Current Alzheimer Research - Online First
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23 results
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Topological Biomarkers of Alzheimer’s Disease from Functional Brain Network Analysis
Authors: Soudeh Behrouzinia and Alireza KhanteymooriAvailable online: 26 August 2025More LessIntroductionAlzheimer’s disease is a progressive neurodegenerative condition characterized by the gradual deterioration of cognitive functions. Early identification of functional brain changes is crucial for timely diagnosis and effective intervention. This study employs multiplex network analysis to examine alterations in brain connectivity topology associated with Alzheimer's Disease, to identify early biomarkers and uncover potential therapeutic targets.
MethodsThis study presents a secondary cross-sectional analysis based on a publicly available EEG dataset comprising spectral coherence measurements from 25 patients with clinically diagnosed Alzheimer's Disease (AD) and 25 age- and gender-matched Healthy Controls (HC). Functional connectivity matrices were generated across seven distinct frequency bands, with each brain region modeled as a network node and inter-regional coherence values represented as weighted edges. These matrices were then used to construct multiplex brain networks, which were rigorously analyzed using graph-theoretical approaches. The analysis encompassed key metrics, including modularity, centrality measures (Betweenness and MultiRank), motif distribution, and network controllability, to characterize and compare the underlying patterns of functional brain organization in AD and healthy aging.
ResultsNetworks associated with AD exhibited significantly reduced modularity, disrupted centrality patterns, and a higher occurrence of 2 and 3-node motifs, indicating local reorganization of connectivity. Additionally, the spatial distribution of driver nodes was markedly altered in AD. Centrality analyses revealed a pronounced shift in network hubs toward the temporal and insular cortices, suggesting compensatory or pathological reallocation of influence. Controllability assessments demonstrated a lower energy requirement for network control in AD, accompanied by increased inter-layer fragmentation, reflecting compromised integrative function across frequency bands.
DiscussionThe findings revealed specific topological alterations, including reduced modularity, altered centrality, and decreased controllability, all of which are closely linked to AD-related network degeneration. By leveraging multi-frequency EEG data, the multiplex approach shows significant clinical potential for monitoring disease progression and supporting personalized treatments, with the ability to detect subtle connectivity disruptions before cognitive symptoms manifest.
ConclusionMultiplex network analysis reveals distinct and robust alterations in the functional brain architecture of individuals with Alzheimer’s Disease. These network-level disruptions offer valuable insights into the pathophysiology of AD and highlight potential avenues for early diagnosis and targeted therapeutic strategies aimed at preserving cognitive function.
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Multimodal Deep Learning Approaches for Early Detection of Alzheimer’s Disease: A Comprehensive Systematic Review of Image Processing Techniques
Authors: Jabli Mohamed Amine and Moussa MouradAvailable online: 07 August 2025More LessIntroductionAlzheimer's disease (AD) is the most common form of dementia, and it is important to diagnose the disease at an early stage to help people with the condition and their families. Recently, artificial intelligence, especially deep learning approaches applied to medical imaging, has shown potential in enhancing AD diagnosis. This comprehensive review investigates the current state of the art in multimodal deep learning for the early diagnosis of Alzheimer's disease using image processing.
MethodsThe research underpinning this review spanned several months. Numerous deep learning architectures are examined, including CNNs, transfer learning methods, and combined models that use different imaging modalities, such as structural MRI, functional MRI, and amyloid PET. The latest work on explainable AI (XAI) is also reviewed to improve the understandability of the models and identify the particular regions of the brain related to AD pathology.
ResultsThe results indicate that multimodal approaches generally outperform single-modality methods, and three-dimensional (volumetric) data provides a better form of representation compared to two-dimensional images.
DiscussionCurrent challenges are also discussed, including insufficient and/or poorly prepared datasets, computational expense, and the lack of integration with clinical practice. The findings highlight the potential of applying deep learning approaches for early AD diagnosis and for directing future research pathways.
ConclusionThe integration of multimodal imaging with deep learning techniques presents an exciting direction for developing improved AD diagnostic tools. However, significant challenges remain in achieving accurate, reliable, and understandable clinical applications.
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Unveiling the Potential Role of Cathinone and Cathine Compounds in Alzheimer's Disease: Predictive Insights
Authors: Mohammed S. Alkaf, Musa A. Said, Noura A. Algamdi and Nadia S. Al-KaffAvailable online: 01 August 2025More LessIntroductionKhat (Catha edulis (Vahl) Forssk. ex Endl.), a stimulant plant native to Africa and Asia, contains psychoactive compounds such as cathinone and cathine that affect the central nervous system. This study aims to investigate the potential neurotoxicological risks associated with these compounds, particularly focusing on their possible relationship with neurodegenerative disorders like Alzheimer's disease (AD). The primary objective was to evaluate the toxicity of khat's main compounds and examine their molecular interactions with Monoamine Oxidase A (MAO-A), an enzyme implicated in the pathology of AD.
MethodsThe toxicological profiles of cathinone, cathine, amphetamine, and the AD medication Donepezil were assessed using the Protox-3 server, which predicted toxicity class, potential for liver damage, carcinogenicity, immunotoxicity, mutagenicity, and cytotoxicity. Molecular docking studies were conducted to analyse the binding interactions of these compounds with MAO-A (PDB ID: 2Z5X). Binding affinities and key interacting residues were identified. The steric effects of the ligands within the enzyme's binding site were quantified by calculating the buried volume (%VBur) using the centroid of centres method.
