The Effect of Growth Factors and Soluble Nogo-66 Receptor Protein on Transplanted Neural Stem/Progenitor Survival and Axonal Regeneration after Complete Transection of Rat Spinal Cord
Bibliographic record
Abstract
Adult central mammalian axons show minimal regeneration after spinal cord injury due to loss of oligodendrocytes, demyelination of surviving axons, absence of growth-promoting molecules, and inhibitors of axonal outgrowth. In the present study, we attempted to address these impediments to regeneration by using a combinatory strategy to enhance cell survival and regeneration after complete spinal cord transection (SCT) in adult rats. The strategy comprised: 1) adult rat brain-derived neural stem/progenitor cells (NSPCs) preseeded on laminin-coated chitosan channels; 2) extramedullary chitosan channels to promote axonal regrowth and reduce the barrier caused by scarring; 3) local delivery of a novel rat soluble Nogo-66 receptor protein [NgR(310)ecto-Fc, referred to as NgR] to block the inhibitory effect of myelin-based inhibitors; and 4) local delivery of basic fibroblast growth factor, epidermal growth factor, and platelet-derived growth factor to enhance survival and promote differentiation of transplanted cells. Compared with our previous studies where brain-derived NSPCs preseeded in extramedullary chitosan channels were implanted in the same SCT model but without growth factors and NgR, the present channel-growth factor combination produced greater numbers of surviving NSPCs after SCT. Also, the growth factors promoted preferential differentiation of NSPCs toward oligodendrocytes, while NgR significantly decreased astrocytic differentiation of NSPCs. NgR alone or in combination with NSPCs significantly enhanced the total number of myelinated fibers in the bridge and increased the area of the bridging tissue between the cord stumps. The combination of NgR, growth factors, and NSPCs had synergistic effect on bridge formation. However, only a small number of descending corticospinal tract axons grew into the central portions of the bridges as shown by anterograde tracing of the corticospinal tract with BDA. The majority of the regenerated axons in the channels originated from local host neurons adjacent to the tissue bridges. In conclusion, we showed that growth factors increased survival of transplanted NSPCs whereas NgR enhanced axonal regeneration, but the combination did not have additive effects on functional recovery or regeneration.
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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 | 0.000 |
| 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".