Current concepts in Alzheimer's disease: a multidisciplinary review

Alzheimer's disease: a comprehensive review of epidemiology, risk factors, symptoms diagnosis, management, caregiving, advanced treatments and associated challenges

Background

Alzheimer's disease (AD) is a chronic, progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired reasoning. It is the leading cause of dementia in older adults, marked by the pathological accumulation of amyloid-beta plaques and neurofibrillary tangles. These pathological changes lead to widespread neuronal damage, significantly impacting daily functioning and quality of life.

Objective

This comprehensive review aims to explore various aspects of Alzheimer's disease, including its epidemiology, risk factors, clinical presentation, diagnostic advancements, management strategies, caregiving challenges, and emerging therapeutic interventions.

Methods

A systematic literature review was conducted across multiple electronic databases, including PubMed, MEDLINE, Cochrane Library, and Scopus, from their inception to May 2024. The search strategy incorporated a combination of keywords and Medical Subject Headings (MeSH) terms such as "Alzheimer's disease," "epidemiology," "risk factors," "symptoms," "diagnosis," "management," "caregiving," "treatment," and "novel therapies." Boolean operators (AND, OR) were used to refine the search, ensuring a comprehensive analysis of the existing literature on Alzheimer's disease.

Results

AD is significantly influenced by genetic predispositions, such as the apolipoprotein E (APOE) ε4 allele, along with modifiable environmental factors like diet, physical activity, and cognitive engagement. Diagnostic approaches have evolved with advances in neuroimaging techniques (MRI, PET), and biomarker analysis, allowing for earlier detection and intervention. The National Institute on Aging and the Alzheimer's Association have updated diagnostic criteria to include biomarker data, enhancing early diagnosis.

Conclusion

The management of AD includes pharmacological treatments, such as cholinesterase inhibitors and NMDA receptor antagonists, which provide symptomatic relief but do not slow disease progression. Emerging therapies, including amyloid-beta and tau-targeting treatments, gene therapy, and immunotherapy, offer potential for disease modification. The critical role of caregivers is underscored, as they face considerable emotional, physical, and financial burdens. Support programs, communication strategies, and educational interventions are essential for improving caregiving outcomes. While significant advancements have been made in understanding and managing AD, ongoing research is necessary to identify new therapeutic targets and enhance diagnostic and treatment strategies. A holistic approach, integrating clinical, genetic, and environmental factors, is essential for addressing the multifaceted challenges of Alzheimer's disease and improving outcomes for both patients and caregivers.

A New Brain Network Construction Paradigm for Brain Disorder via Diffusion-Based Graph Contrastive Learning

Brain network analysis plays an increasingly important role in studying brain function and the exploring of disease mechanisms. However, existing brain network construction tools have some limitations, including dependency on empirical users, weak consistency in repeated experiments and time-consuming processes. In this work, a diffusion-based brain network pipeline, DGCL is designed for end-to-end construction of brain networks. Initially, the brain region-aware module (BRAM) precisely determines the spatial locations of brain regions by the diffusion process, avoiding subjective parameter selection. Subsequently, DGCL employs graph contrastive learning to optimize brain connections by eliminating individual differences in redundant connections unrelated to diseases, thereby enhancing the consistency of brain networks within the same group. Finally, the node-graph contrastive loss and classification loss jointly constrain the learning process of the model to obtain the reconstructed brain network, which is then used to analyze important brain connections. Validation on two datasets, ADNI and ABIDE, demonstrates that DGCL surpasses traditional methods and other deep learning models in predicting disease development stages. Significantly, the proposed model improves the efficiency and generalization of brain network construction. In summary, the proposed DGCL can be served as a universal brain network construction scheme, which can effectively identify important brain connections through generative paradigms and has the potential to provide disease interpretability support for neuroscience research.

Algorithmic Spaced Retrieval Enhances Long-Term Memory in Alzheimer Disease: Case-Control Pilot Study

BACKGROUND

Spaced retrieval is a learning technique that involves engaging in repeated memory testing after increasingly lengthy intervals of time. Spaced retrieval has been shown to improve long-term memory in Alzheimer disease (AD), but it has historically been difficult to implement in the everyday lives of individuals with AD.

OBJECTIVE

This research aims to determine, in people with mild cognitive impairment (MCI) due to AD, the efficacy and feasibility of a mobile app that combines spaced retrieval with a machine learning algorithm to enhance memory retention. Specifically, the app prompts users to answer questions during brief daily sessions, and a machine learning algorithm tracks each user's rate of forgetting to determine the optimal spacing schedule to prevent anticipated forgetting.

METHODS

In this pilot study, 61 participants (young adults: n=21, 34%; healthy older adults: n=20, 33%; people with MCI due to AD: n=20, 33%) used the app for 4 weeks to learn new facts and relearn forgotten name-face associations. Participation during the 4-week period was characterized by using the app once per day to answer 15 questions about the facts and names. After the 4-week learning phase, participants completed 2 recognition memory tests approximately 1 week apart, which tested memory for information they had studied using the app as well as information they had not studied.

RESULTS

After using the mobile app for 1 month, every person with MCI due to AD demonstrated improvements in memory for new facts that they had studied via the app compared to baseline (P<.001). All but one person with MCI due to AD (19/20, 95%) showed improvements of more than 10 percentage points, comparable to the improvements shown by young adults and healthy older adults. Memory for name-face associations was similarly improved for all participant groups after using the app but to a lesser degree. Furthermore, for both new facts and name-face associations, we found no memory decay for any participant group after they took a break of approximately 1 week from using the app at the end of the study. Regarding usability, of the 20 people with MCI due to AD, 16 (80%) self-adhered to the app's automated practice schedule, and half of them (n=10, 50%) expressed an interest in continuing to use it.

CONCLUSIONS

These results demonstrate early evidence that spaced retrieval mobile apps are both feasible for people with early-stage AD to use in their everyday lives and effective for supporting memory retention of recently learned facts and name-face associations.

Predicting conversion from mild cognitive impairment to Alzheimer's disease: a multimodal approach

Successively predicting whether mild cognitive impairment patients will progress to Alzheimer's disease is of significant clinical relevance. This ability may provide information that can be leveraged by emerging intervention approaches and thus mitigate some of the negative effects of the disease. Neuroimaging biomarkers have gained some attention in recent years and may be useful in predicting the conversion of mild cognitive impairment to Alzheimer's disease. We implemented a novel multi-modal approach that allowed us to evaluate the potential of different imaging modalities, both alone and in different degrees of combinations, in predicting the conversion to Alzheimer's disease of mild cognitive impairment patients. We applied this approach to the imaging data from the Alzheimer's Disease Neuroimaging Initiative that is a multi-modal imaging dataset comprised of MRI, Fluorodeoxyglucose PET, Florbetapir PET and diffusion tensor imaging. We included a total of 480 mild cognitive impairment patients that were split into two groups: converted and stable. Imaging data were segmented into atlas-based regions of interest, from which relevant features were extracted for the different imaging modalities and used to construct machine-learning models to classify mild cognitive impairment patients into converted or stable, using each of the different imaging modalities independently. The models were then combined, using a simple weight fusion ensemble strategy, to evaluate the complementarity of different imaging modalities and their contribution to the prediction accuracy of the models. The single-modality findings revealed that the model, utilizing features extracted from Florbetapir PET, demonstrated the highest performance with a balanced accuracy of 83.51%. Concerning multi-modality models, not all combinations enhanced mild cognitive impairment conversion prediction. Notably, the combination of MRI with Fluorodeoxyglucose PET emerged as the most promising, exhibiting an overall improvement in predictive capabilities, achieving a balanced accuracy of 78.43%. This indicates synergy and complementarity between the two imaging modalities in predicting mild cognitive impairment conversion. These findings suggest that β-amyloid accumulation provides robust predictive capabilities, while the combination of multiple imaging modalities has the potential to surpass certain single-modality approaches. Exploring modality-specific biomarkers, we identified the brainstem as a sensitive biomarker for both MRI and Fluorodeoxyglucose PET modalities, implicating its involvement in early Alzheimer's pathology. Notably, the corpus callosum and adjacent cortical regions emerged as potential biomarkers, warranting further study into their role in the early stages of Alzheimer's disease.