ResultsProtox-3 classified cathine and amphetamine as Class 3 toxicants (moderate toxicity), while cathinone and Donepezil were assigned to Class 4 (lower toxicity). Cathinone also demonstrated a moderate probability (0.64) of carcinogenicity. Molecular docking revealed that khat compounds had an average binding affinity of -5.81 ± 0.27 kcal/mol, which was lower than that of amphetamine (-6.10 ± 0.27 kcal/mol) and Donepezil (-7.80 ± 0.38 kcal/mol). Buried volume analysis indicated that khat compounds and amphetamine were more deeply embedded in the MAO-A binding site, correlating with stronger binding affinity.
DiscussionThe computational results suggest that khat compounds exhibit moderate neurotoxic potential and interact with MAO-A in a manner that could be relevant to AD pathology. Although the binding affinities are lower than those of Amphetamine and Donepezil, they point to possible molecular-level interactions significant for neurodegeneration. Steric hindrance, as quantified by %VBur, appeared to influence binding strength, highlighting the importance of molecular fit within the active site.
ConclusionThis study presents evidence of a potential molecular link between khat consumption and an increased risk of Alzheimer's disease. The findings underscore the necessity for further in vivo and epidemiological research, particularly in regions with high rates of khat use, to assess its long-term neurotoxic effects.
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Exploring the Interconnections of Genetic, Lifestyle, and Epigenetic Influences on Brain Aging: A Comprehensive Review
Authors: Shima Mehrabadi and Sama BaratiAvailable online: 01 August 2025More LessAlzheimer's disease (AD) is a devastating neurodegenerative disorder characterized by progressive cognitive decline and memory loss. The etiology of AD is complex and multifactorial, with contributions from genetic, lifestyle, and environmental factors. Recent advances in genetics, epigenetics, and animal models have shed light on the underlying mechanisms of brain aging and the development of AD, revealing potential targets for therapeutic intervention. In this comprehensive review, we examine the current understanding of the genetic, lifestyle, and epigenetic factors that shape the landscape of brain aging and AD. We discuss recent findings in the field of AD genetics, including the role of the APOE gene, and the potential of novel genome-wide association studies to identify new genetic risk factors. We also review the impact of lifestyle factors, such as diet, exercise, and social engagement, on brain aging and AD, and explore the role of epigenetic mechanisms, such as DNA methylation and histone modifications, in shaping AD risk.
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Integration of Neuroimaging and Molecular Biomarkers in the Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia: The Promise of fMRI
Available online: 31 July 2025More LessIntroductionDementia is a set of acquired and progressive neuropsychiatric disorders. The most common types of dementia include Alzheimer’s Disease (AD) and Frontotemporal Dementia (FTD). Early intravital diagnosis of both types of dementia is difficult. Both molecular and neuroimaging markers are important for the diagnosis of different types of dementia.
MethodsThis review employed freely accessible databases, including PubMed, Google Scholar, and ScienceDirect, using keywords such as molecular parameters, neuroimaging factors, dementia, FTD, Alzheimer’s disease, and fMRI.
ResultsAmong the molecular markers of dementia, there are parameters common to its various types and enabling their differentiation. These parameters include both genetic and biochemical factors. Markers include genetic factors that help differentiate AD (APP, PSEN1, PSEN2) from FTD (e.g., TARDBP, FUS, MAPT). Simultaneously, there are important biochemical parameters differentiating AD (amyloid-beta (Aβ), neurofibrillary tangles) from FTD (TDP-43, FUS, and different forms of tau protein aggregates). Currently, there is growing interest in neuroimaging studies in the differential diagnosis of dementia. Positron Emission Tomography (PET) imaging enables the quantification and localization of Aβ deposits in the brain through the selective binding of the Pittsburgh Compound-B (PiB) ligand. This method has become the standard in AD diagnostics. In the context of magnetic resonance imaging studies, it is worth noting the search for structural differences between AD (mainly affecting the temporal lobe, including the hippocampus and entorhinal cortex, and the parietal lobe) and FTD (primarily involving the prefrontal cortex, anterior temporal lobes, and subcortical structures, as well as exhibiting an anteroposterior gradient of atrophy). However, the method of the future appears to be functional Magnetic Resonance Imaging (fMRI), especially since functional changes precede structural changes in the development of dementia.
DiscussionThe review encompasses the basic diagnostic criteria for AD and FTD dementia, as well as molecular and neuroimaging parameters important for the intravital diagnosis of these dementias. It seems that the use of fMRI can contribute to both early diagnosis and early introduction of targeted treatment in developing dementia. Although it is not yet widely used clinically, its diagnostic value is increasingly recognized.
ConclusionThe benefits of fMRI studies complementing molecular markers in the diagnosis of dementia were highlighted.
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Lithium Chloride Improves Electrophysiological and Memory Deficits in Rats with Streptozotocin-Induced Alzheimer's Disease
Authors: Zheng Xing, Xiaolian Jiang, Wenhao Yang, Yuhui Wang, Xiaoxiao Zhang and Chen ZhaoAvailable online: 31 July 2025More LessIntroductionAlzheimer's disease (AD) is a neurodegenerative disorder of the central nervous system characterized by complex pathological manifestations and an unclear pathogenesis. Lithium chloride (LiCl) exhibits certain neuroprotective effects. However, its performance and mechanisms in different types of AD models remain unclear.
