Alzheimer’s Disease

Atmospheric particulate matter (PM) exacerbates the risk factor for Alzheimer's and Parkinson's diseases (PD) by promoting the alpha-synuclein (α-syn) pathology in the brain. However, the molecular mechanisms of astrocytes involvement in α-syn pathology underlying the process remain unclear. This study investigated PM with particle size <200 nm (PM) exposure-induced α-syn pathology in ICR mice and primary astrocytes, then assessed the effects of mammalian target of rapamycin inhibitor (PP242) in vitro studies. We observed the α-syn pathology in the brains of exposed mice. Meanwhile, PM-exposed mice also exhibited the activation of glial cell and the inhibition of autophagy. In vitro study, PM (3, 10 and 30 µg/mL) induced inflammatory response and the disorders of α-syn degradation in primary astrocytes, and lysosomal-associated membrane protein 2 (LAMP2)-mediated autophagy underlies α-syn pathology. The abnormal function of autophagy-lysosome was specifically manifested as the expression of microtubule-associated protein light chain 3 (LC3II), cathepsin B (CTSB) and lysosomal abundance increased first and then decreased, which might both be a compensatory mechanism to toxic α-syn accumulation induced by PM. Moreover, with the transcription factor EB (TFEB) subcellular localization and the increase in LC3II, LAMP2, CTSB, and cathepsin D proteins were identified, leading to the restoration of the degradation of α-syn after the intervention of PP242. Our results identified that PM exposure could promote the α-syn pathological dysregulation in astrocytes, providing mechanistic insights into how PM increases the risk of developing PD and highlighting TFEB/LAMP2 as a promising therapeutic target for antagonizing PM toxicity.

Up to 65% of people with multiple sclerosis (MS) experience disease-related cognitive impairment, but even after decades of research, still very little is known about the cognitive issues among older adults with MS (EwMS; individuals aged 60+). To date, few studies have attempted to characterize cognitive impairment in this group or compare EwMS with those with other neurodegenerative diseases. Our goal was to address this knowledge gap by comparing EwMS with individuals experiencing cognitive impairment due to probable Alzheimer disease (AD) with biomarker confirmation.

This review aims to explore the potential of erythropoietin, a glycopeptide hormone, as a treatment option for Alzheimer's disease, which is the commonest cause of dementia. Despite years of focus and research, therapeutic options for Alzheimer's disease are not yet completely satisfactory. And as people age, they are likely to develop Alzheimer's Disease, further pressuring the healthcare system. So, it is definite to develop treatment options that meet superior outcomes with minimal negative effects. A comprehensive review of the literature was conducted in PubMed and Google Scholar using a combination of keywords, including Alzheimer's disease, dementia, erythropoietin, and neuroprotection. Search results were assessed for relevance before using the data for this study. The beneficial implications of erythropoietin as a therapeutic option have been explored, along with the side effects and mechanisms of erythropoietin in Alzheimer's disease. Overall, the authors' review indicates that erythropoietin presents a promising avenue for mitigating the progression of Alzheimer's disease, with minimal associated side effects.

TRPA1 is a nonselective calcium channel, member of the transient receptor potential (TRP) superfamily, also referred to as the 'irritant' receptor, being activated by pungent and noxious exogenous chemicals as well as by endogenous algogenic stimuli, to elicit pain, itch and inflammatory conditions. For this reason, it is considered an attractive therapeutic target to treat as wide range of diseases including acute and chronic pain, itch, and inflammatory airway diseases.

Alzheimer's disease (AD) is the most common neurodegenerative disorder with progressive memory and cognitive loss. Neuroinflammation is a central mechanism involved in the progression of AD. With the disruption of the blood-brain barrier (BBB), peripheral immune cells and inflammatory molecules enter into AD brain. However, the exact relationship between peripheral immune cells and AD remains unknown due to various challenges. This study aimed to investigate the potential causal association between peripheral immune cells and AD by using a two-sample Mendelian randomization (TSMR) analysis. We conducted a TSMR to decipher the causal relationship between AD and 731 types of peripheral immune cell parameters from the TBNK, regulatory T cell (Treg), myeloid cell, monocyte, maturation stages of T cell, dendritic cell (DC), and B cell panels.  Various analytical methods were employed, including inverse variance weighting (IVW), MR Egger, and weighted median methods. The Cochran's Q statistic, MR-Egger intercept, and MR-PRESSO tests were used to verify the heterogeneity and horizontal pleiotropy of the results. To further verify our results, we also conducted a replication analysis. The analysis identified CD33 on CD14 + monocyte (OR = 1.03; 95% CI, 1.01-1.04; p = 1.14E-04; adjust-p = 0.042) had an increased risk association for AD, which was verified by the replication study. CD33 on CD33dim HLA DR + CD11b- cell (OR = 1.02; 95% CI, 1.01-1.04; p = 2.87E-04; adjust-p = 0.035) had an increased risk association for AD, while secreting CD4 regulatory T cell %CD4 regulatory T cell (OR = 0.97; 95% CI, 0.96-0.99; p = 1.90E-04; adjust-p = 0.046) and CD25 on switched memory B cell (OR = 0.95; 95% CI, 0.92-0.98; p = 2.87E-04; adjust-p = 0.042) were discovered to be related to a lower risk of AD. However, the causal effect of these three immune cells on AD was insufficiently validated in the replication analysis. The MR analysis suggests a potential causal relationship between peripheral immune cells and the risk of AD. Further extensive research is needed on the specific role of peripheral immune cells in AD.

The application of artificial intelligence (AI) in neurology is a growing field offering opportunities to improve accuracy of diagnosis and treatment of complicated neuronal disorders, plus fostering a deeper understanding of the aetiologies of these diseases through AI-based analyses of large omics data. The most common neurodegenerative disease, Alzheimer's disease (AD), is characterized by brain accumulation of specific pathological proteins, accompanied by cognitive impairment. In this review, we summarize the latest progress on the use of AI in different AD-related fields, such as analysis of neuroimaging data enabling early and accurate AD diagnosis; prediction of AD progression, identification of patients at higher risk and evaluation of new treatments; improvement of the evaluation of drug response using AI algorithms to analyze patient clinical and neuroimaging data; the development of personalized AD therapies; and the use of AI-based techniques to improve the quality of daily life of AD patients and their caregivers.

Parkinson's disease with dementia (PDD) is a neurological disorder that clinically and neuropathologically overlaps with Parkinson's disease (PD) and Alzheimer's disease (AD). Although it is assumed that alpha-synuclein ( -Syn), amyloid beta (A ), and the protein Tau might synergistically induce cholinergic neuronal degeneration, presently the pathological mechanism of PDD remains unclear. Therefore, it is essential to delve into the cellular and molecular aspects of this neurological entity to identify potential targets for prevention and treatment strategies. Cholinergic-like neurons (ChLNs) were exposed to rotenone (ROT, 10 M) for 24 h. ROT provokes loss of , generation of reactive oxygen species (ROS), phosphorylation of leucine-rich repeated kinase 2 (LRRK2 at Ser) concomitantly with phosphorylation of -synuclein ( -Syn, Ser), induces accumulation of intracellular A (iA ), oxidized DJ-1 (Cys), as well as phosphorylation of TAU (Ser/Thr), increases the phosphorylation of c-JUN (Ser/Ser), and increases expression of proapoptotic proteins TP53, PUMA, and cleaved caspase 3 (CC3) in ChLNs. These neuropathological features resemble those reproduced in presenilin 1 (PSEN1) E280A ChLNs. Interestingly, anti-oxidant and anti-amyloid cannabidiol (CBD), JNK inhibitor SP600125 (SP), TP53 inhibitor pifithrin- (PFT), and LRRK2 kinase inhibitor PF-06447475 (PF475) significantly diminish ROT-induced oxidative stress (OS), proteinaceous, and cell death markers in ChLNs compared to naïve ChLNs. In conclusion, ROT induces p- -Syn, iA , p-Tau, and cell death in ChLNs, recapitulating the neuropathology findings in PDD. Our report provides an excellent in vitro model to test for potential therapeutic strategies against PDD. Our data suggest that ROT induces a neuropathologic phenotype in ChLNs similar to that caused by the mutation PSEN1 E280A.

Alzheimer's Disease (AD) is a serious neurological illness that causes memory loss gradually by destroying brain cells. This deadly brain illness primarily strikes the elderly, impairing their cognitive and bodily abilities until brain shrinkage occurs. Modern techniques are required for an accurate diagnosis of AD. Machine learning has gained attraction in the medical field as a means of determining a person's risk of developing AD in its early stages. One of the most advanced soft computing neural network-based Deep Learning (DL) methodologies has garnered significant interest among researchers in automating early-stage AD diagnosis. Hence, a comprehensive review is necessary to gain insights into DL techniques for the advancement of more effective methods for diagnosing AD. This review explores multiple biomarkers associated with Alzheimer's Disease (AD) and various DL methodologies, including Deep Neural Networks (DNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), The k-nearest-neighbor (k-NN), Deep Boltzmann Machines (DBM), and Deep Belief Networks (DBN), which have been employed for automating the early diagnosis of AD. Moreover, the unique contributions of this review include the classification of ATN biomarkers for Alzheimer's Disease (AD), systemic description of diverse DL algorithms for early AD assessment, along with a discussion of widely utilized online datasets such as ADNI, OASIS, etc. Additionally, this review provides perspectives on future trends derived from critical evaluation of each variant of DL techniques across different modalities, dataset sources, AUC values, and accuracies.

Sex differences in the brain may play an important role in sex-differential prevalence of neuropsychiatric conditions.

Core biomarkers for Alzheimer's disease (AD), such as Aβ42 and tau, have demonstrated high prognostic accuracy but do not fully capture the complex pathophysiology of AD. In this study, our objective was to identify novel cerebrospinal fluid (CSF) biomarkers using proteomics across the entire AD continuum to predict conversion to AD and explore their involvement in AD pathogenesis.

Central nervous system infections have been suggested as a possible cause for neurodegenerative diseases, particularly sporadic cases. They trigger neuroinflammation which is considered integrally involved in neurodegenerative processes. In this review, we will look at data linking a variety of viral, bacterial, fungal, and protozoan infections to Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, multiple sclerosis and unspecified dementia. This narrative review aims to bring together a broad range of data currently supporting the involvement of central nervous system infections in the development of neurodegenerative diseases. The idea that no single pathogen or pathogen group is responsible for neurodegenerative diseases will be discussed. Instead, we suggest that a wide range of susceptibility factors may make individuals differentially vulnerable to different infectious pathogens and subsequent pathologies.

