Heterogeneous expression of dopaminergic markers and <scp> <i>Vglut2</i> </scp> in mouse mesodiencephalic dopaminergic nuclei <scp>A8–A13</scp>
Bibliographic record
Abstract
Co-transmission of glutamate by brain dopaminergic (DA) neurons was recently proposed as a potential factor influencing cell survival in models of Parkinson's disease. Intriguingly, brain DA nuclei are differentially affected in Parkinson's disease. Whether this is associated with different patterns of co-expression of the glutamatergic phenotype along the rostrocaudal brain axis is unknown in mammals. We hypothesized that, as in zebrafish, the glutamatergic phenotype is present preferentially in the caudal mesodiencephalic DA nuclei. Here, we used in mice a cell fate mapping strategy based on reporter protein expression (ZsGreen) consecutive to previous expression of the vesicular glutamate transporter 2 (Vglut2) gene, coupled with immunofluorescence experiments against tyrosine hydroxylase (TH) or dopamine transporter (DAT). We found three expression patterns in DA cells, organized along the rostrocaudal brain axis. The first pattern (TH-positive, DAT-positive, ZsGreen-positive) was found in A8-A10. The second pattern (TH-positive, DAT-negative, ZsGreen-positive) was found in A11. The third pattern (TH-positive, DAT-negative, ZsGreen-negative) was found in A12-A13. These patterns should help to refine the establishment of the homology of DA nuclei between vertebrate species. Our results also uncover that Vglut2 is expressed at some point during cell lifetime in DA nuclei known to degenerate in Parkinson's disease and largely absent from those that are preserved, suggesting that co-expression of the glutamatergic phenotype in DA cells influences their survival in Parkinson's disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".