MethodsThe streptozotocin (STZ)-induced AD rat model was used to evaluate the ameliorating effects of LiCl. LiCl was administered orally for one month, and then evaluations were conducted in terms of nerve electrophysiology, behavioral science, and molecular biology.
ResultsIn this study, STZ was found to significantly affect the electrophysiological functions and behavioral performances of rats. However, LiCl was able to mitigate these effects. Specifically, it led to the restoration of electrophysiological functions, with long-term potentiation (LTP) being successfully induced. LiCl also demonstrated favorable therapeutic effects in rats, as confirmed by the nest-building tests, Y-maze, and Morris water maze. Further research revealed that LiCl promoted the phosphorylation of GSK-3β in the hippocampal region of rats.
DiscussionThese findings indicated that LiCl demonstrated beneficial effects on AD-like pathological changes in STZ-induced AD rats, possibly by activating GSK-3β phosphorylation in the hippocampus, improving electrophysiological functions, and further restoring behavioral characteristics.
ConclusionIn conclusion, LiCl demonstrated therapeutic potential for AD by improving neurophysiological and behavioral deficits via hippocampal GSK-3β phosphorylation.
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Effective Analysis of Alzheimer's Disease and Mechanisms of Methyl-4-Hydroxybenzoate using Network Toxicology, Molecular Docking, and Machine Learning Strategies
Authors: Jianren Wen, Jingxuan Hu, Xue Yang, Feifei Luo and Guohui ZouAvailable online: 15 July 2025More LessIntroductionNowadays, the large increase in environmental pollutants has led to the occurrence and development of an increasing number of diseases. Studies have shown that exposure to environmental pollutants, such as methyl-4-hydroxybenzoate (MEP) may lead to Alzheimer's disease (AD). Therefore, the purpose of this study was to elucidate the complex effects and potential molecular mechanisms of environmental pollutants MEP on AD.
MethodsThrough exhaustive exploration of databases, such as ChEMBL, STITCH, SwissTargetPrediction, and Gene Expression Omnibus DataSets (GEO DataSets), we have identified a comprehensive list of 46 potential targets closely related to MEP and AD. After rigorous screening using the STRING platform and Cytoscape software, we narrowed the list to nine candidate targets and ultimately identified six hub targets using three proven machine learning methods (LASSO, RF, and SVM): CREBBP, BCL6, CXCR4, GRIN1, GOT2, and ITGA5. The “clusterProfiler” R package was used to conduct GO and KEGG enrichment analysis. At the same time, we also constructed disease prediction models for core genes. At last, six hub targets were executed molecular docking.
ResultsWe derived 46 key target genes related to MEP and AD and conducted gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. MEP might play a role in AD by affecting the pathways of neuroactive ligand-receptor interaction. Nine genes were screened as pivotal targets, followed by machine learning methods to identify six hub targets. Molecular docking analysis showed a good binding ability between MEP and CREBBP, BCL6, CXCR4, GRIN1, GOT2 and ITGA5. In addition, changes in the immune microenvironment revealed a significant impact of immune status on AD.
DiscussionsThis study revealed that MEP may induce AD through multiple mechanisms, such as oxidative stress, neurotoxicity, and immune regulation, and identified six core targets (CREBBP, BCL6, etc.) and found that they are related to changes in the immune microenvironment, such as T cells and B cells, providing new molecular targets for AD intervention.
ConclusionOverall, CREBBP, BCL6, CXCR4, GRIN1, GOT2, and ITGA5 have been identified as the crucial targets correlating with AD. Our findings provide a theoretical framework for understanding the complex molecular mechanisms underlying the effects of MEP on AD and provide insights for the development of prevention and treatment of AD caused by exposure to MEP.
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Identification of MicroRNA Drug Targets for Alzheimer's and Diabetes Mellitus Using Network Medicine
Available online: 14 July 2025More LessIntroductionType 2 diabetes mellitus (T2D) is a known risk factor for developing Alzheimer’s disease (AD). Recent research shows that both diseases share complex and related pathophysiological processes. Network medicine approaches can help to elucidate common dysregulated processes among different diseases, such as AD and T2D. Thus, the aim of this work was to determine differentially expressed genes (DEGs) in AD and T2D and to apply a network medicine approach to identify the microRNAs (miRNAs) involved in the AD-T2D association.
MethodsGene expression microarray data sets consisting of 384 control samples and 399 samples belonging to AD and T2D disease were analyzed to obtain DEGs shared by both diseases; the miRNAs associated with these DEGs were predicted using a network medicine approach. Finally, potential small molecules targeting these potentially deregulated miRNAs were identified.
ResultsAD and T2D shared a subset of 82 downregulated DEGs. These genes were significantly associated (p < 0.01) with the ontology terms of chemical synaptic deregulation. DEGs were associated with 12 miRNAs expressed in specific tissues for AD and T2D. Such miRNAs were also primarily associated with the ontology terms related to synaptic deregulation and cancer, and AKT signaling pathways. Steroid anti-inflammatory drugs, antineoplastics, and glucose metabolites were predicted to be potential regulators of the 12 shared miRNAs.
DiscussionThe network medicine approach integrating DEGs and miRNAs enabled the identification of shared, potentially deregulated biological processes and pathways underlying the pathophysiology of AD and T2D. These common molecular mechanisms were also linked to drugs currently used in clinical practice, suggesting that this strategy may inform future drug repurposing efforts. Nonetheless, further in-depth biological validation is required to confirm these findings.
