Evidence map›Paper›PMID 30027906›Full record

ReviewJournal of genetics2018

Parkinson's disease: what the model systems have taught us so far.

Swagata Ghatak, Dorit Trudler, Nima Dolatabadi, Rajesh Ambasudhan

Abstract readReview
PubMed
In one paragraph

Review in Journal of genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Blood-Brain Barrier Breakdown in Neuroinflammation: Current In Vitro Models.International journal of molecular sciences · 2023
    Review
  6. Article
  7. Article
  8. Article
  9. Modeling Parkinson's Disease: Not Only Rodents?Frontiers in aging neuroscience · 2021
    Article
  10. Article
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

4 authors at 2 institutions in 1 country.

Swagata GhatakNeurodegenerative Disease Center, Scintillon Institute, San Diego, CA 92121, USA. rajesh@scintillon.org.
Dorit Trudler
Nima Dolatabadi
Rajesh Ambasudhan
Scripps Research Institute · USScintillon Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parkinson's disease (PD) is a debilitating neurodegenerative disorder, for which people above the age of 60 show an increased risk. Although there has been great advancement in understanding the disease-related abnormalities in brain circuitry and development of symptomatic treatments, a cure for PD remains elusive. The discovery of PD associated gene mutations and environmental toxins have yielded animal models of the disease. These models could recapitulate several key aspects of PD, and provide more insights into the disease pathogenesis. They have also revealed novel aspects of the disease mechanism including noncell autonomous events and spreading of pathogenic protein species across the brain. Nevertheless, none of these models so far can comprehensively represent all aspects of the human disease. While the field is still searching for the perfect model system, recent developments in stem cell biology have provided a new dimension to modelling PD, especially doing it in a patient-specific manner. In the current review, we attempt to summarize the key findings in the areas discussed above, and highlight how the core PD pathology distinguishes itself from other neurodegenerative disorders while also resembling them in many aspects.

Indexed as

Disease Models, AnimalAnimalsGene-Environment InteractionHumansInflammationModels, BiologicalMutationParkinson Disease

Identifiers

PMID30027906
OpenAlexW2883318904

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.