Treatment Of Alzheimer's Disease Research Articles

Proteomic Alteration in Catalpol Treatment of Alzheimer's disease by regulating HSPA5/ GPX4

Alzheimer's disease (AD), a chronic and progressive neurodegenerative disease, is characterized by the deposition of extracellular amyloid plaques and intracellular neurofibrillary tangles. Conventional anti-AD drugs exhibit high toxicity and adversely impact patients' quality of life. Therefore, novel treatments for AD are urgently required. In recent years, targeting ferroptosis through the modulation of lipid oxidation has emerged as a new approach in the treatment of neurodegenerative diseases. Catalpol, an iridoid glycoside isolated from the roots of Rehmannia glutinosa, has exhibited anti-inflammatory, antioxidant, and neuroprotective properties. Therefore, in this study, we investigated the protective effects and associated underlying mechanisms of catalpol in an APP/PS1 AD mouse model. Catalpol treatment significantly improved the cognitive capabilities and decreased Aβ1-40 and Aβ1-42 levels in mice. Morphological testing revealed that catalpol prevented neuronal loss and reduced mitochondrial swelling in the hippocampal CA1 region. Proteomic studies identified 2,495 hippocampus proteins whose expression was associated with the mechanism of catalpol treatment, including 44 ferroptosis-related proteins. Bioinformatic analysis revealed that catalpol significantly increased the protein levels of HSPA5 and GPX4 in the hippocampus. Additionally, catalpol modulated biological pathways related to apoptosis, cytokine-mediated signaling, and ferroptosis. The considerable upregulation of HSPA5 and GPX4 with catalpol was further confirmed through western blotting. Catalpol exhibited neuroprotective effects through a variety of mechanisms. Among these, HSPA5 and GPX4, associated with ferroptosis, may play key roles in AD pathogenesis, and present promising therapeutic targets.

Prevention and Treatment of Alzheimer's Disease Via the Regulation of the Gut Microbiota With Traditional Chinese Medicine.

Alzheimer's disease (AD) is caused by a variety of factors, and one of the most important factors is gut microbiota dysbiosis. An imbalance in the gut mincrobiota have been shown to change the concentrations of lipopolysaccharide and short-chain fatty acids. These microorganisms synthesize substances that can influence the levels of a variety of metabolites and cause multiple diseases through the immune response, fatty acid metabolism, and amino acid metabolism pathways. Furthermore, these metabolic changes promote the formation of β-amyloid plaques and neurofibrillary tangles. Thus, the microbiota-gut-brain axis plays an important role in AD development. In addition to traditional therapeutic drugs such as donepezil and memantine, traditional Chinese medicines (TCMs) have also showed to significantly decrease the severity of AD symptoms and suppress the underlying related mechanisms. We searched for studies on the effects of different herbal monomers, single herbs, and polyherbal formulas on the gut microbiota of AD patients and identified the relevant pathways through which the gut microbiota affected AD. We conclude that improvements in the gut microbiota not only decrease the occurrence of inflammatory reactions but also reduce the deposition of central pathological products. Herbal monomers have a stronger effect on improving of central pathology. Polyherbal formulas have the most extensive effect on the gut microbiota in patients with AD. Among the effects of formulas, the anti-inflammatory effect is the most essential and is also the main concern regarding the use of TCMs in treating AD from the viewpoint of the gut microbiota. We hope that this review will be helpful for providing new ideas for the clinical application of TCMs in the treatment of AD.

EGb761 Trials for Mild-to-Moderate Dementia—What Have We Learned in the Past 18 years?

