Dementia and Neurodegenerative Disease Research Group, Faculty of Clinical and Biomedical Sciences, School of Dentistry, University of Central Lancashire, Preston PR1 2HE, UK.
Published: July 2022
AI Article Synopsis
Article Abstract
Alzheimer's Disease (AD) is a complex neurodegenerative disease and remains the most common form of dementia. The pathological features include amyloid (Aβ) accumulation, neurofibrillary tangles (NFTs), neural and synaptic loss, microglial cell activation, and an increased blood-brain barrier permeability. One longstanding hypothesis suggests that a microbial etiology is key to AD initiation. Among the various periodontal microorganisms, has been considered the keystone agent to potentially correlate with AD, due to its influence on systemic inflammation. together with and belong to the red complex consortium of bacteria advocated to sustain periodontitis within a local dysbiosis and a host response alteration. Since the implication of in the pathogenesis of AD, evidence has emerged of clusters in some AD brain tissue sections. This narrative review explored the potential mode of spirochetes entry into the AD brain for tracing pathology. Spirochetes are slow-growing bacteria, which can hide within ganglia for many years. It is this feature in combination with the ability of these bacteria to evade the hosts' immune responses that may account for a long lag phase between infection and plausible AD disease symptoms. As the locus coeruleus has direct connection between the trigeminal nuclei to periodontal free nerve endings and proprioceptors with the central nervous system, it is plausible that they could initiate AD pathology from this anatomical region.
Missing Alzheimer's disease (AD) data is prevalent and poses significant challenges for AD diagnosis. Previous studies have explored various data imputation approaches on AD data, but the systematic evaluation of deep learning algorithms for imputing heterogeneous and comprehensive AD data is limited. This study investigates the efficacy of denoising autoencoder-based imputation of missing key features of heterogeneous data that comprised tau-PET, MRI, cognitive and functional assessments, genotype, sociodemographic, and medical history.
Brain waste clearance from the interstitial fluid environment is challenging to measure, which has contributed to controversy regarding the significance of glymphatic transport impairment for neurodegenerative processes. Dynamic contrast enhanced MRI (DCE-MRI) with cerebrospinal fluid administration of Gd-tagged tracers is often used to assess glymphatic system function. We previously quantified glymphatic transport from DCE-MRI data utilizing regularized optimal mass transport (rOMT) analysis, however, information specific to glymphatic clearance was not directly derived.
Dementia with Lewy bodies (DLB) and its prodromal presentation with mild cognitive impairment is characterized by prominent deficits in attention/executive domains and in visual processing abilities with relative sparing of memory. Neuropsychological research is continuously refining the tools to define more in detail the patterns of relatively preserved and impaired cognitive abilities that help differential diagnosis between DLB and Alzheimer disease (AD). This review summarizes the main studies exploring specific cognitive tasks investigating different visual processing abilities and verbal memory that better differentiate DLB from AD.
Department of Neurology, Erenkoy Mental Health and Neurological Diseases Training and Research Hospital, University of Health Sciences, Istanbul, Turkey.
Background And Purpose: Alzheimer's disease (AD) and epileptic seizure are among the most common health problems in the elderly population. This study aimed to estimate the prevalence rate and predictors of seizures in sporadic AD patients.
Methods: The study was conducted by retrospectively for a period of 10 years examining the file records.
