Alzheimer disease

Targeting amyloidogenic proteins through cyclic peptides - A medicinal chemistry perspective

Alzheimer's Disease (AD) is characterized by the formation of amyloid-β (Aβ) in the extracellular region, neurofibrillary tangles (NFTs) in the intracellular region accompanied with neuroinflammation and decreased neurotransmitters in various regions of brain leading to neuroinflammation and neurodegeneration. Of the various bioactive molecules, Cyclic Peptides (CPs) are small circular chains of amino acids that can alter the structure and function of the proteins they interact with. They can be synthesized using chemical or genetic approach leading to the generation of diverse libraries of CPs that are screened for binding with desired target proteins. In AD, CPs can interfere at various levels, by either imitating the structure or altering the conformation of amyloidogenic proteins. They can also interfere with signal transduction by competing with amyloid proteins for various receptors which are involved in AD pathology. This review highlights the application of CPs as scaffolds for the identification of novel small molecules that can interfere with amyloid aggregation or for the formulation of vaccination against AD. Other proteins involved in the pathophysiological pathways of AD that can potentially be targeted for CP design have also been discussed.

Towards a better diagnosis and treatment of dementia: Identifying common and distinct neuropathological mechanisms in Alzheimer's and vascular dementia

Alzheimer's disease (AD) and vascular dementia (VaD) together contribute to almost 90 % of all dementia cases leading to major health challenges of our time with a substantial global socioeconomic burden. While in AD, the improved understanding of Amyloid beta (Aß) mismetabolism and tau hyperphosphorylation as pathophysiological hallmarks has led to significant clinical breakthroughs, similar advances in VaD are lacking. After comparing the clinical presentation, including risk factors, disease patterns, course of diseases and further diagnostic parameters for both forms of dementia, we highlight the importance of shared pathomechanisms found in AD and VaD: Endothelial damage, blood brain barrier (BBB) breakdown and hypoperfusion inducing oxidative stress and inflammation and thus trophic uncoupling in the neurovascular unit. A dysfunctional endothelium and BBB lead to the accumulation of neurotoxic molecules and Aß through impaired clearance, which in turn leads to neurodegeneration. In this context we discuss possible neuropathological parameters, which might serve as biomarkers and thus improve diagnostic accuracy or reveal targets for novel therapeutic strategies for both forms of dementia.

Basic approach on the protective effects of hesperidin and naringin in Alzheimer's disease

OBJECTIVES

Alzheimer's disease (AD) is a neurodegenerative disease characterized by cognitive impairment. This situation imposes a great burden on individuals, both economically and socially. Today, an effective method for treating the disease and protective approach to tau accumulation has not been developed yet. Studies have been conducted on the effects of hesperidin and naringin flavonoids found in citrus fruits on many diseases.

METHODS

In this review, the pathophysiology of AD is defined, and the effects of hesperidin and naringin on these factors are summarized.

RESULTS

Studies have shown that both components may potentially affect AD due to their antioxidative and anti-inflammatory properties. Based on these effects of the components, it has been shown that they may have ameliorative effects on Aβ, α-synuclein aggregation, tau pathology, and cognitive functions in the pathophysiology of AD.

DISCUSSION

There are studies suggesting that hesperidin and naringin may be effective in the prevention/treatment of AD. When these studies are examined, it is seen that more studies should be conducted on the subject.

Biomarkers in Alzheimer's disease: new frontiers with olfactory models

Alzheimer's disease (AD), the leading cause of dementia worldwide, presents a significant diagnostic challenge, as clinical diagnoses are often made at advanced stages when neurodegenerative damage is already extensive. The study of biomarkers is necessary for improving identification, prognosis, and disease monitoring. Current research has primarily focused on cerebrospinal fluid and imaging biomarkers, including amyloid-β (Aβ1-42), phosphorylated tau, and total tau. However, these methods are invasive, expensive, and not widely accessible. Emerging approaches aim to identify novel, cost-effective, and minimally invasive biomarkers, particularly from blood-based and other peripheral sources. This review explores the role of olfactory neuronal precursors (ONPs) derived from the olfactory neuroepithelium (ONE) as a promising and innovative model for biomarker discovery in AD. ONPs can be non-invasively obtained directly from patients, offering a unique resource to study AD-related pathophysiological mechanisms. These neuronal lineage cells exhibit characteristics that make them a reliable surrogate model for central nervous system studies, enabling the evaluation of established biomarkers and facilitating the identification of novel candidates. Additionally, we discuss the potential of ONPs to enhance clinical practice through their accessibility and suitability for high-throughput biomarker analysis. By integrating the study of ONPs with existing biomarker research, this review highlights new frontiers in the quest to refine diagnostic tools and advance our understanding of Alzheimer's disease, paving the way for innovative strategies in early detection and personalized management.

Amyloid-β-Induced Neurotoxicity Modulates miR-98 and miR-200 Expression in SH-SY5Y Cells: A Step Toward Alzheimer's Biomarker Discovery

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by abnormal protein accumulation, with no effective, non-invasive early diagnostic tools currently available. MicroRNAs (miRNAs), essential for neuronal survival and function, have been implicated in AD neuropathology. This study investigates the potential of miRNAs as biomarkers for AD by assessing the expression levels of miRNAs relevant to amyloid toxicity. An AD model was developed in SH-SY5Y human neuroblastoma cells with adequate Aβ42 expression to analyze the involvement of miRNAs in AD diagnosis. ELISA, MTT assays, and Congo red staining were utilized to quantify qualitative and quantitative amyloid formation. The expression of miRNAs and related genes, particularly those targeting APP and β-secretase, was measured using quantitative real-time PCR. Amyloid toxicity was successfully induced, and an increase in amyloid levels and significant changes in Alzheimer's related genes and targeted miRNAs were observed. Specifically, it was observed that miR-200a was upregulated and miR-98 was down-regulated in treated neuroblastoma cells. Notably, the altered expression patterns of these miRNAs showed a strong correlation with the pathological markers of AD, suggesting their potential as diagnostic indicators. Our findings enhance our understanding of AD mechanisms and offer insights into early diagnosis. Detecting AD in preclinical stages may enable earlier symptomatic intervention. In particular, dysregulation of certain miRNAs may play a role in neurodegenerative processes such as amyloid plaque formation in AD. miRNAs that respond to neurotoxic stimuli can be identified using in vitro models and confirmed by in vivo studies. These studies will help us understand both the development of noninvasive diagnostic tests and therapeutic approaches targeting miRNAs.

Clinical trials targeting tau should be halted

Experimental drugs lowering brain tau are heralded as improvements in the treatment of Alzheimer's disease. However, the outcomes in clinical trials testing these agents have consistently failed to improve patient outcomes, i.e. slow down disease or improving cognition. Furthermore, the scientific rationale behind such drugs is rather poor in the first place and has been questioned. Therefore, I argue that trials of anti-tau drugs should be halted.

Water-soluble carotenoid: focused on natural carotenoid crocin

Carotenoids are natural isoprenoid compounds with diverse health benefits, widely used in food, cosmetics, and pharmaceuticals. However, low bioavailability and chemical instability limit their effect according to their fat-soluble property. Some strategies such as nanoencapsulation, emulsions, complexation, and glycosylation have been explored to enhance carotenoid bioavailability. In addition, there is growing interest in water-soluble carotenoids in nature. This review focuses on recent advancements in improving the water solubility of carotenoids, with special attention to naturally occurring water-soluble carotenoids like crocin. Research progress on the biosynthetic pathways of crocin derived from natural plants is summarized. In addition, heterologous production using genetic and metabolic engineering in plants and microorganisms is discussed, along with its potential applications in bio-industries. Finally, the promising pharmacological properties of crocin, including antioxidant, anti-inflammatory and anticancer effects, are presented. The sustainable production of water-soluble carotenoids through biological synthesis offers a potential for improved absorption and functionality.