Background: Dementia leads to cognitive decline affecting memory, thinking, and behavior. Current pharmaceutical treatments are symptomatic, with limited efficacy and significant drawbacks. Ginkgo biloba extract (EGb761) is being explored as an adjuvant therapy for dementia because of its potential neuroprotective effects. Areas of Uncertainty: Despite decades of study, EGb761 has not been incorporated into treatment guidelines for these conditions. This review evaluates research futility in EGb761 trials for dementia, analyzing efficacy and methodological challenges to inform future research directions. Data Sources: In this review, we investigate the efficacy and adverse reactions of Ginkgo biloba extract (EGb761) as a treatment for Alzheimer disease or vascular dementia. We searched the randomized controlled trials published between 2006 and 2023 on PubMed and ScienceDirect. Results: The 7 selected studies have shown that the degree of improvement in standard cognitive assessment scores [Mini-Mental State Examination (MMSE), short cognitive performance test (SKT), neuropsychiatric inventory (NPI)] was not significant enough for a substantial proportion of patients. Improvements of the SKT score with at least 3 points in the Alzheimer disease/vascular dementia groups were found only in 2 out of 7 studies, changes of less than 2 points in MMSE score were found in 2 of the studies, while an improvement of at least 4 points in NPI scores was reported in 4 out of 7 studies. We aim to understand why this extract has not reached the level of evidence to be included in guideline recommendation despite extensive research and what have we learned from systematic reviews performed since 2010? Studies included in this review have shown some improvement in outcome scores with EGb761 treatment compared with placebo, but these improvements did not reach the threshold for clinically significant enhancement in MMSE/SKT/NPI scores. Limitations such as small sample sizes, minimal score changes, predominantly placebo comparisons, and short follow-up durations make it challenging to determine the usefulness of EGb761 in dementia treatment. The changes observed and methodological constraints underscore the uncertainty surrounding the efficacy of EGb761. Conclusion: The findings do not consistently demonstrate the clinical utility of EGb761, and improved scores on cognitive and neuropsychiatric assessments may not necessarily translate into meaningful clinical outcomes for patients with dementia. Starting from the question “What have we learned in the past 18 years?”, the answer would be: not much. Consequently, the question raised is: how long should we go on with the same conclusion, continuing to spend time and financial resources to replicate these results? Research strategies should be refined to optimize decision making and advance evidence-based care for neurocognitive disorders.

Molecular mechanisms of sulforaphane in Alzheimer’s disease: insights from an in-silico study

This study was to identify the molecular pathways that may explain sulforaphane’s Alzheimer’s disease (AD) benefits using multiple advanced in silico approaches. We found that sulforaphane regulates 45 targets, including TNF, INS, and BCL2. Therefore, it may help treat AD by reducing neuroinflammation, insulin resistance, and apoptosis. The important relationships were co-expression and pathways. 45 targets were linked to the midbrain, metabolite interconversion enzymes, 14q23.3 and 1q31.1 chromosomes, and modified residues. “Amyloid precursor protein catabolic process”, “regulation of apoptotic signaling pathway”, and “positive regulation of nitric oxide biosynthetic process” were the main pathways, while NFKB1, SP1, RELA, hsa-miR-17-5p, hsa-miR-16-5p, and hsa-miR-26b-5p were transcription factors and miRNAs implicated in sulforaphane In AD treatment, miRNA sponges, dexibuprofen, and sulforaphane may be effective. Furthermore, its unique physicochemical, pharmacokinetic, and biological qualities make sulforaphane an effective AD treatment, including efficient gastrointestinal absorption, drug-like properties, absence of CYP450 enzyme inhibition, not being a substrate for P-glycoprotein, ability to cross the blood–brain barrier, glutathione S-transferase substrate, immunostimulant effects, and antagonistic neurotransmitter effects. Sulforaphane is a promising compound for AD management. Further work is needed to elucidate its therapeutic effects based on our findings, including genes, miRNAs, molecular pathways, and transcription factors.

Effects of JAL-TA9 on cognitive deficits in Alzheimer's disease model mouse

Many studies have been conducted to find an effective drug for Alzheimer's disease (AD) treatment. However, no effective drug applicable for clinical use has been developed. Recently, the FDA approved Lecanemab, an antibody drug that acts as an aggregation inhibitor against Amyloid-beta (Aβ), for AD treatment. However, there are still no fundamental drugs for AD. In this study, we present a strategy for AD treatment that removes Aβ by cleavage reaction using one of the Catalytides, JAL-TA9 (YKGSGFRMI). A single dose of JAL-TA9 administered into the CA1 region of the hippocampus and the intraventricular space improved the deficits in short-term memory of APP-knock-in mice. It also improved the memory of Aβ25-35-induced model mice, as evaluated by the Y-maze and objective recognition tests. These data strongly suggest that JAL-TA9 could be effective in treating AD. However, these administration methods are difficult to apply clinically due to their high invasiveness. Thus, we tested the improvement effects of dementia by administering JAL-TA9 nasally. It is very interesting and exciting that the dementia of Aβ25-35 induced AD model mice was improved by four applications once every three days. These results strongly suggest that JAL-TA9 is the best candidate for AD treatment because it is effective even in the late stage of AD.