Freezing of gait (FOG) is a debilitating problem that markedly impairs the mobility and independence of 38-65% of people with Parkinson's disease. During a FOG episode, patients report that their feet are suddenly and inexplicably "glued" to the floor. The lack of a widely applicable, objective FOG detection method obstructs research and treatment. To address this problem, we organized a 3-month machine-learning contest, inviting experts from around the world to develop wearable sensor-based FOG detection algorithms. 1,379 teams from 83 countries submitted 24,862 solutions. The winning solutions demonstrated high accuracy, high specificity, and good precision in FOG detection, with strong correlations to gold-standard references. When applied to continuous 24/7 data, the solutions revealed previously unobserved patterns in daily living FOG occurrences. This successful endeavor underscores the potential of machine learning contests to rapidly engage AI experts in addressing critical medical challenges and provides a promising means for objective FOG quantification.

The retrosplenial cortex (RSC) is a hub of diverse afferent and efferent projections thought to be involved in associative learning. RSC shows early pathology in mild cognitive impairment (MCI) and Alzheimer's disease (AD), which impairs associative learning. To understand and develop therapies for diseases such as AD, animal models are essential. Given the importance of human RSC in object-location associative learning and the success of object-location associative paradigms in human studies and in the clinic, it would be of considerable value to establish a translational model of object-location learning for the rodent. For this reason, we sought to test the role of RSC in object-location learning in male rats using the object-location paired-associates learning (PAL) touchscreen task. First, increased cFos immunoreactivity was observed in granular RSC following PAL training when compared to extended pretraining controls. Following this, RSC lesions following PAL acquisition were used to explore the necessity of the RSC in object-location associative learning and memory, and two tasks involving only one modality: trial-unique nonmatching-to-location (TUNL) for spatial working memory and pairwise visual discrimination and reversal (PVD/PVR). RSC lesions impaired both memory for learned paired-associates, and learning of new object-location associations, but did not affect performance in either the spatial or visual single-modality tasks. These findings provide evidence that RSC is necessary for object-location learning and less so for learning and memory involving the individual modalities therein. Animal models are essential to understand and develop therapies for diseases such as Alzheimer's disease (AD). Given the importance of human retrosplenial cortex (RSC) in object-location associative learning and the success of these paradigms in human studies and in the clinic, it is of considerable value to establish a translational model of object-location learning for the rodent. We determined that lesions of the RSC in male rats following object-location paired-associates learning led to impairments in object-location associative memory and new learning but did not affect performance on tasks of the individual modalities (i.e. spatial and visual). These findings further validate the touchscreen PAL test as a viable translational test for modelling diseases, such as AD, in which RSC is compromised.

Perineuronal nets (PNN) are specialized extracellular matrix (ECM) components of the central nervous system, frequently accumulating at the surface of inhibitory GABAergic interneurons. While an altered distribution of PNN has been observed in neurological disorders including Alzheimer's disease, schizophrenia and epilepsy, their anatomical distribution also changes during physiological brain maturation and aging. Such an age-dependent shift was experimentally associated also with hippocampal engram formation during brain maturation. Our aim was to histopathologically assess PNN in the hippocampus of adult and pediatric patients with temporal lobe epilepsy (TLE) compared to age-matched post-mortem control subjects and to compare PNN-related changes with memory impairment observed in our patient cohort.

Tensor-based representations are being increasingly used to represent complex data types such as imaging data, due to their appealing properties such as dimension reduction and the preservation of spatial information. Recently, there is a growing literature on using Bayesian scalar-on-tensor regression techniques that use tensor-based representations for high-dimensional and spatially distributed covariates to predict continuous outcomes. However surprisingly, there is limited development on corresponding Bayesian classification methods relying on tensor-valued covariates. Standard approaches that vectorize the image are not desirable due to the loss of spatial structure, and alternate methods that use extracted features from the image in the predictive model may suffer from information loss. We propose a novel data augmentation-based Bayesian classification approach relying on tensor-valued covariates, with a focus on imaging predictors. We propose two data augmentation schemes, one resulting in a support vector machine (SVM) type of classifier, and another yielding a logistic regression classifier. While both types of classifiers have been proposed independently in literature, our contribution is to extend such existing methodology to accommodate high-dimensional tensor valued predictors that involve low rank decompositions of the coefficient matrix while preserving the spatial information in the image. An efficient Markov chain Monte Carlo (MCMC) algorithm is developed for implementing these methods. Simulation studies show significant improvements in classification accuracy and parameter estimation compared to routinely used classification methods. We further illustrate our method in a neuroimaging application using cortical thickness MRI data from Alzheimer's Disease Neuroimaging Initiative, with results displaying better classification accuracy throughout several classification tasks, including classification on pairs of the three diagnostic groups: normal control, AD patients, and MCI patients; gender classification (males vs females); and cognitive performance based on high and low levels of MMSE scores.

The basolateral amygdala (BLA) is the subregion of the amygdala located in the medial of the temporal lobe, which is connected with a wide range of brain regions to achieve diverse functions. Recently, an increasing number of studies have focused on the participation of the BLA in many neuropsychiatric disorders from the neural circuit perspective, aided by the rapid development of viral tracing methods and increasingly specific neural modulation technologies. However, how to translate this circuit-level preclinical intervention into clinical treatment using noninvasive or minor invasive manipulations to benefit patients struggling with neuropsychiatric disorders is still an inevitable question to be considered. In this review, we summarized the role of BLA-involved circuits in neuropsychiatric disorders including Alzheimer's disease, perioperative neurocognitive disorders, schizophrenia, anxiety disorders, depressive disorders, posttraumatic stress disorders, autism spectrum disorders, and pain-associative affective states and cognitive dysfunctions. Additionally, we provide insights into future directions and challenges for clinical translation.

In this study, we report the cardioprotective effect of the glycerol monooleate (GMO) based nanocurcumin in both in vitro and in vivo conditions under a hyperthyroid state. The heart is one of the primary target organs sensitive to the action of thyroid hormone, and slight variations in the thyroid hormone serum concentrations result in measurable changes in cardiac performance. Hyperthyroidism-induced hypermetabolism is associated with oxidative stress and is an important mechanism responsible for the progression of heart failure. Curcumin has been known to play a protective role against oxidative stress-related diseases like Alzheimer's, asthma, and aging due to its antioxidant properties. Nevertheless, its potent biological activity has been hindered due to its poor bioavailability. To overcome this drawback, a GMO-based biodegradable nanoparticle (NP) formulation loaded with curcumin has been developed, and the protective effect of curcumin-loaded NPs was compared against the native drug. Oxidative stress parameters like reactive oxygen species (ROS) release, change in mitochondrial membrane permeability, lipid peroxidation (LPx), lactate dehydrogenase (LDH) release, and the activity and protein expression of the endogenous antioxidant enzymes like superoxide dismutase, catalase (CAT) and glutathione peroxidase were evaluated. The results from in vitro showed that curcumin-loaded NPs showed better DPPH and NO radical scavenging activity than native curcumin in a concentrations range of 2.5-20 µM. It was also observed that the nanoparticulate curcumin was comparatively more effective than native curcumin in protecting against ROS-induced membrane damage by reducing LPx and LDH leakage at low concentrations of 5-10 µM. Further, curcumin NPs performed better in facilitating the activities of antioxidant enzymes under in vitro and in vivo conditions with respect to time and concentrations, resulting in reduced cellular ROS levels. In this scenario, we anticipate that curcumin-loaded NPs can serve as a better antioxidant than its native counterpart in protecting the heart from oxidative stress-related diseases.

Routine ambulatory care is essential for older adults with Alzheimer's disease and related dementias (ADRD) to manage their health conditions. The federal government expanded telemedicine coverage to mitigate the impact of the COVID-19 pandemic on ambulatory services, which may provide an opportunity to improve access to care. This study aims to examine differences in telemedicine use for ambulatory services by race, ethnicity, and community-level socioeconomic status among community-dwelling older adults with ADRD.

The cognitive decline induced by Alzheimer's disease (AD) is closely related to changes in hippocampal structure captured by magnetic resonance imaging (MRI). To accurately analyze the morphological changes of the hippocampus induced by AD, it is necessary to establish a one-to-one surface correspondence to compare the morphological measurements across different hippocampal surfaces. However, most existing landmark-based registration methods cannot satisfy both landmark matching and diffeomorphism under large deformations. To address these challenges, we propose a landmark-based spherical registration method via quasi-conformal mapping to establish a one-to-one correspondence between different hippocampal surfaces.

In this chapter, we consider lack of racial, ethnic, and geographic diversity in research studies from a public health perspective in which representation of a target population is critical. We review the state of the research field with respect to racial, ethnic, and geographic diversity in study participants. We next focus on key factors which can arise from the lack of diversity and can negatively impact external validity. Finally, we argue that the public's health, and future research, will ultimately be served by approaches from both recruitment and representation science and population neuroscience, and we close with recommendations from these two fields to improve diversity in studies.

The central nervous system, information integration center of the body, is mainly composed of neurons and glial cells. The neuron is one of the most basic and important structural and functional units of the central nervous system, with sensory stimulation and excitation conduction functions. Astrocytes and microglia belong to the glial cell family, which is the main source of cytokines and represents the main defense system of the central nervous system. Nerve cells undergo neurotransmission or gliotransmission, which regulates neuronal activity via the ion channels, receptors, or transporters expressed on nerve cell membranes. Ion channels, composed of large transmembrane proteins, play crucial roles in maintaining nerve cell homeostasis. These channels are also important for control of the membrane potential and in the secretion of neurotransmitters. A variety of cellular functions and life activities, including functional regulation of the central nervous system, the generation and conduction of nerve excitation, the occurrence of receptor potential, heart pulsation, smooth muscle peristalsis, skeletal muscle contraction, and hormone secretion, are closely related to ion channels associated with passive transmembrane transport. Two types of ion channels in the central nervous system, potassium channels and calcium channels, are closely related to various neurological disorders, including Alzheimer's disease, Parkinson's disease, and epilepsy. Accordingly, various drugs that can affect these ion channels have been explored deeply to provide new directions for the treatment of these neurological disorders. In this review, we focus on the functions of potassium and calcium ion channels in different nerve cells and their involvement in neurological disorders such as Parkinson's disease, Alzheimer's disease, depression, epilepsy, autism, and rare disorders. We also describe several clinical drugs that target potassium or calcium channels in nerve cells and could be used to treat these disorders. We concluded that there are few clinical drugs that can improve the pathology these diseases by acting on potassium or calcium ions. Although a few novel ion-channel- specific modulators have been discovered, meaningful therapies have largely not yet been realized. The lack of target-specific drugs, their requirement to cross the blood-brain barrier, and their exact underlying mechanisms all need further attention. This review aims to explain the urgent problems that need research progress and provide comprehensive information aiming to arouse the research community's interest in the development of ion channel-targeting drugs and the identification of new therapeutic targets for that can increase the cure rate of nervous system diseases and reduce the occurrence of adverse reactions in other systems.