Recent advances in mRNA-based therapeutics for neurodegenerative diseases and brain tumors

Messenger RNA (mRNA) therapy is an innovative approach that delivers specific protein-coding information. By promoting the ribosomal synthesis of target proteins within cells, it supplements functional or antigenic proteins to treat diseases. Unlike traditional gene therapy, mRNA does not need to enter the cell nucleus, reducing the risks associated with gene integration. Moreover, protein expression levels can be regulated by adjusting the dosage and degradation rates of mRNA. As a new generation gene therapy strategy, mRNA therapy represents the latest advancements and trends in the field. It offers advantages such as precision, safety, and ease of modification. It has been widely used in the prevention of COVID-19. Unlike acute conditions such as cerebral hemorrhage and stroke that often require immediate surgical or interventional treatments, neurodegenerative diseases (NDs) and brain tumors progress relatively slowly and face challenges such as the blood-brain barrier and complex pathogenesis. These characteristics make them particularly suitable for mRNA therapy. With continued research, mRNA-based therapeutics are expected to play a significant role in the prevention and treatment of NDs and brain tumors. This paper reviews the preparation and delivery of mRNA drugs and summarizes the research progress of mRNA gene therapy in treating NDs and brain tumors. It also discusses the current challenges, providing a theoretical basis and reference for future research in this field.

Cannabidiol-Induced Autophagy Ameliorates Tau Protein Clearance

Tau is a neuronal protein that confers stability to microtubules; however, its hyperphosphorylation and accumulation can lead to an impairment of protein degradation pathways, such as autophagy. Autophagy is a lysosomal catabolic process responsible for degrading cytosolic components, being essential for cellular homeostasis and survival. In this context, autophagy modulation has been postulated as a possible therapeutic target for the treatment of neurodegenerative diseases. Studies point to the modulatory and neuroprotective role of the cannabinoid system in neurodegenerative models and here it was investigated the effects of cannabidiol (CBD) on autophagy in a human neuroblastoma strain (SH-SY5Y) that overexpresses the EGFP-Tau WT (Wild Type) protein in an inducible Tet-On system way. The results demonstrated that CBD (100 nM and 10 µM) decreased the expression of AT8 and total tau proteins, activating autophagy, evidenced by increased expression of light chain 3-II (LC3-II) protein and formation of autophagosomes. Furthermore, the cannabinoid compounds CBD, ACEA (CB1 agonist) and GW-405,833 (CB2 agonist) decreased the fluorescence intensity of EGFP-Tau WT; and when chloroquine, an autophagic blocker, was used, there was a reversal in the fluorescence intensity of EGFP-Tau WT with CBD (1 and 10 µM) and GW-405,833 (2 µM), demonstrating the possible participation of autophagy in these groups. Thus, it was possible to conclude that CBD induced autophagy in EGFP-Tau WT cells which increased tau degradation, showing its possible neuroprotective role. Hence, this study may contribute to a better understanding of how cannabinoids can modulate autophagy and present a potential therapeutic target in a neurodegeneration model.

Cellular stress response and neuroprotection of flavonoids in neurodegenerative diseases: Clinical insights into targeted therapy and molecular signaling pathways

Neurodegenerative diseases (NDs) are caused by the gradual decline of neuronal structure and function, which presents significant challenges in treatment. Cellular stress responses significantly impact the pathophysiology of these disorders, often exacerbating neuronal damage. Plant-derived flavonoids have demonstrated potential as neuroprotective agents due to their potent anti-inflammatory, anti-apoptotic, and antioxidant properties. This review provides an in-depth analysis of the molecular processes and clinical insights that cause the neuroprotective properties of flavonoids in NDs. By controlling essential signaling pathways such as Nrf2/ARE, MAPK, and PI3K/Akt, flavonoids can lower cellular stress and improve neuronal survival. The study discusses the challenges of implementing these discoveries in clinical practice and emphasizes the therapeutic potential of specific flavonoids and their derivatives. Flavonoids are identified as potential therapeutic agents for NDs, potentially slowing progression by regulating cellular stress and improving neuroprotection despite their potential medicinal uses and clinical challenges. The study designed a strategy to identify literature published in prestigious journals, utilizing search results from PubMed, Scopus, and WOS. We selected and investigated original studies, review articles, and research reports published until 2024. It suggests future research and therapeutic approaches to effectively utilize the neuroprotective properties of flavonoids.

Alterations in the inflammatory homeostasis of aging-related cardiac dysfunction and Alzheimer's diseases

Alzheimer's disease (AD) is well known among the elderly and has a profound impact on both patients and their families. Increasing research indicates that AD is a systemic disease, with a strong connection to cardiovascular disease. They share common genetic factors, such as mutations in the presenilin (PS1 and PS2) and the apolipoprotein E (APOE) genes. Cardiovascular conditions can lead to reduced cerebral blood flow and increased oxidative stress. These factors contribute to the accumulation of Aβ plaques and the formation of abnormal tau protein tangles, which are both key pathological features of AD. Additionally, Aβ deposits and abnormal protein responses have been observed in cardiomyocytes as well as in peripheral tissues. The toxic Aβ deposition intensifies damage to the microvascular structure associated with blood-brain barrier disruption and the initiation of neuroinflammation, which may accelerate the onset of neurocognitive deficits and cardiovascular dysfunction. Thus, we discuss the main mechanisms linking AD and cardiac dysfunction to enhance our understanding of these conditions. Ultimately, insights into the brain-heart axis may help us develop effective treatment strategies in the future.

Shape-based disease grading via functional maps and graph convolutional networks with application to Alzheimer's disease

Shape analysis provides methods for understanding anatomical structures extracted from medical images. However, the underlying notions of shape spaces that are frequently employed come with strict assumptions prohibiting the analysis of incomplete and/or topologically varying shapes. This work aims to alleviate these limitations by adapting the concept of functional maps. Further, we present a graph-based learning approach for morphometric classification of disease states that uses novel shape descriptors based on this concept. We demonstrate the performance of the derived classifier on the open-access ADNI database differentiating normal controls and subjects with Alzheimer's disease. Notably, the experiments show that our approach can improve over state-of-the-art from geometric deep learning.

Synthetic data analysis for early detection of Alzheimer progression through machine learning algorithms

Alzheimer's disease (AD) is a serious neurodegenerative disorder that causes incurable and irreversible neuronal loss and synaptic dysfunction. The progress of this disease is gradual and depending on the stage of its detection, only its progression can be treated, reducing the most aggressive symptoms and the speed of its neurodegenerative progress. This article proposes an early detection model for the diagnosis of AD by performing analyses in Alzheimer's progression patient datasets, provided by the Alzheimer's Disease Neuroimaging Initiative (ADNI), including only neuropsychological assessments and making use of feature selection techniques and machine learning models. The focus of this research is to build an ensemble machine learning model capable of early detection of a patient with Alzheimer's or a cognitive state that leads to it, based on their results in neuropsychological assessments identified as highly relevant for the detection of Alzheimer's. The proposed approach for the detection of AD is presented with the inclusion of the feature selection technique recursive feature elimination (RFE) and the Akaike Information Criterion (AIC), the ensemble model consists of logistic regression (LR), artificial neural networks (ANN), support vector machines (SVM), K-nearest neighbors (KNN) and nearest centroid (Nearcent). The datasets downloaded from ADNI were divided into 13 subsets including: cognitively normal (CN) vs subjective memory concern (SMC), CN vs early mild cognitive impairment (EMCI), CN vs late mild cognitive impairment (LMCI), CN vs AD, SMC vs EMCI, SMC vs LMCI, SMC vs AD, EMCI vs LMCI, EMCI vs AD, LMCI vs AD, MCI vs AD, CN vs AD and CN vs MCI. From all the feature results, a custom model was created using RFE, AIC and testing each model. This work presents a customized model for a backend platform to perform one-versus-all analysis and provide a basis for early diagnosis of Alzheimer's at its current stage.