ConclusionNetwork medicine allowed identifying 12 miRNAs involved in the AD-T2D association, and these could be drug targets for the design of new treatments; however, the identified miRNAs need further experimental confirmation.
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The Interaction between Oligodendrocytes and Aβ in Alzheimer's Disease
Authors: Wenjing Wang, Xueyan Huang, Zucai Xu and Changyin YuAvailable online: 07 July 2025More LessOligodendrocytes (OLs) are the primary myelinating cells in the central nervous system (CNS), responsible for maintaining the rapid conduction of nerve signals and ensuring neuronal stability through metabolic and nutritional support. Recent studies have reported that OLs are also involved in the development and progression of Alzheimer's disease (AD), particularly in the production and clearance of amyloid-beta (Aβ), exhibiting complex and critical regulatory functions. While traditional research has predominantly focused on the roles of neurons and microglia in Aβ metabolism, recent evidence indicates that OLs engage in a complex bidirectional interaction with Aβ in AD. On the one hand, OLs can produce Aβ, frequently generating aggregated and highly toxic Aβ42, which contributes to plaque expansion and disease progression. On the other hand, neuron-derived Aβ exerts a concentration-dependent dual effect on OLs. At high concentrations, it induces oxidative stress and cell apoptosis, while at low concentrations, it promotes their differentiation and myelin repair functions. Therefore, OLs serve as both a “source” and a “target” of Aβ production and response, making them a key factor in AD pathogenesis. This review discusses the interaction between OLs and Aβ in AD, aiming to provide new perspectives on targeting OLs for AD therapy. Given the dual role of OLs in Aβ metabolism, targeting OLs dysfunction and the regulatory mechanisms underlying Aβ production and clearance could provide novel therapeutic strategies for AD. Future research should investigate the roles of specific OL populations (including oligodendrocyte precursor cells (OPCs), pre-myelinating OLs, and mature OLs) in Aβ generation and metabolism, focusing on the signaling pathways involved. Additionally, the molecular mechanisms by which OLs regulate other glial cells, such as astrocytes and microglia, through intercellular signaling to facilitate Aβ clearance and maintain neuroglial homeostasis warrant further exploration.
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Comprehending Alzheimer's Disease: Molecular Mechanisms and Treatment Strategies
Authors: Sunny Rathee, Vishal Pandey, Sakshi Soni, Debasis Sen and Sanjay K. JainAvailable online: 04 July 2025More LessAlzheimer's disease (AD) is a complex neurodegenerative disorder and a growing global health challenge, driven by increasing life expectancy and an aging population. This review provides a comprehensive exploration of AD pathophysiology, integrating current hypotheses such as the amyloid cascade, tau protein pathology, cholinergic dysfunction, neuroinflammation, vascular contributions, and potential infection-related mechanisms. The multifactorial etiology of AD, encompassing genetic predispositions and environmental factors, underscores its intricate nature. This study delves into the diagnostic advancements, including the identification and utilization of biomarkers for early detection and disease monitoring. Therapeutic approaches are critically evaluated, highlighting anti-amyloid and anti-tau strategies, alongside emerging innovations in stem cell therapy and nanobiotechnology. A detailed examination of clinical trials offers insights into the achievements and setbacks of translating research into effective treatments. By synthesizing epidemiological trends, molecular mechanisms, and therapeutic developments, this review aims to advance our understanding of AD and foster collaborative efforts to develop transformative solutions. It emphasizes the urgency of addressing this multifaceted disease, presenting a nuanced perspective on its complexity while illuminating future directions for research and clinical practice.
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Alterations of Mitophagy (BNIP3), Apoptosis (CASP3), and Autophagy (BECN1) Genes in the Frontal Cortex in an Ischemic Model of Alzheimer's Disease with Long-Term Survival
Authors: Ryszard Pluta, Janusz Kocki, Anna Bogucka-Kocka, Jacek Bogucki and Stanisław J. CzuczwarAvailable online: 02 July 2025More LessIntroductionCurrently, there is no information on changes in the mitophagy (BNIP3), apoptosis (CASP3), and autophagy (BECN1) genes in the frontal cortex after brain ischemia with animal survival for 2 years. Furthermore, it is not known whether the BNIP3, CASP3, and BECN1 genes possess any influence on neurons in the frontal cortex due to ischemia.
AimsThe goal of the investigation was to evaluate alterations in the behavior of BNIP3, CASP3, and BECN1 genes in the frontal cortex following ischemia with survival of 2 years.
Materials and MethodsGene expression was assessed using an RT-PCR protocol at 2-30 days and 6-24-months after ischemia.
ResultsBECN1 gene expression after ischemic injury was lower than the control group during 7-30- days and 18 months, whereas overexpression was noted after 2 days, 6-, 12- and 24 months. In the case of BNIP3 gene expression, it was lower than the control group for 2-7 days and higher than the control throughout the remaining time after ischemia. Increased expression of the CASP3 gene was observed except on days 7-30 following ischemia when its expression was lower compared to control values.
DiscussionThe data seem to indicate that the observed changes in gene expression may reflect the activation and inhibition of different mechanisms involved in the advancement of neurodegeneration after ischemia.
ConclusionOverexpression of BECN1gene is likely to be associated with the induction of neuroprotective phenomena, whereas overexpression of BNIP3 and CASP3 genes can cause harmful effects.