Vanillin derivatives as antiamnesic agents in scopolamine-induced memory impairment in mice

Amnesia is a major health problem prevalent in almost every part of the world specifically in old age peoples. Vanillin analogues have played an important role in the field medicines. Some of them have been documented to be promising inhibitors of cholinesterases and could therefore, be used as antidepressant, anti-Alzheimer and as neuroprotective drugs. In this connection, the present study was designed to synthesize new vanillin analogues (SB-1 to SB-6) of varied biological potentials. The synthesized compounds were investigated as inhibitors against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes and as scavengers of DPPH and ABTS free radicals followed by behavioural antiamnesic evaluation in mice. The compounds; SB-1, SB-3, SB-4 and SB-6 more potently inhibited AChE with IC50 values of 0.078, 0.157, 0.108, and 0.014 μM respectively. The BChE was more potently inhibited by SB-3 with IC50 of 0.057 μM. Moreover, all of the tested compounds exhibited strong antioxidant potentials with promising results of SB-3 against DPPH with IC50 of 0.305 μM, while SB-5 was most active against ABTS with IC50 of 0.190 μM. The in-vivo studies revealed the improvement in memory deficit caused by scopolamine. Y-Maze and new object recognition test showed a considerable decline in cognitive dysfunctions. In Y-Maze test the spontaneous alteration of 69.44 ± 1% and 84.88 ± 1.35% for SB-1 and 68.92 ± 1% and 80.89 ± 1% for SB-3 at both test doses were recorded while during the novel object recognition test the Discrimination Index percentage of SB-1 was more pronounced as compared to standard drug. All compounds were found to be potent inhibitors of AChE, BChE, DPPH, and ABTS in vitro however, SB-1 and SB-3 were comparatively more potent. SB-1 was also more active in reclamation of memory deficit caused by scopolamine. SB-1 and SB-3 may be considered as excellent drug candidates for treating amnesia subjected to toxicological evaluations in other animal models.

Quantitative-HPLC-DAD polyphenols analysis, anxiolytic and cognition enhancing potentials of Sorbaria tomentosa Lindl. Rehder

ETHNOPHARMACOLOGICAL RELEVANCE

Medicinal plants of the family Rosaceae have a long history of traditional uses in the management of neurological disorders. Sorbaria tomentosa Lindl. Rehder is composed of antioxidant and neuroprotective polyphenolics.

AIMS OF THE STUDY

The current study was designed to explore phenolics profile via high performance liquid chromatography-photodiode array detector (HPLC-DAD) and validated the neuroprotective and anxiolytic potentials of S. tomentosa by applying in vitro and in vivo approaches.

MATERIALS AND METHODS

The plant crude methanolic extract (St.Crm) and fractions were subjected to HPLC-DAD analysis for qualitative and quantitative assessment of phytochemicals. Samples were screened for in vitro free radicals scavenging assays by using 2,2-diphenylpicrylhydrazyl (DPPH), 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) along with acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes inhibition assays. For cognitive and anxiolytic studies, mice were subjected to open field, elevated plus maze (EPM), light-dark model, Y-maze, shallow water maze (SWM), and novel object recognition (NOR) tests.

RESULTS

HPLC-DAD analysis revealed the presence of high concentrations of phenolic compounds. For instance, in St.Cr, 21 phenolics were quantified, among which apigenin-7-glucoside (291.6 mg/g), quercetin (122.1 mg/g), quercetin-3-feruloylsophoroside-7-glucoside (52.6 mg/g), quercetin-7-glucoside (51.8 mg/g), ellagic acid (42.7 mg/g), luteolin (45.0 mg/g), kaempferol (40.5 mg/g), 5-feruloylquinic acid (43.7 mg/g) were present in higher concentrations. Likewise, in ethyl acetate fraction (St.Et.Ac), 21 phenolics were identified as 3,5-di-caffeoylquinic acid (177.4 mg/g) and 5-hydroxybenzoylquinic acid (46.9 mg/g) were most abundant phytochemicals. Highly valuable phenolics were also identified in other fractions including butanol (St.Bt), chloroform (St.Chf), and n-hexane (St.Hex). The various fractions exhibited concentration dependent inhibition of free radicals in DPPH and ABTS assays. Potent AChE inhibitory potentials were revealed by the test samples with St.Chf, St.Bt and St.EtAc being the most active having an IC50 of 298.1, 580.1, and 606.47 μg mL-1, respectively. Similarly, St.Chf, St.Bt, St.EtAc and St.Cr exhibited potent BChE inhibitory activity and was observed as 59.14, 54.73, 51.35 and 49.44%, respectively. A significant improvement in the exploratory behavior was observed in open field test and stress/anxiety was relieved effectively at 50-100 mg/kg. Likewise, EPM, light-dark and NOR tests revealed an anxiolytic and memory enhancing behaviors. These effects were further corroborated from the Y-maze and SWM transgenic studies that showed considerable improvement in cognition retention.

CONCLUSIONS

These findings concluded that S. tomentosa possessed potential anxiolytic and nootropic efficacies and may have therapeutic potential in neurodegenerative disorders.

Pyrimidine-morpholine hybrids as potent druggable therapeutics for Alzheimer's disease: Synthesis, biochemical and in silico analyses

The identification of effective and druggable cholinesterase inhibitors to treat progressive neurodegenerative Alzheimer's disorder remains a continuous drug discovery hunt. In this perspective, the present study investigates the design and discovery of pyrimidine-morpholine hybrids (5a-l) as potent cholinesterase inhibitors. Palladium-catalyzed Suzuki-Miyaura cross-coupling reaction was employed to introduce the structural diversity on the pyrimidine heterocyclic core. A range of commercially available boronic acids was successfully coupled showing a high functional group tolerance. In vitro cholinesterase inhibitory potential using Ellman's method revealed significantly strong potency. Compound 5h bearing a meta-tolyl substituent at 2-position of pyrimidine ring emerged as a lead candidate against AChE with an inhibitory potency of 0.43 ± 0.42 µM, ∼38-fold stronger value than neostigmine (IC50 = 16.3 ± 1.12 µM). Compound 5h also showed the lead inhibition against BuChE with an IC50 value of 2.5 ± 0.04 µM. The kinetics analysis of 5h revealed the non-competitive mode of inhibition against AChE whereas computational modelling results of potent leads depicted diverse contacts with the binding site amino acid residues. Molecular dynamics simulations revealed the stability of biomolecular system, while, ADME analysis demonstrated druglikeness behaviour of potent compounds. Overall, the investigated pyrimidine-morpholine scaffold presented a remarkable potential to be developed as efficacious anti-Alzheimer's drugs.

The efficacy of memory load on speech-based detection of Alzheimer's disease

Introduction

The study aims to test whether an increase in memory load could improve the efficacy in detection of Alzheimer's disease and prediction of the Mini-Mental State Examination (MMSE) score.

Methods

Speech from 45 mild-to-moderate Alzheimer's disease patients and 44 healthy older adults were collected using three speech tasks with varying memory loads. We investigated and compared speech characteristics of Alzheimer's disease across speech tasks to examine the effect of memory load on speech characteristics. Finally, we built Alzheimer's disease classification models and MMSE prediction models to assess the diagnostic value of speech tasks.

Results

The speech characteristics of Alzheimer's disease in pitch, loudness, and speech rate were observed and the high-memory-load task intensified such characteristics. The high-memory-load task outperformed in AD classification with an accuracy of 81.4% and MMSE prediction with a mean absolute error of 4.62.

Discussion

The high-memory-load recall task is an effective method for speech-based Alzheimer's disease detection.

Evaluating the feasibility of cognitive impairment detection in Alzheimer's disease screening using a computerized visual dynamic test

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disease without known cure. However, early medical treatment can help control its progression and postpone intellectual decay. Since AD is preceded by a period of cognitive deterioration, the effective assessment of cognitive capabilities is crucial to develop reliable screening procedures. For this purpose, cognitive tests are extensively used to evaluate cognitive areas such as language, attention, or memory.

METHODS

In this work, we analyzed the potential of a visual dynamics evaluation, the rapid serial visual presentation task (RSVP), for the detection of cognitive impairment in AD. We compared this evaluation with two of the most extended brief cognitive tests applied in Spain: the Clock-drawing test (CDT) and the Phototest. For this purpose, we assessed a group of patients (mild AD and mild cognitive impairment) and controls, and we evaluated the ability of the three tests for the discrimination of the two groups.

RESULTS

The preliminary results obtained suggest the RSVP performance is statistically higher for the controls than for the patients (p-value = 0.013). Furthermore, we obtained promising classification results for this test (mean accuracy of 0.91 with 95% confidence interval 0.72, 0.97).

CONCLUSIONS

Since the RSVP is a computerized, auto-scored, and potentially self-administered brief test, it could contribute to speeding-up cognitive impairment screening and to reducing the associated costs. Furthermore, this evaluation could be combined with other tests to augment the efficiency of cognitive impairment screening protocols and to potentially monitor patients under medical treatment.