From Europe to the World: EMA's Leadership in Alzheimer Disease Treatment

From Europe to the World: EMA's Leadership in Alzheimer Disease Treatment

The next chapter in Alzheimer's disease treatment: Antiamyloid monoclonal antibodies.

The next chapter in Alzheimer's disease treatment: Antiamyloid monoclonal antibodies.

Possibility of short synthetic peptides with activities of suppressing amyloid β aggregation and resolving its aggregated form as therapeutic drugs for Alzheimer's disease

Lecanemab is a new anti-amyloid antibody being developed as a treatment for Alzheimer's disease. It is expected to delay the progression of the disease by reducing the accumulation of amyloid beta (Aβ) in the brain. However, no drug has been developed that can completely eliminate Aβ and improve symptoms. A representative Catalytide, JAL-TA9 (YKGSGFRMI), cleaves Aβ42 and improves symptoms in an Alzheimer's disease mouse model, suggesting that JAL-TA9 is a promising candidate for treating Alzheimer's disease by effectively eliminating Aβ. The catalytic center of JAL-TA9 is GSGFR. To identify better Catalytides for Alzheimer's treatment, we analyzed the structure-activity relationship of 21 point-mutated GSGFR derivatives. In this process, we discovered two peptides, GSGFK and GSGNR, that not only inhibit Aβ25-35 aggregation but also dissolve aggregated Aβ25-35. Intracerebroventricular administration of GSGFK protected mice against Aβ25-35-induced short-term memory deficits and promoted microglial phagocytic activity. Like Lecanemab, GSGFK targets Aβ, but it has advantages such as safety, administration method, and cost. In this talk, we will discuss the potential of GSGFK as a therapeutic candidate for Alzheimer's disease.

A promising drug repurposing approach for Alzheimer's treatment: Givinostat improves cognitive behavior and pathological features in APP/PS1 mice.

Alzheimer’s disease (AD) is the most common neurodegenerative disease, characterized by memory loss, speech and motor defects, personality changes, and psychological disorders. The exact cause of AD remains unclear. Current treatments focus on maintaining neurotransmitter levels or targeting β-amyloid (Aβ) protein, but these only alleviate symptoms and do not reverse the disease. Developing new drugs is time-consuming, costly, and has a high failure rate. Utilizing multi-omics for drug repositioning has emerged as a new strategy. Based on transcriptomic perturbation data of over 40,000 drugs in human cells from the LINCS-L1000 database, our study employed the Jaccard index and hypergeometric distribution test for reverse transcriptional feature matching analysis, identifying Givinostat as a potential treatment for AD. Our research found that Givinostat improved cognitive behavior and brain pathology in models and enhanced hippocampal synaptic plasticity. Transcriptome sequencing revealed increased expression of mitochondrial respiratory chain complex proteins in the brains of APP/PS1 mice after Givinostat treatment. Functionally, Givinostat restored mitochondrial membrane potential, reduced reactive oxygen species, and increased ATP content in Aβ-induced HT22 cells. Additionally, it improved mitochondrial morphology and quantity in the hippocampus of APP/PS1 mice and enhanced brain glucose metabolic activity. These effects are linked to Givinostat promoting mitochondrial biogenesis and improving mitochondrial function. In summary, Givinostat offers a promising new strategy for AD treatment by targeting mitochondrial dysfunction.

Boosting Acetylcholine Signaling by Cannabidiol in a Murine Model of Alzheimer's Disease.

Alzheimer's disease (AD) is a challenging medical issue that requires efficacious treatment options to improve long-term quality of life. Cannabidiol (CBD) is a cannabis-derived phytocannabinoid with potential health benefits, including reports from our laboratory and others showing a therapeutic role in the pre-clinical treatment of AD; however, the mechanisms whereby CBD affects AD progression remain undefined. Innate lymphoid cells (ILCs) are recently discovered immune cells that initiate and orchestrate inflammatory responses. ILC2, a sub-class of ILCs, is proposed to have a role in cognitive function via unknown mechanisms. In this present study, we explored whether CBD ameliorates AD symptoms via the enhancement of acetylcholine (ACh), a cholinergic neurotransmitter involved in cognition that may regulate ILC2. 5xFAD mice were chronically treated by inhalation of a formulation of broad-spectrum CBD for seven months. ACh production, ILC2s profile, brain histopathology, and long-term behavior were assessed. Together, our studies showed that long-term inhalation of CBD improved cognitive function and reduced senile plaques in a murine AD model, effects that were associated with enhanced ACh production and altered ILC2s distribution within the CNS. These findings indicate that inhaled CBD could offer a cost-effective, non-invasive, and effective treatment for managing AD. The beneficial effects of CBD inhalation may be linked to increased ACh production and an altered distribution of ILC2s, highlighting the need for further research in this area.