Alzheimer's disease (AD) is the most common type of human dementia and is responsible for over 60% of diagnosed dementia cases worldwide. Abnormal deposition of β-amyloid and the accumulation of neurofibrillary tangles have been recognised as the two pathological hallmarks targeted by AD diagnostic imaging as well as therapeutics. With the progression of pathological studies, the two hallmarks and their related pathways have remained the focus of researchers who seek for AD diagnostic and therapeutic strategies in the past decades. In this work, we reviewed the development of the AD biomarkers and their corresponding target-specific small molecule drugs for both diagnostic and therapeutic applications, underlining their success, failure, and future possibilities.

N6-methyladenosine (m6A), the most prevalent and conserved RNA modification in eukaryotic cells, profoundly influences virtually all aspects of mRNA metabolism. mRNA plays crucial roles in neural stem cell genesis and neural regeneration, where it is highly concentrated and actively involved in these processes. Changes in m6A modification levels and the expression levels of related enzymatic proteins can lead to neurological dysfunction and contribute to the development of neurological diseases. Furthermore, the proliferation and differentiation of neural stem cells, as well as nerve regeneration, are intimately linked to memory function and neurodegenerative diseases. This paper presents a comprehensive review of the roles of m6A in neural stem cell proliferation, differentiation, and self-renewal, as well as its implications in memory and neurodegenerative diseases. m6A has demonstrated divergent effects on the proliferation and differentiation of neural stem cells. These observed contradictions may arise from the time-specific nature of m6A and its differential impact on neural stem cells across various stages of development. Similarly, the diverse effects of m6A on distinct types of memory could be attributed to the involvement of specific brain regions in memory formation and recall. Inconsistencies in m6A levels across different models of neurodegenerative disease, particularly Alzheimer's disease and Parkinson's disease, suggest that these disparities are linked to variations in the affected brain regions. Notably, the opposing changes in m6A levels observed in Parkinson's disease models exposed to manganese compared to normal Parkinson's disease models further underscore the complexity of m6A's role in neurodegenerative processes. The roles of m6A in neural stem cell proliferation, differentiation, and self-renewal, and its implications in memory and neurodegenerative diseases, appear contradictory. These inconsistencies may be attributed to the time- specific nature of m6A and its varying effects on distinct brain regions and in different environments.

Alzheimer's Disease (AD) pathology has been increasingly explored through single-cell and single-nucleus RNA-sequencing (scRNA-seq & snRNA-seq) and spatial transcriptomics (ST). However, the surge in data demands a comprehensive, user-friendly repository. Addressing this, we introduce a single-cell and spatial RNA-seq database for Alzheimer's disease (ssREAD). It offers a broader spectrum of AD-related datasets, an optimized analytical pipeline, and improved usability. The database encompasses 1,053 samples (277 integrated datasets) from 67 AD-related scRNA-seq & snRNA-seq studies, totaling 7,332,202 cells. Additionally, it archives 381 ST datasets from 18 human and mouse brain studies. Each dataset is annotated with details such as species, gender, brain region, disease/control status, age, and AD Braak stages. ssREAD also provides an analysis suite for cell clustering, identification of differentially expressed and spatially variable genes, cell-type-specific marker genes and regulons, and spot deconvolution for integrative analysis. ssREAD is freely available at https://bmblx.bmi.osumc.edu/ssread/ .

The microtubule-associated protein Tau is a key player in various neurodegenerative conditions, including Alzheimer's disease (AD) and Tauopathies, where its hyperphosphorylation disrupts neuronal microtubular lattice stability. Glaucoma, a neurodegenerative disorder affecting the retina, leads to irreversible vision loss by damaging retinal ganglion cells and the optic nerve, often associated with increased intraocular pressure. Prior studies have indicated Tau expression and phosphorylation alterations in the retina in both AD and glaucoma, yet the causative or downstream nature of Tau protein changes in these pathologies remains unclear. This study investigates the impact of Tau protein modulation on retinal neurons under normal and experimental glaucoma conditions. Employing AAV9-mediated gene therapy for Tau overexpression and knockdown, both manipulations were found to adversely affect retinal structural and functional measures as well as neuroprotective Akt/Erk survival signalling in healthy conditions. In the experimental glaucoma model, Tau overexpression intensified inner retinal degeneration, while Tau silencing provided significant protection against these degenerative changes. These findings underscore the critical role of endogenous Tau protein levels in preserving retinal integrity and emphasize the therapeutic potential of targeting Tau in glaucoma pathology.

The direct access of olfactory afferents to memory-related cortical systems has inspired theories about the role of the olfactory pathways in the development of cortical neurodegeneration in Alzheimer's disease (AD). In this study, we used baseline olfactory identification measures with longitudinal flortaucipir and PiB PET, diffusion MRI of 89 cognitively normal older adults (73.82 ± 8.44 years; 56% females), and a transcriptomic data atlas to investigate the spatiotemporal spreading and genetic vulnerabilities of AD-related pathology aggregates in the olfactory system. We find that odor identification deficits are predominantly associated with tau accumulation in key areas of the olfactory pathway, with a particularly strong predictive power for longitudinal tau progression. We observe that tau spreads from the medial temporal lobe structures toward the olfactory system, not the reverse. Moreover, we observed a genetic background of odor perception-related genes that might confer vulnerability to tau accumulation along the olfactory system.

High TRABD expression is associated with tau pathology in patients with Alzheimer's disease; however, the function of TRABD is unknown. Human TRABD encodes a mitochondrial outer-membrane protein. The loss of TRABD resulted in mitochondrial fragmentation, and TRABD overexpression led to mitochondrial clustering and fusion. The C-terminal tail of the TRABD anchored to the mitochondrial outer membrane and the TraB domain could form homocomplexes. Additionally, TRABD forms complexes with MFN2, MIGA2, and PLD6 to facilitate mitochondrial fusion. Flies lacking dTRABD are viable and have normal lifespans. However, aging flies exhibit reduced climbing ability and abnormal mitochondrial morphology in their muscles. The expression of dTRABD is increased in aged flies. dTRABD overexpression leads to neurodegeneration and enhances tau toxicity in fly eyes. The overexpression of dTRABD also increased reactive oxygen species (ROS), ATP production, and protein turnover in the mitochondria. This study suggested that TRABD-induced mitochondrial malfunctions contribute to age-related neurodegeneration.

A new class of antibody-based drug therapy with the potential for disease modification is now available for Alzheimer's disease (AD). However, the complexity of drug eligibility, administration, cost, and safety of such disease modifying therapies (DMTs) necessitates adopting new treatment and care pathways. A working group was convened in Ireland to consider the implications of, and health system readiness for, DMTs for AD, and to describe a service model for the detection, diagnosis, and management of early AD in the Irish context, providing a template for similar small-medium sized healthcare systems.

Alzheimer's disease (AD), one of the neurodegenerative disorders, is highly correlated with the abnormal hyperphosphorylation of Tau and aggregation of β-amyloid (Aβ). Oxidative stress, neuroinflammation, and abnormal autophagy are key drivers of AD and how they contribute to neuropathology remains largely unknown. The flavonoid compound pongamol is reported to possess a variety of pharmacological activities, such as antioxidant, antibacterial, and anti-inflammatory. This study investigated the neuroprotective effect and its mechanisms of pongamol in lipopolysaccharide (LPS)-induced BV2 cells, d-galactose/sodium nitrite/aluminum chloride (d-gal/NaNO/AlCl)-induced AD mice, and models. Our research revealed that pongamol reduced the release of inflammatory factors IL-1β, TNF-α, COX-2, and iNOS in LPS-induced BV2 cells. Pongamol also protected neurons and significantly restored memory function, inhibited Tau phosphorylation, downregulated Aβ aggregation, and increased oxidoreductase activity in the hippocampus of AD mice. In addition, pongamol reversed the nuclear transfer of NF-κB and increased the levels of Beclin 1 and LC3 II/LC3 I. Most importantly, the anti-inflammatory and promoter autophagy effects of pongamol may be related to the regulation of the Akt/mTOR signaling pathway. In summary, these results showed that pongamol has a potential neuroprotective effect, which greatly enriched the research on the pharmacological activity of pongamol for improving AD.

The current study aims to investigate the association of serum brain-derived neurotrophic factor (BDNF) levels with symptoms of depression in adults with and without prevalent cardiovascular disease (CVD), an often burdensome comorbidity.

We investigated the effect vigorous physical activity (VPA) on the risk of incident mild cognitive impairment (MCI) and probable dementia among individuals with high-risk hypertension.

As the world's population ages, Alzheimer's disease is currently the seventh most common cause of death globally; the burden is anticipated to increase, especially among middle-class and elderly persons. Artificial intelligence-based algorithms that work well in hospital environments can be used to identify Alzheimer's disease. A number of databases were searched for English-language articles published up until March 1, 2024, that examined the relationships between artificial intelligence techniques, eye movements, and Alzheimer's disease. A novel non-invasive method called eye movement analysis may be able to reflect cognitive processes and identify anomalies in Alzheimer's disease. Artificial intelligence, particularly deep learning, and machine learning, is required to enhance Alzheimer's disease detection using eye movement data. One sort of deep learning technique that shows promise is convolutional neural networks, which need further data for precise classification. Nonetheless, machine learning models showed a high degree of accuracy in this context. Artificial intelligence-driven eye movement analysis holds promise for enhancing clinical evaluations, enabling tailored treatment, and fostering the development of early and precise Alzheimer's disease diagnosis. A combination of artificial intelligence-based systems and eye movement analysis can provide a window for early and non-invasive diagnosis of Alzheimer's disease. Despite ongoing difficulties with early Alzheimer's disease detection, this presents a novel strategy that may have consequences for clinical evaluations and customized medication to improve early and accurate diagnosis.

Loss-of-function mutations in the progranulin (GRN) gene are an autosomal dominant cause of Frontotemporal Dementia (FTD). These mutations typically result in haploinsufficiency of the progranulin protein. Grn mice provide a model for progranulin haploinsufficiency and develop FTD-like behavioral abnormalities by 9-10 months of age. In previous work, we demonstrated that Grn mice develop a low dominance phenotype in the tube test that is associated with reduced dendritic arborization of layer II/III pyramidal neurons in the prelimbic region of the medial prefrontal cortex (mPFC), a region key for social dominance behavior in the tube test assay. In this study, we investigated whether progranulin haploinsufficiency induced changes in dendritic spine density and morphology. Individual layer II/III pyramidal neurons in the prelimbic mPFC of 9-10 month old wild-type or Grn mice were targeted for iontophoretic microinjection of fluorescent dye, followed by high-resolution confocal microscopy and 3D reconstruction for morphometry analysis. Dendritic spine density in Grn mice was comparable to wild-type littermates, but the apical dendrites in Grn mice had a shift in the proportion of spine types, with fewer stubby spines and more thin spines. Additionally, apical dendrites of Grn mice had longer spines and smaller thin spine head diameter in comparison to wild-type littermates. These changes in spine morphology may contribute to altered circuit-level activity and social dominance deficits in Grn mice.

