Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 401

The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.

Historical Perspective: Models of Parkinson’s Disease

Open access
Chia, Shyh Jenn, Tan, Eng-King, Chao, Yin-Xia·2020·International Journal of Molecular Sciences

Abstract

Parkinson’s disease (PD) is the most common movement disorder with motor and nonmotor signs. The current therapeutic regimen for PD is mainly symptomatic as the etio-pathophysiology has not been fully elucidated. A variety of animal models has been generated to study different aspects of the disease for understanding the pathogenesis and therapeutic development. The disease model can be generated through neurotoxin-based or genetic-based approaches in a wide range of animals such as non-human primates (NHP), rodents, zebrafish, Caenorhabditis (C.) elegans, and drosophila. Cellular-based disease model is frequently used because of the ease of manipulation and suitability for large-screen assays. In neurotoxin-induced models, chemicals such as 6-hydroxydopamine (6-OHDA), 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), rotenone, and paraquat are used to recapitulate the disease. Genetic manipulation of PD-related genes, such as α-Synuclein(SNCA), Leucine-rich repeat kinase 2 (LRRK2), Pten-Induced Kinase 1 (PINK1), Parkin(PRKN), and Protein deglycase (DJ-1) Are used in the transgenic models. An emerging model that combines both genetic- and neurotoxin-based methods has been generated to study the role of the immune system in the pathogenesis of PD. Here, we discuss the advantages and limitations of the different PD models and their utility for different research purposes.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/ijms21072464

Cites

90 of 90 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 90 references

Cited by

See all 401

Metadata

Authors
Chia, S. J., Tan, E.-K., & Chao, Y.-X.
Venue
International Journal of Molecular Sciences
Publisher
MDPI AG
Published
2020-04-02
Volume
21
Issue
7
Pages
2464
ISSN
1422-0067 (ISSN-L)
OpenAlex
W3015095871
Cited by
401
References
90
FWCI
19.01
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Historical Perspective: Models of Parkinson’s Disease. https://app.cochat.ai/papers/10.3390/ijms21072464
The paper
Chia, S. J., Tan, E.-K., & Chao, Y.-X. (2020). Historical Perspective: Models of Parkinson’s Disease. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms21072464

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.