’s disease, multiple sclerosis, amyotrophic lateral sclerosis, dementia with Lewy bodies, Huntington’s disease, prion disease, and tauopathy/atypical parkinsonism. Mechanisms appear most clear in the case of Parkinson’s disease, where epidemiology suggests an important role in dementia/Alzheimer’s disease, while for other neurodegenerative conditions the evidence is less compelling and may be either mechanistic or modulatory. Confounding issues include sex differences, drug exposures, comorbid conditions, socioeconomic factors, and coexisting inflammatory diseases. Finally, we suggest a strategy based on longitudinal immune phenotyping, CNS biomarkers, and pathway manipulation to assess the relationship between allergic immune signaling and neurodegeneration. Full article