The reason-related identification of mild cognitive impairment (MCI) in primary care is helpful to treat reversible causes or decelerate progression to dementia by optimal management of existing risk factors. In this process general practitioners are in a key position. The present feasibility study investigated the practicability of a diagnostic algorithm (brain check-up), comprising neuropsychological examinations, differential diagnoses and follow-up measures.

The prevention of thromboembolism in atrial fibrillation (AF) is typically restricted to patients with specific risk factors and ignores outcomes such as vascular dementia. This population-based cohort study used electronic healthcare records from 5,199,994 primary care patients (UK; 2005-2020). A total of 290,525 (5.6%) had a diagnosis of AF and were aged 40-75 years, of which 36,340 had no history of stroke, a low perceived risk of stroke based on clinical risk factors and no oral anticoagulant prescription. Matching was performed for age, sex and region to 117,298 controls without AF. During 5 years median follow-up (831,005 person-years), incident stroke occurred in 3.8% with AF versus 1.5% control (adjusted hazard ratio (HR) 2.06, 95% confidence interval (CI) 1.91-2.21; P < 0.001), arterial thromboembolism 0.3% versus 0.1% (HR 2.39, 95% CI 1.83-3.11; P < 0.001), and all-cause mortality 8.9% versus 5.0% (HR 1.44, 95% CI 1.38-1.50; P < 0.001). AF was associated with all-cause dementia (HR 1.17, 95% CI 1.04-1.32; P = 0.010), driven by vascular dementia (HR 1.68, 95% CI 1.33-2.12; P < 0.001) rather than Alzheimer's disease (HR 0.85, 95% CI 0.70-1.03; P = 0.09). Death and thromboembolic outcomes, including vascular dementia, are substantially increased in patients with AF despite a lack of conventional stroke risk factors.

Acetylcholinesterase (AChE) inhibitors are still an important option for managing symptoms of mild to moderate Alzheimer's disease. In this study, we aimed to evaluate the potential AChE inhibitory activity of two Argentinian endemic Solanaceae species, and . UHPLC-DAD-HRMS metabolite profiling revealed the presence of withanolides in the active CHCl subextracts. Their fractionation led to the isolation and identification of two known spiranoid withanolides from and three new withanolides with a skeleton similar to that of trechonolide-type withanolides from . The known compounds showed moderate AChE inhibitory activity, while the new ones were inactive.

Sporadic Alzheimer's disease (AD) and autosomal dominant Alzheimer's disease (ADAD) share pathological features, but differing mechanisms, leading to disease. In this issue of Neuron, Almeida, Eger, et al. uncovered molecular processes that may distinguish sporadic AD from ADAD and how the APOE-Christchurch variant may be protective.

The purpose of this study was to identify the most parsimonious combination of cognitive tests that accurately predicts the likelihood of passing an on-road driving evaluation in order to develop a screening measure that can be administered as an in-office test.

During the COVID-19 pandemic, home health agencies (HHAs) discharges following acute hospitalizations increased. This study examined whether racial and ethnic minoritized and socioeconomically disadvantaged patients (ie, Medicare-Medicaid dual-eligible) were differentially discharged to below-average quality HHAs before and during the COVID-19 pandemic. We focused on post-acute patients with Alzheimer's disease and related dementias (ADRD), who are generally frail and have high care needs.

Astaxanthin is a potent lipid-soluble carotenoid produced by several different freshwater and marine microorganisms, including microalgae, bacteria, fungi, and yeast. The proven therapeutic effects of astaxanthin against different diseases have made this carotenoid popular in the nutraceutical market and among consumers. Recently, astaxanthin is also receiving attention for its effects in the co-adjuvant treatment or prevention of neurological pathologies. In this systematic review, studies evaluating the efficacy of astaxanthin against different neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, cerebrovascular diseases, and spinal cord injury are analyzed. Based on the current literature, astaxanthin shows potential biological activity in both in vitro and in vivo models. In addition, its preventive and therapeutic activities against the above-mentioned diseases have been emphasized in studies with different experimental designs. In contrast, none of the 59 studies reviewed reported any safety concerns or adverse health effects as a result of astaxanthin supplementation. The preventive or therapeutic role of astaxanthin may vary depending on the dosage and route of administration. Although there is a consensus in the literature regarding its effectiveness against the specified diseases, it is important to determine the safe intake levels of synthetic and natural forms and to determine the most effective forms for oral intake.

Timely diagnosis and prognostication of Alzheimer's disease (AD) and mild cognitive impairment (MCI) are pivotal for effective intervention. Artificial intelligence (AI) in neuroradiology may aid in such appropriate diagnosis and prognostication. This study aimed to evaluate the potential of novel diffusion model-based AI for enhancing AD and MCI diagnosis through superresolution (SR) of brain magnetic resonance (MR) images.

Parkinson's is the most common neurodegenerative disease after Alzheimer's. Motor findings in Parkinson's occur as a result of the degeneration of dopaminergic neurons starting in the substantia nigra pars compacta and ending in the putamen and caudate nucleus. Loss of neurons and the formation of inclusions called Lewy bodies in existing neurons are characteristic histopathological findings of Parkinson's. The disease primarily impairs the functional capacity of the person with cardinal findings such as tremor, bradykinesia, etc., as a result of the loss of dopaminergic neurons in the substantia nigra. Experimental animal models of Parkinson's have been used extensively in recent years to investigate the pathology of this disease. These models are generally based on systemic or local(intracerebral) administration of neurotoxins, which can replicate many features of Parkinson's mammals. The development of transgenic models in recent years has allowed us to learn more about the modeling of Parkinson's. Applying animal modeling, which shows the most human-like effects in studies, is extremely important. It has been demonstrated that oxidative stress increases in many neurodegenerative diseases such as Parkinson's and various age-related degenerative diseases in humans and that neurons are sensitive to it. In cases where oxidative stress increases and antioxidant systems are inadequate, natural molecules such as flavonoids and polyphenols can be used as a new antioxidant treatment to reduce neuronal reactive oxygen species and improve the neurodegenerative process. Therefore, in this article, we examined experimental animal modeling in Parkinson's disease and the effect of green chemistry approaches on Parkinson's disease.

Visual attention-related processes that underlie visual search behavior are impaired in both the early stages of Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI), which is considered a risk factor for AD. Although traditional computer-based array tasks have been used to investigate visual search, information on the visual search patterns of AD and MCI patients in real-world environments is limited.

Alzheimer's disease (AD), gradually recognized as an untreatable neurodegenerative disorder, has been considered to be closely associated with Aβ plaques, which consist of β-amyloid protein (Aβ) and is one of the crucial pathological features of AD. There are no obvious symptoms in the initial phase of AD, and thus the therapeutic interventions are important for early diagnosis of AD. Moreover, recent researches have indicated that lipid droplets might serve as a potential ancillary biomarker, and its viscosity changes are closely associated to the pathological process of AD. Herein, two newly fluorescent probes 5QSZ and BQSZ have been developed and synthesized for identifying Aβ aggregates and detecting the viscosity of lipid droplet. After selectively binding to Aβ aggregates, 5QSZ and BQSZ exhibited linear and obvious fluorescence enhancements (32.58 and 36.70 folds), moderate affinity (K = 268.0 and 148.6 nM) and low detection limits (30.11 and 65.37 nM) in aqueous solutions. Further fluorescence staining of 5QSZ on brain tissue sections of APP/PS1 transgenic mouse exhibited the higher selectivity of 5QSZ towards Aβ aggregates locating at the core of the plaques. Furthermore, 5QSZ and BQSZ displayed strong linear fluorescence emission enhancements towards viscosity changes and would be utilized to monitor variation in cellular viscosity induced by LPS or monensin. These two probes were non-cytotoxic and showed good localization in lipid droplets. Therefore, 5QSZ and BQSZ could serve as potential bi-functional fluorescent probes to image Aβ aggregates and monitor the viscosity of lipid droplets, which have significant implications for the early diagnosis and progression of AD.

Increasingly, dementia caregiver interventions are informed by acceptance-based approaches such as Acceptance and Commitment Therapy. These interventions promote psychological skills like psychological flexibility and value-based living. Less is known how these constructs interact within well-established caregiver stress processes. We examined a moderated mediation model (N = 161 dementia caregivers; PROCESS Procedure; SPSS Release 4.1), with BPSD frequency (Revised Memory and Behavior Problems Checklist) predicting depressive symptoms (10-item CES-D), mediated via caregiver burden (short Burden inventory). The moderator was the Values Questionnaire, and we controlled for gender, caregiver duration, age, income, and education. Results: revealed that the indirect effect of BPSD on depressive symptoms through caregiver burden was weakened through higher progress toward values (moderated mediation significant at p < .05). Committed action toward values signify caregivers' success at balancing care-related stress with other priorities. Interventions that build skills in values-based living have promise for caregivers, offering healthier ways to adjust to being a caregiver.

Brain insulin resistance links the failure of energy metabolism with cognitive decline in both type 2 Diabetes Mellitus (T2D) and Alzheimer's disease (AD), although the molecular changes preceding overt brain insulin resistance remain unexplored. Abnormal biliverdin reductase-A (BVR-A) levels were observed in both T2D and AD and were associated with insulin resistance. Here, we demonstrate that reduced BVR-A levels alter insulin signaling and mitochondrial bioenergetics in the brain. Loss of BVR-A leads to IRS1 hyper-activation but dysregulates Akt-GSK3β complex in response to insulin, hindering the accumulation of pGSK3β into the mitochondria. This event impairs oxidative phosphorylation and fosters the activation of the mitochondrial Unfolded Protein Response (UPRmt). Remarkably, we unveil that BVR-A is required to shuttle pGSK3β into the mitochondria. Our data sheds light on the intricate interplay between insulin signaling and mitochondrial metabolism in the brain unraveling potential targets for mitigating the development of brain insulin resistance and neurodegeneration.