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History of Senile Dementia from the Antiquity to the Beginning of the Modern Age
Available online: 02 July 2025More LessAimsThis study aims, to trace the history of age-associated dementia from the earliest historical periods to the beginning of the modern age.
BackgroundSince the medical literature prior to the early 19th century is relatively scarce, the near absence of senile dementia has been hypothesized.
ObjectiveVerify the prevalence of senile dementia across different historical periods.
MethodsBeyond the medical literature, reviewed papers addressing legal and social aspects were examined to provide a comprehensive overview of the subject.
ResultsWhile the medical literature on the subject is limited, there are a greater abundance of sources discussing social and legislative aspects. The scientific study of dementia had began only in the early 1800s.
ConclusionIn ancient times, dementia was not particularly rare, but it was often overlooked, as it was considered an inevitable consequence of aging.
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Serum Biomarkers of Vascular Dysfunction, Neuropsychiatric Symptoms, and Clinical Severity of Alzheimer’s Disease: A Cross-sectional Study
Available online: 25 June 2025More LessIntroductionThe aim of this study was to assess the relationship between serum biomarkers of vascular dysfunction and neuropsychological performance in Alzheimer’s disease (AD) patients.
Materials and MethodsIn this cross-sectional observational study, outpatients with AD who were referred to the Neuropsychiatry Clinic of the Eginition Hospital in Athens from January 2006 to December 2006 were consecutively enrolled. All the participants underwent a neuropsychological assessment.
The serum concentrations of Apolipoprotein A1 (ApoA1), Vascular Cell Adhesion Molecule 1 (VCAM-1), Intercellular Adhesion Molecule 1 (ICAM-1), Lipoprotein-A (LpA), and C-Reactive Protein (CR-P) were determined.
ResultsFifty-six AD patients were enrolled. ApoA1 was correlated with Mini Mental State Examination (MMSE) and AD Cooperative Study-Activities of Daily Living (ADCS-ADL). Combined biomarkers were correlated with MMSE, Neuropsychiatry Inventory, Clinical Dementia Rating Scale, and ADCS-ADL.
DiscussionOur study highlights the association between serum biomarkers of vascular dysfunction-specifically ApoA1, VCAM-1, ICAM-1, LpA, and CRP-and the cognitive and behavioral features of Alzheimer’s Disease.
ConclusionThese findings suggest that assessing vascular biomarkers may offer valuable insights into the pathophysiological mechanisms underlying cognitive and behavioral decline in AD.
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RESIGN: Alzheimer's Disease Detection Using Hybrid Deep Learning based Res-Inception Seg Network
Authors: Amsavalli Kannan, Kanaga Suba Raja Subramanian and Sudha SureshAvailable online: 18 June 2025More LessIntroductionAlzheimer's disease (AD) is a leading cause of death, making early detection critical to improve survival rates. Conventional manual techniques struggle with early diagnosis due to the brain's complex structure, necessitating the use of dependable deep learning (DL) methods. This research proposes a novel RESIGN model is a combination of Res-InceptionSeg for detecting AD utilizing MRI images.
MethodsThe input MRI images were pre-processed using a Non-Local Means (NLM) filter to reduce noise artifacts. A ResNet-LSTM model was used for feature extraction, targeting White Matter (WM), Grey Matter (GM), and Cerebrospinal Fluid (CSF). The extracted features were concatenated and classified into Normal, MCI, and AD categories using an Inception V3-based classifier. Additionally, SegNet was employed for abnormal brain region segmentation.
ResultsThe RESIGN model achieved an accuracy of 99.46%, specificity of 98.68%, precision of 95.63%, recall of 97.10%, and an F1 score of 95.42%. It outperformed ResNet, AlexNet, DenseNet, and LSTM by 7.87%, 5.65%, 3.92%, and 1.53%, respectively, and further improved accuracy by 25.69%, 5.29%, 2.03%, and 1.71% over ResNet18, CLSTM, VGG19, and CNN, respectively.
DiscussionThe integration of spatial-temporal feature extraction, hybrid classification, and deep segmentation makes RESIGN highly reliable in detecting AD. A 5-fold cross-validation proved its robustness, and its performance exceeded that of existing models on the ADNI dataset. However, there are potential limitations related to dataset bias and limited generalizability due to uniform imaging conditions.
ConclusionThe proposed RESIGN model demonstrates significant improvement in early AD detection through robust feature extraction and classification by offering a reliable tool for clinical diagnosis.
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Efficacy of Sodium Valproate in Behavioral and Psychological Symptoms of Dementia: A Retrospective Observational Study from PUMCH Dementia Cohort
Authors: Yuyue Qiu, Li Shang, Tianyi Wang, Yuhan Jiang, Jialu Bao, Wenjun Wang, Bo Li, Yixuan Huang, Liling Dong, Chenhui Mao and Jing GaoAvailable online: 16 June 2025More LessIntroductionBehavioral and Psychological Symptoms of Dementia (BPSD) pose significant challenges for individuals with dementia and their caregivers. Agitation symptoms, in particular, present a complex management dilemma as there is a lack of consensus regarding pharmacotherapy, specifically with respect to the controversial use of valproate formulations. This study aims to assess the effectiveness of valproate treatment in addressing BPSD, with a specific focus on managing agitation symptoms in individuals with dementia.
