Alzheimer disease

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.

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.

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.

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.

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.

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.

Fibroblast growth factor 10 ameliorates neurodegeneration in mouse and cellular models of Alzheimer's disease via reducing tau hyperphosphorylation and neuronal apoptosis

Alzheimer's disease (AD) is characterized with senile plaques formed by Aβ deposition, and neurofibrillary tangles composed of hyperphosphorylated tau protein, which ultimately lead to cognitive impairment. Despite the heavy economic and life burdens faced by the patients with AD, effective treatments are still lacking. Previous studies have reported the neuroprotective effects of FGF10 in CNS diseases, but its role in AD remains unclear. In this study, we demonstrated that FGF10 levels were reduced in the serum of AD patients, as well as in the brains of 3xTg-AD mice and APPswe-transfected HT22 cells, suggesting a close relationship between FGF10 and AD. Further investigations revealed that intranasal delivery of FGF10 improved cognitive functions in 3xTg-AD mice. Additionally, FGF10 treatment reduced tau hyperphosphorylation and neuronal apoptosis, thereby mitigating neuronal cell damage and synaptic deficits in the cortex and hippocampus of 3xTg-AD mice, as well as APPswe-transfected HT22 cells. Furthermore, we evaluated the therapeutic potential of FGF10 gene delivery for treating AD symptoms and pathologies. Tail vein delivery of the FGF10 gene using AAV9 improved cognitive and neuronal functions in 3xTg-AD mice. Similarly, endogenous FGF10 overexpression ameliorated tau hyperphosphorylation and neuronal apoptosis in the cortex and hippocampus of 3xTg-AD mice. Importantly, we confirmed that the FGFR2/PI3K/AKT signaling pathway was activated following intranasal FGF10 delivery and AAV9-mediated FGF10 gene delivery in 3xTg-AD mice and APPswe-transfected HT22 cells. Knockdown of FGFR2 attenuated the protective effect of FGF10. Collectively, these findings suggest that intranasal delivery of FGF10 and AAV9-mediated FGF10 gene delivery could be a promising disease-modifying therapy for AD.

Molecular Mechanisms of Dementia

The various forms of dementia and the other neurodegenerative disorders that affect memory, cognition, and behavior have become a public health priority across the developed world [...].

Metal Nanoparticles in Alzheimer's Disease

Nanotechnology has emerged in different fields of biomedical application, including lifestyle diseases like diabetes, hypertension, and chronic kidney disease, neurodegenerative diseases like Alzheimer's disease (AD), Parkinson's disease, and different types of cancers. Metal nanoparticles are one of the most used drug delivery systems due to the benefits of their enhanced physicochemical properties as compared to bulk metals. Neurodegenerative diseases are the second most cause affecting mortality worldwide after cancer. Hence, they require the most specific and targeted drug delivery systems for maximum therapeutic benefits. Metal nanoparticles are the preferred drug delivery system, possessing greater blood-brain barrier permeability, biocompatibility, and enhanced bioavailability. But some metal nanoparticles exhibit neurotoxic activity owing to their shape, size, surface charge, or surface modification. This review article has discussed the pathophysiology of AD. The neuroprotective mechanism of gold, silver, selenium, ruthenium, cerium oxide, zinc oxide, and iron oxide nanoparticles are discussed. Again, the neurotoxic mechanisms of gold, iron oxide, titanium dioxide, and cobalt oxide are also included. The neuroprotective and neurotoxic effects of nanoparticles targeted for treating AD are discussed elaborately. The review also focusses on the biocompatibility of metal nanoparticles for targeting the brain in treating AD. The clinical trials and the requirement to develop new drug delivery systems are critically analyzed. This review can show a path for the researchers involved in the brain-targeted drug delivery for AD.

Amyloid β induces cardiac dysfunction and neuro-signaling impairment in the heart of an Alzheimer's disease model

Aims

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by cerebral amyloid β (Aβ) deposition and tau pathology. The AD-mediated degeneration of the brain neuro-signaling pathways, together with a potential peripheral amyloid accumulation, may also result in the derangement of the peripheral nervous system, culminating in detrimental effects on other organs, including the heart. However, whether and how AD pathology modulates cardiac function, neurotrophins, innervation, and amyloidosis is still unknown. Here, we report for the first time that cardiac remodeling, amyloid deposition, and neuro-signaling dysregulation occur in the heart of Tg2576 mice, a widely used model of AD and cerebral amyloidosis.