We aimed to characterize the cognitive profile of post-acute COVID-19 syndrome (PACS) patients with cognitive complaints, exploring the influence of biological and psychological factors. Participants with confirmed SARS-CoV-2 infection and cognitive complaints ≥ 8 weeks post-acute phase were included. A comprehensive neuropsychological battery (NPS) and health questionnaires were administered at inclusion and at 1, 3 and 6 months. Blood samples were collected at each visit, MRI scan at baseline and at 6 months, and, optionally, cerebrospinal fluid. Cognitive features were analyzed in relation to clinical, neuroimaging, and biochemical markers at inclusion and follow-up. Forty-nine participants, with a mean time from symptom onset of 10.4 months, showed attention-executive function (69%) and verbal memory (39%) impairment. Apathy (64%), moderate-severe anxiety (57%), and severe fatigue (35%) were prevalent. Visual memory (8%) correlated with total gray matter (GM) and subcortical GM volume. Neuronal damage and inflammation markers were within normal limits. Over time, cognitive test scores, depression, apathy, anxiety scores, MRI indexes, and fluid biomarkers remained stable, although fewer participants (50% vs. 75.5%; p = 0.012) exhibited abnormal cognitive evaluations at follow-up. Altered attention/executive and verbal memory, common in PACS, persisted in most subjects without association with structural abnormalities, elevated cytokines, or neuronal damage markers.

Among gene mutations and variants linked to an increased risk of PD, mutations of leucine-rich repeat kinase 2 gene (LRRK2) are among the most frequently associated with early- and late-onset PD. Clinical and neuropathological characteristics of idiopathic-PD (iPD) and LRRK2-PD are similar, and these similarities suggest that the pathomechanisms between these two conditions are shared. LRRK2 mutations determine a gain-of-function and yield higher levels of lrrk2 across body tissues, including brain. On another side, recent animal studies supported the potential use of low dose radiation (LDR) to modify the pathomechanisms of diseases such as Alzheimer's disease (AD).

The categorization of human diseases is mainly based on the affected organ system and phenotypic characteristics. This is limiting the view to the pathological manifestations, while it neglects mechanistic relationships that are crucial to develop therapeutic strategies. This work aims to advance the understanding of diseases and their relatedness beyond traditional phenotypic views. Hence, the similarity among 502 diseases is mapped using six different data dimensions encompassing molecular, clinical, and pharmacological information retrieved from public sources. Multiple distance measures and multi-view clustering are used to assess the patterns of disease relatedness. The integration of all six dimensions into a consensus map of disease relationships reveals a divergent disease view from the International Classification of Diseases (ICD), emphasizing novel insights offered by a multi-view disease map. Disease features such as genes, pathways, and chemicals that are enriched in distinct disease groups are identified. Finally, an evaluation of the top similar diseases of three candidate diseases common in the Western population shows concordance with known epidemiological associations and reveals rare features shared between Type 2 diabetes (T2D) and Alzheimer's disease. A revision of disease relationships holds promise for facilitating the reconstruction of comorbidity patterns, repurposing drugs, and advancing drug discovery in the future.

The World Health Organization recently released a novel metric for healthy aging: intrinsic capacity (IC). The relationship between IC and the incidence of dementia, and its subtypes, is unknown. We aimed to analyze the relationship between IC and the incidence of dementia and its subtypes. Moreover, we tested whether genetic susceptibility to dementia could be modified by IC.

Migraine is a neurological disease with a significant genetic component and is characterized by recurrent and prolonged episodes of headache. Previous epidemiological studies have reported a higher risk of dementia in migraine patients. Neuroimaging studies have also shown structural brain atrophy in regions that are common to migraine and dementia. However, these studies are observational and cannot establish causality. The present study aims to explore the genetic causal relationship between migraine and dementia, as well as the mediation roles of brain structural changes in this association using Mendelian randomization (MR).

The development of glucagon-like peptide 1 receptor agonists (GLP-1RA) for type 2 diabetes and obesity was followed by data establishing the cardiorenal benefits of GLP-1RA in select patient populations. In ongoing trials investigators are interrogating the efficacy of these agents for new indications, including metabolic liver disease, peripheral artery disease, Parkinson disease, and Alzheimer disease. The success of GLP-1-based medicines has spurred the development of new molecular entities and combinations with unique pharmacokinetic and pharmacodynamic profiles, exemplified by tirzepatide, a GIP-GLP-1 receptor coagonist. Simultaneously, investigational molecules such as maritide block the GIP and activate the GLP-1 receptor, whereas retatrutide and survodutide enable simultaneous activation of the glucagon and GLP-1 receptors. Here I highlight evidence establishing the efficacy of GLP-1-based medicines, while discussing data that inform safety, focusing on muscle strength, bone density and fractures, exercise capacity, gastrointestinal motility, retained gastric contents and anesthesia, pancreatic and biliary tract disorders, and the risk of cancer. Rapid progress in development of highly efficacious GLP-1 medicines, and anticipated differentiation of newer agents in subsets of metabolic disorders, will provide greater opportunities for use of personalized medicine approaches to improve the health of people living with cardiometabolic disorders.

To examine the associations of Life's Essential 8 (LE8) and its predictive performance with mild cognitive impairment (MCI), dementia and brain MRI indices.

Alzheimer's disease (AD) is the most common cause of dementia, and the gradual deterioration of brain function eventually leads to death. Almost all AD patients suffer from neuropsychiatric symptoms (NPS), the emergence of which correlates with dysfunctional serotonergic systems. Our aim is to generate hindbrain organoids containing serotonergic neurons using human induced Pluripotent Stem Cells (iPSCs). Work presented here is laying the groundwork for the application of hindbrain organoids to evaluate individual differences in disease progression, NPS development, and pharmacological treatment response. Human peripheral blood mononuclear cells (PBMCs) from healthy volunteers (n = 3), an AD patient without NPS (n = 1), and AD patients with NPS (n = 2) were reprogrammed into iPSCs and subsequently differentiated into hindbrain organoids. The presence of serotonergic neurons was confirmed by quantitative reverse transcription PCR, flow cytometry, immunocytochemistry, and detection of released serotonin (5-HT). We successfully reprogrammed PBMCs into 6 iPSC lines, and subsequently generated hindbrain organoids from 6 individuals to study inter-patient variability using a precision medicine approach. To assess patient-specific treatment effects, organoids were treated with different concentrations of escitalopram oxalate, commonly prescribed for NPS. Changes in 5-HT levels before and after treatment with escitalopram were dose-dependent and variable across patients. Organoids from different people responded differently to the application of escitalopram in vitro. We propose that this 3D platform might be effectively used for drug screening purposes to predict patients with NPS most likely to respond to treatment in vivo and to understand the heterogeneity of treatment responses.

Oxidative stress (OS) plays an important role in the emergence and prevention of neurodegenerative diseases, such as Alzheimer's disease (AD). Excess reactive oxygen species (ROS) accumulated in a neuronal cell can lead to OS, producing cell injury and death. Seeking nanoantioxidants against AD-related oxidative stress has attracted a lot of attention, especially those potential antioxidant agents derived from natural polyphenols. However, the transformation of abundant plant polyphenols to antioxidative biomaterials against OS is still challenging. In this work, we report a new method to transform amorphous tannic acid (TA) into tailorable shaped ellagic acid (EA) crystalline particles without using an organic solvent. EA crystalline particles were generated from TA, which underwent a chemical transformation, metal phenolic coordination and acid-induced assembly process, and the size and shape could be controlled by varying the amount of acid. As-prepared EA crystalline particles showed excellent stability in water and lysosomal mimicking fluid and possess unique fluorescence properties and a strong response in mass spectrometry, which is beneficial for their imaging analysis in cells and tissues. More importantly, EA particles have shown significant HO-related ROS scavenging ability, a high cellular uptake capacity, an excellent neuroprotective effect in PC12 cells, a high drug loading capacity and BBB permeability to enter the brain. Our study suggested that the EA crystalline particles show great potential for OS-mediated AD treatment.

The high-profile paper contains manipulated images, senior author acknowledges.

To successfully develop disease-modifying therapies (DMT) against Alzheimer's disease (AD), it is important to target the mild stage of the disease, before the pathological changes progress and dementia symptoms are fully manifested. To this end, the AD Neuroimaging Initiative (ADNI), a large-scale observational study, was initiated in the U.S. with the goal of development of DMT that are effective in the early stages of mild cognitive impairment (MCI) by utilizing imaging and biomarkers. In Japan, J-ADNI enrolled and followed up 537 patients, mainly with MCI, and established a platform for evaluation including amyloid PET, and demonstrated a high similarity in the clinical course of amyloid-positive MCI (prodromal AD) in Japan and the U.S. In 2023, the anti-Aβ antibody lecanemab successfully completed a Phase III clinical trial for early AD (prodromal AD + mild AD dementia) and was granted regulatory approval and made available both in the US and Japan. Also, phase III trial of donanemab was completed successful. The J-TRC study was initiated in Japan as a "trial ready cohort (TRC)" consisting of participants who met the eligibility criteria for participation in preclinical and prodromal AD trials. Based on such a platform, the development of DMT for AD will progress more rapidly in the future.

The traditional Chinese herbal remedy Atractylodes macrocephala Koidz is renowned for its purported gastrointestinal regulatory properties and immune-enhancing capabilities. Atractylenolide III (ATL III), a prominent bioactive compound in Atractylodes macrocephala Koidz, has demonstrated significant pharmacological activities. However, its impact on neuroinflammation, oxidative stress, and therapeutic potential concerning Alzheimer's disease (AD) remain inadequately investigated.

A hypothetical concern has been raised that sacubitril/valsartan might cause cognitive impairment because neprilysin is one of several enzymes degrading amyloid-β peptides in the brain, some of which are neurotoxic and linked to Alzheimer-type dementia. To address this, we examined the effect of sacubitril/valsartan compared with valsartan on cognitive function in patients with heart failure with preserved ejection fraction in a prespecified substudy of PARAGON-HF (Prospective Comparison of Angiotensin Receptor Neprilysin Inhibitor With Angiotensin Receptor Blocker Global Outcomes in Heart Failure With Preserved Ejection Fraction).

Progressive difficulty in performing everyday functional activities is a key diagnostic feature of dementia syndromes. However, not much is known about the neural signature of functional decline, particularly during the very early stages of dementia. Early intervention before overt impairment is observed offers the best hope of reducing the burdens of Alzheimer disease (AD) and other dementias. However, to justify early intervention, those at risk need to be detected earlier and more accurately. The decline in complex daily function (CdF) such as managing medications has been reported to precede impairment in basic activities of daily living (eg, eating and dressing).

Cerebral specialization and interhemispheric cooperation are two vital features of the human brain. Their dysfunction may be associated with disease progression in patients with Alzheimer's disease (AD), which is featured as progressive cognitive degeneration and asymmetric neuropathology.

Alzheimer's disease (AD), an age-dependent devastating neuropsychiatric disorder, is a leading cause of learning, memory and intellectual disabilities. Current therapeutic approaches for the amelioration of the anomalies of AD are not effective.

Brain aging is a complex and heterogeneous process characterized by both structural and functional decline. This study aimed to establish a novel deep learning (DL) method for predicting brain age by utilizing structural and metabolic imaging data.