MethodsA retrospective analysis was conducted at Peking Union Medical College Hospital (PUMCH) on patients diagnosed with BPSD who received valproate formulations between 2013 and 2023. Patients were classified into 'effective,' 'ineffective,' and 'unknown' groups based on their response to valproate treatment, and the distribution of BPSD symptoms between the effective and ineffective groups was compared.
ResultsAmong the 116 patients studied, 62.1% exhibited effective responses, 12.1% showed ineffectiveness, and 25.9% had uncertain outcomes with valproate therapy. While the effective group displayed a higher prevalence of agitation symptoms and other behaviors like wandering, restricted and repetitive behaviors, and sleep disturbances compared to the ineffective group, these differences did not reach statistical significance (p = 0.156, 1.000, 0.899, 0.283). Patients in the ineffective group were more likely to experience aggression with comorbid psychotic symptoms compared to those in the effective group (p = 0.023).
DiscussionValproate may benefit agitation-predominant BPSD without psychosis. Discrepancies in prior findings may stem from differing dosing strategies. Its limited efficacy in psychosis-related aggression underscores the need for careful clinical evaluation.
ConclusionThe findings suggest that tailored valproate treatment at low doses may be beneficial in managing agitation without psychosis in Asian BPSD patients. Further validation through randomized controlled trials is essential to substantiate these observations.
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Association of Brain and Ventricular Boundary Shift Integral Measurements with CSF Biomarkers: A Case-Control Study
Available online: 05 June 2025More LessAimsThis study seeks to examine the relationship between cerebrospinal fluid (CSF) biomarkers (Aβ1-42, Phospho-Tau181p, Total-Tau) and brain volumetric changes measured by Brain Shift Integral (BSI) in Alzheimer's disease (AD) spectrum. We explore the potential of BSI as a complementary, non-invasive tool for early diagnosis and progression monitoring of AD.
BackgroundAD is a neurodegenerative disorder marked by amyloid plaques and tau tangles, leading to cognitive decline. CSF biomarkers are key indicators of AD pathology, but their integration with imaging metrics like BSI could enhance early diagnosis. BSI quantifies brain volume changes via MRI, offering valuable insights into neurodegeneration across the AD spectrum.
ObjectivesThe current study explores the use of BSI and CSF biomarkers for the early detection of Alzheimer’s disease.
MethodsThis study utilized data from the ADNI database, including CSF biomarkers (Aβ1-42, t-tau, p- tau181) and BSI measurements from baseline and month 24 visits. Spearman correlations were performed to assess associations between biomarkers and brain volumetric changes. Linear regression models were used to examine the predictive value of biomarkers on BSI, controlling for potential confounders.
ResultsA total of 239 participants were included in the study, comprising 94 cognitively normal (CN) individuals, 104 with mild cognitive impairment (MCI), and 41 with AD. Significant negative correlations were observed between Aβ1-42 and both BBSI and VBSI in MCI at baseline (p=0.013) and 24 months (p=0.018), as well as between Aβ1-42 and VBSI in CN at baseline (p=0.039) and 24 months (p=0.033). In MCI, p-tau181 was positively correlated with BBSI (p=0.013) and VBSI (p=0.030) at baseline and with BBSI at 24 months (p=0.013). Linear regression analysis confirmed that Aβ1-42 and p-tau181 significantly predicted BSI measures in MCI (R2=0.141–0.173, p<0.05), while Aβ1-42 was a significant predictor of VBSI in CN (R2=0.156–0.166, p<0.01). No significant associations were found in AD.
DiscussionThis study underscores the role of CSF biomarkers—particularly Aβ1-42 and p-tau181—in detecting early brain atrophy across the Alzheimer’s disease spectrum, with limited utility in advanced stages. The findings highlight the importance of early intervention and support the integration of CSF biomarkers and BSI as diagnostic tools for monitoring disease progression and staging.
ConclusionThe application of the BSI is pivotal for monitoring brain volume alterations and their association with CSF biomarkers.
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Proposed Therapeutic Strategy to Combat Alzheimer’s Disease by Targeting Beta and Gamma Secretases
Authors: Deepak Kumar, Piyush Anand and Shashi Kant SinghAvailable online: 05 June 2025More LessAlzheimer’s disease (AD) is a degenerative neurological disease characterized by a loss of memory and cognitive ability. One of the main factors influencing the development of AD is the accumulation of amyloid β (Aβ) plaque in the brain. The sequential production of Aβ is mediated by two enzymes: gamma-secretase and β-secretase (BACE1). The goal of beta-secretase inhibitors is to prevent the initial cleavage of amyloid precursor protein (APP), which reduces the production of (Aβ) peptides by limiting the substrate available for gamma-secretase. Simultaneously, gamma-secretase modulators are engineered to specifically modify enzyme performance, reducing the synthesis of the harmful Aβ42 isoform while maintaining vital physiological processes. Targeting both secretases reduces amyloidogenic processing synergistically. Selective inhibitors, which have been recently developed, have also shown good clinical development. They can reduce Aβ levels effectively with minimal side effects. The therapeutic strategy also underlines the importance of early therapy intervention in the preclinical AD phase for an optimum effect. Although there are some problems in the optimization of drug delivery and the alleviation of side effects, targeting beta and gamma secretases remains a promising direction. However, all these strategies still need more research and clinical testing to improve existing treatments and develop new, efficient Alzheimer's disease therapies. This review seeks to examine the therapeutic promise of β- and γ-secretase inhibition in Alzheimer's disease and review recent progress, challenges, and new dual-inhibition approaches.
