scholarly journals Discrimination of MSA-P and MSA-C by RT-QuIC analysis of olfactory mucosa: the first assessment of assay reproducibility between two specialized laboratories

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Connor Bargar ◽  
Chiara Maria Giulia De Luca ◽  
Grazia Devigili ◽  
Antonio Emanuele Elia ◽  
Roberto Cilia ◽  
...  
Keyword(s):  
Disease Duration ◽  
Disease Diagnosis ◽  
Alpha Synuclein ◽  
Olfactory Mucosa ◽  
Clinical Diagnoses ◽  
The Usa ◽  
Healthy Control ◽  
Selection For ◽  
The Brain ◽  
Probable Diagnosis

Abstract Background Detection of the pathological and disease-associated alpha-synuclein (αSynD) in the brain is required to formulate the definitive diagnosis of multiple system atrophy (MSA) and Parkinson’s disease (PD). We recently showed that αSynD can be detected in the olfactory mucosa (OM) of MSA and PD patients. For this reason, we have performed the first interlaboratory study based on α-synuclein Real-Time Quaking-Induced Conversion (αSyn_RT-QuIC) analysis of OM samples collected from PD and MSA patients with the parkinsonian (MSA-P) and cerebellar (MSA-C) phenotypes. Methods OM samples were prospectively collected from patients with a probable diagnosis of MSA-P (n = 20, mean disease duration 4.4 years), MSA-C (n = 10, mean disease duration 4 years), PD (n = 13, mean disease duration 8 years), and healthy control subjects (HS) (n = 11). Each sample was analyzed by αSyn_RT-QuIC in two independent specialized laboratories, one located in Italy (ITA-lab) and one located in the USA (USA-lab). Both laboratories have developed and used harmonized αSyn_RT-QuIC analytical procedures. Results were correlated with demographic and clinical data. Results The αSyn_RT-QuIC analysis reached a 96% interrater agreement of results (IAR) between laboratories (Kappa = 0.93, 95% CI 0.83–1.00). In particular, αSyn_RT-QuIC seeding activity was found in the OM of 9/13 patients with PD (sensitivity 69%, IAR 100%) and 18/20 patients with MSA-P (sensitivity 90%, IAR 100%). Interestingly, samples collected from patients with MSA-C did not induce αSyn_RT-QuIC seeding activity, except for one subject in USA-lab. Therefore, we found that MSA-P and MSA-C induced opposite effects. Regardless of disease diagnosis, the αSyn_RT-QuIC seeding activity correlated with some clinical parameters, including the rigidity and postural instability. Conclusions Our study provides evidence that OM-αSynD may serve as a novel biomarker for accurate clinical diagnoses of PD, MSA-P, and MSA-C. Moreover, αSyn_RT-QuIC represents a reliable assay that can distinguish patients with MSA-P from those with MSA-C, and may lead to significant advancements in patients stratification and selection for emerging pharmacological treatments and clinical trials.

Pathology of Olfactory Mucosa in Patients with Alzheimer's Disease

1994 ◽  
Vol 103 (6) ◽  
pp. 421-427 ◽  
Author(s):  
Masuo Yamagishi ◽  
Yoichi Ishizuka ◽  
Kohji Seki
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurofibrillary Tangle ◽  
Olfactory Mucosa ◽  
Olfactory Pathway ◽  
Protein Tau ◽  
Β Protein ◽  
Clinical Diagnoses ◽  
Olfactory Disturbance ◽  
The Brain

Characteristic changes that appear in the biopsied olfactory mucosa of patients with Alzheimer's disease (AD) were examined with immunohistochemical staining. Specimens were obtained from patients with clinical diagnoses of AD. Patients with vascular dementia and age-matched patients without dementia were used for controls. In most AD cases, neurofibrillary tangle-like abnormal tau protein (Tau) immunoreactivity was seen in the dendrites and perikarya of the olfactory receptor cells and in the nerve bundles. A senile plaquelike extracellular mass was found in the olfactory epithelium, and it reacted strongly to an anti-Tau antiserum and weakly to an antiamyloid-β protein antiserum. Ubiquitin (Ubq) immunoreactivity was also observed in the dendrites. Tau immunoreactivity of the perikarya and extracellular mass, and Ubq immunoreactivity were especially characteristic of the olfactory mucosa of AD patients. From these results, it is clear that the same pathologic changes in the brain are also present in the olfactory mucosa of patients with AD. Not only disruption of the central olfactory pathway, but also an olfactory disturbance of AD patients is caused by peripheral changes. Furthermore, an olfactory mucosal biopsy could be a useful method for a definitive diagnosis of AD.