Methods ad Results

Echocardiographic analysis showed significant deterioration of left ventricle function, evidenced by a decline of both ejection fraction and fraction shortening percentage in 12-month-old Tg2576 mice compared to age-matched WT littermates. Tg2576 mice hearts exhibited an accumulation of amyloid aggregates, including Aβ, an increase in interstitial fibrosis and severe cardiac nervous system dysfunction. The transgenic mice also showed a significant decrease in cardiac nerve fiber density, including both adrenergic and regenerating nerve endings. This myocardial denervation was accompanied by a robust reduction in NGF and BDNF protein expression as well as GAP-43 expression (regenerating fibers) in both the brain and heart of Tg2576 mice. Accordingly, cardiomyocytes and neuronal cells challenged with Aβ oligomers showed significant downregulation of BDNF and GAP-43, indicating a causal effect of Aβ on the loss of cardiac neurotrophic function.

Conclusions

Overall, this study uncovers possible harmful effects of AD on the heart, revealing cardiac degeneration induced by Aβ through fibrosis and neuro-signaling pathway deregulation for the first time in Tg2576 mice. Our data suggest that AD pathology can cause deleterious effects on the heart, and the peripheral neurotrophic pathway may represent a potential therapeutic target to limit these effects.

Effect of Comorbidities Features in Machine Learning Models for Survival Analysis to Predict Prodromal Alzheimer's Disease

Alzheimer's Disease (AD) is the most common form of dementia, specifically a progressive degenerative disorder affecting 47 million people worldwide and is only expected to grow in the elderly population. The detection of AD in its early stages is crucial to allow early intervention aiding in the prevention or slowing down of the disease. The effect of using comorbidity features in machine learning models to predict the time until a patient develops a prodrome was observed. In this study, we used Alzheimer's Disease Neuroimaging Initiative (ADNI) high-dimensional clinical data to compare the performance of six machine learning algorithms for survival analysis, combined with six feature selection methods trained on two settings: with and without comorbidities features. Our ridge model combined with permutation feature selection achieves maximum performance of 0.90 when using comorbidity features with the concordance index as a performance indicator. This demonstrated that incorporating comorbidities into the feature set enhances the performance of survival analysis for Alzheimer's disease. There is potential to identify risk factors (coronary artery disease) from comorbidities which could guide preventative care based on medical history.

Ferulago angulata Methanolic Extract Protects PC12 Cells Against Beta-amyloid-induced Toxicity

Introduction

Alzheimer's disease (AD) is an age-dependent neurodegenerative disease. Beta-amyloid (Aβ)-induced neurotoxicity has a pivotal role in AD pathogenesis; therefore, the modulation of Aβ toxicity is the promising therapeutic approach to control the disease progression. Medicinal plants because of their multiple active ingredients are effective in complex diseases, such as AD. Therefore, several studies have studied medicinal plants to find an effective treatment for AD. Ferulago angulata is a medicinal plant with antioxidant and neuroprotective activity. The present study was done to assess the protective effect of the methanolic extract of Ferulago angulate on Aβ-induced toxicity and oxidative stress in PC12 cells.

Methods

The methanolic extract of aerial parts of the plant was prepared by the maceration method. PC12 cells were cultured according to a standard protocol. PC12 cells were incubated for 24 hours with Aβ alone, and Aβ in combination with various concentrations of the F. angulata extract. Cell viability was determined by the methyl thiazole tetrazolium (MTT) assay. Also, reactive oxygen species (ROS) production and the activity of acetylcholine esterase (AChE), glutathione peroxidase (GPx), and caspase-3 enzymes were measured.

Results

The extract dose-dependently protected PC12 cells against Aβ-induced cell death. Also, Aβ increased ROS production, AChE, and caspase-3 activity, and decreased the GPx activity, which all were ameliorated by F. angulata extract.

Conclusion

F. angulata extract protects against Aβ-induced oxidative stress and apoptosis. These effects may be due to the antioxidant and anticholinesterase activity of the extract. It is recommended to assess F. angulata extract as an anti-AD agent.

