scholarly journals Biomarkers in Parkinson’s disease

2014 ◽  
pp. 7-12
Author(s):  
Grace Crotty
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Disease Mechanisms ◽  
Age Related ◽  
Potential Biomarkers

Do you know anyone who has been diagnosed with Parkinson’s disease? What is Parkinson’s disease? In the Department of Medicine in UCC I am carrying out research on this condition, and I’m working with people who have Parkinson’s disease (PD). I hope to increase our understanding of the disease mechanisms underlying PD along with identifying potential biomarkers for PD. What are biomarkers? Why do we need a biomarker? Keep on reading to discover more! It is the second most common age-related neurodegenerative condition after Alzheimer’s disease. It affects 1% of people over 65 years and 4% over 80 years. 30 million people are currently affected worldwide. It was first described by Dr. James Parkinson in 1817 in his book “An Essay on the shaking palsy”. Parkinson’s disease occurs when there is not enough of a chemical called dopamine being produced by your brain. People with PD classically present to their ...

scholarly journals The Role of Lysosomes in a Broad Disease-Modifying Approach Evaluated across Transgenic Mouse Models of Alzheimer’s Disease and Parkinson’s Disease and Models of Mild Cognitive Impairment

2019 ◽  
Vol 20 (18) ◽  
pp. 4432 ◽  
Author(s):  
Jeannie Hwang ◽  
Candice M. Estick ◽  
Uzoma S. Ikonne ◽  
David Butler ◽  
Morgan C. Pait ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Amyloid Β ◽  
Age Related ◽  
Disease Modifying

Many neurodegenerative disorders have lysosomal impediments, and the list of proposed treatments targeting lysosomes is growing. We investigated the role of lysosomes in Alzheimer’s disease (AD) and other age-related disorders, as well as in a strategy to compensate for lysosomal disturbances. Comprehensive immunostaining was used to analyze brains from wild-type mice vs. amyloid precursor protein/presenilin-1 (APP/PS1) mice that express mutant proteins linked to familial AD. Also, lysosomal modulation was evaluated for inducing synaptic and behavioral improvements in transgenic models of AD and Parkinson’s disease, and in models of mild cognitive impairment (MCI). Amyloid plaques were surrounded by swollen organelles positive for the lysosome-associated membrane protein 1 (LAMP1) in the APP/PS1 cortex and hippocampus, regions with robust synaptic deterioration. Within neurons, lysosomes contain the amyloid β 42 (Aβ42) degradation product Aβ38, and this indicator of Aβ42 detoxification was augmented by Z-Phe-Ala-diazomethylketone (PADK; also known as ZFAD) as it enhanced the lysosomal hydrolase cathepsin B (CatB). PADK promoted Aβ42 colocalization with CatB in lysosomes that formed clusters in neurons, while reducing Aβ deposits as well. PADK also reduced amyloidogenic peptides and α-synuclein in correspondence with restored synaptic markers, and both synaptic and cognitive measures were improved in the APP/PS1 and MCI models. These findings indicate that lysosomal perturbation contributes to synaptic and cognitive decay, whereas safely enhancing protein clearance through modulated CatB ameliorates the compromised synapses and cognition, thus supporting early CatB upregulation as a disease-modifying therapy that may also slow the MCI to dementia continuum.

scholarly journals S-nitrosylation-impaired autophagy: An alternative mechanism underlying aging?

2013 ◽  
Author(s):  
Qing-Ping Zeng
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Neurodegenerative Disorders ◽  
Alternative Mechanism ◽  
Age Related ◽  
Surprising Finding

Aging is mysterious with unknown managing patterns. A surprising finding on the tune mode of autophagy by S-nitrosylation is a distinctive step towards the interpretation of the mechanism underlying aging and age-related diseases. This commentary article will discuss, in a wider sense, the implications of S-nitrosylation- and nitration-switched dysfunction of proteins/enzymes in neurodegenerative disorders including Alzheimer's disease (AD), Huntington's diseases (HD) and Parkinson's disease (PD).

scholarly journals Role of Mitochondria in Neurodegenerative Diseases: Mitochondria as a Therapeutic Target in Alzheimer's Disease

CNS Spectrums ◽  
2009 ◽  
Vol 14 (S7) ◽  
pp. 8-13 ◽  
Author(s):  
P. Hemachandra Reddy
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Cell Death ◽  
Neurodegenerative Diseases ◽  
Disease Progression ◽  
Neuronal Cell ◽  
Causal Factors ◽  
Age Related

A growing body of evidence suggests that mitochondrial abnormalities are involved in aging and in age-related neurodegenerative diseases as well as cancer, diabetes, and several other diseases known to be affected by mitochondria. Causal factors for most age-related neurodegenerative diseases—including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis (ALS), and Friedrich ataxia (FRDA)—are largely unknown. Genetic defects are reported to cause a small number of neurodegenerative diseases (Slide 1), but cellular, molecular, and pathological mechanisms of disease progression and selective neuronal cell death are not understood fully in these diseases. However, based on several cellular, molecular, and animal model studies of Alzheimer's disease, Parkinson's disease, ALS, FRDA, cancer, and diabetes, aging may play a large role in cell death in these diseases. Age-dependent, mitochondrially-generated reactive oxygen species (ROS) have been identified as important factors responsible for disease progression and cell death, particularly in late-onset diseases, in which genetic mutations are not causal factors.

scholarly journals S-nitrosylation-impaired autophagy: An alternative mechanism underlying aging?

2013 ◽  
Author(s):  
Qing-Ping Zeng
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Neurodegenerative Disorders ◽  
Alternative Mechanism ◽  
Age Related ◽  
Surprising Finding

Aging is mysterious with unknown managing patterns. A surprising finding on the tune mode of autophagy by S-nitrosylation is a distinctive step towards the interpretation of the mechanism underlying aging and age-related diseases. This commentary article will discuss, in a wider sense, the implications of S-nitrosylation- and nitration-switched dysfunction of proteins/enzymes in neurodegenerative disorders including Alzheimer's disease (AD), Huntington's diseases (HD) and Parkinson's disease (PD).

scholarly journals Advances in Parkinson’s Disease Drugs

Biomolecules ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1640
Author(s):  
Antonio Di Stefano ◽  
Lisa Marinelli
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Related Disorder ◽  
Age Related

Parkinson’s disease (PD) is the second most common neurodegenerative age-related disorder worldwide after Alzheimer’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.

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