While vitamin B12 deficiency is classically associated with hematological abnormalities and subacute combined degeneration, its presentation as rapidly progressive cognitive decline with episodic movement disorders remains an underrecognized clinical phenomenon. This case highlights the diagnostic challenges posed by such non-classical neurological manifestations and underscores the need for increased clinical suspicion in cases of unexplained cognitive-motor decline. A patient presented with rapidly progressive memory impairment and episodic limb tremors in the absence of overt hematological signs. Serum anti-parietal cell antibody (Anti- PCA) was positive (++; titer 1:32), and anti-intrinsic factor antibody (Anti-IFA) was positive (+) in the patient. Extensive diagnostic workup ruled out common neurodegenerative and structural causes, leading to the detection of severe vitamin B12 deficiency. Initiation of high-dose B12 replacement therapy resulted in marked improvement in both cognitive function and tremor control over subsequent weeks. This case illustrates that vitamin B12 deficiency can manifest as a rapidly progressive neurocognitive disorder mimicking neurodegenerative conditions. It emphasizes the importance of routinely assessing B12 status in patients with unexplained cognitive and movement abnormalities, as timely intervention can prevent irreversible neurological injury and yield significant clinical improvement.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory loss, cognitive decline, and neuronal dysfunction. Despite thorough research efforts, effective disease-modifying treatments have yet to be discovered. MicroRNAs (miRNAs), small noncoding RNAs that control gene expression after transcription, have become key factors in AD development. Changes in miRNA levels influence critical molecular pathways such as amyloid precursor protein (APP) processing, tau phosphorylation, oxidative stress, neuroinflammation, and synaptic plasticity, all of which contribute to neuronal damage. By increasing β-secretase (BACE1) activity, downregulation of miR-29a/b and miR-107 encourages the buildup of amyloid-β (Aβ) and the development of plaques. Through the deregulation of the CDK5 and MAPK pathways, overexpression of miR-125b and decreased levels of miR-132/212 lead to tau hyperphosphorylation. While oxidative stress-associated miRNAs like miR-34a and miR- 21 worsen mitochondrial malfunction and neuronal death, pro-inflammatory miRNAs like miR-146a and miR-155 cause NF-κB-mediated signalling and glial activation. Circulating miRNAs found in blood and cerebral fluid are potential, minimally invasive indicators for tracking the course of a disease and making early diagnoses. Additionally, therapeutic manipulation with antagomiRs or miRNA mimics has the potential to prevent neurodegeneration and restore normal gene regulation. This review deciphers the molecular mechanisms underlying miRNA dysregulation in AD and explores their translational potential as biomarkers and therapeutic targets. A comprehensive understanding of miRNA-protein interaction networks could facilitate the development of targeted, precision- based interventions for Alzheimer's disease.

Alzheimer's Disease (AD) is a major global challenge and the most common cause of dementia worldwide. Accumulation of Amyloid-Beta (Aβ) is considered a key factor in AD pathophysiology and progression, and is linked to disruptions of neuronal integrity and the initiation of several downstream neurodegenerative cascades. Immunotherapeutic agents targeting Aβ have emerged as potential disease-modifying drug candidates, and extensive efforts have been dedicated to both active and passive modalities. Early Aβ vaccines demonstrated proof of concept; however, they were later discontinued due to several safety concerns, which, in turn, guided the refinement of epitope design and immune response modulation in the second-generation ones. On the other hand, early monoclonal antibodies have also faced challenges, such as variable efficacy and adverse events, particularly Amyloid-Related Imaging Abnormalities (ARIA), which ultimately led to their discontinuation. Nonetheless, recent regulatory advances have led to the approvals of Aduhelm® (Aducanumab), Leqembi® (Lecanemab), and Kisunla® (Donanemab), each of which has demonstrated the ability to reduce Aβ burden and slow cognitive decline. Despite these advancements, challenges persist regarding patient selection, biomarker-guided monitoring, ARIA risk reduction, long-term outcomes, and global accessibility. Notably, the clinical benefits observed to date remain modest, and it remains uncertain whether the currently approved Aβ-targeted immunotherapies achieve meaningful long-term disease modification. Collectively, the evolution of Aβ-targeted immunotherapies has provided further insights into the complexity of AD pathology and the challenges associated with future progress toward achieving effective disease modification. This paper aims to provide a comprehensive review of all Aβ-directed immunotherapies, both active and passive agents, that have advanced into clinical trials, including those currently approved, discontinued, or undergoing late-stage evaluation.