scholarly journals The Gut–Brain Axis and Its Relation to Parkinson’s Disease: A Review

2022 ◽  
Vol 13 ◽  
Author(s):  
Emily M. Klann ◽  
Upuli Dissanayake ◽  
Anjela Gurrala ◽  
Matthew Farrer ◽  
Aparna Wagle Shukla ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Current Knowledge ◽  
Lewy Bodies ◽  
Disease Diagnosis ◽  
Alpha Synuclein ◽  
Motor Symptoms ◽  
Abnormal Gait ◽  
Non Motor Symptoms ◽  
The Brain

Parkinson’s disease is a chronic neurodegenerative disease characterized by the accumulation of misfolded alpha-synuclein protein (Lewy bodies) in dopaminergic neurons of the substantia nigra and other related circuitry, which contribute to the development of both motor (bradykinesia, tremors, stiffness, abnormal gait) and non-motor symptoms (gastrointestinal issues, urinogenital complications, olfaction dysfunction, cognitive impairment). Despite tremendous progress in the field, the exact pathways and mechanisms responsible for the initiation and progression of this disease remain unclear. However, recent research suggests a potential relationship between the commensal gut bacteria and the brain capable of influencing neurodevelopment, brain function and health. This bidirectional communication is often referred to as the microbiome–gut–brain axis. Accumulating evidence suggests that the onset of non-motor symptoms, such as gastrointestinal manifestations, often precede the onset of motor symptoms and disease diagnosis, lending support to the potential role that the microbiome–gut–brain axis might play in the underlying pathological mechanisms of Parkinson’s disease. This review will provide an overview of and critically discuss the current knowledge of the relationship between the gut microbiota and Parkinson’s disease. We will discuss the role of α-synuclein in non-motor disease pathology, proposed pathways constituting the connection between the gut microbiome and the brain, existing evidence related to pre- and probiotic interventions. Finally, we will highlight the potential opportunity for the development of novel preventative measures and therapeutic options that could target the microbiome–gut–brain axis in the context of Parkinson’s disease.

scholarly journals Phase II Dose Selection for Alpha Synuclein–Targeting Antibody Cinpanemab (BIIB054) Based on Target Protein Binding Levels in the Brain

2020 ◽  
Vol 9 (9) ◽  
pp. 515-522
Author(s):  
Mita Kuchimanchi ◽  
Michael Monine ◽  
Kumar Kandadi Muralidharan ◽  
Caroline Woodward ◽  
Natalia Penner
Keyword(s):  
Protein Binding ◽  
Phase Ii ◽  
Alpha Synuclein ◽  
Target Protein ◽  
Dose Selection ◽  
Selection For ◽  
The Brain

Clinical relevance of the brain morphometric indicators for the Alzheimer’s disease diagnosis

2020 ◽  
Vol 18 (5) ◽  
pp. 150-156
Author(s):  
E. S. KOLUPAEVA ◽  
◽  
I. A. ZHUKOVA ◽  
N. G. ZHUKOVA ◽  
I. V. TOLMACHEV ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
Educational Level ◽  
Neuropsychological Testing ◽  
Disease Diagnosis ◽  
Morphometric Data ◽  
Resonance Imaging ◽  
The Brain ◽  
Probable Diagnosis

The purpose — to study the morphometric data of the brain in patients with Alzheimer’s disease (AD) as a possible additional instrumental paraclinical neuroimaging marker to verify the accuracy of the diagnosis. Material and methods. We examined 27 patients with Alzheimer’s disease: 14 (51,9%) men and 13 (45,1%) women, average age 74,5 ± 8,7 years with a probable diagnosis of Alzheimer’s disease, anamnestic type. All patients received standard combination therapy with anti-dementia drugs. The patients underwent magnetic resonance imaging of the brain, followed by automated image segmentation and neuropsychological examination using the Montreal scale for assessing cognitive functions. Results. In our study, no statistically significant correlations were found between the data of neuropsychological testing, educational level, age, gender, and volumes of gray and white matter of the brain. Conclusion. According to the study, indicators of the volume of gray and white matter of the brain are not recommended as an additional neuroimaging marker of AD.

