Systematic Review of Environmental Epigenetic Modifiers in Neurodegenerative Diseases
by Pranay Wal·Updated 10d ago
130.7 KB1files
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Description
A systematic review compiled according to PRISMA principles, summarizing experimental, epidemiological, and translational data on environmental neurotoxicants and epigenetic mechanisms. The 130.7 KB PDF document was authored by Pranay Wal and last updated on May 27, 2026. It synthesizes findings on how exposures to heavy metals, pollutants, and synthetic neurotoxicants are linked to epigenetic dysregulation and neurological outcomes.
Use Cases
Identify potential epigenetic biomarkers for neurodegenerative diseases based on described mechanisms like DNA methylation changes and microRNA dysregulation.
Survey molecular pathways connecting environmental exposures to neurodegeneration based on the review's synthesis of oxidative stress, mitochondrial dysfunction, and neuroinflammation.
Guide future research priorities in precision prevention based on the review's conclusions regarding multi-omics techniques and longitudinal studies.
Strengths
The review follows PRISMA principles for systematic methodology, as stated in the description.
It synthesizes multiple data types, including experimental, epidemiological, mechanistic, and translational data, as mentioned in the method section.
The document is openly licensed under CC-BY-4.0.
Limitations
The dataset is a single 130.7 KB PDF file, representing a very limited textual scope rather than primary data.
Row count and column-level documentation are absent; field semantics must be inferred from the review text after download.
The data may reflect publication bias inherent to the systematic review's source selection from biomedical databases.
Provenance
Source
figshare
Collection Method
Structured searches across major biomedical databases followed by a multistage selection procedure, as described.
Freshness
Last updated 2026-05-27 22:01:48; freshness should be verified.
The file is a PDF containing a review article, not a structured dataset.