Introduction: This study aimed to assess the association of Geriatric Nutritional Risk Index (GNRI) with cognitive function level and cognitive impairment risk among older adults with cardiometabolic disease using data from the National Health and Nutrition Examination Survey (NHANES). Methods: Using cross-sectional data from the NHANES, this research included 1,937 participants aged 60 years or older with at least one cardiometabolic disease (diabetes, hypertension, stroke, or congestive heart failure). Cognitive function was assessed using the CERAD tests, Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST). Multivariable linear and logistic regression analyses were used to estimate the β coefficients and odds ratios (ORs) with 95% confidence intervals (CIs) for the associations of GNRI with cognitive function level and risk of cognitive impairment. Results: A total of 1937 participants aged≥60 years with cardiometabolic disease were included. The results showed that per 1-SD increase in GNRI was associated with increased cognitive function levels, including CERAD: Trial 1 (β=0.11, 95% CI: 0.03-0.19), CERAD: Trial 3 (β=0.12, 95% CI: 0.04-0.21), CERAD: Delayed Recall (β=0.21, 95% CI: 0.11-0.32), CERAD test (β=0.53, 95% CI: 0.23-0.82), and AFT (β=0.34, 95% CI: 0.11-0.57) scores. Restricted cubic splines showed significantly positive linear dose-response associations between GNRI and cognitive function. Compared to participants with the lowest quartile (Q1) of GNRI, those with the highest quartile (Q4) had a lower cognitive impairment risk (OR=0.59, 95% CI: 0.41-0.85). Discussion: Potential mechanisms underlying GNRI’s protective effect against cognitive impairment may involve the pleiotropic neuroprotection of albumin and body mass index-mediated brain structural changes. Conclusion: Higher GNRI is independently associated with better cognitive function and reduced risk of cognitive impairment in older adults with cardiometabolic diseases. To mitigate cognitive risk, implementing GNRI screening may identify high-risk older adults with cognitive impairment, prompting timely nutritional support that improves cognitive health and disease management.

<p> Olfactory Dysfunction (OD) is a prevalent yet underdiagnosed sensory disorder with profound implications for quality of life and for the early detection of neurodegenerative diseases such as Parkinson's and Alzheimer's. Beyond its sensory role, OD has emerged as an early, noninvasive biomarker of neurodegenerative pathology, often preceding measurable cognitive decline in Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI). Quantitative smell loss correlates with pathological changes in the olfactory bulb and entorhinal cortex, highlighting its diagnostic potential for early screening and longitudinal monitoring. </p><p> Traditional diagnostic tools, though validated, often require specialized personnel, laboratory infrastructure, and extended testing time, limiting accessibility. This review critically examines recent innovations in the detection of olfactory dysfunction, focusing on portable, user-friendly smell test kits and their comparative performance with self-reported tools such as the Mini Olfactory Questionnaire (Self-MOQ) and 4-CAST. We synthesize evidence on diagnostic reliability, usability, and cultural adaptability, evaluating how these methods align with emerging needs in Alzheimer's and dementia research. </p><p> Portable kits such as PT-Smell and SSomix demonstrate high diagnostic precision and cultural adaptability, while self-administered and self-report tools enable scalable deployment in memory clinics and community screening programs. Within Alzheimer's research, these approaches present practical solutions for early identification of sensory biomarkers linked to cognitive decline. </p><p> To optimize diagnostic integration, a two-step framework is proposed: first-line screening with self-administered tools such as Self-MOQ or 4-CAST, followed by confirmatory psychophysical testing with portable kits such as PT-Smell or SSomix. This tiered model supports early AD and MCI detection, enhances accessibility, and promotes digital health integration for widespread olfactory monitoring. </p>.