Highlights

Ferulago angulata extract dose-dependently ameliorates Aβ-induced cytotoxicity in PC12 cells.Aβ induced oxidative stress in PC12 cells, which was attenuated by the F. angulata extract.Aβ increased acetylcholinesterase activity in PC12 cells, which was prevented by the F. angulata extract.

Plain Language Summary

Alzheimer's disease (AD) is a common form of dementia in the elderly with a complex pathophysiology. Beta-amyloid (Aβ)- induced neurotoxicity plays a pivotal role in AD progression. So far, there is no cure for AD. Medicinal plants contain various pharmacologically active compounds that make them suitable for the treatment of complex diseases. In this study, the anti-AD effect of F. angulata extract was investigated by assessing its protective effect against Aβ-induced toxicity in PC12 cells F. angulata extract improved Aβ-induced toxicity by diminishing oxidative stress and apoptosis. Therefore, F. angulata extract merits further studies for use in the treatment of AD.

Unraveling Molecular and Genetic Insights into Neurodegenerative Diseases: Advances in Understanding Alzheimer's, Parkinson's, and Huntington's Diseases and Amyotrophic Lateral Sclerosis

Neurodegenerative diseases are, according to recent studies, one of the main causes of disability and death worldwide. Interest in molecular genetics has started to experience exponential growth thanks to numerous advancements in technology, shifts in the understanding of the disease as a phenomenon, and the change in the perspective regarding gene editing and the advantages of this action. The aim of this paper is to analyze the newest approaches in genetics and molecular sciences regarding four of the most important neurodegenerative disorders: Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. We intend through this review to focus on the newest treatment, diagnosis, and predictions regarding this large group of diseases, in order to obtain a more accurate analysis and to identify the emerging signs that could lead to a better outcome in order to increase both the quality and the life span of the patient. Moreover, this review could provide evidence of future possible novel therapies that target the specific genes and that could be useful to be taken into consideration when the classical approaches fail to shed light.

TG2 promotes amyloid beta aggregates: Impact on ER-mitochondria crosstalk, calcium homeostasis and synaptic function in Alzheimer’s disease

Alzheimer's Disease (AD) is a neurodegenerative disorder characterized by cognitive impairment that increasingly affects the elderly. AD's main features have been related to cellular and molecular events, including the aberrant aggregation of the amyloid beta peptide (Aβ), Ca²⁺ dyshomeostasis, and increased mitochondria-associated membranes (MAMs). Transglutaminase type 2 (TG2) is a ubiquitous enzyme whose primary role is the Ca²⁺-dependent proteins transamidation, including the Aβ peptide. TG2 activity has been closely related to cellular damage and death. We detected increased TG2 levels in neuronal cells treated with Aβ oligomers (AβOs) and hippocampal slices from J20 mice using cellular and molecular approaches. In this work, we characterized the capacity of TG2 to interact and promote Aβ toxic aggregates (AβTG2). AβTG2 induced an acute increase in intracellular Ca²⁺, miniature currents, and hiperexcitability, consistent with an increased mitochondrial Ca²⁺ overload, IP3R-VDAC tethering, and mitochondria-endoplasmic reticulum contacts (MERCs). AβTG2 also decreased neuronal viability and excitatory postsynaptic currents, reinforcing the idea of synaptic failure associated with MAMs dysregulation mediated by TG2. Z-DON treatment, TG2 inhibitor, reduced calcium overload, mitochondrial membrane potential loss, and synaptic failure, indicating an involvement of TG2 in a toxic cycle which increases Aβ aggregation, Ca²⁺ overload, and MAMs upregulation. These data provide novel information regarding the role TG2 plays in synaptic function and contribute additional evidence to support the further development of TG2 inhibitors as a disease-modifying strategy for AD.

ExHiF: Alzheimer's disease detection using exemplar histogram-based features with CT and MR images

PURPOSE

The classification of medical images is an important priority for clinical research and helps to improve the diagnosis of various disorders. This work aims to classify the neuroradiological features of patients with Alzheimer's disease (AD) using an automatic hand-modeled method with high accuracy.

