A multitarget basal ganglia dopaminergic and GABAergic transplantation strategy enhances behavioural recovery in parkinsonian rats
Bibliographic record
Abstract
The current transplantation paradigm for Parkinson's disease that places foetal dopaminergic cells in the striatum neither normalizes neuronal activity in basal ganglia structures such as the substantia nigra (SN) and subthalamic nucleus (STN) nor leads to complete functional recovery. It was hypothesized that restoration of parkinsonian deficits requires inhibition of the pathological overactivity of the STN and SN in addition to restoration of dopaminergic activity in the striatum. To achieve inhibition, a multitargeted basal ganglia transplantation strategy using GABAergic cells derived from either foetal striatal primordia (FSP) cells or human neural precursor cells (hNPCs) expanded in suspension bioreactors was investigated. In hemiparkinsonian rats, transplantation of foetal rat dopaminergic cells in the striatum in conjunction with GABAergic grafts in the STN and/or SN promoted significant improvement in forelimb akinesia and motor function compared to transplantation of intrastriatal dopaminergic grafts alone or in conjunction with undifferentiated hNPCs. In culture, FSP cells exhibited neuronal electrophysiological properties. However, recordings from GABAergic hNPCs revealed limited ionic conductances and an inability to fire action potentials. Despite this, they were almost as efficacious as FSP cells in inducing functional recovery following transplantation, suggesting that such recovery may have been mediated by secretion of GABA rather than by functional integration into the host. Thus, restoration of dopaminergic activity to the striatum in concert with inhibition of the STN and SN by GABAergic grafts may be beneficial for improving clinical outcomes in patients with Parkinson's disease and potential clinical application of this strategy may be enhanced by the use of differentiated hNPCs.
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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) | 0.000 | 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 | 0.000 |
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".