Liquid-liquid phase separation (LLPS) is common in the aggregation of proteins associated with neurodegenerative diseases. Many efforts have been made to reproduce crowded conditions with artificial polymeric materials to understand the effect of LLPS in physiological conditions with significantly highly concentrated proteins, such as intrinsically disordered proteins. Although the possibility that LLPS is involved in intracellular amyloid-β (Aβ) aggregation, a protein related to the pathogenesis of Alzheimer's disease, has been investigated, the relationship between LLPS and the aggregation of Aβ is poorly characterized. Thus, in this study, we mimicked the intracellular crowding environment using polyethylene glycol and dextran, used commonly as model polymers, to examine the relationship of Aβ with LLPS and aggregation dynamics . We confirmed that Aβ undergoes LLPS under specific polymer coexistence conditions. Moreover, the addition of different electrolytes modulated LLPS and fibril formation. These results suggest that hydrophobic and electrostatic interactions are the driving forces for the LLPS of Aβ. Similar to the role of the liposome interface, the interface of droplets induced by LLPS functioned as the site for heterogeneous nucleation. These findings offer valuable insights into the complex mechanisms of Aβ aggregation and may be useful in establishing therapeutic methods for Alzheimer's disease.

Only a third of individuals with mild cognitive impairment (MCI) progress to dementia of the Alzheimer's type (DAT). Identifying biomarkers that distinguish individuals with MCI who will progress to DAT (MCI-Converters) from those who will not (MCI-Non-Converters) remains a key challenge in the field. In our study, we evaluate whether the individual rates of loss of volumes of the Hippocampus and entorhinal cortex (EC) with age in the MCI stage can predict progression to DAT. Using data from 758 MCI patients in the Alzheimer's Disease Neuroimaging Database, we employ Linear Mixed Effects (LME) models to estimate individual trajectories of regional brain volume loss over 12 years on average. Our approach involves three key analyses: (1) mapping age-related volume loss trajectories in MCI-Converters and Non-Converters, (2) using logistic regression to predict progression to DAT based on individual rates of hippocampal and EC volume loss, and (3) examining the relationship between individual estimates of these volumetric changes and cognitive decline across different cognitive functions-episodic memory, visuospatial processing, and executive function. We find that the loss of Hippocampal volume is significantly more rapid in MCI-Converters than Non-Converters, but find no such difference in EC volumes. We also find that the rate of hippocampal volume loss in the MCI stage is a significant predictor of conversion to DAT, while the rate of volume loss in the EC and other additional regions is not. Finally, individual estimates of rates of regional volume loss in both the Hippocampus and EC, and other additional regions, correlate strongly with individual rates of cognitive decline. Across all analyses, we find significant individual variation in the initial volumes and the rates of changes in volume with age in individuals with MCI. This study highlights the importance of personalized approaches in predicting AD progression, offering insights for future research and intervention strategies.

This study examines the effectiveness of lupeol and metformin in a mouse model of dementia generated by intracerebroventricular streptozotocin (i.c.v., STZ). Dementia was induced in Swiss mice with the i.c.v. administration of STZ at a dosage of 3 mg/kg on the first and third day. The assessment of dementia involved an examination of the Morris Water Maze (MWM) performance, as well as a number of biochemical and histological studies. STZ treatment resulted in significant decrease in MWM performance; various biochemical alterations (increase in brain acetyl cholinesterase (AChE) activity, thiobarbituric acid reactive species (TBARS), nitrite/nitrate, and reduction in nuclear factor erythroid 2 related factor-2 (Nrf-2), reduced glutathione (GSH) levels) and neuroinflammation [increased myeloperoxidase (MPO) activity & neutrophil infiltration]. The administration of Lupeol (50 mg/kg & 100 mg/kg; p.o.) and Metformin (150 mg/kg & 300 mg/kg; p.o.) demonstrated a considerable reduction in the behavioral, biochemical, and histological alterations produced by STZ. Low dose combination of lupeol (50 mg/kg; p.o.) and Metformin (150 mg/kg; p.o.) produced more pronounced effect than that of high doses of either agent alone. It is concluded that Lupeol and Metformin has shown efficacy in dementia with possible synergism between the two and can be explored as potential therapeutic agents for managing dementia of Alzheimer's disease (AD) type.

Our current understanding of the spread and neurodegenerative effects of tau neurofibrillary tangles (NFTs) within the medial temporal lobe (MTL) during the early stages of Alzheimer's Disease (AD) is limited by the presence of confounding non-AD pathologies and the two-dimensional (2-D) nature of conventional histology studies. Here, we combine ex vivo MRI and serial histological imaging from 25 human MTL specimens to present a detailed, 3-D characterization of quantitative NFT burden measures in the space of a high-resolution, ex vivo atlas with cytoarchitecturally-defined subregion labels, that can be used to inform future in vivo neuroimaging studies. Average maps show a clear anterior to poster gradient in NFT distribution and a precise, spatial pattern with highest levels of NFTs found not just within the transentorhinal region but also the cornu ammonis (CA1) subfield. Additionally, we identify granular MTL regions where measures of neurodegeneration are likely to be linked to NFTs specifically, and thus potentially more sensitive as early AD biomarkers.

Neurodegeneration, known as the progressive loss of neurons in terms of their structure and function, is the principal pathophysiological change found in the majority of brain-related disorders. Ageing has been considered the most well-established risk factor in most common neurodegenerative diseases, such as Parkinson's disease (PD) and Alzheimer's disease (AD). There is currently no effective treatment or cure for these diseases; the approved therapeutic options to date are only for palliative care. Ageing and neurodegenerative diseases are closely intertwined; reversing the aspects of brain ageing could theoretically mitigate age-related neurodegeneration. Ever since the regenerative properties of young blood on aged tissues came to light, substantial efforts have been focused on identifying and characterizing the circulating factors in the young and old systemic milieu that may attenuate or accentuate brain ageing and neurodegeneration. Later studies discovered the superiority of old plasma dilution in tissue rejuvenation, which is achieved through a molecular reset of the systemic proteome. These findings supported the use of therapeutic blood exchange for the treatment of degenerative diseases in older individuals. The first objective of this article is to explore the rejuvenating properties of blood-based therapies in the ageing brains and their therapeutic effects on AD. Then, we also look into the clinical applications, various limitations, and challenges associated with blood-based therapies for AD patients.

The cautious optimism following recent anti-amyloid therapeutic trials for Alzheimer's disease (AD) provides a glimmer of hope after years of disappointment. Although these encouraging results represent discernible progress, they also highlight the need to enhance further the still modest clinical efficacy of current disease-modifying immunotherapies. Here, we highlight crucial milestones essential for advancing precision medicine in AD. These include reevaluating the choice of therapeutic targets by considering the key role of both central neuroinflammation and peripheral immunity in disease pathogenesis, refining patient stratification by further defining the inflammatory component within the forthcoming ATN(I) (amyloid, tau and neurodegeneration (and inflammation)) classification of AD biomarkers and defining more accurate clinical outcomes and prognostic biomarkers that better reflect disease heterogeneity. Next-generation immunotherapies will need to go beyond the current antibody-only approach by simultaneously targeting pathological proteins together with innate neuroinflammation and/or peripheral-central immune crosstalk. Such innovative immunomodulatory combination therapy approaches should be evaluated in appropriately redesigned clinical therapeutic trials, which must carefully integrate the neuroimmune component.

To cross-culturally adapt the Australian National University Alzheimer Disease Risk Index (ANU-ADRI) and verify the reliability and validity of its cognitive activity domain.

Caffeic acid, a phenolic compound of the hydroxycinnamic acid family, is abundant in various plant-based foods, such as fruits, vegetables, and coffee, alongside other biologically active compounds. Recognizing its potential to address various health issues and its widespread presence in commonly consumed foods underscores the importance of comprehending and harnessing the benefits of caffeic acid for human nutrition and well-being. This versatile substance, characterized by acrylic and phenolic functional groups, plays a pivotal role in the food and pharmaceutical industries. Furthermore, a detailed exploration of its pharmacokinetic properties, absorption, distribution, metabolism, and excretion enhances our understanding of how the human body processes it. Functioning as a precursor for essential compounds, caffeic acid contributes to formulations with notable anti-inflammatory, antiviral, anti-cancer, anti-diabetic, antibacterial, neuroprotective, and hepatoprotective qualities. Its current applications in treating Parkinson's and Alzheimer's disease underscore its therapeutic significance. This comprehensive analysis sheds light on caffeic acid's importance, showcasing its diverse applications across various domains and paving the way for further research and development to fully unlock its therapeutic potential. In conclusion, caffeic acid emerges as a bioactive substance with a broad spectrum of pharmacological properties, suggesting its potential utility in diverse therapeutic contexts. The comprehensive information provided in this article serves as a foundation for further research and learning regarding the various ways that caffeic acid supports human health.

Protein aggregation is a key process in the development of many neurodegenerative disorders, including dementias such as Alzheimer's disease. Significant progress has been made in understanding the molecular mechanisms of aggregate formation in pure buffer systems, much of which was enabled by the development of integrated rate laws that allowed for mechanistic analysis of aggregation kinetics. However, in order to translate these findings into disease-relevant conclusions and to make predictions about the effect of potential alterations to the aggregation reactions by the addition of putative inhibitors, the current models need to be extended to account for the altered situation encountered in living systems. In particular, , the total protein concentrations typically do not remain constant and aggregation-prone monomers are constantly being produced but also degraded by cells. Here, we build a theoretical model that explicitly takes into account monomer production, derive integrated rate laws and discuss the resulting scaling laws and limiting behaviours. We demonstrate that our models are suited for the aggregation-prone Huntington's disease-associated peptide HttQ45 utilizing a system for continuous monomer production and the aggregation of the tumour suppressor protein P53. The aggregation-prone HttQ45 monomer was produced through enzymatic cleavage of a larger construct in which a fused protein domain served as an internal inhibitor. For P53, only the unfolded monomers form aggregates, making the unfolding a rate-limiting step which constitutes a source of aggregation-prone monomers. The new model opens up possibilities for a quantitative description of aggregation in living systems, allowing for example the modelling of inhibitors of aggregation in a dynamic environment of continuous protein synthesis.

