Translational profiling reveals novel gene expression changes in the direct and indirect pathways in a mouse model of LDOPA-induced dyskinesia
Bibliographic record
Abstract
Abstract The molecular mechanisms underlying L-dihydroxyphenylalanine (LDOPA) induced dyskinesia in Parkinson’s disease are poorly understood. Here we employ two transgenic mouse lines, combining translating ribosomal affinity purification (TRAP) with bacterial artificial chromosome expression (Bac), to selectively isolate RNA from either DRD1A expressing striatonigral, or DRD2 expressing striatopallidal medium spiny neurons (MSNs) of the direct and indirect pathways respectively, to study changes in translational gene expression following repeated LDOPA treatment. 6-OHDA lesioned DRD1A and DRD2 BacTRAP mice were treated with either saline or LDOPA bi-daily for 21 days over which time they developed abnormal involuntary movements reminiscent of dyskinesia. On day 22, all animals received LDOPA 40 minutes prior to sacrifice. The striatum of the lesioned hemisphere was dissected and subject to TRAP. Extracted ribosomal RNA was amplified, purified and gene expression was quantified using microarray. 195 significantly varying transcripts were identified among the 4 treatment groups. Pathway analysis revealed an overrepresentation of calcium signaling and long-term potentiation in the DRD1A expressing MSNs of the direct pathway, with significant involvement of long-term depression in the DRD2 expressing MSNs of the indirect pathway following chronic treatment with LDOPA. Several MAPK associated genes ( NR4A1 , GADD45G , STMN1 , FOS and DUSP1 ) differentiated the direct and indirect pathways following both acute and chronic LDOPA treatment. However, the MAPK pathway activator PAK1 was downregulated in the indirect pathway and upregulated in the direct pathway, strongly suggesting a role for PAK1 in regulating the opposing effects of LDOPA on these two pathways in dyskinesia. Future studies will assess the potential of targeting these genes and pathways to prevent the development of LDOPA-induced dyskinesia.
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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 | 0.001 | 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".