Anti-Alzheimer's Disease Target and Beneficial Effect in Formononetin

Introduction: Alzheimer's Disease (AD), a common neurodegenerative relevance of dementia, is spreading in the world. Hitherto, the pharmacological treatment for AD is prescribed limitedly in clinical application. Recently, it has been found that naturally occurring extracts possess promising anti-neurodegenerative properties, including AD. Method: Our previous study indicated that formononetin (FMN) exerts the anti-AD benefits based on bioinformatics analysis. However, the experimental validation for bioinformatics findings has not been conducted. In this study, we primarily applied the molecule docking analysis to ascertain the pharmacological targets, including cytochrome P450 19A1 (CYP19A1). Transgenic AD mice were used to validate the bioinformatics findings in vivo experimentally. Molecular docking data showed that FMN acted directly on CYP19A1 target protein with effective binding sites and potent combining affinity/energy. Results: Meanwhile, FMN intervention contributed to an increased trend of body weight in transgenic AD mice reduced hippocampal expression of Aβ1-42, and elevated content of CYP19A1. Additionally, FMN intervention showed reduced terminal deoxynucleotidyl Transferase dUTP Nick-End Labeling (TUNEL) expression and increased CYP19A1 and Ki67 expressions in hippocampal sections of transgenic AD mice. Conclusion: Collectively, FMN may be used for the prevention of AD, and the pharmacological activities are possibly related to reducing Aβ1-42, and TUNEL expressions to increase Ki67 and CYP19A1 activities.

Endothelial Dysfunctions in Blood-Brain Barrier Breakdown in Alzheimer's Disease: From Mechanisms to Potential Therapies.

Recent research has shown the presence of blood-brain barrier (BBB) breakdown in Alzheimer's disease (AD). BBB is a dynamic interface consisting of a continuous monolayer of brain endothelial cells (BECs) enveloped by pericytes and astrocytes. The restricted permeability of BBB strictly controls the exchange of substances between blood and brain parenchyma, which is crucial for brain homeostasis by excluding blood-derived detrimental factors and pumping out brain-derived toxic molecules. BBB breakdown in AD is featured as a series of BEC pathologies such as increased paracellular permeability, abnormal levels and functions of transporters, and inflammatory or oxidative profile, which may disturb the substance transportation across BBB, thereafter induce CNS disorders such as hypometabolism, Aβ accumulation, and neuroinflammation, eventually aggravate cognitive decline. Therefore, it seems important to protect BEC properties for BBB maintenance and neuroprotection. In this review, we thoroughly summarized the pathological alterations of BEC properties reported in AD patients and numerous AD models, including paracellular permeability, influx and efflux transporters, and inflammatory and oxidative profiles, and probably associated underlying mechanisms. Then we reviewed current therapeutic agents that are effective in ameliorating a series of BEC pathologies, and ultimately protecting BBB integrity and cognitive functions. Regarding the current drug development for AD proceeds extremely hard, this review aims to discuss the therapeutic potentials of targeting BEC pathologies and BBB maintenance for AD treatment, therefore expecting to shed a light on the future AD drug development by targeting BEC pathologies and BBB protection.

REAL AD-Validation of a realistic screening approach for early Alzheimer's disease.

