scholarly journals Diagnostic utility of quantitating neurofilament-immunoreactive Alzheimer's disease lesions.

1994 ◽  
Vol 42 (12) ◽  
pp. 1625-1634 ◽  
Author(s):  
S M de la Monte ◽  
J R Wands
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Monoclonal Antibodies ◽  
Neurofibrillary Tangles ◽  
Paired Helical Filament ◽  
Dystrophic Neurites ◽  
Associated Lesions ◽  
End Stage

The diagnosis of Alzheimer's disease (AD) neurodegeneration is based on histopathological detection of paired helical filament-associated lesions. Silver stains are routinely used but the results are fraught with intra- and interinstitutional variability. This study employed monoclonal antibodies to middle and high molecular weight neurofilament subunits in an immunohistochemical assay to assess the extent of paired helical filament-associated lesions in brains with AD, Down's syndrome plus AD lesions (AD+DN), Parkinson's disease dementia (PD), AD+PD, and normal aging changes. The densities of neurofilament-immunoreactive (NFI) cortical neurofibrillary tangles and plaques were significantly higher in AD and AD+DN than in PD and aged control brains (p < 0.001), and NFI neurofibrillary tangles and plaques were more abundant in AD and AD+DN compared with AD+PD and PD, yet all patients with AD, AD+PD, or PD died with end-stage dementia. In contrast, the densities of NFI dystrophic neurites (primarily dendrites) in cortical Layer 2 were similar among the AD, AD+DN, AD+PD, and PD groups, and all were significantly higher than control (p < 0.005). Stepwise multivariate regression analysis demonstrated significant correlations between AD diagnosis and high densities of NFI neurofibrillary tangles and plaques (p < 0.001) and between end-stage AD-type dementia and high densities of NFI dystrophic neurites (p < 0.001). This study demonstrates that the histopathological lesions correlated with AD dementia can be readily detected and quantified by immunostaining with monoclonal antibodies to phosphorylated and non-phosphorylated neurofilaments. Moreover, the findings suggest that NFI neurite pathology may be an important feature contributing to the clinically manifested AD-type dementia in individuals with Parkinson's disease.

scholarly journals Aluminum and Neurofibrillary Tangle Co-Localization in Familial Alzheimer’s Disease and Related Neurological Disorders

2020 ◽  
Vol 78 (1) ◽  
pp. 139-149 ◽  
Author(s):  
Matthew John Mold ◽  
Adam O’Farrell ◽  
Benjamin Morris ◽  
Christopher Exley
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Neurofibrillary Tangles ◽  
Mossy Fiber ◽  
Neurofibrillary Tangle ◽  
Familial Alzheimer’S Disease ◽  
Disease States ◽  
Familial Alzheimer's Disease

Background: Protein misfolding disorders are frequently implicated in neurodegenerative conditions. Familial Alzheimer’s disease (fAD) is an early-onset and aggressive form of Alzheimer’s disease (AD), driven through autosomal dominant mutations in genes encoding the amyloid precursor protein and presenilins 1 and 2. The incidence of epilepsy is higher in AD patients with shared neuropathological hallmarks in both disease states, including the formation of neurofibrillary tangles. Similarly, in Parkinson’s disease, dementia onset is known to follow neurofibrillary tangle deposition. Objective: Human exposure to aluminum has been linked to the etiology of neurodegenerative conditions and recent studies have demonstrated a high level of co-localization between amyloid-β and aluminum in fAD. In contrast, in a donor exposed to high levels of aluminum later developing late-onset epilepsy, aluminum and neurofibrillary tangles were found to deposit independently. Herein, we sought to identify aluminum and neurofibrillary tangles in fAD, Parkinson’s disease, and epilepsy donors. Methods: Aluminum-specific fluorescence microscopy was used to identify aluminum in neurofibrillary tangles in human brain tissue. Results: We observed aluminum and neurofibrillary-like tangles in identical cells in all respective disease states. Co-deposition varied across brain regions, with aluminum and neurofibrillary tangles depositing in different cellular locations of the same cell. Conclusion: Neurofibrillary tangle deposition closely follows cognitive-decline, and in epilepsy, tau phosphorylation associates with increased mossy fiber sprouting and seizure onset. Therefore, the presence of aluminum in these cells may exacerbate the accumulation and misfolding of amyloidogenic proteins including hyperphosphorylated tau in fAD, epilepsy, and Parkinson’s disease.

