Treating Parkinson’s Disease with Antibodies: Previous Studies and Future Directions
Bibliographic record
Abstract
Parkinson's disease is a neurodegenerative disorder mainly characterized by the degeneration of dopaminergic neurons in the substantia nigra. Degenerating neurons contain abnormal aggregates called Lewy bodies, that are predominantly composed of the misfolded and/or mutated alpha-synuclein protein. Post-translational modifications, cellular stress, inflammation and gene mutations are thought to trigger its pathological misfolding and aggregation. With alpha-synuclein pathology being strongly associated with dopaminergic neuronal toxicity, strategies aimed to reduce its burden are expected to be beneficial in slowing disease progression. Moreover, multiple sources of evidence suggest a cell-to-cell transmission of pathological alpha-synuclein in a prion-like manner. Therefore, antibodies targeting extra- or intracellular alpha-synuclein could be efficient in limiting the aggregation and transmission. Several active and passive immunization strategies have been explored to target alpha-synuclein. Here, we summarize immunotherapeutic approaches that were tested in pre-clinical or clinical studies in the last two decades in an attempt to treat Parkinson's disease.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".