Early diagnosis is crucial to treatment success. This is especially relevant for Alzheimer's disease (AD), with its protracted preclinical phase. Most health care systems do not have the resources to conduct large-scale AD screenings in middle-aged individuals in need of novel AD treatment options and early, accurate diagnosis. Recent developments in blood-based biomarkers and remote cognitive testing offer novel, cost-effective, and scalable methods to detect cognitive and biomarker changes that may indicate early AD. In research cohorts, promising results have been reported, but these modalities have not been validated in population-based settings. The validation of a realistic screening approach for early Alzheimer's disease (REAL AD) study aims to validate the diagnostic and prognostic performance of the combined use of blood-based biomarkers and remote cognitive testing as a screening approach for early AD employing an existing health care infrastructure (the Swedish Västra Götaland Region Primary Healthcare). REAL AD aims to provide a concrete, individualized diagnostic framework, which could significantly improve AD prognosis. HIGHLIGHTS: In Sweden, most Alzheimer's disease (AD) diagnoses are made in primary care, where access to AD biomarkers is almost non-existent. Most health care systems have limited resources for the screening of middle-aged adults for early evidence of AD pathology. Blood-based biomarkers and remote cognitive testing offer novel, cost-effective, and scalable methods for detecting cognitive and biomarker changes that may indicate early AD. The REAL AD study aims to validate the diagnostic and prognostic performance of blood-based biomarkers and remote cognitive testing as a screening approach for early AD in an existing primary health care infrastructure in the Västra Götaland Region in Sweden. Studies such as REAL AD will play a vital role in helping to move the field toward concrete implementation of biomarkers in AD diagnostic workup at all care levels, eventually providing more comprehensive treatments options for the large and growing AD population, and for those at risk.

Cutting-Edge Strategies for Overcoming Therapeutic Barriers in Alzheimer's Disease.

Alzheimer's disease (AD) remains one of the hardest neurodegenerative diseases to treat due to its enduring cognitive deterioration and memory loss. Despite extensive research, few viable treatment approaches have been found; these are mostly due to several barriers, such as the disease's complex biology, limited pharmaceutical efficacy, and the BBB. This presentation discusses current strategies for addressing these therapeutic barriers to enhance AD treatment. Innovative drug delivery methods including liposomes, exosomes, and nanoparticles may be able to pass the blood-brain barrier and allow medicine to enter specific brain regions. These innovative strategies of medicine distribution reduce systemic side effects by improving absorption. Moreover, the development of disease-modifying treatments that target tau protein tangles, amyloid-beta plaques, and neuroinflammation offers the chance to influence the course of the illness rather than only treat its symptoms. Furthermore, gene therapy and CRISPR-Cas9 technologies have surfaced as potentially groundbreaking methods for addressing the underlying genetic defects associated with AD. Furthermore, novel approaches to patient care may involve the utilization of existing medications having neuroprotective properties, such as those for diabetes and cardiovascular conditions. Furthermore, biomarker research and personalized medicine have made individualized therapy approaches possible, ensuring that patients receive the best care possible based on their unique genetic and molecular profiles.

Modeling the Population Equity of Alzheimer Disease Treatments in the US

The arrival of new medications for Alzheimer disease (AD) has prompted efforts to measure their value using conventional cost-effectiveness analyses; however, these analyses focus on how much health improvement new medications generate per dollar spent. As AD disproportionately affects older adults, women, racial and ethnic minority individuals, and individuals with lower socioeconomic and educational levels, it is critical to also examine the health equity outcomes of treatment. To estimate the health equity impact of a hypothetical disease-modifying treatment for early AD in the US and to examine targeted policies to mitigate health care disparities. This economic evaluation, which used a distributional cost-effectiveness analysis, was conducted from June 16, 2022, to January 11, 2024. The study included subgroups defined by race and ethnicity and by social vulnerability quintiles in the US. A hypothetical disease-modifying treatment compared with best supportive care. The main outcomes were population-level quality-adjusted life-years (QALYs), lifetime costs, and net health benefits. The social welfare impact and change in health inequality were estimated using the Atkinson index. The distributional cost-effectiveness analysis simulated 316 037 100 individuals from the US population, including 25 subgroups defined by 5 categories of race and ethnicity and population quintiles of social vulnerability, with the fifth quintile representing the most socially vulnerable group. At an opportunity cost benchmark of $150 000 per QALY, treatment was associated with improved population health, adding 28 197 QALYs per year to the US population. Accounting for health inequality preferences (using an aversion level of 11, based on an Atkinson inequality aversion parameter that can range from 0 to infinity, with higher values assigning greater weight to health gains that accrue to the population with the lowest lifetime quality-adjusted life expectancy), treatment was associated with a 0.009% reduction in existing population health inequalities annually. Scenario analyses examining earlier and expanded treatment access suggested a population health improvement of up to 221 358 QALYs. The findings of this economic evaluation suggest that treatment for AD could improve population health and health equity. Policies to enable earlier diagnosis and treatment initiation, as well as expanded access to treatment, may further improve treatment and health equity impacts.