Assessing polyomic risk to predict Alzheimer's disease using a machine learning model

INTRODUCTION

Alzheimer's disease (AD) is the most common form of dementia in the elderly. Given that AD neuropathology begins decades before symptoms, there is a dire need for effective screening tools for early detection of AD to facilitate early intervention.

METHODS

Here, we used tree-based and deep learning methods to train polyomic prediction models for AD affection status and age at onset, employing genomic, proteomic, metabolomic, and drug use data from UK Biobank. We used SHAP to determine the feature's importance.

RESULTS

Our best-performing polyomic model achieved an area under the receiver operating characteristics curve (AUROC) of 0.87. We identified GFAP and CXCL17 proteins to be the strongest predictors of AD, besides apolipoprotein E (APOE) alleles. Increasing the number of cases by including "AD-by-proxy" cases did not improve AD prediction.

DISCUSSION

Among the four modalities, genomics, and proteomics were the most informative modality based on AUROC (area under the receiver operating characteristic curve). Our data suggest that two blood-based biomarkers (glial fibrillary acidic protein [GFAP] and CXCL17) may be effective for early presymptomatic prediction of AD.

HIGHLIGHTS

We developed a polyomic model to predict AD and age-at-onset using omics and medication use data from EHR. We identified GFAP and CXCL17 proteins to be the strongest predictors of AD, besides APOE alleles. "AD-by-proxy" cases, if used in training, do not improve AD prediction. Proteomics was the most informative modality overall for affection status and AAO prediction.

Identification of novel potential cathepsin-B inhibitors through pharmacophore-based virtual screening, molecular docking, and dynamics simulation studies for the treatment of Alzheimer's disease

Cathepsin B is a cysteine protease lysosomal enzyme involved in several physiological functions. Overexpression of the enzyme enhances its proteolytic activity and causes the breakdown of amyloid precursor protein (APP) into neurotoxic amyloid β (Aβ), a characteristic hallmark of Alzheimer's disease (AD). Therefore, inhibition of the enzyme is a crucial therapeutic aspect for treating the disease. Combined structure and ligand-based drug design strategies were employed in the current study to identify the novel potential cathepsin B inhibitors. Five different pharmacophore models were developed and used for the screening of the ZINC-15 database. The obtained hits were analyzed for the presence of duplicates, interfering PAINS moieties, and structural similarities based on Tanimoto's coefficient. The molecular docking study was performed to screen hits with better target binding affinity. The top seven hits were selected and were further evaluated based on their predicted ADME properties. The resulting best hits, ZINC827855702, ZINC123282431, and ZINC95386847, were finally subjected to molecular dynamics simulation studies to determine the stability of the protein-ligand complex during the run. ZINC123282431 was obtained as the virtual lead compound for cathepsin B inhibition and may be a promising novel anti-Alzheimer agent.

Green synthesis of nanoparticles using medicinal plants as an eco-friendly and therapeutic potential approach for neurodegenerative diseases: a comprehensive review

Central nervous system disorders impact over 1.5 billion individuals globally, with neurodegenerative diseases such as Alzheimer's, Parkinson's, and Huntington's diseases being particularly prominent. These conditions, often associated with aging, present debilitating symptoms including memory loss and movement difficulties. The growing incidence of neurological disorders, alongside a scarcity of effective anti-amyloidogenic therapies, highlights an urgent need for innovative treatment methodologies. Nanoparticles (NPs), derived from medicinal plants and characterized by their favorable pharmacological properties and minimal side effects, offer a promising solution. Their inherent attributes allow for successful traversal of the blood-brain barrier (BBB), enabling targeted delivery to the brain and the modulation of specific molecular pathways involved in neurodegeneration. NPs are crucial in managing oxidative stress, apoptosis, and neuroinflammation in ND. This study reviews the efficacy of green-synthesized nanoparticles in conjunction with various medicinal plants for treating neurodegenerative diseases, advocating for further research to refine these formulations for enhanced clinical applicability and improved patient outcomes.

Exploring the Effect of Single-Session Transcranial Direct Current Stimulation on Attention, Verbal Fluency, and Working Memory in Patients With Alzheimer's Disease-Related Dementia

OBJECTIVES

Alzheimer's disease (AD) is a leading cause of morbidity and mortality among the elderly. Transcranial direct current stimulation (tDCS) applies low-intensity currents to the brain, resulting in short-term neurocognitive effects and long-term neuroplasticity enhancement. Limited research reported on the impact of tDCS on cognitive functions in dementia due to AD. This study aims to compare changes in verbal fluency and working memory following a single tDCS application to the left dorsolateral prefrontal cortex (DLPFC) in AD patients.

METHODS

Patients with mild dementia due to AD underwent cognitive assessment using the Standardized Mini-Mental Test, Clock Drawing Test, Rey Auditory Verbal Learning Test, Functional Activities Questionnaire, Informant Questionnaire on Cognitive Decline in the Elderly, and Montreal Cognitive Assessment Scale. A single-session tDCS was administered by applying anodal tDCS to the left DLPFC for a duration of 30 minutes. Verbal fluency and working memory were evaluated before and after tDCS using the WAIS-R Digit Span Test forward and backward subscales, Trail Making Test (TMT) A and B, and Verbal Fluency Test.

RESULTS

Regarding cognitive test scores before and after tDCS application, there were statistically significant reductions in the durations of TMT-A and TMT-B. However, there were no significant differences observed for TMT B-A, VFT, DST-forward, and DST-backward performances.

CONCLUSIONS

The findings indicate that a single anodal tDCS targeting the left DLPFC enhances attention and processing speed in AD patients but has no effect on working memory or verbal fluency.

Association between Atrial Fibrillation and Risk of Alzheimer's Disease and Vascular Dementia: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVES

Recent research suggests that atrial fibrillation (AF) may influence the risk of developing Alzheimer's disease (AD) and vascular dementia (VaD). However, existing studies have provided inconsistent results, with some showing a significant association between AF and the risk of AD and VaD, while others do not. The objective of this study is to conduct a meta-analysis to investigate the association between AF and the risk of AD and VaD.

METHODS

A comprehensive search was conducted in several databases, including PubMed, Web of Science, Embase, and Google Scholar, covering research published before December 2023. Odds ratios (ORs) or relative risks (RRs) and 95% confidence intervals (CIs) were calculated using Stata 12.0 software to assess the association between AF and the risk of AD or VaD.

RESULTS

The meta-analysis revealed a significant association between AF and an increased risk of AD, using a random effects model (OR/RR: 1.23, 95% CI: 1.13-1.34, I2 = 81.3%, P < 0.001). Similarly, a significant association was found between AF and an increased risk of VaD, using a random effects model (OR/RR: 1.80, 95% CI: 1.57-2.07, I2 = 82.1%, P < 0.001).

CONCLUSION

In summary, our comprehensive meta-analysis provides compelling evidence of a significant association between AF and an elevated risk of AD and VaD. The findings are corroborated by robust cross-sectional and longitudinal cohort studies, which further validate the observed link. However, further large-scale prospective studies are necessary to comprehensively investigate the relationship between AF and the risk of AD and VaD.