The accumulation of amyloid-β (Aβ) peptides is a major hallmark of Alzheimer's disease (AD) and plays a crucial role in its pathogenesis. Particularly, the structured oligomeric species rich in β-sheet formations were implicated in neuronal organelle damage. Addressing this formidable challenge requires identifying candidates capable of inhibiting peptide aggregation or disaggregating preformed oligomers for effective antiaggregation-based AD therapy. Here, we present a dual-functional nanoinhibitor meticulously designed to target the aggregation driving force and amyloid fibril spatial structure. Leveraging the exceptional structural stability and facile tailoring capability of endohedral metallofullerene Gd@C, we introduce desired hydrogen-binding sites and charged groups, which are abundant on its surface for specific designs. Impressively, these designs endow the resultant functionalized-Gd@C nanoparticles (f-Gd@C NPs) with high capability of redirecting peptide self-assembly toward disordered, off-pathway species, obstructing the early growth of protofibrils, and disaggregating the preformed well-ordered protofibrils or even mature Aβ fibrils. This results in considerable alleviation of Aβ peptide-induced neuronal cytotoxicity, rescuing neuronal death and synaptic loss in primary neuron models. Notably, these modifications significantly improved the dispersibility of f-Gd@C NPs, thus substantially enhancing its bioavailability. Moreover, f-Gd@C NPs demonstrate excellent cytocompatibility with various cell lines and possess the ability to penetrate the blood-brain barrier in mice. Large-scale molecular dynamics simulations illuminate the inhibition and disaggregation mechanisms. Our design successfully overcomes the limitations of other nanocandidates, which often overly rely on hydrophobic interactions or photothermal conversion properties, and offers a viable direction for developing anti-AD agents through the inhibition and even reversal of Aβ aggregation.

Functional assessment in neurocognitive evaluation is often provided via informant reports. These subjective reports can vary based on the characteristics of informants and their relationships with participants, such as informant sex. However, whether informant sex intersects with participant sex to impact subjective ratings of participants' daily functioning, and whether such effects mirror observed patterns in neuropsychological performance, has not been adequately examined with ethnoracially diverse samples. We examined differences among participant-informant sex-based dyads on subjective informant reports of participants' daily functioning (assessed via the Functional Activities Questionnaire [FAQ]), and whether any observed differences on reported functioning corresponded to differences in objective participant performance on neuropsychological performance, among middle-aged and older Hispanic/Latino (n = 543), non-Hispanic Black (NHB; n = 1030), and non-Hispanic White (NHW; n = 5356) adults in the National Alzheimer's Coordinating Center cohort (n = 6929). Analysis of covariance (ANCOVA) tests revealed significant dyad differences on FAQ scores in the NHB (<.001) and NHW subsamples (<.05), but not in the Hispanic/Latino subsample (>.05). For the Hispanic/Latino and NHB subsamples, ANCOVA tests revealed no significant effects of dyad on neuropsychological performance (s>.01), whereas for the NHW subsample, ANCOVA tests revealed significant dyad differences on performance in multiple cognitive domains (s<.01). Nevertheless, the pattern of dyad differences on neuropsychological performance did not mirror the pattern of observed differences on FAQ scores in the NHW subsample. Findings and their implications, including potential contributions of other informant characteristics on observed dyad differences on reported functioning, are discussed.

Microglia, the brain's resident macrophages, maintain brain homeostasis and respond to injury and infection. During aging they undergo functional changes, but the underlying mechanisms and their contributions to neuroprotection versus neurodegeneration are unclear. Previous studies suggested that microglia are sex dimorphic, so we compared microglial aging in mice of both sexes. RNA-sequencing of hippocampal microglia revealed more aging-associated changes in female microglia than male microglia, and more sex differences in old microglia than young microglia. Pathway analyses and subsequent validation assays revealed a stronger AKT-mTOR-HIF1α-driven shift to glycolysis among old female microglia and indicated that C3a production and detection was elevated in old microglia, especially in females. Recombinant C3a induced AKT-mTOR-HIF1α signaling and increased the glycolytic and phagocytic activity of young microglia. Single cell analyses attributed the aging-associated sex dimorphism to more abundant disease-associated microglia (DAM) in old female mice than old male mice, and evaluation of an Alzheimer's Disease mouse model revealed that the metabolic and complement changes are also apparent in the context of neurodegenerative disease and are strongest in the neuroprotective DAM2 subset. Collectively, our data implicate autocrine C3a-C3aR signaling in metabolic reprogramming of microglia to neuroprotective DAM during aging, especially in females, and also in Alzheimer's Disease.

Cholesterol plays a crucial role in brain, where it is highly concentrated and tightly regulated to support normal brain functions. It serves as a vital component of cell membranes, ensuring their integrity, and acts as a key regulator of various brain processes. Dysregulation of cholesterol metabolism in the brain has been linked to impaired brain function and the onset of neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD).

The prevailing but not undisputed amyloid cascade hypothesis places the β-site of APP cleaving enzyme 1 (BACE1) center stage in Alzheimer's Disease pathogenesis. Here, we investigated functional properties of BACE1 with novel tag- and antibody-free labeling tools, which are conjugates of the BACE1-inhibitor IV (also referred to as C3) linked to different impermeable Alexa Fluor dyes. We show that these fluorescent small molecules bind specifically to BACE1, with a 1:1 labeling stoichiometry at their orthosteric site. This is a crucial property especially for single-molecule and super-resolution microscopy approaches, allowing characterization of the dyes' labeling capabilities in overexpressing cell systems and in native neuronal tissue. With multiple colors at hand, we evaluated BACE1-multimerization by Förster resonance energy transfer (FRET) acceptor-photobleaching and single-particle imaging of native BACE1. In summary, our novel fluorescent inhibitors, termed , offer unprecedented insights into protein-protein interactions and diffusion behavior of BACE1 down to the single molecule level.

The World Health Organization has identified Alzheimer's disease (AD), the leading cause of dementia globally, as a public health priority. However, the complex multifactorial pathology of AD means that its etiology remains incompletely understood. Despite being recognized a century ago, incomplete knowledge has hindered the development of effective treatments for AD. Recent scientific advancements, particularly in induced pluripotent stem cell (iPSC) technology, show great promise in elucidating the fundamental mechanisms of AD. iPSCs play a dual role in regenerating damaged cells for therapeutic purposes and creating disease models to understand AD pathology and aid in drug screening. Nevertheless, as an emerging field, iPSC technology requires further technological advancement to develop effective AD treatments in the future. Thus, this review summarizes recent advances in stem cell therapies, specifically iPSCs, aimed at understanding AD pathology and developing treatments.

Cerebrospinal fluid total-tau (t-tau) and neurofilament light chain (NfL) are biomarkers of neurodegeneration and are increased in Alzheimer's disease (AD). In order to adjust for age-related increases in t-tau and NfL, cross-sectional age-adjusted norms were developed based on amyloid negative cognitively normal (CN) adults aged 41-78 years (CN, n = 137). The age-adjusted norms for t-tau and NfL did not improve receiver operating curve based diagnostic accuracies in individuals with mild cognitive impairment (MCI) due to AD (AD-MCI, n = 144). Furthermore, while NfL was correlated with higher age in AD-MCI, no significant correlation was found for t-tau. The cox proportional hazard models, applied in 429 participants with baseline t-tau and NfL, showed higher hazard ratio of progression to MCI or dementia without age-adjustments (HR = 3.39 for t-tau and HR = 3.17 for NfL), as compared to using our norms (HR = 2.29 for t-tau and HR = 1.89 for NfL). Our results indicate that utilizing normative reference data could obscure significant age-related increases in these markers associated with neurodegeneration and AD leading to a potential loss of overall diagnostic accuracy.

Cognitive impairment poses considerable challenges among older adults, with the role of family support becoming increasingly crucial. This study examines the association of children's residential proximity and spousal presence with key modifiable risk factors for dementia in cognitively impaired older adults.

Alzheimer's disease (AD) is one of the most prevalent chronic neurodegenerative disorders globally, with a rapidly growing population of AD patients and currently no effective therapeutic interventions available. Consequently, the development of therapeutic anti-AD drugs and the identification of AD targets represent one of the most urgent tasks. In this study, in addition to considering known drugs and targets, we explore compound-protein interactions (CPIs) between compounds and proteins relevant to AD. We propose a deep learning model called CKG-IMC to predict Alzheimer's disease compound-protein interaction relationships. CKG-IMC comprises three modules: a collaborative knowledge graph (CKG), a principal neighborhood aggregation graph neural network (PNA), and an inductive matrix completion (IMC). The collaborative knowledge graph is used to learn semantic associations between entities, PNA is employed to extract structural features of the relationship network, and IMC is utilized for CPIs prediction. Compared with a total of 16 baseline models based on similarities, knowledge graphs, and graph neural networks, our model achieves state-of-the-art performance in experiments of 10-fold cross-validation and independent test. Furthermore, we use CKG-IMC to predict compounds interacting with two confirmed AD targets, 42-amino-acid β-amyloid (Aβ42) protein and microtubule-associated protein tau (tau protein), as well as proteins interacting with five FDA-approved anti-AD drugs. The results indicate that the majority of predictions are supported by literature, and molecular docking experiments demonstrate a strong affinity between the predicted compounds and targets.

Alzheimer's disease (AD), the most common neurodegenerative disorder, affects a broad spectrum of aging populations. AD is characterized by pathological amyloid-β (Aβ) plaques and neurofibrillary tangles, leading to neural degeneration and cognitive decline. The lack of effective treatments for AD highlights the urgent need for novel therapeutic agents, particularly in the early stages. Dimethylsulfoniopropionate (DMSP) is a natural marine compound with antioxidant and neuroprotective properties. However, studies on the efficacy of DMSP in the treatment of AD and its associated mechanisms are limited.

[This retracts the article DOI: 10.1515/tnsci-2020-0101.].

Pragmatic clinical trials (PCTs) are designed to connect researchers with clinicians to assess the real-world effectiveness and feasibility of interventions, treatments, or health care delivery strategies in routine practice. Within PCTs larger, more representative sampling is possible to improve the external validity of the research. Older adults from underrepresented groups can benefit from PCTs given their historically lower engagement in clinical research. The current article focuses on older Hispanic adults with Alzheimer disease and related dementias (ADRDs). Older Hispanic adults represent 19% of the US population and have a higher prevalence of ADRDs than Whites. We provide data from 2 PCTs about the recruitment of older Hispanics with ADRDs and discuss unique challenges associated with conducting PCTs and propose strategies to overcome challenges.

To characterize the National Institutes of Health (NIH) prevention research portfolio on leading causes of death focused on racial or ethnic minority populations.