Aβ8-20 Fragment as an Anti-Fibrillogenic and Neuroprotective Agent: Advancing toward Efficient Alzheimer's Disease Treatment

Alzheimer's disease (AD) is the most common cause of dementia, characterized by a spectrum of symptoms associated with memory loss and cognitive decline with deleterious consequences in everyday life. The lack of specific drugs for the treatment and/or prevention of this pathology makes AD an ever-increasing economic and social emergency. Oligomeric species of amyloid-beta (Aβ) are recognized as the primary cause responsible for synaptic dysfunction and neuronal degeneration, playing a crucial role in the onset of the pathology. Several studies have been focusing on the use of small molecules and peptides targeting oligomeric species to prevent Aβ aggregation and toxicity. Among them, peptide fragments derived from the primary sequence of Aβ have also been used to exploit any eventual recognition abilities toward the full-length Aβ parent peptide. Here, we test the Aβ_8-20 fragment which contains the self-recognizing Lys-Leu-Val-Phe-Phe sequence and lacks Arg 5 and Asp 7 and the main part of the C-terminus, key points involved in the aggregation pathway and stabilization of the fibrillary structure of Aβ. In particular, by combining chemical and biological techniques, we show that Aβ_8-20 does not undergo random coil to β sheet conformational transition, does not form amyloid fibrils by itself, and is not toxic for neuronal cells. Moreover, we demonstrate that Aβ_8-20 mainly interacts with the 4-11 region of Aβ_1-42 and inhibits the formation of toxic oligomeric species and Aβ fibrils. Finally, our data show that Aβ_8-20 protects neuron-like cells from Aβ_1-42 oligomer toxicity. We propose Aβ_8-20 as a promising drug candidate for the treatment of AD.

In vitro enzymatic evaluation of some pyrazolo[1,5-a]pyrimidine derivatives: Design, synthesis, antioxidant, anti-diabetic, anti-Alzheimer, and anti-arthritic activities with molecular modeling simulation

The strategy of utilizing nitrogen compounds in various biological applications has recently emerged as a powerful approach to exploring novel classes of therapeutics to face the challenge of diseases. A series of pyrazolo[1,5-a]pyrimidine-based compounds 3a-l and 5a-f were prepared by the direct cyclo-condensation reaction of 5-amino-1H-pyrazoles 1a, b with 2-(arylidene)malononitriles and 3-(dimethylamino)-1-aryl-prop-2-en-1-ones, respectively. The structures of the new pyrazolo[1,5-a]pyrimidine compounds were confirmed via spectroscopic techniques. The in vitro biological activities of all pyrazolo[1,5-a]pyrimidines 3a-l and 5a-f were evaluated by assaying total antioxidant capacity, iron-reducing power, the scavenging activity against 1-diphenyl-2-picryl-hydrazyl (DPPH) and 2, 2'-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radicals, anti-diabetic, anti-Alzheimer, and anti-arthritic biological activities. All compounds displayed good to potent bioactivity, and three compounds 3g, 3h, and 3l displayed the most active derivatives. Among these derivatives, compound 3l exhibited the highest antioxidant (total antioxidant capacity [TAC] = 83.09 mg gallic acid/g; iron-reducing power [IRP] = 47.93 µg/ml) and free radicals scavenging activities with (DPPH = 18.77 µg/ml; ABTS = 40.44%) compared with ascorbic acid (DPPH = 4.28 µg/ml; ABTS = 38.84%). Furthermore, compound 3l demonstrated the strongest inhibition of α-amylase with a percent inhibition of 72.91 ± 0.14 compared to acarbose = 67.92 ± 0.09%. Similarly, it displayed acetylcholinesterase inhibition of 62.80 ± 0.06%. However, compound 3i showed a significantly higher inhibition percentage for protein denaturation and proteinase at 20.66 ± 0.00 and 26.42 ± 0.06%, respectively. Additionally, some in silico ADMET properties were predicted and studied. Finally, molecular docking simulation was performed inside the active site of α-amylase and acetylcholinesterase to study their interactions.

Synthesis, characterization, and in vitro anti-cholinesterase screening of novel indole amines

The present study involved the targeted synthesis and characterization of novel indole amines with anti-acetylcholinesterase profiling. A series of proposed indole amines was virtually screened against human acetylcholinesterase. A few indole amines (23, 24, and 25) showing strong enzyme binding in the in silico studies were synthesized in the laboratory and characterized using spectroscopic (IR, UV, NMR, single crystal XRD) and spectrometric (EIMS, HR-EIMS) methods. The indole amine 23 was crystallized from EtOH and analyzed with single crystal XRD. These ligands interacted with the PAS site in the enzyme, and their binding may disrupt the activity. The in vitro acetylcholinesterase inhibition studies revealed that the IC50 values for indole amines 25 and 24 (4.28 and 4.66 μM, respectively) were comparable to that of galantamine (4.15 μM) and may be studied further as cost-effective acetylcholinesterase inhibitors.

Oxidative Stress and Natural Antioxidants: Back and Forth in the Neurological Mechanisms of Alzheimer's Disease

Alzheimer's disease (AD) is characterized by the progressive degeneration of neuronal cells. With the increase in aged population, there is a prevalence of irreversible neurodegenerative changes, causing a significant mental, social, and economic burden globally. The factors contributing to AD are multidimensional, highly complex, and not completely understood. However, it is widely known that aging, neuroinflammation, and excessive production of reactive oxygen species (ROS), along with other free radicals, substantially contribute to oxidative stress and cell death, which are inextricably linked. While oxidative stress is undeniably important in AD, limiting free radicals and ROS levels is an intriguing and potential strategy for deferring the process of neurodegeneration and alleviating associated symptoms. Therapeutic compounds from natural sources have recently become increasingly accepted and have been effectively studied for AD treatment. These phytocompounds are widely available and a multitude of holistic therapeutic efficiencies for treating AD owing to their antioxidant, anti-inflammatory, and biological activities. Some of these compounds also function by stimulating cholinergic neurotransmission, facilitating the suppression of beta-site amyloid precursor protein-cleaving enzyme 1, α-synuclein, and monoamine oxidase proteins, and deterring the occurrence of AD. Additionally, various phenolic, flavonoid, and terpenoid phytocompounds have been extensively described as potential palliative agents for AD progression. Preclinical studies have shown their involvement in modulating the cellular redox balance and minimizing ROS formation, displaying them as antioxidant agents with neuroprotective abilities. This review emphasizes the mechanistic role of natural products in the treatment of AD and discusses the various pathological hypotheses proposed for AD.

Catalpol Mitigates Alzheimer's Disease Progression by Promoting the Expression of Neural Stem Cell Exosomes Released miR-138-5p

Alzheimer's disease (Alzheimer's disease, AD) is a neurodegenerative disease characterized by senile plaque deposition and neurofibrillary tangles. The pathogenesis of AD is complicated and the drugs used to treat AD are single-targeted drugs, which can only improve or alleviate the symptoms of patients, but cannot delay or prevent the progress of the disease. Because of its ability to act on multiple targets, multiple systems, multiple links, and multiple pathways, Chinese herbal compound prescriptions have shown unique advantages in the research and treatment of AD. Our previous study has demonstrated the protect role of the Chinese medicine Rehmannia in AD. However, the underlying mechanism remains unclear. In the present study, both in vitro and vivo experiments were employed, and we found Catalpol (Ca), the main extract of Rehmannia, could mitigate AD progression both in vitro and in vivo by promoting miR-138-5p level in neural stem cell secreted exosomes.

Novel bioengineered MBenes for the treatment of Alzheimer's disease: An in-Sillico study

Alzheimer's disease is a neurodegenerative disease caused by the deposition and accumulation of amyloid-β (Aβ) peptides in the brain neurons. Current medications are not a definitive cure for this disease, but they can hamper the signs and symptoms of Alzheimer's disease. Therefore, prevention is the best way to deal with this disease. In this study, the novel structures based on MBenes (such as Cd₂B, Mo₂B, Cu₂B, and Ta₂B) are proposed to prevent amyloid-β accumulation in Alzheimer's disease. Regarding the remarkable MBene properties such as tunability, biocompatibility, and low manufacturing cost, the effect of these structures on amyloid-β deformation was explored using molecular dynamics simulation. To provide an atomic analysis of Beta-amyloid behavior in the presence of these structures, the compaction, contact area, and stability of Beta-amyloid were investigated. The results indicated the satisfactory performance of MBenes on the destabilization of amyloid-β structures. Moreover, given the higher interactions between Cd₂B and amyloid-β, the instability, compaction, and the contact area of amyloid-β particles were investigated in this complex. The findings confirmed Cd₂B as the best structure to prevent amyloid-β accumulation. The results of this investigation paved the way for the development of these structures as a medicinal agent to prevent Alzheimer's disease.

