Evidence map›Paper›PMID 29722028›Full record

ReviewBritish journal of pharmacology2018

Emerging disease-modifying strategies targeting α-synuclein for the treatment of Parkinson's disease.

Darren M O'Hara, Suneil K Kalia, Lorraine V Kalia

Open access · bronzeAbstract readReview
In one paragraph

Review in British journal of pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Mathematical Biology Models of Parkinson's Disease.CPT: pharmacometrics & systems pharmacology · 2019
    Review
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Darren M O'HaraKrembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Canada.ORCID 0000-0002-0766-2061
Suneil K KaliaKrembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Canada.
Lorraine V KaliaKrembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Canada.ORCID 0000-0002-9384-1305
University Health Network · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parkinson's disease is the most common neurodegenerative movement disorder. It arises as a result of neuronal cell death in specific brain regions, notably the substantia nigra pars compacta, and is characterized by the accumulation of α-synuclein in these brain regions. Current pharmacological therapies alleviate the motor symptoms of the disease and are particularly effective in the early stages of the disease. Ongoing drug development efforts focus on disease-modifying strategies that aim to halt or slow disease progression. In this review, we explore a number of emerging disease-modifying strategies with a focus on direct and indirect targeting of α-synuclein dysfunction. We summarize newer classes of small molecules and biological agents intended to attenuate protein aggregation or to target enzymes that may increase the degradation of the pathogenic forms of α-synuclein. Finally, we discuss emerging strategies that are demonstrating the potential for disease modification at the preclinical stage.

Indexed as

AcetylglucosamineAdrenergic beta-Agonistsalpha-SynucleinAnimalsGastrointestinal MicrobiomeHumansParkinson DiseaseAcetylglucosamineAdrenergic beta-Agonistsalpha-Synuclein

Identifiers

PMID29722028
PMCPMC6031880
OpenAlexW2803017118

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.