Oxidative Processes and Xenobiotic Metabolism in Plants: Mechanisms of Defense and Potential Therapeutic Implications

Plants are continuously exposed to environmental challenges, including pollutants, pesticides, and heavy metals, collectively termed xenobiotics. These substances induce oxidative stress by generating reactive oxygen species (ROS), which can damage cellular components such as lipids, proteins, and nucleic acids. To counteract this, plants have evolved complex metabolic pathways to detoxify and process these harmful compounds. Oxidative stress in plants primarily arises from the overproduction of hydrogen peroxide (H2O2), superoxide anions (O2•-), singlet oxygen (1O2), and hydroxyl radicals (•OH), by-products of metabolic activities such as photosynthesis and respiration. The presence of xenobiotics leads to a notable increase in ROS, which can result in cellular damage and metabolic disruption. To combat this, plants have developed a strong antioxidant defense mechanism that includes enzymatic antioxidants that work together to eliminate ROS, thereby reducing their harmful effects. In addition to enzymatic defenses, plants also synthesize various non-enzymatic antioxidants, including flavonoids, phenolic acids, and vitamins. These compounds effectively neutralize ROS and help regenerate other antioxidants, offering extensive protection against oxidative stress. The metabolism of xenobiotic substances in plants occurs in three stages: the first involves modification, which refers to the chemical alteration of xenobiotics to make them less harmful. The second involves conjugation, where the modified xenobiotics are combined with other substances to increase their solubility, facilitating their elimination from the plant. The third stage involves compartmentalization, which is the storage or isolation of conjugated xenobiotics in specific parts of the plant, helping to prevent damage to vital cellular functions. Secondary metabolites found in plants, such as alkaloids, terpenoids, and flavonoids, play a vital role in detoxification and the defense against oxidative stress. Gaining a deeper understanding of the oxidative mechanisms and the pathways of xenobiotic metabolism in plants is essential, as this knowledge can lead to the formulation of plant-derived strategies aimed at alleviating the effects of environmental pollution and enhancing human health by improving detoxification and antioxidant capabilities, as discussed in this review.

Destabilisation of Alzheimer's amyloid-β protofibrils by Baicalein: mechanistic insights from all-atom molecular dynamics simulations

Alzheimer's disease (AD) is the most common form of dementia and the fifth leading cause of death globally. Aggregation and deposition of neurotoxic Aβ fibrils in the neural tissues of the brain is a key hallmark in AD pathogenesis. Destabilisation studies of the amyloid-peptide by various natural molecules are highly relevant due to their neuroprotective and therapeutic potential for AD. We performed molecular dynamics (MD) simulation to investigate the destabilisation mechanism of amyloidogenic protofilament intermediate by Baicalein (BCL), a naturally occurring flavonoid. We found that the BCL molecule formed strong hydrophobic contacts with non-polar residues, specifically F19, A21, V24, and I32 of Chain A and B of the pentameric protofibril. Upon binding, it competed with the native hydrophobic contacts of the Aβ protein. BCL loosened the tight packing of the hydrophobic core by disrupting the hydrogen bonds and the prominent D23-K28 inter-chain salt bridges of the protofibril. The decrease in the structural stability of Aβ protofibrils was confirmed by the increased RMSD, radius of gyration, solvent accessible surface area (SASA), and reduced β-sheet content. PCA indicated that the presence of the BCL molecule intensified protofibril motions, particularly affecting residues in Chain A and B regions. Our findings propose that BCL would be a potent destabiliser of Aβ protofilament, and may be considered as a therapeutic agent in treating AD.

Comorbidity-based framework for Alzheimer's disease classification using graph neural networks

Alzheimer's disease (AD), the most prevalent form of dementia, requires early prediction for timely intervention. Current deep learning approaches, particularly those using traditional neural networks, face challenges such as handling high-dimensional data, interpreting complex relationships, and managing data bias. To address these limitations, we propose a framework utilizing graph neural networks (GNNs), which excel in modeling relationships within graph-structured data. Our study employs GNNs on data from the Alzheimer's Disease Neuroimaging Initiative for binary and multi-class classification across the three stages of AD: cognitively normal (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD). By incorporating comorbidity data derived from electronic health records, we achieved the most effective multi-classification results. Notably, the GNN model (Chebyshev Convolutional Neural Networks) demonstrated superior performance with a 0.98 accuracy in multi-class classification and 0.99, 0.93, and 0.94 in the AD/CN, AD/MCI, and CN/MCI binary tasks, respectively. The model's robustness was further validated using the Australian Imaging, Biomarker & Lifestyle dataset as an external validation set. This work contributes to the field by offering a robust, accurate, and cost-effective method for early AD prediction (CN vs. MCI), addressing key challenges in existing deep learning approaches.

Mechanisms of damage and therapies for cardiac amyloidosis: a role for inflammation?

The term cardiac amyloidosis (CA) refers to the accumulation of extracellular amyloid deposits in the heart because of different conditions often affecting multiple organs including brain, kidney and liver. Notably, cardiac involvement significantly impacts prognosis of amyloidosis, with cardiac biomarkers playing a pivotal role in prognostic stratification. Therapeutic management poses a challenge due to limited response to conventional heart failure therapies, necessitating targeted approaches aimed at preventing, halting or reversing amyloid deposition. Mechanisms underlying organ damage in CA are multifactorial, involving proteotoxicity, oxidative stress, and mechanical interference. While the role of inflammation in CA remains incompletely understood, emerging evidence suggests its potential contribution to disease progression as well as its utility as a therapeutic target. This review reports on the cardiac involvement in systemic amyloidosis, its prognostic role and how to assess it. Current and emerging therapies will be critically discussed underscoring the need for further efforts aiming at elucidating CA pathophysiology. The emerging evidence suggesting the contribution of inflammation to disease progression and its prognostic role will also be reviewed possibly offering insights into novel therapeutic avenues for CA.

Neuroprotective Effects of Phenolic Constituents from Drynariae Rhizoma

This study aimed to provide scientific data on the anti-Alzheimer's disease (AD) effects of phenolic compounds from Drynariae Rhizoma (DR) extract using a multi-component approach. Screening of DR extracts, fractions, and the ten phenolic compounds isolated from DR against the key AD-related enzymes acetylcholinesterase (AChE), butyrylcholinesterase (BChE), β-site amyloid precursor protein cleaving enzyme 1 (BACE1), and monoamine oxidase-B (MAO-B) confirmed their significant inhibitory activities. The DR extract was confirmed to have BACE1-inhibitory activity, and the ethyl acetate and butanol fractions were found to inhibit all AD-related enzymes, including BACE1, AChE, BChE, and MAO-B. Among the isolated phenolic compounds, compounds (2) caffeic acid 4-O-β-D-glucopyranoside, (6) kaempferol 3-O-rhamnoside 7-O-glucoside, (7) kaempferol 3-o-b-d-glucopyranoside-7-o-a-L-arabinofuranoside, (8) neoeriocitrin, (9) naringin, and (10) hesperidin significantly suppressed AD-related enzymes. Notably, compounds 2 and 8 reduced soluble Amyloid Precursor Protein β (sAPPβ) and β-secretase expression by over 45% at a concentration of 1.0 μM. In the thioflavin T assay, compounds 6 and 7 decreased Aβ aggregation by approximately 40% and 80%, respectively, and degraded preformed Aβ aggregates. This study provides robust evidence regarding the potential of DR as a natural therapeutic agent for AD, highlighting specific compounds that may contribute to its efficacy.