Sexual Dimorphism in Neurodegenerative Diseases and in Brain Ischemia

Epidemiological studies and clinical observations show evidence of sexual dimorphism in brain responses to several neurological conditions. It is suggested that sex-related differences between men and women may have profound effects on disease susceptibility, pathophysiology, and progression. Sexual differences of the brain are achieved through the complex interplay of several factors contributing to this phenomenon, such as sex hormones, as well as genetic and epigenetic differences. Despite recent advances, the precise link between these factors and brain disorders is incompletely understood. This review aims to briefly outline the most relevant aspects that differ between men and women in ischemia and neurodegenerative disorders (AD, PD, HD, ALS, and SM). Recognition of disparities between both sexes could aid the development of individual approaches to ameliorate or slow the progression of intractable disorders.

Asymmetry-enhanced attention network for Alzheimer's diagnosis with structural Magnetic Resonance Imaging

BACKGROUND AND OBJECTIVE

With the aging of the global population becoming severe, Alzheimer's disease (AD) has become one of the world's most common senile diseases. Many studies have suggested that the brain's left-right asymmetry is one of the possible diagnostic landmarks for AD. However, most published approaches to classification problems may not adequately explore the asymmetry between the left and right hemispheres. At the same time, the relationship between asymmetry traits and other classifier features remains understudied.

METHODS

In this paper, we proposed an asymmetry enhanced attention network (ASEAN) for AD diagnosis that effectively combines the anatomical asymmetry characteristics of the brain to enhance the accuracy and stability of classification tasks. First, we proposed a multi-scale asymmetry feature extraction module (MSAF) that can extract the asymmetry features of the brain from various scales. Second, we proposed an asymmetry refinement module (ARM) that considers the dependency between feature maps to suppress the irrelevant regions of the asymmetric feature maps. In addition, a parameter-free attention module was introduced to infer 4D attention weights and improve the network's representation capability.

RESULTS

The proposed method achieved performance improvements on two databases: Alzheimer's Disease Neuroimaging Initiative (ADNI) and Australian Imaging, Biomarkers and Lifestyle (AIBL). For the classification tasks on ADNI, the proposed method achieves 92.1% accuracy, 96.2% sensitivity, and 91.3% specificity on the AD vs. CN (Cognitively Normal) task. Compared with state-of-the-art methods, the proposed method could achieve comparable results.

CONCLUSION

The proposed model can extract long-range left-right brain similarity as complementary information and improve the model's diagnostic performance. A large number of experiments also support the model's validity. At the same time, this work provides a valuable reference for other neurological diseases, particularly those that exhibit left-right brain asymmetry during development.

Microglial VPS35 deficiency impairs Aβ phagocytosis and Aβ-induced disease-associated microglia, and enhances Aβ associated pathology

Background

Vacuolar sorting protein 35 (VPS35), a key component of the retromer, plays an essential role in selectively retrieval of transmembrane proteins from endosomes to trans-Golgi networks. Dysfunctional retromer is a risk factor for neurodegenerative disorders, including Alzheimer’s disease (AD). Microglial VPS35 deficiency is found in AD patients’ brain; however, it remains unclear if and how microglial VPS35-loss contributes to AD development.

Methods

We used mice with VPS35 cKO (conditional knockout) in microglial cells in 5XFAD, an AD mouse model. The AD related brain pathology (Aβ and glial activation), behavior, and phagocytosis of Aβ were accessed by a combination of immunofluorescence staining analyses and neurological behavior tests.

Results

A decrease in learning and memory function, but increases in insoluble, fibrillar, and plaques of β-amyloids (Aβ), dystrophic neurites, and reactive astrocytes are observed in microglial VPS35 deficient 5XFAD mice. Further examining microglial phenotype demonstrates necessity of microglial VPS35 in disease-associated microglia (DAM) development and microglial uptake of Aβ, revealing a tight association of microglial Aβ uptake with DAM development.

Conclusions

Together, these results uncovered a mechanism by which microglial VPS35-deficiency precipitates AD pathology in 5XFAD mice likely by impairing DAM development and DAM mediated Aβ uptake and clearance, and thus accelerating the cognition decline.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02422-0.

Supporting auditory word recognition with transcranial direct current stimulation: effects in elderly individuals with and without objective memory complaints

Healthy elderly people often experience a subjective loss of daily memory performance whereas an objective decrease in memory performance is often observed in patients with memory complaints. In this paper, we investigate the influence of a single session of "anodal" transcranial direct current stimulation (a-tDCS) on auditory word recognition performance in a decision time experiment. Three groups of participants (>64 years of age) with and without memory complaints underwent a word recognition task, in which they had to recognize words previously encoded among several distractors (semantically or phonologically related words) via a button press. In this double-blinded study, the participants completed two sessions (sham/a-tDCS), counterbalanced between subjects with a washout period of at least 10 days. Twenty minutes of 1.5 mA a-tDCS was applied over the left temporal cortex during the memorizing and decision phases. Overall, our results demonstrated that the participants, independent of their memory performance, were faster in word recognition during a-tDCS. As expected, older participants with memory complaints recognized significantly less words correctly compared to other participants. However, tDCS did not have a beneficial effect on the extent of successful word recognition. These results suggest a general effect of a single session of a-tDCS over the left temporal cortex, with participants becoming faster in their word recognition, thus having easier access to encoded words.

Semax, a Synthetic Regulatory Peptide, Affects Copper-Induced Abeta Aggregation and Amyloid Formation in Artificial Membrane Models

Alzheimer’s disease, the most common form of dementia, is characterized by the aggregation of amyloid beta protein (Aβ). The aggregation and toxicity of Aβ are strongly modulated by metal ions and phospholipidic membranes. In particular, Cu²⁺ ions play a pivotal role in modulating Aβ aggregation. Although in the last decades several natural or synthetic compounds were evaluated as candidate drugs, to date, no treatments are available for the pathology. Multifunctional compounds able to both inhibit fibrillogenesis, and in particular the formation of oligomeric species, and prevent the formation of the Aβ:Cu²⁺ complex are of particular interest. Here we tested the anti-aggregating properties of a heptapeptide, Semax, an ACTH-like peptide, which is known to form a stable complex with Cu²⁺ ions and has been proven to have neuroprotective and nootropic effects. We demonstrated through a combination of spectrofluorometric, calorimetric, and MTT assays that Semax not only is able to prevent the formation of Aβ:Cu²⁺ complexes but also has anti-aggregating and protective properties especially in the presence of Cu²⁺. The results suggest that Semax inhibits fiber formation by interfering with the fibrillogenesis of Aβ:Cu²⁺ complexes.

Amyloidosis in Alzheimer's Disease: Pathogeny, Etiology, and Related Therapeutic Directions

The amyloid hypothesis of Alzheimer's disease has long been the predominant theory, suggesting that Alzheimer's disease is caused by the accumulation of amyloid beta protein (Aβ) in the brain, leading to neuronal toxicity in the central nervous system (CNS). Because of breakthroughs in molecular medicine, the amyloid pathway is thought to be central to the pathophysiology of Alzheimer's disease (AD). Currently, it is believed that altered biochemistry of the Aβ cycle remains a central biological feature of AD and is a promising target for treatment. This review provides an overview of the process of amyloid formation, explaining the transition from amyloid precursor protein to amyloid beta protein. Moreover, we also reveal the relationship between autophagy, cerebral blood flow, ACHE, expression of LRP1, and amyloidosis. In addition, we discuss the detailed pathogenesis of amyloidosis, including oxidative damage, tau protein, NFTs, and neuronal damage. Finally, we list some ways to treat AD in terms of decreasing the accumulation of Aβ in the brain.

Compromised Astrocyte Swelling/Volume Regulation in the Hippocampus of the Triple Transgenic Mouse Model of Alzheimer’s Disease

In this study, we aimed to disclose the impact of amyloid-β toxicity and tau pathology on astrocyte swelling, their volume recovery and extracellular space (ECS) diffusion parameters, namely volume fraction (α) and tortuosity (λ), in a triple transgenic mouse model of Alzheimer’s disease (3xTg-AD). Astrocyte volume changes, which reflect astrocyte ability to take up ions/neurotransmitters, were quantified during and after exposure to hypo-osmotic stress, or hyperkalemia in acute hippocampal slices, and were correlated with alterations in ECS diffusion parameters. Astrocyte volume and ECS diffusion parameters were monitored during physiological aging (controls) and during AD progression in 3-, 9-, 12- and 18-month-old mice. In the hippocampus of controls α gradually declined with age, while it remained unaffected in 3xTg-AD mice during the entire time course. Moreover, age-related increases in λ occurred much earlier in 3xTg-AD animals than in controls. In 3xTg-AD mice changes in α induced by hypo-osmotic stress or hyperkalemia were comparable to those observed in controls, however, AD progression affected α recovery following exposure to both. Compared to controls, a smaller astrocyte swelling was detected in 3xTg-AD mice only during hyperkalemia. Since we observed a large variance in astrocyte swelling/volume regulation, we divided them into high- (HRA) and low-responding astrocytes (LRA). In response to hyperkalemia, the incidence of LRA was higher in 3xTg-AD mice than in controls, which may also reflect compromised K+ and neurotransmitter uptake. Furthermore, we performed single-cell RT-qPCR to identify possible age-related alterations in astrocytic gene expression profiles. Already in 3-month-old 3xTg-AD mice, we detected a downregulation of genes affecting the ion/neurotransmitter uptake and cell volume regulation, namely genes of glutamate transporters, α2β2 subunit of Na+/K+-ATPase, connexin 30 or Kir4.1 channel. In conclusion, the aged hippocampus of 3xTg-AD mice displays an enlarged ECS volume fraction and an increased number of obstacles, which emerge earlier than in physiological aging. Both these changes may strongly affect intercellular communication and influence astrocyte ionic/neurotransmitter uptake, which becomes impaired during aging and this phenomenon is manifested earlier in 3xTg-AD mice. The increased incidence of astrocytes with limited ability to take up ions/neurotransmitters may further add to a cytotoxic environment.