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Advance Nanotechnology-Based Drug Delivery Systems for Alzheimer's Disease: Advancements and Future Perspectives
Available online: 05 June 2025More LessAlzheimer's Disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, significantly impacting the quality of life for affected individuals. This manuscript explores various innovative therapeutic strategies aimed at enhancing drug delivery to the brain, particularly through the use of nanotechnology. This paper discussed the application of Solid Lipid Nanoparticles (SLNs), dendrimers, and Polymeric Nanoparticles (PNPs) in targeting the Central Nervous System (CNS) to improve bioavailability and therapeutic efficacy. The findings indicate that these advanced delivery systems can enhance brain penetration, reduce Amyloid-Beta (Aβ) deposition, and improve cognitive functions in animal models of AD. Furthermore, the review highlights the challenges associated with these technologies, including limited scalability and potential toxicity, while suggesting future directions for research and development in the field of AD treatment.
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Assessment of the Inhibition of AChE and BChE by Carthamus caeruleus Essential Oil and Carline Oxide: Neuroprotective Effects and In Vivo Toxicity Assessment for the Management of Alzheimer’s Disease
Authors: Assia Keniche, Chaimaa Kalache, Mohammed El Amine Dib and Ibtissem El OuarAvailable online: 05 June 2025More LessBackgroundAlzheimer’s disease is associated with dysfunction of the cholinergic system, making the inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) a promising therapeutic approach.
ObjectiveThis study aimed to evaluate the neuroprotective effects and toxicity of essential oil (EO) and carlina oxide from Carthamus caeruleus in mice, assessing their potential for Alzheimer’s disease treatment.
MethodsThe chemical composition of the essential oil extracted from the roots of Carthamus caeruleus was analyzed using gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS). The main component, carlina oxide, was isolated via column chromatography. The inhibitory activities of AChE and BChE were evaluated in vitro for both the essential oil and carlina oxide. Additionally, in vivo, toxicity was assessed in laboratory mice.
ResultsChemical analysis identified carlina oxide (81.6%) as the major constituent, along with minor compounds such as 13-methoxycarlin oxide and hexadecanoic acid. Both the essential oil and its main component, carlina oxide, exhibited significant inhibitory activity against AChE and BChE, enzymes associated with Alzheimer’s disease. The essential oil demonstrated promising IC50 values, with stronger anti-BChE activity compared to the reference drug, galantamine. Toxicity tests in mice revealed no adverse effects at lower doses (0.2-0.5 g/kg). However, higher doses (1.0-2.0 g/kg) resulted in mild to significant toxicity, including weight loss and mortality.
DiscussionThe essential oil and carlina oxide demonstrated potent BChE inhibition, particularly relevant in advanced Alzheimer's disease. While effective at low doses, signs of toxicity were observed at higher concentrations, highlighting the importance of dose optimization. These findings suggest that C. caeruleus may serve as a natural source of cholinesterase inhibitors, pending further in vivo studies and clinical validation.
ConclusionCarthamus caeruleus essential oil and carlina oxide show promising inhibitory effects on AChE and BChE, suggesting their potential as neuroprotective agents. However, their toxicity at higher doses highlights the need for cautious use and further investigation.
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Exploring the Neuroprotective Potential of Polyphenolic Compounds in Mitigating Quinolinic Acid-Induced Neurotoxicity in Alzheimer's Disease
Authors: Pallav Gandhi and Shital PanchalAvailable online: 05 June 2025More LessBackgroundQuinolinic Acid (QA), a neurotoxic metabolite in the kynurenine pathway, contributes to neuronal damage, oxidative stress, and neuroinflammation, playing a key role in Alzheimer's Disease (AD) pathogenesis. This study investigates the neuroprotective potential of polyphenolic compounds, particularly lycopene and a Curcumin-Zinc (Cur-Zn) complex, using in-silico and in-vitro approaches targeting the kynurenine pathway.
MethodologyThis study evaluated the neuroprotective potential of lycopene and Cur-Zn complex using in-silico and in-vitro approaches. Molecular docking was performed to assess their binding affinities with the kynurenine pathway enzymes, and in-vitro neuroprotection assays on N2a cells measured their efficacy against QA-induced oxidative stress.
ResultsDocking analysis revealed strong binding affinities of Cur-Zn and lycopene to IDO1 and KMO, with fitness scores of 143.11 and 126.41, respectively, indicating their potential as enzyme-specific inhibitors. Lycopene exhibited the most potent neuroprotective effect (IC50 = 0.63 µM), followed by Cur-Zn (1.59 µM). Both compounds significantly reduced QA-induced ROS levels, as confirmed by DCFDA fluorescence imaging. Additionally, they upregulated KAT and QPRT enzymes, promoting neuroprotective metabolite production.
DiscussionLycopene and Cur-Zn effectively modulate key kynurenine pathway enzymes while mitigating oxidative stress, supporting their potential as neuroprotective agents. Although bisabolol and bromelain exhibited some efficacy, their effects were comparatively lower.
ConclusionLycopene and Cur-Zn are promising candidates for AD therapy, demonstrating not only anti-oxidant activity but also a capacity to minimise the neurotoxic effects of QA, offering a dual mechanism of action. Further, in-vivo studies are needed to validate their therapeutic potential in neurodegenerative diseases.
