Involvement of the bed nucleus of the stria terminalis in L-Dopa induced dyskinesia
Bibliographic record
Abstract
A whole brain immediate early gene mapping highlighted the dorsolateral bed nucleus of the stria terminalis (dlBST) as a structure putatively involved in L-3,4-dihydroxyphenylalanine (L-Dopa)-induced dyskinesia (LID), the debilitating side-effects of chronic dopamine replacement therapy in Parkinson's disease (PD). dlBST indeed displayed an overexpression of ∆FosB, ARC, Zif268 and FRA2 only in dyskinetic rats. We thus hypothesized that dlBST could play a role in LID hyperkinetic manifestations. To assess the causal role of the dlBST in LID, we used Daun02 inactivation to selectively inhibit the electrical activity of dlBST ΔFosB-expressing neurons. Daun02 is a prodrug converted into Daunorubicin by ß-galactosidase. Then, the newly synthesized Daunorubicin is an inhibitor of neuronal excitability. Therefore, following induction of abnormal involuntary movements (AIMs), 6-OHDA rats were injected with Daun02 in the dlBST previously expressing ß-galactosidase under control of the FosB/ΔFosB promoter. Three days after Daun02 administration, the rats were tested daily with L-Dopa to assess LID. Pharmacogenetic inactivation of ∆FosB-expressing neuron electrophysiological activity significantly reduced AIM severity. The present study highlights the role of dlBST in the rodent analog of LID, offering a new target to investigate LID pathophysiology.
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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".