MEDAS: an open-source platform as a service to help break the walls between medicine and informatics

In the past decade, deep learning (DL) has achieved unprecedented success in numerous fields, such as computer vision and healthcare. Particularly, DL is experiencing an increasing development in advanced medical image analysis applications in terms of segmentation, classification, detection, and other tasks. On the one hand, tremendous needs that leverage DL's power for medical image analysis arise from the research community of a medical, clinical, and informatics background to share their knowledge, skills, and experience jointly. On the other hand, barriers between disciplines are on the road for them, often hampering a full and efficient collaboration. To this end, we propose our novel open-source platform, i.e., MEDAS-the MEDical open-source platform As Service. To the best of our knowledge, MEDAS is the first open-source platform providing collaborative and interactive services for researchers from a medical background using DL-related toolkits easily and for scientists or engineers from informatics modeling faster. Based on tools and utilities from the idea of RINV (Rapid Implementation aNd Verification), our proposed platform implements tools in pre-processing, post-processing, augmentation, visualization, and other phases needed in medical image analysis. Five tasks, concerning lung, liver, brain, chest, and pathology, are validated and demonstrated to be efficiently realizable by using MEDAS. MEDAS is available at http://medas.bnc.org.cn/.

Antioxidant Activity of Fluoxetine and Vortioxetine in a Non-Transgenic Animal Model of Alzheimer's Disease

Depression is a risk factor for the development of Alzheimer’s disease (AD). A neurobiological and clinical continuum exists between AD and depression, with neuroinflammation and oxidative stress being involved in both diseases. Second-generation antidepressants, in particular selective serotonin reuptake inhibitors (SSRIs), are currently investigated as neuroprotective drugs in AD. By employing a non-transgenic AD model, obtained by intracerebroventricular (i.c.v.) injection of amyloid-β (Aβ) oligomers in 2-month-old C57BL/6 mice, we recently demonstrated that the SSRI fluoxetine (FLX) and the multimodal antidepressant vortioxetine (VTX) reversed the depressive-like phenotype and memory deficits induced by Aβ oligomers rescuing the levels of transforming growth factor-β1 (TGF-β1). Aim of our study was to test FLX and VTX for their ability to prevent oxidative stress in the hippocampus of Aβ-injected mice, a brain area strongly affected in both depression and AD. The long-term intraperitoneal (i.p.) administration of FLX (10 mg/kg) or VTX (5 and 10 mg/kg) for 24 days, starting 7 days before Aβ injection, was able to prevent the over-expression of inducible nitric oxide synthase (iNOS) and NADPH oxidase 2 (Nox2) induced by Aβ oligomers. Antidepressant pre-treatment was also able to rescue the mRNA expression of glutathione peroxidase 1 (Gpx1) antioxidant enzyme. FLX and VTX also prevented Aβ-induced neurodegeneration in mixed neuronal cultures treated with Aβ oligomers. Our data represent the first evidence that the long-term treatment with the antidepressants FLX or VTX can prevent the oxidative stress phenomena related to the cognitive deficits and depressive-like phenotype observed in a non-transgenic animal model of AD.

Relevance of a Novel Circuit-Level Model of Episodic Memories to Alzheimer's Disease

The medial temporal lobe memory system has long been identified as the brain region showing the first histopathological changes in early Alzheimer's disease (AD), and the functional decline observed in patients also points to a loss of function in this brain area. Nonetheless, the exact identity of the neurons and networks that undergo deterioration has not been determined so far. A recent study has identified the entorhinal and hippocampal neural circuits responsible for encoding new episodic memories. Using this novel model we describe the elements of the episodic memory network that are especially vulnerable in early AD. We provide a hypothesis of how reduced reelin signaling within such a network can promote AD-related changes. Establishing novel associations and creating a temporal structure for new episodic memories are both affected in AD. Here, we furnish a reasonable explanation for both of these previous observations.

Phytosterols: Potential Metabolic Modulators in Neurodegenerative Diseases

Phytosterols constitute a class of natural products that are an important component of diet and have vast applications in foods, cosmetics, and herbal medicines. With many and diverse isolated structures in nature, they exhibit a broad range of biological and pharmacological activities. Among over 200 types of phytosterols, stigmasterol and β-sitosterol were ubiquitous in many plant species, exhibiting important aspects of activities related to neurodegenerative diseases. Hence, this mini-review presented an overview of the reported studies on selected phytosterols related to neurodegenerative diseases. It covered the major phytosterols based on biosynthetic considerations, including other phytosterols with significant in vitro and in vivo biological activities.

Brain controllability distinctiveness between depression and cognitive impairment

Alzheimer's disease (AD) is a progressive form of dementia marked by cognitive and memory deficits, estimated to affect ∼5.7 million Americans and account for ∼$277 billion in medical costs in 2018. Depression is one of the most common neuropsychiatric disorders that accompanies AD, appearing in up to 50% of patients. AD and Depression commonly occur together with overlapped symptoms (depressed mood, anxiety, apathy, and cognitive deficits.) and pose diagnostic challenges early in the clinical presentation. Understanding their relationship is critical for advancing treatment strategies, but the interaction remains poorly studied and thus often leads to a rapid decline in functioning. Modern systems and control theory offer a wealth of novel methods and concepts to assess the important property of a complex control system, such as the brain. In particular, the brain controllability analysis captures the ability to guide the brain behavior from an initial state (healthy or diseased) to a desired state in finite time, with suitable choice of inputs such as external or internal stimuli. The controllability property of the brain's dynamic processes will advance our understanding of the emergence and progression of brain diseases and thus helpful in the early diagnosis and novel treatment approaches. This study aims to assess the brain controllability differences between mild cognitive impairment (MCI), as prodromal AD, and Depression. This study used diffusion tensor imaging (DTI) data from 60 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI): 15 cognitively normal subjects and 45 patients with MCI, including 15 early MCI (EMCI) patients without depression, 15 EMCI patients with mild depression (EMCID), and 15 late MCI (LMCI) patients without depression. The structural brain network was firstly constructed and the brain controllability was characterized for each participant. The controllability of default mode network (DMN) and its sub-regions were then compared across groups in a structural basis. Results indicated that the brain average controllability of DMN in EMCI, LMCI, and EMCID were significantly decreased compared to healthy subjects (P < 0.05). The EMCI and LMCI groups also showed significantly greater average controllability of DMN versus the EMCID group. Furthermore, compared to healthy subjects, the regional controllability of the left/right superior prefrontal cortex and the left/right cingulate gyrus in the EMCID group showed a significant decrease (P < 0.01). Among these regions, the left superior prefrontal region's controllability was significantly decreased (P < 0.05) in the EMCID group compared with EMCI and LMCI groups. Our results provide a new perspective in understanding depressive symptoms in MCI patients and provide potential biomarkers for diagnosing depression from MCI and AD.

Orientational changes of white matter fibers in Alzheimer's disease and amnestic mild cognitive impairment

White matter abnormalities represent early neuropathological events in neurodegenerative diseases such as Alzheimer's disease (AD), investigating these white matter alterations would likely provide valuable insights into pathological changes over the course of AD. Using a novel mathematical framework called "Director Field Analysis" (DFA), we investigated the geometric microstructural properties (i.e., splay, bend, twist, and total distortion) in the orientation of white matter fibers in AD, amnestic mild cognitive impairment (aMCI), and cognitively normal (CN) individuals from the Alzheimer's Disease Neuroimaging Initiative 2 database. Results revealed that AD patients had extensive orientational changes in the bilateral anterior thalamic radiation, corticospinal tract, inferior and superior longitudinal fasciculus, inferior fronto-occipital fasciculus, and uncinate fasciculus in comparison with CN. We postulate that these orientational changes of white matter fibers may be partially caused by the expansion of lateral ventricle, white matter atrophy, and gray matter atrophy in AD. In contrast, aMCI individuals showed subtle orientational changes in the left inferior longitudinal fasciculus and right uncinate fasciculus, which showed a significant association with the cognitive performance, suggesting that these regions may be preferential vulnerable to breakdown by neurodegenerative brain disorders, thereby resulting in the patients' cognitive impairment. To our knowledge, this article is the first to examine geometric microstructural changes in the orientation of white matter fibers in AD and aMCI. Our findings demonstrate that the orientational information of white matter fibers could provide novel insight into the underlying biological and pathological changes in AD and aMCI.