scholarly journals Preclinical Detection of Alpha-Synuclein Seeding Activity in the Colon of a Transgenic Mouse Model of Synucleinopathy by RT-QuIC

Viruses ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 759
Author(s):  
Jung-Youn Han ◽  
Chaewon Shin ◽  
Young Pyo Choi
Keyword(s):  
Mouse Model ◽  
Transgenic Mice ◽  
Lewy Body ◽  
Dementia With Lewy Body ◽  
Transgenic Mouse Model ◽  
Alpha Synuclein ◽  
Gi Tract ◽  
Colon Tissue ◽  
Presymptomatic Stage ◽  
The Brain

In synucleinopathies such as Parkinson’s disease (PD) and dementia with Lewy body (DLB), pathological alpha-synuclein (α-syn) aggregates are found in the gastrointestinal (GI) tract as well as in the brain. In this study, using real-time quaking-induced conversion (RT-QuIC), we investigated the presence of α-syn seeding activity in the brain and colon tissue of G2-3 transgenic mice expressing human A53T α-syn. Here we show that pathological α-syn aggregates with seeding activity were present in the colon of G2-3 mice as early as 3 months old, which is in the presymptomatic stage prior to the observation of any neurological abnormalities. In contrast, α-syn seeding activity was not detectable in 3 month-old mouse brains and only identified at 6 months of age in one of three mice. In the symptomatic stage of 12 months of age, RT-QuIC seeding activity was consistently detectable in both the brain and colon of G2-3 mice. Our results indicate that the RT-QuIC assay can presymptomatically detect pathological α-syn aggregates in the colon of G2-3 mice several months prior to their detection in brain tissue.

scholarly journals Integrating additional knowledge into the estimation of graphical models

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Yunqi Bu ◽  
Johannes Lederer
Keyword(s):  
Graphical Models ◽  
Tuning Parameter ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Graphical Modeling ◽  
Standard Methods ◽  
Neighborhood Selection ◽  
Selection For ◽  
The Brain

Abstract Graphical models such as brain connectomes derived from functional magnetic resonance imaging (fMRI) data are considered a prime gateway to understanding network-type processes. We show, however, that standard methods for graphical modeling can fail to provide accurate graph recovery even with optimal tuning and large sample sizes. We attempt to solve this problem by leveraging information that is often readily available in practice but neglected, such as the spatial positions of the measurements. This information is incorporated into the tuning parameter of neighborhood selection, for example, in the form of pairwise distances. Our approach is computationally convenient and efficient, carries a clear Bayesian interpretation, and improves standard methods in terms of statistical stability. Applied to data about Alzheimer’s disease, our approach allows us to highlight the central role of lobes in the connectivity structure of the brain and to identify an increased connectivity within the cerebellum for Alzheimer’s patients compared to other subjects.

scholarly journals An improved framework for brain tumor analysis using MRI based on YOLOv2 and convolutional neural network

2021 ◽  
Author(s):  
Muhammad Irfan Sharif ◽  
Jian Ping Li ◽  
Javeria Amin ◽  
Abida Sharif
Keyword(s):  
Brain Tumor ◽  
Tumor Detection ◽  
Entropy Method ◽  
Feature Extraction And Selection ◽  
Tumor Region ◽  
Selection For ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain ◽  
Complicated Task

AbstractBrain tumor is a group of anomalous cells. The brain is enclosed in a more rigid skull. The abnormal cell grows and initiates a tumor. Detection of tumor is a complicated task due to irregular tumor shape. The proposed technique contains four phases, which are lesion enhancement, feature extraction and selection for classification, localization, and segmentation. The magnetic resonance imaging (MRI) images are noisy due to certain factors, such as image acquisition, and fluctuation in magnetic field coil. Therefore, a homomorphic wavelet filer is used for noise reduction. Later, extracted features from inceptionv3 pre-trained model and informative features are selected using a non-dominated sorted genetic algorithm (NSGA). The optimized features are forwarded for classification after which tumor slices are passed to YOLOv2-inceptionv3 model designed for the localization of tumor region such that features are extracted from depth-concatenation (mixed-4) layer of inceptionv3 model and supplied to YOLOv2. The localized images are passed toMcCulloch'sKapur entropy method to segment actual tumor region. Finally, the proposed technique is validated on three benchmark databases BRATS 2018, BRATS 2019, and BRATS 2020 for tumor detection. The proposed method achieved greater than 0.90 prediction scores in localization, segmentation and classification of brain lesions. Moreover, classification and segmentation outcomes are superior as compared to existing methods.