MATERIALS AND METHOD

This work uses two (private and public) datasets. The private dataset consists of 3807 magnetic resonance imaging (MRI) and computer tomography (CT) images belonging to two (normal and AD) classes. The second public (Kaggle AD) dataset contains 6400 MR images. The presented classification model comprises three fundamental phases: feature extraction using an exemplar hybrid feature extractor, neighborhood component analysis-based feature selection, and classification utilizing eight different classifiers. The novelty of this model is feature extraction. Vision transformers inspire this phase, and hence 16 exemplars are generated. Histogram-oriented gradients (HOG), local binary pattern (LBP) and local phase quantization (LPQ) feature extraction functions have been applied to each exemplar/patch and raw brain image. Finally, the created features are merged, and the best features are selected using neighborhood component analysis (NCA). These features are fed to eight classifiers to obtain highest classification performance using our proposed method. The presented image classification model uses exemplar histogram-based features; hence, it is called ExHiF.

RESULTS

We have developed the ExHiF model with a ten-fold cross-validation strategy using two (private and public) datasets with shallow classifiers. We have obtained 100% classification accuracy using cubic support vector machine (CSVM) and fine k nearest neighbor (FkNN) classifiers for both datasets.

CONCLUSIONS

Our developed model is ready to be validated with more datasets and has the potential to be employed in mental hospitals to assist neurologists in confirming their manual screening of AD using MRI/CT images.

Exploring the relationship between socioeconomic deprivation index and Alzheimer's disease using summary-level data: From genetic correlation to causality

Patients with Alzheimer's disease (AD) are markedly increasing as population aging and no disease-modifying therapies are currently available for AD. Previous studies suggested a broad link between socioeconomic status and a variety of disorders, including mental illness and cognitive abilities. However, the association between socioeconomic deprivation and AD has been unknown. We here employed Townsend deprivation index (TDI) to explore such relation and found a positive genetic correlation (r̂_g=0.211, P = 8.00 × 10^-4) between the two traits with summary statistics data (N = 455,258 for TDI and N = 455,815 for AD). Then, we performed pleiotropy analysis at both variant and gene levels using a powerful method called PLACO and detected 87 distinct pleiotropic genes. Functional analysis demonstrated these genes were significantly enriched in pancreas, liver, heart, blood, brain, and muscle tissues. Using Mendelian randomization methods, we further found that one genetically predicted standard deviation elevation in TDI could lead to approximately 18.5% (95% confidence intervals 1.6- 38.2%, P = 0.031) increase of AD risk, and that the identified causal association was robust against used MR approaches, horizontal pleiotropy, and instrumental selection. Overall, this study provides deep insight into common genetic components underlying TDI and AD, and further reveals causal connection between them. It is also helpful to develop a more suitable plan for ameliorating inequities, hardship, and disadvantage, with the hope of improving health outcomes among economically disadvantaged people.

An ongoing journey of chalcone analogues as single and multi-target ligands in the field of Alzheimer's disease: A review with structural aspects

Alzheimer's disease (AD) is a chronic and irreversible neurodegenerative disorder with progressive dementia and cognitive impairment. AD poses severe health challenge in elderly people and become one of the leading causes of death worldwide. It possesses complex pathophysiology with several hypotheses (cholinergic hypothesis, amyloid hypothesis, tau hypothesis, oxidative stress, mitochondrial dysfunction etc.). Several attempts have been made for the management of multifactorial AD. Acetylcholinesterase is the only target has been widely explored in the management of AD to the date. The current review set forth the chalcone based natural, semi-synthetic and synthetic compounds in the search of potential anti-Alzheimer's agents. The main highlights of current review emphasizes on chalcone target different enzymes and pathways like Acetylcholinesterase, β-secretase (BACE1), tau proteins, MAO, free radicals, Advanced glycation end Products (AGEs) etc. and their structure activity relationships contributing in the inhibition of above mentioned various targets of AD.