Design, Synthesis, and Biological Evaluation of Ferulic Acid-Piperazine Derivatives Targeting Pathological Hallmarks of Alzheimer's Disease

Alzheimer's disease (AD) is the most prevalent cause of dementia and is characterized by low levels of acetyl and butyrylcholine, increased oxidative stress, inflammation, accumulation of metals, and aggregations of Aβ and tau proteins. Current treatments for AD provide only symptomatic relief without impacting the pathological hallmarks of the disease. In our ongoing efforts to develop naturally inspired novel multitarget molecules for AD, through extensive medicinal chemistry efforts, we have developed 13a, harboring the key functional groups to provide not only symptomatic relief but also targeting oxidative stress, able to chelate iron, inhibiting NLRP3, and Aβ1-42 aggregation in various AD models. 13a exhibited promising anticholinesterase activity against AChE (IC50 = 0.59 ± 0.19 μM) and BChE (IC50 = 5.02 ± 0.14 μM) with excellent antioxidant properties in DPPH assay (IC50 = 5.88 ± 0.21 μM) over ferulic acid (56.49 ± 0.62 μM). The molecular docking and dynamic simulations further corroborated the enzyme inhibition studies and confirmed the stability of these complexes. Importantly, in the PAMPA-BBB assay, 13a turned out to be a promising molecule that can efficiently cross the blood-brain barrier. Notably, 13a also exhibited iron-chelating properties. Furthermore, 13a effectively inhibited self- and metal-induced Aβ1-42 aggregation. It is worth mentioning that 13a demonstrated no symptom of cytotoxicity up to 30 μM concentration in PC-12 cells. Additionally, 13a inhibited the NLRP3 inflammasome and mitigated mitochondrial-induced reactive oxygen species and mitochondrial membrane potential damage triggered by LPS and ATP in HMC-3 cells. 13a could effectively reduce mitochondrial and cellular reactive oxygen species (ROS) in the Drosophila model of AD. Finally, 13a was found to be efficacious in reversing memory impairment in a scopolamine-induced AD mouse model in the in vivo studies. In ex vivo assessments, 13a notably modulates the levels of superoxide, catalase, and malondialdehyde along with AChE and BChE. These findings revealed that 13a holds promise as a potential candidate for further development in AD management.

Could Mushrooms' Secondary Metabolites Ameliorate Alzheimer Disease? A Computational Flexible Docking Investigation

Herein, we highlight the significance of molecular modeling approaches prior to in vitro and in vivo studies; particularly, in diseases with no recognized treatments such as neurological abnormalities. Alzheimer disease is a neurodegenerative disorder that causes irreversible cognitive decline. Toxicity and ADMET studies were conducted using the Qikprop platform in Maestro software and Discovery Studio 2.0, respectively, to select the promising skeletons from more than 45 reviewed compounds isolated from mushrooms in the last decade. Using rigid and flexible molecular docking approaches such as induced fit docking (IFD) in the binding sites of β-secretase (BACE1) and acetylcholine esterase (ACHE), promising structures were screened through high precision molecular docking compared with standard drugs donepezil and (2E)-2-imino-3-methyl-5,5-diphenylimidazolidin-4-one (OKK) using Maestro and Cresset Flare platforms. Molecular interactions, binding distances, and RMSD values were measured to reveal key interactions at the binding sites of the two neurodegenerative enzymes. Analysis of IFD results revealed consistent bindings of dictyoquinazol A and gensetin I in the pocket of 4ey7 while inonophenol A, ganomycin, and fornicin fit quite well in 4dju demonstrating binding poses very close to native ligands at ACHE and BACE1. Respective key amino acid contacts manifested the least steric problems according to their Gibbs free binding energies, Glide XP scores, RMSD values, and molecular orientation respect to the key amino acids. Molecular dynamics simulations further confirmed our findings and prospected these compounds to show significant in vitro results in their future pharmacological studies.

Bio-inspired deep learning-personalized ensemble Alzheimer's diagnosis model for mental well-being

Most classification models for Alzheimer's Diagnosis (AD) do not have specific strategies for individual input samples, leading to the problem of easily overlooking personalized differences between samples. This research introduces a customized dynamically ensemble convolution neural network (PDECNN), which is able to build a specific integration strategy based on the distinctiveness of the sample. In this paper, we propose a personalized dynamic ensemble alzheimer's Diagnosis classification model. This model will dynamically modify the deteriorated brain areas of interest depending on various samples since it can adjust to variations in the degeneration of sample brain areas. In clinical problems, the PDECNN model has additional diagnostic importance since it can identify sample-specific degraded brain areas based on input samples. This model considers the variability of brain region degeneration levels between input samples, evaluates the degree of degeneration of specific brain regions using an attention mechanism, and selects and integrates brain region features based on the degree of degeneration. Furthermore, by redesigning the classification accuracy performance, we respectively improve it by 4 %, 11 %, and 8 %. Moreover, the degraded brain regions identified by the model show high consistency with the clinical manifestations of AD.

The duality of amyloid-β: its role in normal and Alzheimer's disease states

Alzheimer's disease (AD) is a degenerative neurological condition that gradually impairs cognitive abilities, disrupts memory retention, and impedes daily functioning by impacting the cells of the brain. A key characteristic of AD is the accumulation of amyloid-beta (Aβ) plaques, which play pivotal roles in disease progression. These plaques initiate a cascade of events including neuroinflammation, synaptic dysfunction, tau pathology, oxidative stress, impaired protein clearance, mitochondrial dysfunction, and disrupted calcium homeostasis. Aβ accumulation is also closely associated with other hallmark features of AD, underscoring its significance. Aβ is generated through cleavage of the amyloid precursor protein (APP) and plays a dual role depending on its processing pathway. The non-amyloidogenic pathway reduces Aβ production and has neuroprotective and anti-inflammatory effects, whereas the amyloidogenic pathway leads to the production of Aβ peptides, including Aβ40 and Aβ42, which contribute to neurodegeneration and toxic effects in AD. Understanding the multifaceted role of Aβ, particularly in AD, is crucial for developing effective therapeutic strategies that target Aβ metabolism, aggregation, and clearance with the aim of mitigating the detrimental consequences of the disease. This review aims to explore the mechanisms and functions of Aβ under normal and abnormal conditions, particularly in AD, by examining both its beneficial and detrimental effects.

The Alzheimer's patients interaction through digital and arts (AIDA) program: A feasibility study to improve wellbeing in people with Alzheimer's disease

Alzheimer's disease (AD) presents a growing global challenge, with an increasing prevalence and significant impact on individuals and public health. Effective pharmacological treatments directly impacting the disease are still lacking, highlighting the importance of programs and interventions aimed at improving the wellbeing of those affected. The present feasibility study aimed to evaluate the effectiveness and feasibility of the Alzheimer's patients Interaction through Digital and Arts (AIDA) program. AIDA's main objective is to enhance perceived wellbeing and quality of life of people with AD and their caregivers through a series of structured activities through museum- and art-based activities over five sessions. Pre- and post-program evaluations were conducted using Visual Analog Scales (VASs) to measure various dimensions of perceived wellbeing such as confidence, happiness, interest, optimism, and wellness. Results showed significant improvements in all considered dimensions for people with AD following AIDA activities, highlighting its potential to enhance overall wellbeing. Caregivers also reported increased perceived wellness post-program, demonstrating some positive effects also in healthy participants. The feasibility of AIDA was supported by positive feedback and engagement of participants. Overall, the AIDA program offers a non-intrusive and engaging approach to improve the perceived wellbeing of people with AD and caregivers while facilitating meaningful experiences (e.g., silence, sharing etc.) in cultural settings.

Incidence of Alzheimer Disease and Related Dementias in Iran From 2010 to 2019

This is the first comprehensive national and subnational epidemiological study reporting the incidence of Alzheimer disease and related dementias (ADRD) in Iran from 2010 to 2019 and predictions for 2024. We extracted age-standardized incidence stratified by sex and provinces from the Institute for Health Measurement and Evaluation (IHME). Arc Map GIS was used to report the geographical distribution, and the Cochran-Armitage test was used for prediction. Predictions showed that the incidence of ADRD would reach 118 (women) and 109 (men) cases per 100,000 population in Iran in 2024. The most increasing incidence from 2010 to 2019 was reported among women in Qom, while Yazd had the most incidences among men and women in 2019. The results showed an increase in the incidence of ADRD in Iran in recent years, and the increase in life expectancy and population aging can be considered as an influential factor.