Alzheimer's disease (AD) is characterized by significant brain atrophy, detectable via structural MRI. There has been less focus on cortical degeneration in subcortical regional deterioration-particularly during the transition from Mild Cognitive Impairment (MCI) to AD-which remains underexplored. This study aims to identify subcortical regions with progressive atrophy using surface-based morphometry (SBM) and evaluate their potential for early AD diagnosis. This longitudinal study collected data from MCI patients (6 months) who later progressed to Alzheimer's within 3 years, alongside healthy controls followed across four time points (6 months-3 years). Reported in line with STARD guidelines, the study aimed to evaluate model performance in distinguishing progressive MCI-to-AD from healthy controls to advance early Alzheimer's diagnosis. The study leveraged the ADNI dataset to analyse 68 subcortical regions in MCI-to-AD converters (MCI-AD) and Healthy Controls (HC) over 6 months to 3 years (i.e., at 6 months, 1 year, 2 years, and 3 years). The groups were classified beforehand using the Clinical Dementia Rating and the Mini-Mental Status Examination scores. Accordingly, three surfacebased morphometry (SBM) metrics-cortical thickness (CTh), gyrification index (GI), and sulcal depth (SD)-were evaluated in the progressive MCI group (individuals with MCI who later converted to Alzheimer's disease) as well as in healthy controls, to quantify morphological changes. Finally, the morphological data were utilized to train and test machine learning models for classification and prediction. Cortical regions exhibiting significant atrophy were identified using paired-samples ttests between 6 months and 3 years. In parallel, machine learning (ML) models were trained and tested on the same dataset to differentiate progressive MCI-to-AD cases from healthy controls across multiple time points (6 months, 1 year, 2 years, and 3 years), and subsequently to predict the progression to Alzheimer's disease. Certain evaluation metrics were considered for the classifier performance, i.e., Accuracy, F1-score, and AUC-ROC. Sub-cortical SBM metrics, particularly CTh, are sensitive to early AD-related atrophy, offering potential biomarkers for disease progression. ML models trained on these features enable accurate classification, with performance peaking near diagnosis-highlighting their utility in early intervention. SBM-derived subcortical atrophy patterns aid early AD detection and, when combined with ML, offer a scalable predictive framework. Among metrics, CTh showed the greatest decline in MCI-AD, followed by SD and GI. Progressive deterioration was observed in specific subcortical regions, accelerating near diagnosis. Classifiers achieved higher accuracy in distinguishing MCI-AD from HC at later time points, highlighting stage-specific shifts in feature importance.

Dementia is the most common neurodegenerative disease, but the risk factors associated with its progression remain incompletely understood. Identifying clinical and medication-related determinants of cognitive decline may inform patient management and guide treatment strategies. Individuals with dementia who underwent paired Mini-Mental State Examination (MMSE) assessments between 2013 and 2019 were identified from the Taipei Medical University Clinical Research Database. To ensure adequate follow-up, paired assessments were required to be at least 90 days apart, with an actual mean follow-up interval of 21.5 ± 18.0 months. Demographic data, comorbidities, medication prescriptions, and blood biochemistry results were extracted. Generalized estimating equations were applied to evaluate associations between these factors and MMSE changes. A total of 3,054 individuals with dementia were included (mean age 78.0 ± 9.2 years, 61.1% women). The mean baseline MMSE score was 18.5 ± 6.7 and it declined to 16.0 ± 7.5 at follow-up. Male sex was significantly associated with greater MMSE decline (estimate: -0.920, 95% CI: -1.552 to -0.289, p = 0.004). Antidementia medications were significantly associated with less decline in MMSE scores (estimate: 1.245, 95% CI: 0.676 to 1.815, p < 0.001). In contrast, non-aspirin antiplatelet agent use was associated with a greater decline among men (estimate: -1.346, 95% CI: -2.518 to -0.173, p = 0.025). These findings highlighted that both clinical and pharmacological factors influence cognitive decline in dementia. Antidementia medications were linked to slower deterioration, supporting their role in disease management. Conversely, the association of non-aspirin antiplatelet agents with faster decline in men suggested potential adverse effects that warrant further investigation. In this large real-world cohort, sex and medication use were key determinants of cognitive decline in dementia. Antidementia medications mitigated decline. Notably, only non-aspirin antiplatelet agents, but not aspirin, were associated with greater cognitive decline in men., underscoring the need for personalized treatment approaches.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder marked by the accumulation of amyloid-beta (Aβ) peptides, especially the toxic Aβ42 isoform, which induces excessive reactive oxygen species (ROS) production leading to oxidative damage, lipid peroxidation, and neuronal loss. Given the critical role of oxidative stress in AD pathogenesis, antioxidants such as ascorbic acid (AA) are being explored for their therapeutic potential. This study aimed to investigate the neuroprotective efficacy of ascorbic acid in a transgenic Drosophila melanogaster model expressing human Aβ42 in neuronal tissues. Transgenic and wild-type flies were maintained on diets supplemented with optimized, non-toxic concentrations of AA. Biochemical assays were performed to evaluate oxidative stress and antioxidant defense, including glutathione (GSH) levels, glutathione S-transferase (GST), superoxide dismutase (SOD), catalase (CAT), thiobarbituric acid-reactive substances (TBARS), and protein carbonyl content (PCC). Acetylcholinesterase (AChE) activity and locomotor performance were also assessed. Ascorbic acid supplementation significantly enhanced GSH levels, normalized GST, SOD, and CAT activities, and reduced TBARS and PCC levels, indicating restoration of redox balance. Partial recovery of AChE activity suggested protection of cholinergic neurotransmission. Functionally, AA-fed AD flies exhibited improved locomotor performance, delayed onset of memory impairment, and extended lifespan compared to untreated AD flies. The findings demonstrate that ascorbic acid provides multifaceted neuroprotection by mitigating oxidative stress, stabilizing cholinergic function, improving behavioural outcomes, and enhancing longevity. AA emerges as a promising, low-cost natural antioxidant for potential use in Alzheimer's disease management.