Antiamnesic Effects of Novel Phthalimide Derivatives in Scopolamine-Induced Memory Impairment in Mice: A Useful Therapy for Alzheimer's Disease

Phthalimides have diverse bioactivities and are attractive molecules for drug discovery and development. Here, we explored new synthesized phthalimide derivatives (compounds 1-3) in improving memory impairment associated with Alzheimer's disease (AD), using in vitro and ex vivo acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibition and in vivo models, including Y-maze test and novel object recognition test (NORT). Compounds 1-3 exhibited significant AChE activity with IC₅₀ values of 10, 140, and 18 μM and BuChE with IC₅₀ values of 80, 50, and 11 μM, respectively. All compounds 1-3 showed excellent antioxidant potential in DPPH and ABTS assays with IC₅₀ values in the range of 105-340 and 205-350 μM, respectively. In ex vivo studies, compounds 1-3 also significantly inhibited both enzymes in a concentration-dependent manner along with significant antioxidant activities. In in vivo studies, compounds 1-3 reversed scopolamine-induced amnesia as indicated by a significant increase in the spontaneous alternation in the Y-maze test and an increase in the discrimination index in the NORT. Molecular docking was also conducted for compounds 1-3 against AChE and BuChE, which showed that compounds 1 and 3 have excellent binding with AChE and BuChE as compared to 2. These findings suggest that compounds 1-3 possess significant antiamnesic potential and may serve as useful leads to develop novel therapeutics for the symptomatic management and treatment of AD.

Long-term use of metformin and Alzheimer's disease: beneficial or detrimental effects

Alzheimer's disease (AD) is the most common neurodegenerative disease characterized by extracellular deposition of amyloid beta (Aβ) leading to cognitive decline. Evidence from epidemiological studies has shown the association between type 2 diabetes mellitus (T2DM) and the development of AD. T2DM and peripheral insulin resistance (IR) augment the risk of AD with the development of brain IR with inhibition of neuronal insulin receptors. These changes impair clearance of Aβ, increase secretion of Aβ_1-42, reduce brain glucose metabolism, and abnormal deposition of Aβ plaques. Insulin-sensitizing drug metformin inhibits aggregation of Aβ by increasing the activity of the insulin-degrading enzyme (IDE) and neprilysin (NEP) levels. Additionally, different studies raised conflicting evidence concerning long-term metformin therapy in T2DM patients, as it may increase the risk of AD or it may prevent the progression of AD. Therefore, the objective of this review was to clarify the beneficial and detrimental effects of long-term metformin therapy in T2DM patients and risk of AD. Evidence from clinical trial studies revealed the little effect of metformin on AD. Various animal studies showed that metformin increases Aβ formation by activation of amyloid precursor protein (APP)-cleaving enzymes with the generation of insoluble tau species. Of note, the metformin effect on cognitive function relative to AD pathogenesis is mostly assessed in animal model studies. The duration of metformin therapy was short in most animal studies, this finding cannot apply to the long-term duration of metformin in humans. Therefore, large-scale prospective and comparative studies involving long-term metformin therapy in both diabetic and non-diabetic patients are required to exclude the effect of T2DM-induced AD.

Effect of substrate charge density on the adsorption of intrinsically disordered protein amyloid β40: a molecular dynamics study

The inhibitory effect of negatively charged gold nanoparticles (AuNPs) on amyloidogenic protein fibrillation has been established from experiments and computer simulations. Here, we investigate the effect of the charge density (σ) of gold (Au) surfaces on the adsorption of the intrinsically disordered amyloid β40 (Aβ40) monomer using molecular dynamics (MD) simulations. On the basis of the binding free energy, some key residues (ARG5, LYS16, LYS28, LEU17-ALA21, ILE31-VAL38) were found to be responsible for preventing the β-sheet formation, which is known to be a precursor for fibrillation. Until a critical charge density (σ_c) of -0.167 e nm^-2, the key residues remained adsorbed on the Au slab. A saturation in the number of condensed counterions (Na⁺) on Aβ40 was also observed at σ_c. Beyond σ_c, the condensation of Na⁺ occurs only on the Au slab, leading to competition between positively charged key residues and condensed ions. This competition was found to be responsible for the lack of adsorption of the key residues, leading to β-sheet formation for σ > -0.167 e nm^-2. This study suggests that if the key residues are not adsorbed, then β-sheet formation is observed, which can then lead to the development of proto-fibrils and subsequently fibrillation. Therefore the surface should have an optimal charge density to be an effective inhibitor of fibrillation.