Caspases in Alzheimer's Disease: Mechanism of Activation, Role, and Potential Treatment

With the aging of the population, treatment of conditions emerging in old age, such as neurodegenerative disorders, has become a major medical challenge. Of these, Alzheimer's disease, leading to cognitive dysfunction, is of particular interest. Neuronal loss plays an important role in the pathophysiology of this condition, and over the years, a great effort has been made to determine the role of various factors in this process. Unfortunately, until now, the exact pathomechanism of this condition remains unknown. However, the most popular theories associate AD with abnormalities in the Tau and β-amyloid (Aβ) proteins, which lead to their deposition and result in neuronal death. Neurons, like all cells, die in a variety of ways, among which pyroptosis, apoptosis, and necroptosis are associated with the activation of various caspases. It is worth mentioning that Tau and Aβ proteins are considered to be one of the caspase activators, leading to cell death. Moreover, the protease activity of caspases influences both of the previously mentioned proteins, Tau and Aβ, converting them into more toxic derivatives. Due to the variety of ways caspases impact the development of AD, drugs targeting caspases could potentially be useful in the treatment of this condition. Therefore, there is a constant need to search for novel caspase inhibitors and evaluate them in preclinical and clinical trials.

Novel Alzheimer's Disease Stating Based on Comorbidities-Informed Graph Neural Networks

Alzheimer's Disease (AD), the most prevalent form of dementia, requires early prediction for timely intervention. Leveraging data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), our study employs Graph Neural Networks (GNNs) for multi-class AD classification. Initial steps involve creating a patient-clinical graph network considering latent relationships among cognitive normal (CN), mild cognitive impairment (MCI), and AD patients, followed by training several GNN-based techniques for building prediction models. Incorporating comorbidity data from electronic health records into the feature set yielded the most effective classification results. Notably, the GNN model with attention mechanisms outperforms state-of-the-art techniques in multi-class AD classification, achieving an accuracy = 0.92 [0.91,0.94], AUC = 0.96 [0.95,0.96], and F1-score = 0.92 [0.91,0.94]. This work highlights comorbidity data's impact on AD classification and suggests its potential to deepen disease understanding.

Innovative technologies for the fabrication of 3D/4D smart hydrogels and its biomedical applications - A comprehensive review

Repairing and regenerating damaged tissues or organs, and restoring their functioning has been the ultimate aim of medical innovations. 'Reviving healthcare' blends tissue engineering with alternative techniques such as hydrogels, which have emerged as vital tools in modern medicine. Additive manufacturing (AM) is a practical manufacturing revolution that uses building strategies like molding as a viable solution for precise hydrogel manufacturing. Recent advances in this technology have led to the successful manufacturing of hydrogels with enhanced reproducibility, accuracy, precision, and ease of fabrication. Hydrogels continue to metamorphose as the vital compatible bio-ink matrix for AM. AM hydrogels have paved the way for complex 3D/4D hydrogels that can be loaded with drugs or cells. Bio-mimicking 3D cell cultures designed via hydrogel-based AM is a groundbreaking in-vivo assessment tool in biomedical trials. This brief review focuses on preparations and applications of additively manufactured hydrogels in the biomedical spectrum, such as targeted drug delivery, 3D-cell culture, numerous regenerative strategies, biosensing, bioprinting, and cancer therapies. Prevalent AM techniques like extrusion, inkjet, digital light processing, and stereo-lithography have been explored with their setup and methodology to yield functional hydrogels. The perspectives, limitations, and the possible prospects of AM hydrogels have been critically examined in this study.

Trajectories of activities of daily living according to dementia among middle-aged and older people in South Korea: a longitudinal study from 2006 to 2020 (14 years)

Introduction

The aging population in South Korea faces numerous health challenges, one of which is the decline in Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL). This study aims to investigate the patterns of change in ADL and IADL among older adults and examines how these patterns vary between individuals with and without dementia.

Methods

We conducted an analysis of data collected from the Korea Longitudinal Study of Ageing (KLoSA) between 2006 and 2022. Our cohort consisted of individuals aged 45 and older with non-dementia conditions, including mild cognitive impairment (N=6042), and a smaller group with dementia (N=91). Using Latent Growth Curve Models, we explored the developmental trajectories of ADL and IADL among our sample.

Results

Our findings indicate a linear decline in both ADL and IADL scores as individuals age. The decline in IADL was more pronounced in the dementia group, suggesting a greater sensitivity to sociocultural factors within this domain. The data revealed that individuals with dementia had consistently lower ADL and IADL scores. Notably, the variance in scores within the dementia group increased with age, signifying a worsening in daily living performance and an increase in individual variation (F=226.630, p<.001).

Discussion

The results of this study underscore the impact of dementia on both the self-regulation function and the social and cultural aspects of daily living performance, particularly reflected in IADL scores. These findings point to the necessity for comprehensive care strategies that address the multifaceted needs of older adults with dementia, including support for complex daily activities that are influenced by sociocultural factors.

Predicting early Alzheimer's with blood biomarkers and clinical features

Alzheimer's disease (AD) is an incurable neurodegenerative disorder that leads to dementia. This study employs explainable machine learning models to detect dementia cases using blood gene expression, single nucleotide polymorphisms (SNPs), and clinical data from Alzheimer's Disease Neuroimaging Initiative (ADNI). Analyzing 623 ADNI participants, we found that the Support Vector Machine classifier with Mutual Information (MI) feature selection, trained on all three data modalities, achieved exceptional performance (accuracy = 0.95, AUC = 0.94). When using gene expression and SNP data separately, we achieved very good performance (AUC = 0.65, AUC = 0.63, respectively). Using SHapley Additive exPlanations (SHAP), we identified significant features, potentially serving as AD biomarkers. Notably, genetic-based biomarkers linked to axon myelination and synaptic vesicle membrane formation could aid early AD detection. In summary, this genetic-based biomarker approach, integrating machine learning and SHAP, shows promise for precise AD diagnosis, biomarker discovery, and offers novel insights for understanding and treating the disease. This approach addresses the challenges of accurate AD diagnosis, which is crucial given the complexities associated with the disease and the need for non-invasive diagnostic methods.

Urine biomarkers for Alzheimer's disease: A new opportunity for wastewater-based epidemiology?

While Alzheimer's disease (AD) diagnosis, management, and care have become priorities for healthcare providers and researcher's worldwide due to rapid population aging, epidemiologic surveillance efforts are currently limited by costly, invasive diagnostic procedures, particularly in low to middle income countries (LMIC). In recent years, wastewater-based epidemiology (WBE) has emerged as a promising tool for public health assessment through detection and quantification of specific biomarkers in wastewater, but applications for non-infectious diseases such as AD remain limited. This early review seeks to summarize AD-related biomarkers and urine and other peripheral biofluids and discuss their potential integration to WBE platforms to guide the first prospective efforts in the field. Promising results have been reported in clinical settings, indicating the potential of amyloid β, tau, neural thread protein, long non-coding RNAs, oxidative stress markers and other dysregulated metabolites for AD diagnosis, but questions regarding their concentration and stability in wastewater and the correlation between clinical levels and sewage circulation must be addressed in future studies before comprehensive WBE systems can be developed.

