The Evolution of Pharmacological Treatment for Parkinsons Disease
Bibliographic record
Abstract
Since the introduction of levodopa therapy in the 60's, there has yet to be a more efficacious drug identified for the symptomatic treatment of Parkinson's disease (PD). Perhaps more importantly, there has been little to no success finding agents that have proven effective in protecting against neurodegeneration. In fact, recent development efforts have been primarily directed at stabilizing the side effects (wearing off, drug-induced dyskinesias, motor fluctuations) that accompany prolonged levodopa therapy, such as catechol O-methyltransferase inhibiton to combat the side effects of levodopa therapy. This review also examines alternative strategies to levodopa therapy, including potential adjuncts therapies, recent patents and future directions to be evaluated for neuroprotection. While dopamine agonists are inferior to levodopa in controlling motor symptoms, potential benefits and drawbacks with this class of drugs are presented. Potential neuroprotective agents such as monoamine oxidase-B inhibitors are also examined for their therapeutic benefit as well as their potential to slow disease progression. Neuroprotection will continue to be an important area of research in CNS drug development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 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 | 0.003 |
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".