Previous research explores the relationship between the cognitive status of people with dementia (PwD) and their performance in complex, domain-specific interaction tasks. However, these activities and their sophisticated instructions are challenging for PwD, potentially biasing performance metrics. This study aims to answer whether the cognitive status of PwD is related to their performance in simple touch and tangible tasks disassociated from a domain. This study involved 7 formal caregivers and data from 21 PwD corresponding to completion times of interaction tasks. Relationships between completion times and the cognitive status of PwD were explored using Spearman's rank correlation, mutual information, gini importance, permutation importance, and a principal component analysis (PCA) visualization. Completion times of drag & drop, grasp, and tap interaction tasks have a strong negative monotonic association with the MMSE score (Bonferroni-corrected p-value < 0.05). The most relevant gestures were drag & drop, tap, and grasp. The PCA visualization allowed formal caregivers to detect relationships between patients' performance and their MMSE scores (p-value < 0.05). The cognitive status of PwD is related to their performance in simple interaction tasks disassociated from a domain. As the MMSE score decreases, task completion times increase. In addition, the PCA visualization was considered useful to inform decision-making. This work provides the foundation for technology-enhanced cognitive activities supported by touch and tangible gestures that can be used to determine the cognitive status of PwD.

Primary progressive aphasia (PPA) is a clinical syndrome characterized by progressive language impairment. Three subtypes have been identified: semantic (svPPA), nonfluent (nfPPA), and logopenic (lvPPA). Although clinical criteria exist to classify these subtypes, the specific ways in which semantic cognition is impaired across these variants have not yet been fully elucidated. This cross-sectional study aimed to analyze the effects of cognitive demand and imaginability on semantic cognition in patients with PPA. Fifteen patients with PPA (five per variant) and 20 healthy controls completed a semantic association task comprising 20 items. The task included two levels of cognitive demand (low and high) and two types of concepts (concrete and abstract). Participants selected the word with the strongest semantic link to a probe word, based on synonymy, categorical relations, or shared features. Accuracy and reaction times were recorded and analyzed using nonparametric statistics. All PPA groups performed significantly worse than controls, showing fewer correct responses and longer reaction times. svPPA patients exhibited the greatest impairment across all conditions. nfPPA patients performed similarly to controls with concrete concepts but showed deficits with abstract words. lvPPA patients experienced greater difficulty under high cognitive demand, particularly with abstract words, indicating impaired semantic control. These findings suggest that svPPA is characterized by global impairment of conceptual knowledge, whereas nfPPA and lvPPA exhibit more selective deficits depending on concept type and cognitive demand. The research herein highlights the importance of considering cognitive demand and imaginability when assessing semantic cognition in PPA.