Assessing the Role of the Generative Pretrained Transformer (GPT) in Alzheimer's Disease Management: Comparative Study of Neurologist- and Artificial Intelligence-Generated Responses.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder posing challenges to patients, caregivers, and society. Accessible and accurate information is crucial for effective AD management. This study aimed to evaluate the accuracy, comprehensibility, clarity, and usefulness of the Generative Pretrained Transformer's (GPT) answers concerning the management and caregiving of patients with AD. In total, 14 questions related to the prevention, treatment, and care of AD were identified and posed to GPT-3.5 and GPT-4 in Chinese and English, respectively, and 4 respondent neurologists were asked to answer them. We generated 8 sets of responses (total 112) and randomly coded them in answer sheets. Next, 5 evaluator neurologists and 5 family members of patients were asked to rate the 112 responses using separate 5-point Likert scales. We evaluated the quality of the responses using a set of 8 questions rated on a 5-point Likert scale. To gauge comprehensibility and participant satisfaction, we included 3 questions dedicated to each aspect within the same set of 8 questions. As of April 10, 2023, the 5 evaluator neurologists and 5 family members of patients with AD rated the 112 responses: GPT-3.5: n=28, 25%, responses; GPT-4: n=28, 25%, responses; respondent neurologists: 56 (50%) responses. The top 5 (4.5%) responses rated by evaluator neurologists had 4 (80%) GPT (GPT-3.5+GPT-4) responses and 1 (20%) respondent neurologist's response. For the top 5 (4.5%) responses rated by patients' family members, all but the third response were GPT responses. Based on the evaluation by neurologists, the neurologist-generated responses achieved a mean score of 3.9 (SD 0.7), while the GPT-generated responses scored significantly higher (mean 4.4, SD 0.6; P<.001). Language and model analyses revealed no significant differences in response quality between the GPT-3.5 and GPT-4 models (GPT-3.5: mean 4.3, SD 0.7; GPT-4: mean 4.4, SD 0.5; P=.51). However, English responses outperformed Chinese responses in terms of comprehensibility (Chinese responses: mean 4.1, SD 0.7; English responses: mean 4.6, SD 0.5; P=.005) and participant satisfaction (Chinese responses: mean 4.2, SD 0.8; English responses: mean 4.5, SD 0.5; P=.04). According to the evaluator neurologists' review, Chinese responses had a mean score of 4.4 (SD 0.6), whereas English responses had a mean score of 4.5 (SD 0.5; P=.002). As for the family members of patients with AD, no significant differences were observed between GPT and neurologists, GPT-3.5 and GPT-4, or Chinese and English responses. GPT can provide patient education materials on AD for patients, their families and caregivers, nurses, and neurologists. This capability can contribute to the effective health care management of patients with AD, leading to enhanced patient outcomes.

Tetradecyl 2,3-Dihydroxybenzoate Improves Cognitive Function in AD Mice by Modulating Autophagy and Inflammation Through IPA and Hsc70 Targeting.

Drug development for Alzheimer's disease (AD) treatment is challenging due to its complex pathogenesis. Tetradecyl 2,3-dihydroxybenzoate (ABG-001), a leading compound identified in our prior research, has shown promising NGF-mimicking activity and anti-aging properties. In the present study, both high-fat diet (HFD)-induced AD mice and naturally aging AD mice were used to evaluate anti-AD effects. Meanwhile, RNA-sequences, Western blotting, immunofluorescence staining, enzyme-linked immunosorbent assay (ELISA), cellular thermal shift assay (CETSA), drug affinity-responsive target stability (DARTS) assay, construction of expression plasmid and protein purification, surface plasmon resonance (SPR) analysis, and 16S rRNA sequence analysis were used to identify the target protein of ABG-001 and clarify the mechanism of action for this molecule. ABG-001 effectively mitigates the memory dysfunction in both HFD-induced AD mice and naturally aging AD mice. The therapeutic effect of ABG-001 is attributed to its ability to promote neurogenesis, activate chaperone-mediated autophagy (CMA), and reduce neuronal inflammation. Additionally, ABG-001 positively influenced the gut microbiota, enhancing the production of indole-3-propionic acid (IPA), which is capable of crossing the blood-brain barrier (BBB) and contributes to neuronal regeneration. Furthermore, our research revealed that IPA, linked to the anti-AD properties of ABG-001, targets the heat shock cognate 70 kDa protein (Hsc70) and regulates the Hsc70/PKM2/HK2/LC3 and FOXO3a/SIRT1 signaling pathways. ABG-001 improves the memory dysfunction of AD mice by modulating autophagy and inflammation through IPA and Hsc70 targeting. These findings offer a novel approach for treating neurodegenerative diseases, focusing on the modification of the gut microbiota and metabolites coupled with anti-aging strategies.

