Non-coding RNAs in Parkinson's Disease: Pathogenesis, Exosomes, and Therapeutic Horizons
Bibliographic record
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons and the accumulation of α-synuclein. Non-coding RNAs (ncRNAs)-including microRNAs, long non-coding RNAs, and circular RNAs-have emerged as critical regulators in PD pathogenesis by modulating pathways such as neuroinflammation, mitochondrial function, and protein clearance. Furthermore, exosomal ncRNAs facilitate intercellular communication, propagating pathological signals but also offering therapeutic potential. This review synthesizes the current understanding of ncRNA involvement in PD, structuring the analysis around key pathogenic mechanisms. We provide a critical perspective on the strengths and weaknesses of the current evidence, evaluate the major challenges facing the field-including biomarker validation and therapeutic delivery-and propose a path forward for future research. A deeper, more integrated understanding of these ncRNA networks is essential for developing novel diagnostics and treatments to halt the progression of PD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".