A Review of Automated Techniques for Assisting the Early Detection of Alzheimer's Disease with a Focus on EEG

In this paper, we review state-of-the-art approaches that apply signal processing (SP) and machine learning (ML) to automate the detection of Alzheimer's disease (AD) and its prodromal stages. In the first part of the document, we describe the economic and social implications of the disease, traditional diagnosis techniques, and the fundaments of automated AD detection. Then, we present electroencephalography (EEG) as an appropriate alternative for the early detection of AD, owing to its reduced cost, portability, and non-invasiveness. We also describe the main time and frequency domain EEG features that are employed in AD detection. Subsequently, we examine some of the main studies of the last decade that aim to provide an automatic detection of AD and its previous stages by means of SP and ML. In these studies, brain data was acquired using multiple medical techniques such as magnetic resonance imaging, positron emission tomography, and EEG. The main aspects of each approach, namely feature extraction, classification model, validation approach, and performance metrics, are compiled and discussed. Lastly, a set of conclusions and recommendations for future research on AD automatic detection are drawn in the final section of the paper.

Multimodal Imaging Analysis Reveals Frontal-Associated Networks in Relation to Individual Resilience Strength

Psychological resilience is regarded as a critical protective factor for preventing the development of mental illness from experienced adverse events. Personal strength is one key element of resilience that reflects an individual's reactions to negative life events and is crucial for successful adaptation. Previous studies have linked unimodal imaging measures with resilience. However, applying multimodal imaging measures could provide comprehensive organization information at the system level to examine whether an individual's resilience strength is reflected in the brain's structural and functional network. In this study, MRI was used to acquire multimodal imaging properties and subscales of personal strength in terms of resilience from 109 participants (48 females and 61 males). We employed a method of fusion independent component analysis to link the association between multimodal imaging components and personal strength of psychological resilience. The results reveal that a fusion component involving multimodal frontal networks in connecting with the parietal, occipital, and temporal regions is associated with the resilience score for personal strength. A multiple regression model further explains the predictive role of frontal-associated regions that cover a visual-related network regulating cognition and emotion to discern the perceived adverse experience. Overall, this study suggests that frontal-associated regions are related to individual resilience strength.

Single Administration of the T-Type Calcium Channel Enhancer SAK3 Reduces Oxidative Stress and Improves Cognition in Olfactory Bulbectomized Mice

Alzheimer’s disease (AD), characterized by cognitive impairments, is considered to be one of the most widespread chronic neurodegenerative diseases worldwide. We recently introduced a novel therapeutic agent for AD treatment, the T-type calcium channel enhancer ethyl-8-methyl-2,4-dioxo-2-(piperidin-1-yl)-2H-spiro[cyclopentane-1,3-imidazo[1,2-a]pyridin]-2-ene-3-carboxylate (SAK3). SAK3 enhances calcium/calmodulin-dependent protein kinase II and proteasome activity, thereby promoting amyloid beta degradation in mice with AD. However, the antioxidative effects of SAK3 remain unclear. We investigated the antioxidative effects of SAK3 in olfactory bulbectomized mice (OBX mice), compared with the effects of donepezil as a positive control. As previously reported, single oral administration of both SAK3 (0.5 mg/kg, p.o.) and donepezil (1.0 mg/kg, p.o.) significantly improved cognitive and depressive behaviors in OBX mice. Single oral SAK3 administration markedly reduced 4-hydroxy-2-nonenal and nitrotyrosine protein levels in the hippocampus of OBX mice, which persisted until 1 week after administration. These effects are similar to those observed with donepezil therapy. Increased protein levels of oxidative stress markers were observed in the microglial cells, which were significantly rescued by SAK3 and donepezil. SAK3 could ameliorate oxidative stress in OBX mice, like donepezil, suggesting that the antioxidative effects of SAK3 and donepezil are among the neuroprotective mechanisms in AD pathogenesis.

A Cu-bis(imidazole) Substrate Intermediate Is the Catalytically Competent Center for Catechol Oxidase Activity of Copper Amyloid-β

Interaction of copper ions with Aβ peptides alters the redox activity of the metal ion and can be associated with neurodegeneration. Many studies deal with the characterization of the copper binding mode responsible for the reactivity. Oxidation experiments of dopamine and related catechols by copper(II) complexes with the N-terminal amyloid-β peptides Aβ₁₆ and Aβ₉, and the Aβ₁₆[H6A] and Aβ₁₆[H13A] mutant forms, both in their free amine and N-acetylated forms show that efficient reactivity requires the oxygenation of a Cu^I-bis(imidazole) complex with a bound substrate. Therefore, the active intermediate for catechol oxidation differs from the proposed “in-between state” for the catalytic oxidation of ascorbate. During the catechol oxidation process, hydrogen peroxide and superoxide anion are formed but give only a minor contribution to the reaction.

The redox cycling of copper bound to amyloid-β peptide requires the generation of a Cu(I)-Aβ-catecholate complex. When copper(II) is confined in the N-terminal portion, its reduction is slow and causes a shift toward a bis-His coordination environment. The addition of catechol to the Cu(I)-bis(imidazole) complex results in a faster reaction with dioxygen. The reactive species for catechol oxidation does not correspond to the proposed “in-between state” for ascorbate oxidation.

Hippocampal shape and asymmetry analysis by cascaded convolutional neural networks for Alzheimer's disease diagnosis

Hippocampal atrophy is often considered as one of the important biomarkers for early diagnosis of Alzheimer's disease (AD), which is an irreversible neurodegenerative disorder. Traditional methods for hippocampus analysis usually computed the shape and volume features from structural Magnetic Resonance Image (sMRI) for the computer-aided diagnosis of AD as well as its prodromal stage, i.e., mild cognitive impairment (MCI). Motivated by the success of deep learning, this paper proposes a deep learning method with the multi-channel cascaded convolutional neural networks (CNNs) to gradually learn the combined hierarchical representations of hippocampal shapes and asymmetries from the binary hippocampal masks for AD classification. First, image segmentation is performed to generate the bilateral hippocampus binary masks for each subject and the mask difference is obtained by subtracting them. Second, multi-channel 3D CNNs are individually constructed on the hippocampus masks and mask differences to extract features of hippocampal shapes and asymmetries for classification. Third, a 2D CNN is cascaded on the 3D CNNs to learn high-level correlation features. Finally, the features learned by multi-channel and cascaded CNNs are combined with a fully connected layer followed by a softmax classifier for disease classification. The proposed method can gradually learn the combined hierarchical features of hippocampal shapes and asymmetries to enhance the classification. Our method is verified on the baseline sMRIs from 807 subjects including 194 AD patients, 397 MCI (164 progressive MCI (pMCI) + 233 stable MCI (sMCI)), and 216 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Experimental results demonstrate that the proposed method achieves an AUC (Area Under the ROC Curve) of 88.4%, 74.6% and 71.9% for AD vs. NC, MCI vs. NC and pMCI vs. sMCI classifications, respectively. It proves the promising classification performance and also shows that both hippocampal shape and asymmetry are helpful for AD diagnosis.

Improving Alzheimer's stage categorization with Convolutional Neural Network using transfer learning and different magnetic resonance imaging modalities

BACKGROUND

Alzheimer's Disease (AD) is a neurodegenerative disease characterized by progressive loss of memory and general decline in cognitive functions. Multi-modal imaging such as structural MRI and DTI provide useful information for the classification of patients on the basis of brain biomarkers. Recently, CNN methods have emerged as powerful tools to improve classification using images.

NEW METHOD

In this paper, we propose a transfer learning scheme using Convolutional Neural Networks (CNNs) to automatically classify brain scans focusing only on a small ROI: e.g. a few slices of the hippocampal region. The network's architecture is similar to a LeNet-like CNN upon which models are built and fused for AD stage classification diagnosis. We evaluated various types of transfer learning through the following mechanisms: (i) cross-modal (sMRI and DTI) and (ii) cross-domain transfer learning (using MNIST) (iii) a hybrid transfer learning of both types.

RESULTS

Our method shows good performances even on small datasets and with a limited number of slices of small brain region. It increases accuracy with more than 5 points for the most difficult classification tasks, i.e., AD/MCI and MCI/NC.

COMPARISON WITH EXISTING METHODS

Our methodology provides good accuracy scores for classification over a shallow convolutional network. Besides, we focused only on a small region; i.e., the hippocampal region, where few slices are selected to feed the network. Also, we used cross-modal transfer learning.

