High-Frequency Stimulation of the Subthalamic Nucleus Potentiates l-DOPA-Induced Neurochemical Changes in the Striatum in a Rat Model of Parkinson's Disease
Bibliographic record
Abstract
This study examined the cellular changes produced in the striatum by chronic L-DOPA treatment and prolonged subthalamic nucleus high-frequency stimulation (STN-HFS) applied separately, successively, or in association, in the 6-hydroxydopamine-lesioned rat model of Parkinson's disease (PD). Only animals showing severe L-DOPA-induced dyskinesias (LIDs) were included, and STN-HFS was applied for 5 d at an intensity efficient for alleviating akinesia without inducing dyskinesias. L-DOPA treatment alone induced FosB/deltaFosB immunoreactivity, exacerbated the postlesional increase in preproenkephalin, reversed the decrease in preprotachykinin, and markedly increased mRNA levels of preprodynorphin and of the glial glutamate transporter GLT1, which were respectively decreased and unaffected by the dopamine lesion. STN-HFS did not affect per se the postlesion changes in any of these markers. However, when applied in association with L-DOPA treatment, it potentiated the positive modulation exerted by L-DOPA on all of the markers examined and tended to exacerbate LIDs. After 5 d of L-DOPA withdrawal, the only persisting drug-induced responses were an elevation in preprodynorphin mRNA levels and in the number of FosB/deltaFosB-immunoreactive neurons. Selective additional increases in these two markers were measured when STN-HFS was applied subsequently to L-DOPA treatment. These data provide the first evidence that STN-HFS exacerbates the responsiveness of striatal cells to L-DOPA medication and suggest that STN-HFS acts specifically through an L-DOPA-modulated signal transduction pathway associated with LIDs in the striatum. They point to striatal cells as a primary site for the complex interactions between these two therapeutic approaches in PD and argue against a direct anti-dyskinetic action of STN-HFS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".