Mannose-Integrated Nanoparticle Hitchhike Glucose Transporter 1 Recycling to Overcome Various Barriers of Oral Delivery for Alzheimer's Disease Therapy

A brain-targeting nanodelivery system has been a hot topic and has undergone rapid progression. However, due to various obstacles such as the intestinal epithelial barrier (IEB) and the blood-brain barrier (BBB), few nanocarriers can achieve brain-targeting through oral administration. Herein, an intelligent oral brain-targeting nanoparticle (FTY@Man NP) constructed from a PLGA-PEG skeleton loaded with fingolimod (FTY) and externally modified with mannose was designed in combination with a glucose control strategy for the multitarget treatment of Alzheimer's disease (AD). The hydrophilic and electronegative properties of the nanoparticle facilitated its facile penetration through the mucus barrier, while the mannose ligand conferred IEB targeting abilities to the nanoparticle. Subsequently, glycemic control allowed the mannose-integrated nanoparticle to hitchhike the glucose transporter 1 (GLUT1) circulation across the BBB. Finally, the released FTY modulated the polarity of microglia from pro-inflammatory M1 to anti-inflammatory M2 and normalized the activated astrocyte, enhancing the clearance of toxic protein Amyloid-β (Aβ) while alleviating oxidative stress and neuroinflammation. Notably, both in vitro and in vivo results have consistently demonstrated that the oral administration of FTY@Man NP could effectively traverse the multiple barriers, thereby exerting significant therapeutic effects. This breakthrough holds the promise of realizing a highly effective orally administered treatment for AD.

Two decades of research on the role of diet in Alzheimer's disease (2003-2023): a bibliometric and visual analysis based on CiteSpace

BACKGROUND

In recent years, the impact of diet on Alzheimer's disease (AD) as a modifiable lifestyle has attracted widespread attention. We aimed to elucidate the current research status, frontiers, and research trends regarding the role of diet in AD over the past two decades through CiteSpace.

METHODS

Studies related to AD and diet that were published from January 1, 2003, to June 30, 2023, were retrieved via the Web of Science Core Collection. We imported the study data into CiteSpace for visual analysis of countries, institutions, co-authors, and co-occurring keywords.

RESULTS

A total of 922 relevant studies were included in our analysis, which found Nikolaos Scarmeas was the most prolific author (13 studies, 1.41%). The results also indicated that USA and Columbia University were the country and institution with the highest number of publications, with 209 (22.67%) and 23 (2.49%), respectively. The keywords that had a burst in the past four years were neuroinflammation, AD, tau, association, and beta.

CONCLUSION

Talent exchange and regional cooperation are recommended in this study field. The results indicate that the effectiveness of various dietary patterns and mechanisms of dietary interventions using biomarkers and supplementation with refined nutrients will be the main research trends in the future.

Breath biomarkers in Non-Carcinogenic diseases

The analysis of volatile organic compounds (VOCs) from human matrices like breath, perspiration, and urine has received increasing attention from academic and medical researchers worldwide. These biological-borne VOCs molecules have characteristics that can be directly related to physiologic and pathophysiologic metabolic processes. In this work, gathers a total of 292 analytes that have been identified as potential biomarkers for the diagnosis of various non-carcinogenic diseases. Herein we review the advances in VOCs with a focus on breath biomarkers and their potential role as minimally invasive tools to improve diagnosis prognosis and therapeutic monitoring.

The importance of education for understanding variability of dementia onset in the United States

BACKGROUND

Greater levels of education are associated with lower risk of dementia, but less is known about how education is also associated with the compression of dementia incidence.

OBJECTIVE

We extend the literature on morbidity compression by evaluating whether increased levels of education are associated with greater dementia compression. We evaluate these patterns across race and gender groups.

METHODS

We use the Health and Retirement Study (2000-2016), a nationally representative longitudinal study of older adults in the United States. To evaluate the onset and compression of dementia across education groups, we examine the age-specific distribution of dementia events, identifying the modal age of onset and the standard deviation above the mode (a measure of compression).

RESULTS

While the modal age of onset is around 85 years among adults with a college degree, the modal age for adults with less than a high school education occurs before age 65 - at least a 20-year difference. The standard deviation of dementia onset is about three times greater for adults with less than a high school education compared to adults with a college degree. Patterns were consistent across race and gender groups.

CONCLUSION

This research highlights the variability of dementia experiences in the older population by documenting differences in longevity without dementia and compression of dementia onset among more educated adults and less educated adults.

CONTRIBUTION

We incorporate conceptual insights from the life span variability and compression literature to better understand education-dementia disparities in both the postponement and uncertainty of dementia onset in the US population.

A Study of Assisted Screening for Alzheimer's Disease Based on Handwriting and Gait Analysis

Background

Alzheimer's disease (AD) is a progressive neurodegenerative disease that is not easily detected in the early stage. Handwriting and walking have been shown to be potential indicators of cognitive decline and are often affected by AD.

Objective

This study proposes an assisted screening framework for AD based on multimodal analysis of handwriting and gait and explores whether using a combination of multiple modalities can improve the accuracy of single modality classification.

Methods

We recruited 90 participants (38 AD patients and 52 healthy controls). The handwriting data was collected under four handwriting tasks using dot-matrix digital pens, and the gait data was collected using an electronic trail. The two kinds of features were fused as inputs for several different machine learning models (Logistic Regression, SVM, XGBoost, Adaboost, LightGBM), and the model performance was compared.

Results

The accuracy of each model ranged from 71.95% to 96.17%. Among them, the model constructed by LightGBM had the best performance, with an accuracy of 96.17%, sensitivity of 95.32%, specificity of 96.78%, PPV of 95.94%, NPV of 96.74%, and AUC of 0.991. However, the highest accuracy of a single modality was 93.53%, which was achieved by XGBoost in gait features.

Conclusions

The research results show that the combination of handwriting features and gait features can achieve better classification results than a single modality. In addition, the assisted screening model proposed in this study can achieve effective classification of AD, which has development and application prospects.

Comparison of the diagnostic accuracy of resting-state fMRI driven machine learning algorithms in the detection of mild cognitive impairment

Mild cognitive impairment (MCI) is a potential therapeutic window in the prevention of dementia; however, automated detection of early cognitive deterioration is an unresolved issue. The aim of our study was to compare various classification approaches to differentiate MCI patients from healthy controls, based on rs-fMRI data, using machine learning (ML) algorithms. Own dataset (from two centers) and ADNI database were used during the analysis. Three fMRI parameters were applied in five feature selection algorithms: local correlation, intrinsic connectivity, and fractional amplitude of low frequency fluctuations. Support vector machine (SVM) and random forest (RF) methods were applied for classification. We achieved a relatively wide range of 78-87% accuracy for the various feature selection methods with SVM combining the three rs-fMRI parameters. In the ADNI datasets case we can also see even 90% accuracy scores. RF provided a more harmonized result among the feature selection algorithms in both datasets with 80-84% accuracy for our local and 74-82% for the ADNI database. Despite some lower performance metrics of some algorithms, most of the results were positive and could be seen in two unrelated datasets which increase the validity of our methods. Our results highlight the potential of ML-based fMRI applications for automated diagnostic techniques to recognize MCI patients.

Lipidomics profiling reveals distinct patterns of plasma sphingolipid alterations in Alzheimer's disease and vascular dementia

BACKGROUND

Alzheimer's disease (AD) and vascular dementia (VaD) are two of the commonest causes of dementia in the elderly. Of the myriad biomolecules implicated in dementia pathogenesis, sphingolipids have attracted relatively scant research attention despite their known involvement in multiple pathophysiological processes. The potential utility of peripheral sphingolipids as biomarkers in dementia cohorts with high concomitance of cerebrovascular diseases is also unclear.

METHODS

Using a lipidomics platform, we performed a case-control study of plasma sphingolipids in a prospectively assessed cohort of 526 participants (non-cognitively impaired, NCI = 93, cognitively impaired = 217, AD = 166, VaD = 50) using a lipidomics platform.