scholarly journals Recurrent Multi-Fiber Network for 3D MRI Brain Tumor Segmentation

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 320
Author(s):  
Yue Zhao ◽  
Xiaoqiang Ren ◽  
Kun Hou ◽  
Wentao Li
Keyword(s):  
Brain Tumor ◽  
Network Architecture ◽  
Contextual Information ◽  
Computational Cost ◽  
Disease Diagnosis ◽  
Tumor Segmentation ◽  
Brain Tumor Segmentation ◽  
Fiber Network ◽  
3D Network ◽  
The Brain

Automated brain tumor segmentation based on 3D magnetic resonance imaging (MRI) is critical to disease diagnosis. Moreover, robust and accurate achieving automatic extraction of brain tumor is a big challenge because of the inherent heterogeneity of the tumor structure. In this paper, we present an efficient semantic segmentation 3D recurrent multi-fiber network (RMFNet), which is based on encoder–decoder architecture to segment the brain tumor accurately. 3D RMFNet is applied in our paper to solve the problem of brain tumor segmentation, including a 3D recurrent unit and 3D multi-fiber unit. First of all, we propose that recurrent units segment brain tumors by connecting recurrent units and convolutional layers. This quality enhances the model’s ability to integrate contextual information and is of great significance to enhance the contextual information. Then, a 3D multi-fiber unit is added to the overall network to solve the high computational cost caused by the use of a 3D network architecture to capture local features. 3D RMFNet combines both advantages from a 3D recurrent unit and 3D multi-fiber unit. Extensive experiments on the Brain Tumor Segmentation (BraTS) 2018 challenge dataset show that our RMFNet remarkably outperforms state-of-the-art methods, and achieves average Dice scores of 89.62%, 83.65% and 78.72% for the whole tumor, tumor core and enhancing tumor, respectively. The experimental results prove our architecture to be an efficient tool for brain tumor segmentation accurately.

Utility of CT perfusion scanning in patient selection for acute stroke intervention: experience at University at Buffalo Neurosurgery–Millard Fillmore Gates Circle Hospital

2011 ◽  
Vol 30 (6) ◽  
pp. E4 ◽  
Author(s):  
Peter T. Kan ◽  
Kenneth V. Snyder ◽  
Parham Yashar ◽  
Adnan H. Siddiqui ◽  
L. Nelson Hopkins ◽  
...  
Keyword(s):  
Acute Stroke ◽  
Patient Selection ◽  
Ct Perfusion ◽  
Brain Parenchyma ◽  
National Institutes Of Health ◽  
Time Interval ◽  
Case Examples ◽  
Flow Parameters ◽  
Selection For ◽  
The Brain

Computed tomography perfusion scanning generates physiological flow parameters of the brain parenchyma, allowing differentiation of ischemic penumbra and core infarct. Perfusion maps, along with the National Institutes of Health Stroke Scale score, are used as the bases for endovascular stroke intervention at the authors' institute, regardless of the time interval from stroke onset. With case examples, the authors illustrate their perfusion-based imaging guidelines in patient selection for endovascular treatment in the setting of acute stroke.

scholarly journals Genetics of naked grain oats in crosses with Brazilian genotypes

2000 ◽  
Vol 23 (4) ◽  
pp. 851-854 ◽  
Author(s):  
Cândida Braga Cabral ◽  
Sandra Cristina Kothe Milach ◽  
Luiz Carlos Federizzi ◽  
Cristhiane Abegg Bothona ◽  
Ivone Taderka ◽  
...  
Keyword(s):  
Avena Sativa ◽  
Major Gene ◽  
Incomplete Dominance ◽  
Naked Oat ◽  
The Usa ◽  
Selection For

Six crosses between three naked oat (Avena sativa L.) germplasm sources from the USA and Australia and three Brazilian hulled genotypes were studied for the segregation of naked grain and multiflorous spikelet traits in the F2 and F3 generations. One major gene with incomplete dominance and expressivity for both traits was identified in all populations. The occurrence of intermediate types for naked grain varied with the population and did not depend on the germplasm source of naked grain used. The frequency of intermediate types varied among F2 populations indicating that selection for higher expressivity of naked grain could be used to develop Brazilian oat lines with naked grain.

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