CONCLUSIONS

Our proposed method is suitable for working with a shallow CNN network for low-resolution MRI and DTI scans. It yields to significant results even if the model is trained on small datasets, which is often the case in medical image analysis.

The Impact of the CX3CL1/CX3CR1 Axis in Neurological Disorders

Fractalkine (FKN, CX3CL1) is a transmembrane chemokine expressed by neurons in the central nervous system (CNS). CX3CL1 signals through its unique receptor, CX3CR1, that is expressed in microglia. Within the CNS, fractalkine acts as a regulator of microglia activation in response to brain injury or inflammation. During the last decade, there has been a growing interest in the roles that the CX3CL1/CX3CR1 signaling pathway plays in the neuropathology of a diverse array of brain disorders. However, the reported results have proven controversial, indicating that a disruption of the CX3CL1 axis induces a disease-specific microglial response that may have either beneficial or detrimental effects. Therefore, it has become clear that the understanding of neuron-to-glia signals mediated by CX3CL1/CX3CR1 at different stages of diseases could provide new insight into potential therapeutic targets. Hence, the aim of this review is to provide a summary of the literature on the emerging role of CX3CL1 in animal models of some brain disorders.

Interactions of Aβ1-42 Peptide and Its Three Fragments (Aβ8-12, Aβ8-13, and Aβ5-16) with Selected Nonsteroidal Drugs and Compounds of Natural Origin

In the following paper, we present the results of our studies on the interactions of the Aβ1-42 peptide and its three short fragments, namely Aβ5-16 (RHDSGYEVHHQK; HZ1), Aβ8-13 (SGYEVH; HZ2), and Aβ8-12 (SGYEV; HZ3) with selected painkillers (ibuprofen and aspirin) and compounds of natural origin (anabasine and epinephrine). Steady-state fluorescence spectroscopy was used to study the binding properties of the selected systems. Additionally, based on molecular dynamics (MD) calculations supported by NMR-derived restrains, we have proposed the most likely area of the interactions of Aβ1-42 and Aβ5-16 peptides with the investigated compounds. The influence of symmetrically oriented side chains of amino acid residues present in the first part of the Aβ1-42 sequence on the stability of the resulting complexes has been discussed. Finally, the changes in the peptide structures on account of complex formation were analyzed.

Screening and identification of secondary metabolites in the bark of Bauhinia variegata to treat Alzheimer's disease by using molecular docking and molecular dynamics simulations

Acetylcholinesterase (AChE) and Butyrylcholinesterase (BChE) acts as a promising protein targets for which drug as an inhibitor can be designed to treat Alzheimer's Disease. Different flavonoids and alkaloids of Bauhinia variegata were used as an inhibitor to target the protein. The current in silico study was carried out to explore the binding patterns of flavanoids and alkaloids against Acetylcholinesterase (PDB ID: 4PQE) and Butyrylcholinesterase (PDB ID: 1P0I) using molecular docking and molecular dynamics simulations approach. Molecular docking result shows that Dihydroquercetin (CID:439533) binds with the active region of AChE and BChE. Using molsoft, molinspiration, and pkCSM all the properties of the candidate were analyzed. The best compound Dihydroquercetin was compared with Donepezil drug through molecular dynamic simulation studies. The analysis of Molecular Dynamics Simulations showed that AChE and AChE-Dihydroquercetin complex became stable at 3000 ps and there was little conformational change in BChE and BChE-Dihydroquercetin complex. The in silico study finally predicts that Dihydroquercetin may act as a good inhibitor for treating Alzheimer's disease and further in vitro and in vivo studies may prove its therapeutic potential.Communicated by Ramaswamy H. Sarma.

Optical coherence tomography reveals light-dependent retinal responses in Alzheimer's disease

Spectral-domain optical coherence tomography (SD-OCT) is an accessible clinical tool for measuring structural changes to the retina, and increasingly as a biomarker for brain-predominant neurodegenerative diseases like Alzheimer's. Information about retinal function can also be extracted from OCT images, but is under-studied, with literature examples often employing challenging protocols or requiring specialized hardware. The first goal of this study was to verify that functional retinal imaging was feasible with a commercially-available SD-OCT device and a clinically practical protocol. Inspired by methods from other functional imaging modalities, we acquired images while repeatedly cycling lights on and off, and spatially normalized retinas to facilitate intra- and inter-individual analyses. In eight healthy young adults, light-dependent increases in reflectivity were easily demonstrated at photoreceptor inner and outer segments, changing by ~7% in bright light and ~3% in dim light. Bright light elicited a subtle (~2%) but consistent light-dependent decrease in reflectivity through much of the rest of the retina, including the avascular outer nuclear layer (ONL). We speculated that some of these changes are influenced by glial function - as through water management - a topic of high interest in neurodegenerative diseases that may involve the glymphatic system. Functional abnormalities in patients with antibodies against aquaporin-4 (n ​= ​3) supported this interpretation. We next compared patients with early-onset Alzheimer's disease (n ​= ​14) to age-matched controls (n ​= ​14), revealing that patients had a relatively exaggerated light-induced change in ONL reflectivity (p ​< ​0.05). Because these measurements can be obtained within 30 ​min, regular use in research and limited clinical settings is feasible.

Spaced Retrieval and Episodic Memory Training in Alzheimer's Disease

Introduction

This study replicated and extended the findings from the author's previous pilot study to further explore how a spaced retrieval (SR) memory training program might be effectively applied to help persons with Alzheimer’s disease (AD)  improve both short- and long-term recall of recent episodic events.

Methods

A quasi-experimental within-subject group study was conducted with 15 participants with a diagnosis of AD.

Results

Compared to a control condition, all participants were able to spontaneously recall significantly more specific details about trained events, and their recall was significantly enhanced when they were provided with cues. Although the findings indicated that people with AD were able to encode information during training, recall gains diminished by the end of the maintenance period.

Discussion

This study provides evidence that individuals with mild to moderate AD can learn and recall new episodic information through SR training. These findings support the use of SR as an intervention tool to help individuals maintain their functioning in episodic recent memory. However, more research into maintaining the long-term recall of recent episodic events is warranted.

Positive association between soil arsenic concentration and mortality from alzheimer's disease in mainland China

OBJECTIVES

The current study was designed to investigate the relationship between the soil arsenic (As) concentration and the mortality from Alzheimer's disease (AD) in mainland China.

STUDY DESIGN

Ecological study.

METHODS

Twenty-two provinces and 3 municipal districts in mainland China were included in this study. The As concentrations in soil in 1990 was obtained from the China State Environmental Protection Bureau; the data on annual mortality of AD from 1991 to 2000 were obtained from the National Death Cause Surveillance Database of China. Using these data, we calculated the spearman correlation coefficient between soil As concentration and AD mortality, and the relative risk (RR) between soil As levels and AD mortality by quartile-dividing study groups.

RESULTS

The spearman correlation coefficient between As concentration and AD mortality was 0.552 (p = 0.004), 0.616 (p = 0.001) and 0.622 (p = 0.001) in the A soil As (eluvial horizon), the C soil As (parent material horizon), and the Total soil As (A soil As + C soil As), respectively. When the A soil As concentration was over 9.05 mg/kg, 10.40 mg/kg and 13.10 mg/kg, the relative risk was 0.835 (95 % CI: 0.832, 0.838), 1.969 (95 %CI: 1.955, 1.982), and 2.939 (95 % CI: 2.920, 2.958), respectively; when the C soil As reached 9.45 mg/kg, 11.10 mg/kg and 13.55 mg/kg, the relative risk was 4.349 (95 % CI: 4.303, 4.396), 6.108 (95 % CI: 6.044, 6.172), and 9.125 (95 %CI: 9.033, 9.219), respectively. No correlation was found between lead, cadmium, and mercury concentration in the soil and AD mortality.

CONCLUSION

There was an apparent soil As concentration dependent increase in AD mortality. Results of this study may provide evidence for a possible causal linkage between arsenic exposure and the death risk from AD.