Neurobehavioral Consequences Associated with Long Term Tramadol Utilization and Pathological Mechanisms

2020 ◽  
Vol 18 (10) ◽  
pp. 758-768 ◽  
Author(s):  
Khadga Raj ◽  
Pooja Chawla ◽  
Shamsher Singh
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Serotonin Reuptake ◽  
Selective Serotonin Reuptake Inhibitors ◽  
Serotonin Syndrome ◽  
Dopamine Synthesis ◽  
Synthetic Analog

: Tramadol is a synthetic analog of codeine used to treat pain of moderate to severe intensity and is reported to have neurotoxic potential. At therapeutic dose, tramadol does not cause major side effects in comparison to other opioid analgesics, and is useful for the management of neurological problems like anxiety and depression. Long term utilization of tramadol is associated with various neurological disorders like seizures, serotonin syndrome, Alzheimer’s disease and Parkinson’s disease. Tramadol produces seizures through inhibition of nitric oxide, serotonin reuptake and inhibitory effects on GABA receptors. Extensive tramadol intake alters redox balance through elevating lipid peroxidation and free radical leading to neurotoxicity and produces neurobehavioral deficits. During Alzheimer’s disease progression, low level of intracellular signalling molecules like cGMP, cAMP, PKC and PKA affect both learning and memory. Pharmacologically tramadol produces actions similar to Selective Serotonin Reuptake Inhibitors (SSRIs), increasing the concentration of serotonin, which causes serotonin syndrome. In addition, tramadol also inhibits GABAA receptors in the CNS has been evidenced to interfere with dopamine synthesis and release, responsible for motor symptoms. The reduced level of dopamine may produce bradykinesia and tremors which are chief motor abnormalities in Parkinson’s Disease (PD).

scholarly journals Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson’s disease and schizophrenia

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Manan Binth Taj Noor ◽  
Nusrat Zerin Zenia ◽  
M Shamim Kaiser ◽  
Shamim Al Mamun ◽  
Mufti Mahmud
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Deep Learning ◽  
Magnetic Resonance ◽  
Neurological Disorders ◽  
Magnetic Resonance Images ◽  
Future Research ◽  
Comparative Performance

Abstract Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided.

Generalized Rhythmic Delta Activity Frontally Predominant Differentiates Dementia With Lewy Bodies From Alzheimer's Disease and Parkinson's Disease Dementia: A Conventional Electroencephalography Visual Analysis

2021 ◽  
pp. 155005942199714
Author(s):  
Lucia Zinno ◽  
Anna Negrotti ◽  
Chiara Falzoi ◽  
Giovanni Messa ◽  
Matteo Goldoni ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Dementia With Lewy Bodies ◽  
Visual Analysis ◽  
Lewy Bodies ◽  
Delta Activity ◽  
Rhythmic Delta Activity

Introduction. An easily accessible and inexpensive neurophysiological technique such as conventional electroencephalography may provide an accurate and generally applicable biomarker capable of differentiating dementia with Lewy bodies (DLB) from Alzheimer’s disease (AD) and Parkinson’s disease-associated dementia (PDD). Method. We carried out a retrospective visual analysis of resting-state electroencephalography (EEG) recording of 22 patients with a clinical diagnosis of 19 probable and 3 possible DLB, 22 patients with probable AD and 21 with PDD, matched for age, duration, and severity of cognitive impairment. Results. By using the grand total EEG scoring method, the total score and generalized rhythmic delta activity frontally predominant (GRDAfp) alone or, even better, coupled with a slowing of frequency of background activity (FBA) and its reduced reactivity differentiated DLB from AD at an individual level with an high accuracy similar to that obtained with quantitative EEG (qEEG). GRDAfp alone could also differentiate DLB from PDD with a similar level of diagnostic accuracy. AD differed from PDD only for a slowing of FBA. The duration and severity of cognitive impairment did not differ between DLB patients with and without GRDAfp, indicating that this abnormal EEG pattern should not be regarded as a disease progression marker. Conclusions. The findings of this investigation revalorize the role of conventional EEG in the diagnostic workup of degenerative dementias suggesting the potential inclusion of GRDAfp alone or better coupled with the slowing of FBA and its reduced reactivity, in the list of supportive diagnostic biomarkers of DLB.

scholarly journals The Role of Salivary Biomarkers in the Early Diagnosis of Alzheimer’s Disease and Parkinson’s Disease

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 371
Author(s):  
Patrycja Pawlik ◽  
Katarzyna Błochowiak
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Early Diagnosis ◽  
Neurodegenerative Diseases ◽  
Diagnostic Tool ◽  
Clinical Symptoms ◽  
Early Screening ◽  
Salivary Biomarkers

Many neurodegenerative diseases present with progressive neuronal degeneration, which can lead to cognitive and motor impairment. Early screening and diagnosis of neurodegenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) are necessary to begin treatment before the onset of clinical symptoms and slow down the progression of the disease. Biomarkers have shown great potential as a diagnostic tool in the early diagnosis of many diseases, including AD and PD. However, screening for these biomarkers usually includes invasive, complex and expensive methods such as cerebrospinal fluid (CSF) sampling through a lumbar puncture. Researchers are continuously seeking to find a simpler and more reliable diagnostic tool that would be less invasive than CSF sampling. Saliva has been studied as a potential biological fluid that could be used in the diagnosis and early screening of neurodegenerative diseases. This review aims to provide an insight into the current literature concerning salivary biomarkers used in the diagnosis of AD and PD. The most commonly studied salivary biomarkers in AD are β-amyloid1-42/1-40 and TAU protein, as well as α-synuclein and protein deglycase (DJ-1) in PD. Studies continue to be conducted on this subject and researchers are attempting to find correlations between specific biomarkers and early clinical symptoms, which could be key in creating new treatments for patients before the onset of symptoms.

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