Serotonin- and Dopamine-mediated Neurotransmission in the Pathophysiology and Treatment of Parkinsonâs Disease
Bibliographic record
Abstract
Dopamine deficiency in the striatum is a central feature of Parkinson’s disease (PD). Symptomatic therapy with L-3,4-dihydroxyphenylalanine (L-DOPA) aims at restoring physiological dopaminergic neurotransmission within the brain. Unfortunately, current treatment paradigms fail to achieve this goal, which leads to the emergence of motor complications, secondary to long term L-DOPA administration, including dyskinesia and wearing-OFF, and non-motor symptoms related to disease progression, including neuropsychiatric symptoms such as psychosis. However, degenerative changes in PD are not limited to the dopaminergic system, but also affect the serotonergic system. There is increasing evidence suggesting an involvement of the serotonergic system in the pathophysiology of both motor and non-motor complications of PD. The work presented in this Thesis has investigated the serotonergic and dopaminergic systems in PD, by performing post mortem studies in the brains of PD patients and of parkinsonian non-human primates (NHPs), and by performing behavioural studies in the parkinsonian rat and NHP models of PD. The main conclusions presented are that: 1) serotonergic type 1A (5-HT1A) and 2A (5-HT2A) levels are altered in the brains of dyskinetic parkinsonian NHPs, suggesting abnormal 5-HT1A- and 5-HT2A-mediated neurotransmission in dyskinesia; 2) 5-HT2A receptor levels are altered in the brains of PD patients with visual hallucinations (VH), suggesting abnormal 5-HT2A-mediated neurotransmission in VH; 3) some of the anti-dyskinetic actions attributed to stimulating 5-HT1A or antagonising 5-HT2A receptors might in fact be due to an antagonist action at D4 receptors, as antagonising D4 receptors significantly alleviates L-DOPA-induced dyskinesia in rat and NHP models of PD; 4) concurrent inhibition of the serotonin and dopamine transporters (SERT and DAT, respectively) enhances duration of L-DOPA-induced ON-time in the parkinsonian NHP. However, the ratio of SERT/ DAT inhibition appears crucial in determining the quality of this extra ON-time; SERT > DAT inhibition exacerbates the severity of L-DOPA-induced dyskinesia, whereas SERT = DAT and DAT > SERT inhibition do not worsen the severity of L-DOPA-induced dyskinesia. Together these data extend our knowledge of the interaction between serotonin and dopamine, specifically as they relate to symptoms and side effects of dopamine replacement therapy in PD and highlight potential novel therapeutic approaches to 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".