GDNF rescues the fate of neural progenitor grafts by attenuating Notch signals in the injured spinal cord in rodents
Bibliographic record
Abstract
Neural progenitor cell (NPC) transplantation is a promising strategy for the treatment of spinal cord injury (SCI). In this study, we show that injury-induced Notch activation in the spinal cord microenvironment biases the fate of transplanted NPCs toward astrocytes in rodents. In a screen for potential clinically relevant factors to modulate Notch signaling, we identified glial cell-derived neurotrophic factor (GDNF). GDNF attenuates Notch signaling by mediating delta-like 1 homolog (DLK1) expression, which is independent of GDNF's effect on cell survival. When transplanted into a rodent model of cervical SCI, GDNF-expressing human-induced pluripotent stem cell-derived NPCs (hiPSC-NPCs) demonstrated higher differentiation toward a neuronal fate compared to control cells. In addition, expression of GDNF promoted endogenous tissue sparing and enhanced electrical integration of transplanted cells, which collectively resulted in improved neurobehavioral recovery. CRISPR-induced knockouts of the DLK1 gene in GDNF-expressing hiPSC-NPCs attenuated the effect on functional recovery, demonstrating that this effect is partially mediated through DLK1 expression. These results represent a mechanistically driven optimization of hiPSC-NPC therapy to redirect transplanted cells toward a neuronal fate and enhance their integration.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".