Platelet‐derived growth factor‐responsive neural precursors give rise to myelinating oligodendrocytes after transplantation into the spinal cords of contused rats and dysmyelinated mice
Bibliographic record
Abstract
Spinal cord injury (SCI) results in substantial oligodendrocyte death and subsequent demyelination leading to white-matter defects. Cell replacement strategies to promote remyelination are under intense investigation; however, the optimal cell for transplantation remains to be determined. We previously isolated a platelet-derived growth factor (PDGF)-responsive neural precursor (PRP) from the ventral forebrain of fetal mice that primarily generates oligodendrocytes, but also astrocytes and neurons. Importantly, human PRPs were found to possess a greater capacity for oligodendrogenesis than human epidermal growth factor- and/or fibroblast growth factor-responsive neural stem cells. Therefore, we tested the potential of PRPs isolated from green fluorescent protein (GFP)-expressing transgenic mice to remyelinate axons in the injured rat spinal cord. PRPs were transplanted 1 week after a moderate thoracic (T9) spinal cord contusion in adult male rats. After initial losses, PRP numbers remained stable from 2 weeks posttransplantation onward and those surviving cells integrated into host tissue. Approximately one-third of the surviving cells developed the typical branched phenotype of mature oligodendrocytes, expressing the marker APC-CC1. The close association of GFP cells with myelin basic protein as well as with Kv1.2 and Caspr in the paranodal and juxtaparanodal regions of nodes of Ranvier indicated that the transplanted cells successfully formed mature myelin sheaths. Transplantation of PRPs into dysmyelinated Shiverer mice confirmed the ability of PRP-derived cells to produce compact myelin sheaths with normal periodicity. These findings indicate that PRPs are a novel candidate for CNS myelin repair, although PRP-derived myelinating oligodendrocytes were insufficient to produce behavioral improvements in our model of SCI.
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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 | 0.000 | 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".