scholarly journals The Presence of Human Herpesvirus 6 in the Brain in Health and Disease

Biomolecules ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1520
Author(s):  
Gabriel Santpere ◽  
Marco Telford ◽  
Pol Andrés-Benito ◽  
Arcadi Navarro ◽  
Isidre Ferrer
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Current Knowledge ◽  
Human Herpesvirus ◽  
Brain Regions ◽  
Specific Cell ◽  
Human Herpesvirus 6 ◽  
Detection Techniques ◽  
Herpesvirus 6 ◽  
The Brain

The human herpesvirus 6 (HHV‐6) ‐A and ‐B are two dsDNA beta‐herpesviruses infectingalmost the entire worldwide population. These viruses have been implicated in multipleneurological conditions in individuals of various ages and immunological status, includingencephalitis, epilepsy, and febrile seizures. HHV‐6s have also been suggested as playing a role inthe etiology of neurodegenerative diseases such as multiple sclerosis and Alzheimer’s disease. Theapparent robustness of these suggested associations is contingent on the accuracy of HHV‐6detection in the nervous system. The effort of more than three decades of researching HHV‐6 in thebrain has yielded numerous observations, albeit using variable technical approaches in terms oftissue preservation, detection techniques, sample sizes, brain regions, and comorbidities. In thisreview, we aimed to summarize current knowledge about the entry routes and direct presence ofHHV‐6 in the brain parenchyma at the level of DNA, RNA, proteins, and specific cell types, inhealthy subjects and in those with neurological conditions. We also discuss recent findings relatedto the presence of HHV‐6 in the brains of patients with Alzheimer’s disease in light of availableevidence.

Human Herpesvirus-6 (HHV-6) Detection in Alzheimer's Disease Cases and Controls Across Multiple Cohorts

2019 ◽  
Author(s):  
Mary Alice Allnutt ◽  
Kory Johnson ◽  
David A. Bennett ◽  
Sarah M. Connor ◽  
Juan C. Troncoso ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Human Herpesvirus ◽  
Human Herpesvirus 6 ◽  
Herpesvirus 6

Animal Models of Alzheimer’s Disease Should Be Controlled for Roseolovirus

2020 ◽  
Vol 77 (2) ◽  
pp. 543-545
Author(s):  
Joachim Denner ◽  
Rudolph Tanzi ◽  
Steve Jacobson
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Genetic Factors ◽  
Human Herpesvirus ◽  
Main Topic ◽  
Human Herpesvirus 6 ◽  
Herpesvirus 6 ◽  
Pathogenic Process

Animal models to study Alzheimer’s disease (AD) pathogenesis are under development. Since herpesviruses have been postulated to be capable of triggering the pathogenic process, AD animal models (mouse, pig, and non-human primates) should be controlled for the presence of these viruses. Only virus-free models allow studying the genetic factors and the effect of adding viruses. Roseoloviruses such as human herpesvirus 6 and the related viruses in the animals are the main topic of this commentary.

scholarly journals Human Herpesvirus 6 Detection in Alzheimer’s Disease Cases and Controls across Multiple Cohorts

Neuron ◽  
2020 ◽  
Vol 105 (6) ◽  
pp. 1027-1035.e2 ◽  
Author(s):  
Mary Alice Allnutt ◽  
Kory Johnson ◽  
David A. Bennett ◽  
Sarah M. Connor ◽  
Juan C. Troncoso ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Human Herpesvirus ◽  
Human Herpesvirus 6 ◽  
Herpesvirus 6

scholarly journals Deep-MEG: spatiotemporal CNN features and multiband ensemble classification for predicting the early signs of Alzheimer’s disease with magnetoencephalography

2021 ◽  
Author(s):  
Antonio Giovannetti ◽  
Gianluca Susi ◽  
Paola Casti ◽  
Arianna Mencattini ◽  
Sandra Pusil ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Brain Regions ◽  
Ensemble Classification ◽  
The Novel ◽  
Ensemble Classifiers ◽  
Deep Convolutional Neural Networks ◽  
Early Signs ◽  
Data Representations ◽  
The Brain