Life-course exposure to risk and protective factors impacts brain macro- and micro-structure, which in turn affects cognition. The concept of brain-age gap assesses brain health by comparing an individual's neuroimaging-based predicted age with their calendar age. A higher BAG implies accelerated brain ageing and is expected to be associated with worse cognition. In this study, we comprehensively modelled mutual associations between brain health and lifestyle factors, brain age and cognition in a large, middle-aged population. For this study, cognitive test scores, lifestyle and 3T MRI data for = 4881 participants [mean age (± SD) = 59.2 (±8.6), 50.1% male] were available from The Maastricht Study, a population-based cohort study with extensive phenotyping. Whole-brain volumes (grey matter, cerebrospinal fluid and white matter hyperintensity), cerebral microbleeds and structural white matter connectivity were calculated. Lifestyle factors were combined into an adapted LIfestyle for BRAin health weighted sum score, with higher score indicating greater dementia risk. Cognition was calculated by averaging -scores across three cognitive domains (memory, information processing speed and executive function and attention). Brain-age gap was calculated by comparing calendar age to predictions from a neuroimaging-based multivariable regression model. Paths between LIfestyle for BRAin health tertiles, brain-age gap and cognitive function were tested using linear regression and structural equation modelling, adjusting for sociodemographic and clinical confounders. The results show that cerebrospinal fluid, grey matter, white matter hyperintensity and cerebral microbleeds best predicted brain-age gap ( = 0.455, root mean squared error = 6.44). In regression analysis, higher LIfestyle for BRAin health scores (greater dementia risk) were associated with higher brain-age gap (standardized regression coefficient = 0.126, < 0.001) and worse cognition ( = -0.046, = 0.013), while higher brain-age gap was associated with worse cognition (=-0.163, < 0.001). In mediation analysis, 24.7% of the total difference in cognition between the highest and lowest LIfestyle for BRAin health tertile was mediated by brain-age gap ( = -0.049, < 0.001; = -0.198, < 0.001) and an additional 3.8% was mediated via connectivity ( = -0.006, < 0.001; = -0.150, < 0.001). Findings suggest that associations between health- and lifestyle-based risk/protective factors (LIfestyle for BRAin health) and cognition can be partially explained by structural brain health markers (brain-age gap) and white matter connectivity markers. Lifestyle interventions targeted at high-risk individuals in mid-to-late life may be effective in promoting and preserving cognitive function in the general public.

Alongside non-pharmacological intervention, pharmacotherapy particularly with atypical antipsychotics is assumed to be effective for behavioral and psychological symptoms of dementia (BPSD).

Dementia can disrupt how people experience and describe events as well as their own role in them. Alzheimer's disease (AD) compromises the processing of entities expressed by nouns, while behavioral variant frontotemporal dementia (bvFTD) entails a depersonalized perspective with increased third-person references. Yet, no study has examined whether these patterns can be captured in connected speech via natural language processing tools. To tackle such gaps, we asked 96 participants (32 AD patients, 32 bvFTD patients, 32 healthy controls) to narrate a typical day of their lives and calculated the proportion of nouns, verbs, and first- or third-person markers (via part-of-speech and morphological tagging). We also extracted objective properties (frequency, phonological neighborhood, length, semantic variability) from each content word. In our main study (with 21 AD patients, 21 bvFTD patients, and 21 healthy controls), we used inferential statistics and machine learning for group-level and subject-level discrimination. The above linguistic features were correlated with patients' scores in tests of general cognitive status and executive functions. We found that, compared with HCs, (i) AD (but not bvFTD) patients produced significantly fewer nouns, (ii) bvFTD (but not AD) patients used significantly more third-person markers, and (iii) both patient groups produced more frequent words. Machine learning analyses showed that these features identified individuals with AD and bvFTD (AUC = 0.71). A generalizability test, with a model trained on the entire main study sample and tested on hold-out samples (11 AD patients, 11 bvFTD patients, 11 healthy controls), showed even better performance, with AUCs of 0.76 and 0.83 for AD and bvFTD, respectively. No linguistic feature was significantly correlated with cognitive test scores in either patient group. These results suggest that specific cognitive traits of each disorder can be captured automatically in connected speech, favoring interpretability for enhanced syndrome characterization, diagnosis, and monitoring.

Protein kinase C (PKC) plays a key role in modulating the activities of the innate immune cells of the central nervous system (CNS). A delicate balance between pro-inflammatory and regenerative activities by microglia and CNS-associated macrophages is necessary for the proper functioning of the CNS. Thus, a maladaptive activation of these CNS innate immune cells results in neurodegeneration and demyelination associated with various neurologic disorders, such as multiple sclerosis (MS) and Alzheimer's disease. Prior studies have demonstrated that modulation of PKC activity by bryostatin-1 (bryo-1) and its analogs (bryologs) attenuates the pro-inflammatory processes by microglia/CNS macrophages and alleviates the neurologic symptoms in experimental autoimmune encephalomyelitis (EAE), an MS animal model. Here, we demonstrate that (2S,5S)-(E,E)-8-(5-(4-(trifluoromethyl)phenyl)-2,4-pentadienoylamino)benzolactam (TPPB), a structurally distinct PKC modulator, has a similar effect to bryo-1 on CNS innate immune cells both and , attenuating neuroinflammation and resulting in CNS regeneration and repair. This study identifies a new structural class of PKC modulators, which can therapeutically target CNS innate immunity as a strategy to treat neuroinflammatory and neurodegenerative disorders.

Liver hepatocellular carcinoma (LIHC) exhibits a multifactorial etiology, insidious onset, and a significantly low 5-year survival rate. We aimed to evaluate the causal impact of exposure factors (Alzheimer's disease, platelet count, ambidextrousness, cigarettes smoked per day, alcohol consumption, and endocarditis) on the risk of LIHC using a two-sample Mendelian randomization (MR) study.

Photobiomodulation involves the use of low-level light therapy or near-infrared light therapy found to be useful in the treatment of a wide range of neurological diseases. The aim is to review the mechanism and clinical applications of photobiomodulation therapy (PBMT) in managing Alzheimer's disease. To ensure that the consensus statement accurately reflects both the experts' viewpoint and the most recent developments in the field, the expert opinions were recorded and thoroughly reviewed. PBMT elicits reduction of beta-amyloid plaque, restoration of mitochondrial function, anti-inflammatory and antioxidant properties with a stimulation in ATP synthesis. The PBMT could be helpful in patients non-responsive to traditional pharmacological therapy providing significant aid in the management of Alzheimer's disease when introduced into the medical field.

is the dried tuber of the orchid Bl. It is considered a food consisting of a source of precious medicinal herbs, whose chemical composition is relatively rich. and its extracted fractions have been shown to have neuroprotective effects. -hydroxybenzaldehyde (-HBA), as one of the main active components of , has anti-inflammatory, antioxidative stress, and cerebral protective effects, which has potential for the treatment of Alzheimer's disease (AD). The aim of this study was to verify the role of -HBA in AD treatment and to investigate its mechanism of action in depth based using the () model.

Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) is a potential neuroinflammatory biomarker linked to the pathogenesis of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Previous studies have produced inconsistent results regarding sTREM2 levels in various clinical stages of AD. This study aims to establish the correlation between sTREM2 levels and AD progression through a meta-analysis of sTREM2 levels in cerebrospinal fluid (CSF) and blood.

Long non-coding RNAs (lncRNAs) have emerged as critical players in brain development and disease. These non-coding transcripts, which once considered as "transcriptional junk," are now known for their regulatory roles in gene expression. In brain development, lncRNAs participate in many processes, including neurogenesis, neuronal differentiation, and synaptogenesis. They employ their effect through a wide variety of transcriptional and post-transcriptional regulatory mechanisms through interactions with chromatin modifiers, transcription factors, and other regulatory molecules. Dysregulation of lncRNAs has been associated with certain brain diseases, including Alzheimer's disease, Parkinson's disease, cancer, and neurodevelopmental disorders. Altered expression and function of specific lncRNAs have been implicated with disrupted neuronal connectivity, impaired synaptic plasticity, and aberrant gene expression pattern, highlighting the functional importance of this subclass of brain-enriched RNAs. Moreover, lncRNAs have been identified as potential biomarkers and therapeutic targets for neurological diseases. Here, we give a comprehensive review of the existing knowledge of lncRNAs. Our aim is to provide a better understanding of the diversity of lncRNA structure and functions in brain development and disease. This holds promise for unravelling the complexity of neurodevelopmental and neurodegenerative disorders, paving the way for the development of novel biomarkers and therapeutic targets for improved diagnosis and treatment.

Alzheimer's disease (AD) is the most occurring neurodegenerative disorder that destroys learning, memory, and thinking skills. Although the pathophysiology of the disease is least understood, the post-mortem brain of AD patients as well as animal models revealed the part of down regulated Wnt signalling in progression of the disease. The deficit in the Wnt signalling leads to the accumulation of amyloid beta peptides, phosphorylation of tau proteins, and synaptic dysfunctions, which are regarded as the major pathological features of AD. As the available drugs for AD are only able to mitigate the symptoms and are also associated with several side effects, the therapeutic potential of the bioactive compounds is being explored for their efficacies in managing the major pathologies. Consequently, a few bioactive compounds fundamentally isolated from species are established as promising neuroprotective agents in AD, however; their potential to regulate the Wnt signalling pathway is yet to be discovered. Considering the neuroprotective properties, in the present study efficiency of six small bioactive compounds viz., amentoflavone, isovitexin, orientin, apigenin, kaempferol, and garcinol have been investigated in modulating the receptor proteins (LRP6, DKK1, WIF1 and GSK3β) of the Wnt signalling pathway by molecular docking technique. While all the bioactive compounds could efficiently interact with the target proteins, amentoflavone, orientin, and isovitexin interact with all the target proteins viz., LRP6, DKK1, WIF1, and GSK3β with higher free energy of binding, more number of interactions, and similar mode of binding in comparison to their known or reported modulators. Thus, the present study set forth the investigated small bioactive molecules as potential drug candidates in AD therapeutics.

Recently, large-scale scRNA-seq datasets have been generated to understand the complex signaling mechanisms within the microenvironment of Alzheimer's Disease (AD), which are critical for identifying novel therapeutic targets and precision medicine. However, the background signaling networks are highly complex and interactive. It remains challenging to infer the core intra- and inter-multi-cell signaling communication networks using scRNA-seq data. In this study, we introduced a novel graph transformer model, PathFinder, to infer multi-cell intra- and inter-cellular signaling pathways and communications among multi-cell types. Compared with existing models, the novel and unique design of PathFinder is based on the divide-and-conquer strategy. This model divides complex signaling networks into signaling paths, which are then scored and ranked using a novel graph transformer architecture to infer intra- and inter-cell signaling communications. We evaluated the performance of PathFinder using two scRNA-seq data cohorts. The first cohort is an APOE4 genotype-specific AD, and the second is a human cirrhosis cohort. The evaluation confirms the promising potential of using PathFinder as a general signaling network inference model.

Parkinson's disease (PD) is a chronic neurodegenerative disease that affects the central nervous system, primarily the motor nervous system, and occurs most often in older adults. A large number of studies have shown that high intelligence leads to an increased risk of PD. However, whether there is a causal relationship between intelligence on PD has not yet been reported.