Cognitive Deficits in Alzheimer’s Disease, Parkinson’s Disease, and Huntington’s Chorea

Author(s):  
Elka Stefanova ◽  
Vladimir Kostic ◽  
Gordana Ocic ◽  
Ljubomir Ziropadja
Author(s):  
Peter Falkai ◽  
Bernhard Bogerts

The traditional domains of neuropathology are well-defined organic brain diseases with an obvious pathology, such as tumours, infections, vascular diseases, trauma, or toxic and hypoxemic changes, as well as degenerative brain diseases (e.g. Alzheimer's disease, Parkinson's disease, and Huntington's chorea). Neuropathological investigations of these brain disorders have been rewarding, because patients with any of these conditions can be expected to have gross morphological or more or less specific neurohistological anomalies related to the clinical symptoms of the disorders. Moreover, the type of brain pathology of these well-defined disease entities is quite homogenous. For example, it is highly unlikely that a patient with Parkinson's disease would not exhibit morphological changes and Lewy bodies in the nigrostriatal system, just as much a person with Huntington's chorea would have a normal striatum, or a patient with Pick'sor Alzheimer's disease would have no changes in the cerebralcortex. In contrast, the history of the neuropathology of psychiatric disorders outside primary degenerative diseases is much more controversial, because no such obvious and homogenous types of brain pathology (as seen in neurological disorders) have yet been detected for the major psychiatric illnesses such as schizophrenia, affective disorders, substance-related disorders, or personality disorders. The scope of this chapter is to summarize the neuropathological findings in schizophrenia, affective disorders, and alcoholism. Tables 2.3.5.1, 2.3.5.2, 2.3.5.3, and 2.3.5.4 highlight the significant findings. It goes beyond the scope of this chapter to review thelarge body of literature on the dementias, including specifically Alzheimer's disease. Concerning this matter, the reader is referred to several comprehensive reviews (e.g. Jellinger and Bancher 1998).


2019 ◽  
Vol 20 (14) ◽  
pp. 3380 ◽  
Author(s):  
Akira Nakajima ◽  
Yasushi Ohizumi

Alzheimer’s disease (AD), which is characterized by the presence of amyloid-β (Aβ) plaques and neurofibrillary tangles, accompanied by neurodegeneration, is the most common form of age-related neurodegenerative disease. Parkinson’s disease (PD) is the second most common neurodegenerative disease after AD, and is characterized by early prominent loss of dopaminergic neurons in the substantia nigra pars compacta. As currently available treatments are not able to significantly alter the progression of these diseases, successful therapeutic and preventive interventions are strongly needed. In the course of our survey of substances from natural resources having anti-dementia and neuroprotective activity, we found nobiletin, a polymethoxylated flavone from the peel of Citrus depressa. Nobiletin improved cognitive deficits and the pathological features of AD, such as Aβ pathology, hyperphosphorylation of tau, and oxidative stress, in animal models of AD. In addition, nobiletin improved motor and cognitive deficits in PD animal models. These observations suggest that nobiletin has the potential to become a novel drug for the treatment and prevention of neurodegenerative diseases such as AD and PD.


2018 ◽  
Vol 76 (3) ◽  
pp. 145-149
Author(s):  
Carlos Henrique Ferreira Camargo ◽  
Augusto Bronzini ◽  
Eduardo de Souza Tolentino ◽  
Camila Medyk ◽  
Gustavo Leopold Schultz-Pereira

ABSTRACT The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological battery was created to assess cognitive impairment in Alzheimer's disease (AD) but it is widely-used for various dementias. The aim of this study was to analyze the efficacy of using the CERAD battery in the assessment of patients with Parkinson's disease. Forty-nine patients with Parkinson's disease were divided into two groups (one with dementia and one without) using the Movement Disorder Society criteria for Parkinson's disease dementia. Cognitive deficits were assessed with the Clinical Dementia Rating Scale as the gold standard, and the CERAD. The ROC curve for the CERAD battery had an area under the curve = 0.989 (95% CI = 0.967 – 1, p<0.0001). Among the CERAD subtests, verbal fluency had the worst accuracy, and word list learning had the best accuracy. Despite the limits of this study, the CERAD battery can be efficient for assessment of cognitive deficits in Parkinson's disease patients.


2015 ◽  
Vol 8 (2) ◽  
pp. 142-147 ◽  
Author(s):  
Vaitsa Giannouli ◽  
Magda Tsolaki

The article aims at investigating whether patients from Greece with different kinds of cognitive deficits (resulting from Alzheimer’s Disease, Parkinson’s Disease Dementia, and Mild Cognitive Impairment) can be characterized as financially capable (based on neuropsychological assessment), and if this claimed (in)capacity is in accordance with their personal belief of (in)capacity. Results revealed that the vast majority of the mild, moderate and severe Alzheimer’s disease patients as well as patients with Mild Cognitive Impairment and Parkinson’s disease, who scored significantly lower than normal on a relevant financial decision-making capacity test, believed that they were capable to handle their finances. This finding is in contrast with their actual financial capacity scores and the beliefs of their family members-caregivers on this issue. Some critical questions concerning incapacity and intellectual insight are raised, and future cross-cultural investigative attempts on this issue are suggested.


2020 ◽  
Vol 18 (10) ◽  
pp. 758-768 ◽  
Author(s):  
Khadga Raj ◽  
Pooja Chawla ◽  
Shamsher Singh

: 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).


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Manan Binth Taj Noor ◽  
Nusrat Zerin Zenia ◽  
M Shamim Kaiser ◽  
Shamim Al Mamun ◽  
Mufti Mahmud

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.


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