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Therapeutic Advances in Alzheimer’s Disease: Integrating Natural, Semi-Synthetic, and Synthetic Drug Strategies
Authors: Brijesh Singh Chauhan, Yash Pal Singh, Burkhard Poeggeler and Sandeep Kumar SinghAvailable online: 29 May 2025More LessAlzheimer’s disease (AD) is a neurodegenerative disorder associated with age, marked by progressive memory loss linked to the decline of cholinergic neurons, accumulation of amyloid plaques, and the presence of Neurofibrillary Tangles (NFTs). Neuropil threads in the brain contribute to amyloidosis and dementia. Despite extensive research, AD’s etiology remains unclear, and currently, no promising therapy exists. This review examines the role of natural, semi-synthetic, and synthetic drugs in AD treatment. Natural drugs demonstrate safety and efficacy with minimal adverse effects, while most agents, whether natural or synthetic, target multiple steps or directly counteract amyloidogenesis, tau protein pathology, oxidative stress, NMDA receptor activity, inflammation, acetylcholine (AChE) function, or α, β, γ secretase activity. In pursuit of improved treatment outcomes, we explore the effectiveness and challenges of various therapeutic interventions. Our hypothesis underscores the importance of an integrated approach combining these drug types for tailored symptom relief, suggesting combined therapies may offer greater therapeutic benefits compared to single-drug approaches. The drugs discussed show potential in regulating AD, thereby presenting viable options for its management. However, to obtain more favorable results, additional studies are needed by combining these drugs.
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Anthocyanidins Intake is Associated with Alzheimer’s Disease Risk in Americans over 60 Years of Age: Data from NHANES 2007-2008, 2009-2010, and 2017-2018
Authors: Yan Chen, Jingyi Zhao, Chen Li, Yinhui Yao and Yazhen ShangAvailable online: 29 May 2025More LessObjectiveAt present, there is limited research on the association between dietary intake of anthocyanidins and Alzheimer's disease (AD). More epidemiological studies are needed to better understand this relationship.
MethodsWe explored the relationship between dietary Anthocyanidins intake and AD among 3806 American adults in the National Health and Nutrition Examination Survey (NHANES) and the United States Department of Agriculture’s Food and Nutrient Database for Dietary Studies (FNDDS) from 2007 to 2010, and 2017 to 2018. We use weighted logistic regression model, restricted cubic spline (RCS) and weighted quantile sum (WQS) regression analysis to analyze the relationship between anthocyanidins monomer and AD.
ResultsThe weighted logistic regression model showed that the total intake of anthocyanidins was the fourth (OR:0.979; 95% CI: 0.966-0.992) quantile (relative to the lowest quantile) is related to the reduction of AD risk. RCS analysis showed that the total intake of anthocyanidins was negatively linearly correlated with AD (nonlinear P value was 0.002). The WQS regression analysis shows that cyanidin and malvidin are the main contributors to the comprehensive effects of six anthocyanidins.
DiscussionOur findings indicate that higher dietary anthocyanin intake may reduce the risk of AD and alleviate neurodegenerative processes. However, the mechanisms underlying this relationship remain unclear. Future studies should confirm these associations and investigate the relevant biological pathways.
ConclusionOur results show that a higher dietary intake of anthocyanidins is associated with a lower risk of AD.
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Quantitative Proteomic Analysis of APP/PS1 Transgenic Mice
Authors: Jiayuan Wang, Xinyu Wang, Zihui An, Xuan Wang, Yaru Wang, Yuehan Lu, Mengsheng Qiu, Zheqi Liu and Zhou TanAvailable online: 02 December 2024More LessBackgroundAlzheimer's disease (AD) is a prevalent neurodegenerative disorder affecting the central nervous system (CNS), with its etiology still shrouded in uncertainty. The interplay of extracellular amyloid-β (Aβ) deposition, intracellular neurofibrillary tangles (NFTs) composed of tau protein, cholinergic neuronal impairment, and other pathogenic factors is implicated in the progression of AD.
ObjectiveThe current study endeavors to delineate the proteomic landscape alterations in the hippocampus of an AD murine model, utilizing proteomic analysis to identify key physiological and pathological shifts induced by the disease. This endeavor aims to shed light on the underlying pathogenic mechanisms, which could facilitate early diagnosis and pave the way for novel therapeutic interventions for AD.
MethodsTo dissect the proteomic perturbations induced by Aβ and Presenilin-1 (PS1) in the AD pathogenesis, we undertook a label-free quantitative (LFQ) proteomic analysis focusing on the hippocampal proteome of the APP/PS1 transgenic mouse model. Employing a multi-faceted approach that included differential protein functional enrichment, cluster analysis, and protein-protein interaction (PPI) network analysis, we conducted a comprehensive comparative proteomic study between APP/PS1 transgenic mice and their wild-type C57BL/6 counterparts.
ResultsMass spectrometry identified a total of 4817 proteins in the samples, with 2762 proteins being quantifiable. Comparative analysis revealed 396 proteins with differential expression between the APP/PS1 and control groups. Notably, 35 proteins exhibited consistent temporal regulation trends in the hippocampus, with concomitant alterations in biological pathways and PPI networks.
ConclusionsThis study presents a comparative proteomic profile of transgenic (APP/PS1) and wild-type mice, highlighting the proteomic divergences. Furthermore, it charts the trajectory of proteomic changes in the AD mouse model across the developmental stages from 2 to 12 months, providing insights into the physiological and pathological implications of the disease-associated genetic mutations.
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Cognitive Reserve in Aging
Authors: A. M. Tucker and Y. Stern
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