MicroRNAs regulation in Parkinson’s disease, and their potential role as diagnostic and therapeutic targets
Bibliographic record
Abstract
MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression by binding to target messenger RNA (mRNA) molecules and promoting their degradation or blocking their translation. Parkinson's disease (PD) is a neurodegenerative disorder caused by the loss of dopaminergic neurons in the substantia nigra. There is increasing evidence to suggest that miRNAs play a role in the pathogenesis of PD. Studies have identified several miRNAs that are dysregulated in the brains of PD patients, and animal models of the disease. MiRNA expression dysregulation contributes to the onset and progression of PD by modulating neuroinflammation, oxidative stress, and protein aggregation genes. Moreover, miRNAs have emerged as potential therapeutic targets for PD. This review elucidates the changes in miRNA expression profiles associated with PD, emphasising their potential as diagnostic biomarkers and therapeutic targets, and detailing specific miRNAs implicated in PD and their downstream targets. Integrated Insights into miRNA Function, Microglial Activation, Diagnostic, and Treatment Prospects in PD Note: This figure is an original figure created by the authors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".