Alzheimer's Disease: Innovative Therapeutic Approaches Based on Peptides and Nanoparticles

Alzheimer's disease (AD) is the main cause of dementia in the world and its etiology is not yet fully understood. The pathology of AD is primarily characterized by intracellular neurofibrillary tangles and extracellular amyloid-β plaques. Unfortunately, few treatment options are available, and most treat symptoms, as is the case of acetylcholinesterase inhibitors (IAChE) and N-methyl-d-aspartate receptor antagonists. For more than 20 years pharmaceutical research has targeted the "amyloid cascade hypothesis," but this has not produced meaningful results, leading researchers to focus now on other characteristics of the disease and on multitarget approaches. This review aims to evaluate some new treatments that are being developed and studied. Among these are new treatments based on peptides, which have high selectivity and low toxicity; however, these compounds have a short half-life and encounter challenges when crossing the blood-brain barrier. The present review discusses up-and-coming peptides tested as treatments and explores some nanotechnological strategies to overcome the downsides. These compounds are promising, as they not only act on the symptoms but also aim to prevent progressive neuronal loss.

Autonomic nervous system and cardiac neuro-signaling pathway modulation in cardiovascular disorders and Alzheimer's disease

The heart is a functional syncytium controlled by a delicate and sophisticated balance ensured by the tight coordination of its several cell subpopulations. Accordingly, cardiomyocytes together with the surrounding microenvironment participate in the heart tissue homeostasis. In the right atrium, the sinoatrial nodal cells regulate the cardiac impulse propagation through cardiomyocytes, thus ensuring the maintenance of the electric network in the heart tissue. Notably, the central nervous system (CNS) modulates the cardiac rhythm through the two limbs of the autonomic nervous system (ANS): the parasympathetic and sympathetic compartments. The autonomic nervous system exerts non-voluntary effects on different peripheral organs. The main neuromodulator of the Sympathetic Nervous System (SNS) is norepinephrine, while the principal neurotransmitter of the Parasympathetic Nervous System (PNS) is acetylcholine. Through these two main neurohormones, the ANS can gradually regulate cardiac, vascular, visceral, and glandular functions by turning on one of its two branches (adrenergic and/or cholinergic), which exert opposite effects on targeted organs. Besides these neuromodulators, the cardiac nervous system is ruled by specific neuropeptides (neurotrophic factors) that help to preserve innervation homeostasis through the myocardial layers (from epicardium to endocardium). Interestingly, the dysregulation of this neuro-signaling pathway may expose the cardiac tissue to severe disorders of different etiology and nature. Specifically, a maladaptive remodeling of the cardiac nervous system may culminate in a progressive loss of neurotrophins, thus leading to severe myocardial denervation, as observed in different cardiometabolic and neurodegenerative diseases (myocardial infarction, heart failure, Alzheimer's disease). This review analyzes the current knowledge on the pathophysiological processes involved in cardiac nervous system impairment from the perspectives of both cardiac disorders and a widely diffused and devastating neurodegenerative disorder, Alzheimer's disease, proposing a relationship between neurodegeneration, loss of neurotrophic factors, and cardiac nervous system impairment. This overview is conducive to a more comprehensive understanding of the process of cardiac neuro-signaling dysfunction, while bringing to light potential therapeutic scenarios to correct or delay the adverse cardiovascular remodeling, thus improving the cardiac prognosis and quality of life in patients with heart or neurodegenerative disorders.

Functional changes in brain oscillations in dementia: a review

A growing body of evidence indicates that several characteristics of electroencephalography (EEG) and magnetoencephalography (MEG) play a functional role in cognition and could be linked to the progression of cognitive decline in some neurological diseases such as dementia. The present paper reviews previous studies investigating changes in brain oscillations associated to the most common types of dementia, namely Alzheimer's disease (AD), frontotemporal degeneration (FTD), and vascular dementia (VaD), with the aim of identifying pathology-specific patterns of alterations and supporting differential diagnosis in clinical practice. The included studies analysed changes in frequency power, functional connectivity, and event-related potentials, as well as the relationship between electrophysiological changes and cognitive deficits. Current evidence suggests that an increase in slow wave activity (i.e., theta and delta) as well as a general reduction in the power of faster frequency bands (i.e., alpha and beta) characterizes AD, VaD, and FTD. Additionally, compared to healthy controls, AD exhibits alteration in latencies and amplitudes of the most common event related potentials. In the reviewed studies, these changes generally correlate with performances in many cognitive tests. In conclusion, particularly in AD, neurophysiological changes can be reliable early markers of dementia.