AbstractIn this paper, we present the novel Deep-MEG approach in which image-based representations of magnetoencephalography (MEG) data are combined with ensemble classifiers based on deep convolutional neural networks. For the scope of predicting the early signs of Alzheimer’s disease (AD), functional connectivity (FC) measures between the brain bio-magnetic signals originated from spatially separated brain regions are used as MEG data representations for the analysis. After stacking the FC indicators relative to different frequency bands into multiple images, a deep transfer learning model is used to extract different sets of deep features and to derive improved classification ensembles. The proposed Deep-MEG architectures were tested on a set of resting-state MEG recordings and their corresponding magnetic resonance imaging scans, from a longitudinal study involving 87 subjects. Accuracy values of 89% and 87% were obtained, respectively, for the early prediction of AD conversion in a sample of 54 mild cognitive impairment subjects and in a sample of 87 subjects, including 33 healthy controls. These results indicate that the proposed Deep-MEG approach is a powerful tool for detecting early alterations in the spectral–temporal connectivity profiles and in their spatial relationships.

scholarly journals Transcriptomic analysis to identify genes associated with selective hippocampal vulnerability in Alzheimer’s disease

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Angela M. Crist ◽  
Kelly M. Hinkle ◽  
Xue Wang ◽  
Christina M. Moloney ◽  
Billie J. Matchett ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Digital Pathology ◽  
Selective Vulnerability ◽  
Brain Regions ◽  
Biochemical Analyses ◽  
The Brain ◽  
Relevant Gene ◽  
Tau Expression

AbstractSelective vulnerability of different brain regions is seen in many neurodegenerative disorders. The hippocampus and cortex are selectively vulnerable in Alzheimer’s disease (AD), however the degree of involvement of the different brain regions differs among patients. We classified corticolimbic patterns of neurofibrillary tangles in postmortem tissue to capture extreme and representative phenotypes. We combined bulk RNA sequencing with digital pathology to examine hippocampal vulnerability in AD. We identified hippocampal gene expression changes associated with hippocampal vulnerability and used machine learning to identify genes that were associated with AD neuropathology, including SERPINA5, RYBP, SLC38A2, FEM1B, and PYDC1. Further histologic and biochemical analyses suggested SERPINA5 expression is associated with tau expression in the brain. Our study highlights the importance of embracing heterogeneity of the human brain in disease to identify disease-relevant gene expression.

Intranasal administration of mitochondria improves spatial memory in olfactory bulbectomized mice

2021 ◽  
pp. 153537022110568
Author(s):  
Natalia V Bobkova ◽  
Daria Y Zhdanova ◽  
Natalia V Belosludtseva ◽  
Nikita V Penkov ◽  
Galina D Mironova
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Spatial Memory ◽  
Intranasal Administration ◽  
Brain Structures ◽  
Brain Regions ◽  
Dependent Manner ◽  
Behavioral Experiments ◽  
Hippocampal Cell Culture ◽  
The Brain

Here, we found that functionally active mitochondria isolated from the brain of NMRI donor mice and administrated intranasally to recipient mice penetrated the brain structures in a dose-dependent manner. The injected mitochondria labeled with the MitoTracker Red localized in different brain regions, including the neocortex and hippocampus, which are responsible for memory and affected by degeneration in patients with Alzheimer's disease. In behavioral experiments, intranasal microinjections of brain mitochondria of native NMRI mice improved spatial memory in the olfactory bulbectomized (OBX) mice with Alzheimer’s type degeneration. Control OBX mice demonstrated loss of spatial memory tested in the Morris water maze. Immunocytochemical analysis revealed that allogeneic mitochondria colocalized with the markers of astrocytes and neurons in hippocampal cell culture. The results suggest that a non-invasive route intranasal administration of mitochondria may be a promising approach to the treatment of neurodegenerative diseases characterized, like Alzheimer's disease, by mitochondrial dysfunction.

scholarly journals Ceramide and Related-Sphingolipid Levels Are Not Altered in Disease-Associated Brain Regions of APPSLand APPSL/PS1M146LMouse Models of Alzheimer's Disease: Relationship with the Lack of Neurodegeneration?

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Laurence Barrier ◽  
Bernard Fauconneau ◽  
Anastasia Noël ◽  
Sabrina Ingrand
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Neuronal Death ◽  
Time Course ◽  
Neuronal Loss ◽  
Brain Regions ◽  
App Processing ◽  
Ceramide Accumulation ◽  
The Brain

There is evidence linking sphingolipid abnormalities, APP processing, and neuronal death in Alzheimer's disease (AD). We previously reported a strong elevation of ceramide levels in the brain of the APPSL/PS1Ki mouse model of AD, preceding the neuronal death. To extend these findings, we analyzed ceramide and related-sphingolipid contents in brain from two other mouse models (i.e., APPSLand APPSL/PS1M146L) in which the time-course of pathology is closer to that seen in most currently available models. Conversely to our previous work, ceramides did not accumulate in disease-associated brain regions (cortex and hippocampus) from both models. However, the APPSL/PS1Ki model is unique for its drastic neuronal loss coinciding with strong accumulation of neurotoxic Aβisoforms, not observed in other animal models of AD. Since there are neither neuronal loss nor toxic Aβspecies accumulation in APPSLmice, we hypothesized that it might explain the lack of ceramide accumulation, at least in this model.

