Maladaptive plasticity of serotonin axon terminals in levodopa‐induced dyskinesia
Bibliographic record
Abstract
OBJECTIVE: Striatal serotonin projections have been implicated in levodopa-induced dyskinesia by providing an unregulated source of dopamine release. We set out to determine whether these projections are affected by levodopa treatment in a way that would favor the occurrence of dyskinesia. METHODS: As an index of terminal serotonin innervation density, we measured radioligand binding to the plasma membrane serotonin transporter (SERT) in levodopa-treated dyskinetic and nondyskinetic subjects, using brain tissue from both rat and monkey models of Parkinson disease as well as parkinsonian patients. In addition, striatal tissue from dyskinetic rats was used for morphological and ultrastructural analyses of serotonin axon terminals, and for studies of stimulated [³H]dopamine release. RESULTS: Across all conditions examined, striatal levels of SERT radioligand binding were significantly elevated in dyskinetic subjects compared to nondyskinetic cases. In the rat striatum, dyskinesiogenic levodopa treatment had induced sprouting of serotonin axon varicosities having a relatively high synaptic incidence. This response was associated with increased depolarization-induced [³H]dopamine release and with a stronger release potentiation by brain-derived neurotrophic factor. INTERPRETATION: This study provides the first evidence that L-dopa treatment induces sprouting of serotonin axon terminals, with an increased incidence of synaptic contacts, and a larger activity-dependent potentiation of dopamine release in the dopamine-denervated striatum. Treatment-induced plasticity of the serotonin innervation may therefore represent a previously unappreciated cause of altered dopamine dynamics. These results are important for understanding the mechanisms by which L-dopa pharmacotherapy predisposes to dyskinesia, and for defining biomarkers of motor complications in Parkinsons 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 | 0.000 | 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 | 0.000 |
| 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".