P.115 Regenerative white matter effect of neurod1-based gene therapy in non-human primate stroke model
Bibliographic record
Abstract
Background: Stroke therapies remain an area of ongoing research. Gene therapies offer a novel approach to repair tissue damage, particularly NeuroD1-mediated astrocyte-to-neuron conversion, which regenerates functional neurons after ischemic injury. Here, we applied NeuroD1 therapy in a non-human primates (NHPs) stroke model to evaluate its effects on corticospinal tract (CST) recovery and motor performance. Methods: Eight NHPs underwent middle cerebral artery occlusion (MCAO). Fourteen days later, six animals received intracranial NeuroD1 treatment (three high-dose, three low-dose), while two received a control solution. Neurological and functional performance were assessed daily. MRI scans were performed at baseline and at 7, 30, 90, 120, and 240 days post-MCAO, with the bilateral CST reconstructed at each time point. All procedures followed Canadian Council of Animal Care guidelines and were approved by Queen’s University’s Animal Use Subcommittee. Results: We found that NHPs receiving the control solution exhibited poorer motor recovery and minimal CST reconstruction. In contrast, those treated with a low dose of NeuroD1 demonstrated motor and functional recovery along with CST reconstruction. Notably, animals receiving the higher dose showed the most significant overall recovery including a greater CST integrity. Conclusions: NeuroD1 treatment promotes white matter tract restoration and facilitates motor recovery following stroke.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".