Human stem cells harboring a suicide gene improve the safety and standardisation of neural transplants in Parkinsonian rats
Bibliographic record
Abstract
Abstract Despite advancements in human pluripotent stem cells (hPSCs) differentiation protocols to generate appropriate neuronal progenitors suitable for transplantation in Parkinson’s disease, resultant grafts contain low proportions of dopamine neurons. Added to this is the tumorigenic risk associated with the potential presence of incompletely patterned, proliferative cells within grafts. Here, we utilised a hPSC line carrying a FailSafe TM suicide gene (thymidine kinase linked to cyclinD1) to selectively ablate proliferative cells in order to improve safety and purity of neural transplantation in a Parkinsonian model. The engineered FailSafe TM hPSCs demonstrated robust ventral midbrain specification in vitro, capable of forming neural grafts upon transplantation. Activation of the suicide gene within weeks after transplantation, by ganciclovir administration, resulted in significantly smaller grafts without affecting the total yield of dopamine neurons, their capacity to innervate the host brain or reverse motor deficits at six months in a rat Parkinsonian model. Within ganciclovir-treated grafts, other neuronal, glial and non-neural populations (including proliferative cells), were significantly reduced—cell types that may pose adverse or unknown influences on graft and host function. These findings demonstrate the capacity of a suicide gene-based system to improve both the standardisation and safety of hPSC-derived grafts in a rat model of Parkinsonism.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".