Graph Theory-Based Brain Network Connectivity Analysis and Classification of Alzheimer’s Disease

2021 ◽  
Author(s):  
A. Thushara ◽  
C. Ushadevi Amma ◽  
Ansamma John
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Graph Theory ◽  
Neurodegenerative Disorder ◽  
Brain Networks ◽  
Network Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Fiber Tracts ◽  
The Brain

Alzheimer’s Disease (AD) is basically a progressive neurodegenerative disorder associated with abnormal brain networks that affect millions of elderly people and degrades their quality of life. The abnormalities in brain networks are due to the disruption of White Matter (WM) fiber tracts that connect the brain regions. Diffusion-Weighted Imaging (DWI) captures the brain’s WM integrity. Here, the correlation betwixt the WM degeneration and also AD is investigated by utilizing graph theory as well as Machine Learning (ML) algorithms. By using the DW image obtained from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, the brain graph of each subject is constructed. The features extracted from the brain graph form the basis to differentiate between Mild Cognitive Impairment (MCI), Control Normal (CN) and AD subjects. Performance evaluation is done using binary and multiclass classification algorithms and obtained an accuracy that outperforms the current top-notch DWI-based studies.

Swearing and the brain

2018 ◽  
pp. 107-139 ◽  
Author(s):  
Shlomit Ritz Finkelstein
Keyword(s):  
Alzheimer’S Disease ◽  
Tourette Syndrome ◽  
Clinical Data ◽  
Brain Injuries ◽  
Current Knowledge ◽  
Brain Regions ◽  
Future Research ◽  
Social Inhibition ◽  
Previous Knowledge ◽  
The Brain

This chapter explores and summarizes the current knowledge about the neurophysiological substrata of the utterance of expletives—its brain regions, pathways, and neurotransmitters, and its interaction with hormones. The chapter presents clinical data that have been gathered directly from patients of aphasia, Tourette syndrome, Alzheimer’s disease, and brain injuries—all are disorders often accompanied with expletives. It also discusses the possible relations between swearing and aggression, swearing and pain, and swearing and social inhibition in the population at large. Finally, the chapter examines the clinical data and the data gathered from the population at large within one frame, and proposes two hypotheses that can serve as possible directions for future research about the biological substrata of swearing. No previous knowledge of the brain is assumed.

scholarly journals Effects of Ketone Bodies on Brain Metabolism and Function in Neurodegenerative Diseases

2020 ◽  
Vol 21 (22) ◽  
pp. 8767
Author(s):  
Nicole Jacqueline Jensen ◽  
Helena Zander Wodschow ◽  
Malin Nilsson ◽  
Jørgen Rungby
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Diseases ◽  
Brain Metabolism ◽  
Ketone Bodies ◽  
Current Knowledge ◽  
Ketogenic Diets ◽  
Cognitive Benefits ◽  
The Brain

Under normal physiological conditions the brain primarily utilizes glucose for ATP generation. However, in situations where glucose is sparse, e.g., during prolonged fasting, ketone bodies become an important energy source for the brain. The brain’s utilization of ketones seems to depend mainly on the concentration in the blood, thus many dietary approaches such as ketogenic diets, ingestion of ketogenic medium-chain fatty acids or exogenous ketones, facilitate significant changes in the brain’s metabolism. Therefore, these approaches may ameliorate the energy crisis in neurodegenerative diseases, which are characterized by a deterioration of the brain’s glucose metabolism, providing a therapeutic advantage in these diseases. Most clinical studies examining the neuroprotective role of ketone bodies have been conducted in patients with Alzheimer’s disease, where brain imaging studies support the notion of enhancing brain energy metabolism with ketones. Likewise, a few studies show modest functional improvements in patients with Parkinson’s disease and cognitive benefits in patients with—or at risk of—Alzheimer’s disease after ketogenic interventions. Here, we summarize current knowledge on how ketogenic interventions support brain metabolism and discuss the therapeutic role of ketones in neurodegenerative disease, emphasizing clinical data.

Sign in / Sign up

Export Citation Format

Share Document