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Parkinson’s Disease: Biomarkers, Treatment, and Risk Factors

Overview of attention for article published in Frontiers in Neuroscience, August 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

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1 news outlet
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8 X users
facebook
1 Facebook page
wikipedia
1 Wikipedia page

Citations

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349 Dimensions

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944 Mendeley
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Title
Parkinson’s Disease: Biomarkers, Treatment, and Risk Factors
Published in
Frontiers in Neuroscience, August 2018
DOI 10.3389/fnins.2018.00612
Pubmed ID
Authors

Fatemeh N. Emamzadeh, Andrei Surguchov

Abstract

Parkinson's disease (PD) is a progressive neurodegenerative disorder caused mainly by lack of dopamine in the brain. Dopamine is a neurotransmitter involved in movement, motivation, memory, and other functions; its level is decreased in PD brain as a result of dopaminergic cell death. Dopamine loss in PD brain is a cause of motor deficiency and, possibly, a reason of the cognitive deficit observed in some PD patients. PD is mostly not recognized in its early stage because of a long latency between the first damage to dopaminergic cells and the onset of clinical symptoms. Therefore, it is very important to find reliable molecular biomarkers that can distinguish PD from other conditions, monitor its progression, or give an indication of a positive response to a therapeutic intervention. PD biomarkers can be subdivided into four main types: clinical, imaging, biochemical, and genetic. For a long time protein biomarkers, dopamine metabolites, amino acids, etc. in blood, serum, cerebrospinal liquid (CSF) were considered the most promising. Among the candidate biomarkers that have been tested, various forms of α-synuclein (α-syn), i.e., soluble, aggregated, post-translationally modified, etc. were considered potentially the most efficient. However, the encouraging recent results suggest that microRNA-based analysis may bring considerable progress, especially if it is combined with α-syn data. Another promising analysis is the advanced metabolite profiling of body fluids, called "metabolomics" which may uncover metabolic fingerprints specific for various stages of PD. Conventional pharmacological treatment of PD is based on the replacement of dopamine using dopamine precursors (levodopa, L-DOPA, L-3,4 dihydroxyphenylalanine), dopamine agonists (amantadine, apomorphine) and MAO-B inhibitors (selegiline, rasagiline), which can be used alone or in combination with each other. Potential risk factors include environmental toxins, drugs, pesticides, brain microtrauma, focal cerebrovascular damage, and genomic defects. This review covers molecules that might act as the biomarkers of PD. Then, PD risk factors (including genetics and non-genetic factors) and PD treatment options are discussed.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 944 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 944 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 167 18%
Student > Master 111 12%
Student > Ph. D. Student 94 10%
Researcher 59 6%
Student > Doctoral Student 31 3%
Other 83 9%
Unknown 399 42%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 127 13%
Neuroscience 88 9%
Medicine and Dentistry 80 8%
Pharmacology, Toxicology and Pharmaceutical Science 58 6%
Nursing and Health Professions 36 4%
Other 124 13%
Unknown 431 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 July 2022.
All research outputs
#2,232,769
of 25,385,509 outputs
Outputs from Frontiers in Neuroscience
#1,316
of 11,542 outputs
Outputs of similar age
#44,854
of 344,376 outputs
Outputs of similar age from Frontiers in Neuroscience
#39
of 241 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 344,376 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 241 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.