RESULTS

Distinct patterns of sphingolipid alterations were found in AD and VaD, namely an upregulation of d18:1 species in AD compared to downregulation of d16:1 species in VaD. In particular, GM3 d18:1/16:0 and GM3 d18:1/24:1 showed the strongest positive associations with AD. Furthermore, evaluation of sphingolipids panels showed specific combinations with higher sensitivity and specificity for classification of AD (Cer d16:1/24:0. Cer d18:1/16:0, GM3 d16:1/22:0, GM3 d18:1/16:0, SM d16:1/22:0, HexCer d18:1/18:0) and VAD (Cer d16:1/24:0, Cer d18:1/16:0, Hex2Cer d16:1/16:0, HexCer d18:1/18:0, SM d16:1/16:0, SM d16:1/20:0, SM d18:2/22:0) compared to NCI.

CONCLUSIONS

AD and VaD are associated with distinct changes of plasma sphingolipids, warranting further studies into underlying pathophysiological mechanisms and assessments of their potential utility as dementia biomarkers and therapeutic targets.

The latest perspectives of small molecules FMS kinase inhibitors

FMS kinase is a type III tyrosine kinase receptor that plays a central role in the pathophysiology and management of several diseases, including a range of cancer types, inflammatory disorders, neurodegenerative disorders, and bone disorders among others. In this review, the pathophysiological pathways of FMS kinase in different diseases and the recent developments of its monoclonal antibodies and inhibitors during the last five years are discussed. The biological and biochemical features of these inhibitors, including binding interactions, structure-activity relationships (SAR), selectivity, and potencies are discussed. The focus of this article is on the compounds that are promising leads and undergoing advanced clinical investigations, as well as on those that received FDA approval. In this article, we attempt to classify the reviewed FMS inhibitors according to their core chemical structure including pyridine, pyrrolopyridine, pyrazolopyridine, quinoline, and pyrimidine derivatives.

Summary of the Current Status of DNA Vaccination for Alzheimer Disease

Alzheimer disease (AD) is one of the most common and disabling neuropathies in the ever-growing aged population around the world, that especially affects Western countries. We are in urgent need of finding an effective therapy but also a valid prophylactic means of preventing AD. There is a growing attention currently paid to DNA vaccination, a technology particularly used during the COVID-19 era, which can be used also to potentially prevent or modify the course of neurological diseases, including AD. This paper aims to discuss the main features and hurdles encountered in the immunization and therapy against AD using DNA vaccine technology. Ultimately, this work aims to effectively promote the efforts in research for the development of safe and effective DNA and RNA vaccines for AD.

Parenchymal border macrophages regulate tau pathology and tau-mediated neurodegeneration

Parenchymal border macrophages (PBMs) reside close to the central nervous system parenchyma and regulate CSF flow dynamics. We recently demonstrated that PBMs provide a clearance pathway for amyloid-β peptide, which accumulates in the brain in Alzheimer's disease (AD). Given the emerging role for PBMs in AD, we explored how tau pathology affects the CSF flow and the PBM populations in the PS19 mouse model of tau pathology. We demonstrated a reduction of CSF flow, and an increase in an MHCII+PBM subpopulation in PS19 mice compared with WT littermates. Consequently, we asked whether PBM dysfunction could exacerbate tau pathology and tau-mediated neurodegeneration. Pharmacological depletion of PBMs in PS19 mice led to an increase in tau pathology and tau-dependent neurodegeneration, which was independent of gliosis or aquaporin-4 depolarization, essential for the CSF-ISF exchange. Together, our results identify PBMs as novel cellular regulators of tau pathology and tau-mediated neurodegeneration.

Common and Trace Metals in Alzheimer's and Parkinson's Diseases

Trace elements and metals play critical roles in the normal functioning of the central nervous system (CNS), and their dysregulation has been implicated in neurodegenerative disorders such as Alzheimer's disease (AD) and Parkinson's disease (PD). In a healthy CNS, zinc, copper, iron, and manganese play vital roles as enzyme cofactors, supporting neurotransmission, cellular metabolism, and antioxidant defense. Imbalances in these trace elements can lead to oxidative stress, protein aggregation, and mitochondrial dysfunction, thereby contributing to neurodegeneration. In AD, copper and zinc imbalances are associated with amyloid-beta and tau pathology, impacting cognitive function. PD involves the disruption of iron and manganese levels, leading to oxidative damage and neuronal loss. Toxic metals, like lead and cadmium, impair synaptic transmission and exacerbate neuroinflammation, impacting CNS health. The role of aluminum in AD neurofibrillary tangle formation has also been noted. Understanding the roles of these elements in CNS health and disease might offer potential therapeutic targets for neurodegenerative disorders. The Codex Alimentarius standards concerning the mentioned metals in foods may be one of the key legal contributions to safeguarding public health. Further research is needed to fully comprehend these complex mechanisms and develop effective interventions.

Aggregation, Transmission, and Toxicity of the Microtubule-Associated Protein Tau: A Complex Comprehension

The microtubule-associated protein tau is an intrinsically disordered protein containing a few short and transient secondary structures. Tau physiologically associates with microtubules (MTs) for its stabilization and detaches from MTs to regulate its dynamics. Under pathological conditions, tau is abnormally modified, detaches from MTs, and forms protein aggregates in neuronal and glial cells. Tau protein aggregates can be found in a number of devastating neurodegenerative diseases known as "tauopathies", such as Alzheimer's disease (AD), frontotemporal dementia (FTD), corticobasal degeneration (CBD), etc. However, it is still unclear how the tau protein is compacted into ordered protein aggregates, and the toxicity of the aggregates is still debated. Fortunately, there has been considerable progress in the study of tau in recent years, particularly in the understanding of the intercellular transmission of pathological tau species, the structure of tau aggregates, and the conformational change events in the tau polymerization process. In this review, we summarize the concepts of tau protein aggregation and discuss the views on tau protein transmission and toxicity.

A Concise Review of the Recent Structural Explorations of Chromones as MAO-B Inhibitors: Update from 2017 to 2023

Monoamine oxidases (MAOs) are a family of flavin adenine dinucleotide-dependent enzymes that catalyze the oxidative deamination of a wide range of endogenous and exogenous amines. Multiple neurological conditions, including Parkinson's disease (PD) and Alzheimer's disease (AD), are closely correlated with altered biogenic amine concentrations in the brain caused by MAO. Toxic byproducts of this oxidative breakdown, including hydrogen peroxide, reactive oxygen species, and ammonia, can cause oxidative damage and mitochondrial dysfunction in brain cells. Certain MAO-B blockers have been recognized as effective treatment options for managing neurological conditions, including AD and PD. There is still a pressing need to find potent therapeutic molecules to fight these disorders. However, the focus of neurodegeneration studies has recently increased, and certain compounds are now in clinical trials. Chromones are promising structures for developing therapeutic compounds, especially in neuronal degeneration. This review focuses on the MAO-B inhibitory potential of several synthesized chromones and their structural activity relationships. Concerning the discovery of a novel class of effective chromone-based selective MAO-B-inhibiting agents, this review offers readers a better understanding of the most recent additions to the literature.

Mitochondrial dynamics in health and disease: mechanisms and potential targets

Mitochondria are organelles that are able to adjust and respond to different stressors and metabolic needs within a cell, showcasing their plasticity and dynamic nature. These abilities allow them to effectively coordinate various cellular functions. Mitochondrial dynamics refers to the changing process of fission, fusion, mitophagy and transport, which is crucial for optimal function in signal transduction and metabolism. An imbalance in mitochondrial dynamics can disrupt mitochondrial function, leading to abnormal cellular fate, and a range of diseases, including neurodegenerative disorders, metabolic diseases, cardiovascular diseases and cancers. Herein, we review the mechanism of mitochondrial dynamics, and its impacts on cellular function. We also delve into the changes that occur in mitochondrial dynamics during health and disease, and offer novel perspectives on how to target the modulation of mitochondrial dynamics.