A modified deep learning method for Alzheimer’s disease detection based on the facial submicroscopic features in mice

Alzheimer’s disease (AD) is a chronic disease among people aged 65 and older. As the aging population continues to grow at a rapid pace, AD has emerged as a pressing public health issue globally. Early detection of the disease is important, because increasing evidence has illustrated that early diagnosis holds the key to effective treatment of AD. In this work, we developed and refined a multi-layer cyclic Residual convolutional neural network model, specifically tailored to identify AD-related submicroscopic characteristics in the facial images of mice. Our experiments involved classifying the mice into two distinct groups: a normal control group and an AD group. Compared with the other deep learning models, the proposed model achieved a better detection performance in the dataset of the mouse experiment. The accuracy, sensitivity, specificity and precision for AD identification with our proposed model were as high as 99.78%, 100%, 99.65% and 99.44%, respectively. Moreover, the heat maps of AD correlation in the facial images of the mice were acquired with the class activation mapping algorithm. It was proven that the facial images contained AD-related submicroscopic features. Consequently, through our mouse experiments, we validated the feasibility and accuracy of utilizing a facial image-based deep learning model for AD identification. Therefore, the present study suggests the potential of using facial images for AD detection in humans through deep learning-based methods.

Autophagy-lysosomal pathway impairment and cathepsin dysregulation in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by neuronal loss, attributed to amyloid-beta (Aβ) aggregation and accumulation. The autophagy-lysosomal pathway, including cathepsins B and D, is crucial for protein degradation and clearance, but it is impaired in some diseases. This review summarizes current knowledge on the dysregulation of this pathway in AD. Accumulating evidence suggests that Aβ overload impairs autophagy-lysosomal function and cathepsin activity, exacerbating Aβ accumulation and neurodegeneration. However, the precise mechanisms underlying these interactions remain elusive. Despite these challenges, targeting the lysosomal pathway emerges as a promising therapeutic strategy, and a comprehensive understanding of the autophagy-lysosomal system is essential to develop effective interventions for AD.

Spectral graph convolutional neural network for Alzheimer's disease diagnosis and multi-disease categorization from functional brain changes in magnetic resonance images.

Alzheimer's disease (AD) is a progressive neurological disorder characterized by the gradual deterioration of cognitive functions, leading to dementia and significantly impacting the quality of life for millions of people worldwide. Early and accurate diagnosis is crucial for the effective management and treatment of this debilitating condition. This study introduces a novel framework based on Spectral Graph Convolutional Neural Networks (SGCNN) for diagnosing AD and categorizing multiple diseases through the analysis of functional changes in brain structures captured via magnetic resonance imaging (MRI). To assess the effectiveness of our approach, we systematically analyze structural modifications to the SGCNN model through comprehensive ablation studies. The performance of various Convolutional Neural Networks (CNNs) is also evaluated, including SGCNN variants, Base CNN, Lean CNN, and Deep CNN. We begin with the original SGCNN model, which serves as our baseline and achieves a commendable classification accuracy of 93%. In our investigation, we perform two distinct ablation studies on the SGCNN model to examine how specific structural changes impact its performance. The results reveal that Ablation Model 1 significantly enhances accuracy, achieving an impressive 95%, while Ablation Model 2 maintains the baseline accuracy of 93%. Additionally, the Base CNN model demonstrates strong performance with a classification accuracy of 93%, whereas both the Lean CNN and Deep CNN models achieve 94% accuracy, indicating their competitive capabilities. To validate the models' effectiveness, we utilize multiple evaluation metrics, including accuracy, precision, recall, and F1-score, ensuring a thorough assessment of their performance. Our findings underscore that Ablation Model 1 (SGCNN Model 1) delivers the highest predictive accuracy among the tested models, highlighting its potential as a robust approach for Alzheimer's image classification. Ultimately, this research aims to facilitate early diagnosis and treatment of AD, contributing to improved patient outcomes and advancing the field of neurodegenerative disease diagnosis.