Targeting Ubiquitin-Proteasome Pathway by Natural Products: Novel Therapeutic Strategy for Treatment of Neurodegenerative Diseases

Misfolded proteins are the main common feature of neurodegenerative diseases, thereby, normal proteostasis is an important mechanism to regulate the neural survival and the central nervous system functionality. The ubiquitin-proteasome system (UPS) is a non-lysosomal proteolytic pathway involved in numerous normal functions of the nervous system, modulation of neurotransmitter release, synaptic plasticity, and recycling of membrane receptors or degradation of damaged and regulatory intracellular proteins. Aberrant accumulation of intracellular ubiquitin-positive inclusions has been implicated to a variety of neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington disease (HD), Amyotrophic Lateral Sclerosis (ALS), and Multiple Myeloma (MM). Genetic mutation in deubiquitinating enzyme could disrupt UPS and results in destructive effects on neuron survival. To date, various agents were characterized with proteasome-inhibitory potential. Proteins of the ubiquitin-proteasome system, and in particular, E3 ubiquitin ligases, may be promising molecular targets for neurodegenerative drug discovery. Phytochemicals, specifically polyphenols (PPs), were reported to act as proteasome-inhibitors or may modulate the proteasome activity. PPs modify the UPS by means of accumulation of ubiquitinated proteins, suppression of neuronal apoptosis, reduction of neurotoxicity, and improvement of synaptic plasticity and transmission. This is the first comprehensive review on the effect of PPs on UPS. Here, we review the recent findings describing various aspects of UPS dysregulation in neurodegenerative disorders. This review attempts to summarize the latest reports on the neuroprotective properties involved in the proper functioning of natural polyphenolic compounds with implication for targeting ubiquitin-proteasome pathway in the neurodegenerative diseases. We highlight the evidence suggesting that polyphenolic compounds have a dose and disorder dependent effects in improving neurological dysfunctions, and so their mechanism of action could stimulate the UPS, induce the protein degradation or inhibit UPS and reduce protein degradation. Future studies should focus on molecular mechanisms by which PPs can interfere this complex regulatory system at specific stages of the disease development and progression.

Regional brain susceptibility to neurodegeneration: what is the role of glial cells?

The main pathological feature of the neurodegenerative diseases is represented by neuronal death that represents the final step of a cascade of adverse/hostile events. Early in the neurodegenerative process, glial cells (including astrocytes, microglial cells, and oligodendrocytes) activate and trigger an insidious neuroinflammatory reaction, metabolic decay, blood brain barrier dysfunction and energy impairment, boosting neuronal death. How these mechanisms might induce selective neuronal death in specific brain areas are far from being elucidated. The last two decades of neurobiological studies have provided evidence of the main role of glial cells in most of the processes of the central nervous system, from development to synaptogenesis, neuronal homeostasis and integration into, highly specific neuro-glial networks. In this mini-review, we moved from in vitro and in vivo models of neurodegeneration to analyze the putative role of glial cells in the early mechanisms of neurodegeneration. We report changes of transcriptional, genetic, morphological, and metabolic activity in astrocytes and microglial cells in specific brain areas before neuronal degeneration, providing evidence in experimental models of neurodegenerative disorders, including Parkinson's and Alzheimer's diseases. Understanding these mechanisms might increase the insight of these processes and pave the way for new specific glia-targeted therapeutic strategies for neurodegenerative disorders.

Neurotheranostics as personalized medicines

The discipline of neurotheranostics was forged to improve diagnostic and therapeutic clinical outcomes for neurological disorders. Research was facilitated, in largest measure, by the creation of pharmacologically effective multimodal pharmaceutical formulations. Deployment of neurotheranostic agents could revolutionize staging and improve nervous system disease therapeutic outcomes. However, obstacles in formulation design, drug loading and payload delivery still remain. These will certainly be aided by multidisciplinary basic research and clinical teams with pharmacology, nanotechnology, neuroscience and pharmaceutic expertise. When successful the end results will provide "optimal" therapeutic delivery platforms. The current report reviews an extensive body of knowledge of the natural history, epidemiology, pathogenesis and therapeutics of neurologic disease with an eye on how, when and under what circumstances neurotheranostics will soon be used as personalized medicines for a broad range of neurodegenerative, neuroinflammatory and neuroinfectious diseases.

FDG-PET as an independent biomarker for Alzheimer's biological diagnosis: a longitudinal study

BACKGROUND

Reduced ¹⁸F-fluorodeoxyglucose-positron emission tomography (FDG-PET) brain metabolism was recognized as a biomarker of neurodegeneration in the recently proposed ATN framework for Alzheimer's disease (AD) biological definition. However, accumulating evidence suggested it is an independent biomarker, which is denoted as "F" in the very study.

METHODS

A total of 551 A+T+ individuals from the Alzheimer's Disease Neuroimaging Initiative database were recruited and then further divided into four groups based on the biomarker positivity as 132 A+T+N-F-, 102 A+T+N-F+, 113 A+T+N+F-, and 204 A+T+N+F+. Frequency distributions of the groups were compared, as well as the clinical progression [measured by the longitudinal changes in cognition and brain structure, and mild cognitive impairment (MCI) to AD dementia conversion] between every pair of F+ and F- groups.

RESULTS

The prevalence of A+T+N+F+ profile was 66.24% in clinically diagnosed AD dementia patients; similarly, the majority of individuals with reduced FDG-PET were AD dementia subjects. Among the 551 individuals that included, 537 had at least one follow-up (varied from 1 to 8 years). Individuals in F+ groups performed worse and dropped faster in Mini-Mental State Examination scale and had faster shrinking middle temporal lobe than those in F- groups (all p < 0.05). Moreover, in MCI patients, reduced FDG-PET exerted 2.47 to 4.08-fold risk of AD dementia progression compared with those without significantly impaired FDG-PET (both p < 0.001).

CONCLUSIONS

Based on the analyses, separating FDG-PET from "N" biomarker to build the ATN(F) system is necessary and well-founded. The analysis from this study could be a complement to the original ATN framework for AD's biological definition.

Transcriptional Dysregulation Study Reveals a Core Network Involving the Progression of Alzheimer's Disease

Background: The pathogenesis of Alzheimer's disease is associated with dysregulation at different levels from transcriptome to cellular functioning. Such complexity necessitates investigations of disease etiology to be carried out considering multiple aspects of the disease and the use of independent strategies. The established works more emphasized on the structural organization of gene regulatory network while neglecting the internal regulation changes. Methods: Applying a strategy different from popularly used co-expression network analysis, this study investigated the transcriptional dysregulations during the transition from normal to disease states. Results: Ninety- seven genes were predicted as dysregulated genes, which were also associated with clinical outcomes of Alzheimer's disease. Both the co-expression and differential co-expression analysis suggested these genes to be interconnected as a core network and that their regulations were strengthened during the transition to disease states. Functional studies suggested the dysregulated genes to be associated with aging and synaptic function. Further, we checked the conservation of the gene co-expression and found that human and mouse brain might have divergent transcriptional co-regulation even when they had conserved gene expression profiles. Conclusion: Overall, our study reveals a core network of transcriptional dysregulation associated with the progression of Alzheimer's disease by affecting the aging and synaptic functions related genes; the gene regulation is not conserved in the human and mouse brains.

Radiomics: a novel feature extraction method for brain neuron degeneration disease using 18F-FDG PET imaging and its implementation for Alzheimer's disease and mild cognitive impairment

Background:

Alzheimer’s disease (AD) is the most common form of progressive and irreversible dementia, and accurate diagnosis of AD at its prodromal stage is clinically important. Currently, computer-aided diagnosis of AD and mild cognitive impairment (MCI) using ¹⁸F-fluorodeoxy-glucose positron emission tomography (¹⁸F-FDG PET) imaging is usually based on low-level imaging features or deep learning methods, which have difficulties in achieving sufficient classification accuracy or lack clinical significance. This research therefore aimed to implement a new feature extraction method known as radiomics, to improve the classification accuracy and discover high-order features that can reveal pathological information.

Methods:

In this study, ¹⁸F-FDG PET and clinical assessments were collected in a cohort of 422 individuals [including 130 with AD, 130 with MCI, and 162 healthy controls (HCs)] from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and 44 individuals (including 22 with AD, and 22 HCs) from Huashan Hospital, Shanghai, China. First, we performed a group comparison using a two-sample Student’s t test to determine the regions of interest (ROIs) based on 30 AD patients and 30 HCs from ADNI cohorts. Second, based on two time scans of 32 HCs from ADNI cohorts, we used Cronbach’s alpha coefficient for radiomic feature stability analyses. Pearson’s correlation coefficients were regarded as a feature selection criterion, to select effective features associated with the clinical cognitive scale [clinical dementia rating scale in its sum of boxes (CDRSB); Alzheimer’s disease assessment scale (ADAS)] with 500-times cross-validation. Finally, a support vector machine (SVM) was used to test the ability of the radiomic features to classify HCs, MCI and AD patients.

Results:

As a result, we identified brain regions which were mainly distributed in the temporal, occipital and frontal areas as ROIs. A total of 168 radiomic features of AD were stable (alpha > 0.8). The classification experiment led to maximal accuracies of 91.5%, 83.1% and 85.9% for classifying AD versus HC, MCI versus HCs and AD versus MCI.

Conclusion:

The research in this paper proved that the novel approach based on high-order radiomic features extracted from ¹⁸F-FDG PET brain images that can be used for AD and MCI computer-aided diagnosis.