Cell type analysis of functional fetal dopamine cell suspension transplants in the striatum and substantia nigra of patients with Parkinson's disease
Bibliographic record
Abstract
We report the first post-mortem analysis of two patients with Parkinson's disease who received fetal midbrain transplants as a cell suspension in the striatum, and in one case also in the substantia nigra. These patients had a favourable clinical evolution and positive 18F-fluorodopa PET scans and did not develop motor complications. The surviving transplanted dopamine neurons were positively identified with phenotypic markers of normal control human substantia nigra (n = 3), such as tyrosine hydroxylase, G-protein-coupled inward rectifying current potassium channel type 2 (Girk2) and calbindin. The grafts restored the cell type that provides specific dopaminergic innervation to the most affected striatal regions in the parkinsonian brain. Such transplants were able to densely reinnervate the host putamen with new dopamine fibres. The patients received only 6 months of standard immune suppression, yet by post-mortem analysis 3-4 years after surgery the transplants appeared only mildly immunogenic to the host brain, by analysis of microglial CD45 and CD68 markers. This study demonstrates that, using these methods, dopamine neuronal replacement cell therapy can be beneficial for patients with advanced disease, and that changing technical approaches could have a favourable impact on efficacy and adverse events following neural transplantation.
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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 | 0.001 | 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".