Intraspinal Transplantation of hNT Neurons in the Lesioned Adult Rat Spinal Cord
Bibliographic record
Abstract
BACKGROUND: The role of neural transplantation as a restorative strategy for spinal cord injury continues to be intensely investigated. Ideally, the tissue source for transplantation must be readily available, free of disease and able to survive and mature following implantation into the adverse environment created by the injury. We have studied the use of a commercially available cell line of cultured human neurons (hNT neurons) as a tissue source for neural transplantation in spinal cord injury. METHODS: Following a left lateral thoracic hemisection, 54 immunosuppressed, female Wistar rats were randomly allocated into different treatment groups; hemisection only or hemisection and hNT cell transplantation (via a bridge, double or triple graft). Grafting occurred three days after spinal cord injury. After thirteen weeks the animals were sacrificed and tissue sections were stained with human neuron specific enolase and human specific neural cell adhesion molecule. RESULTS: Immunohistochemical evidence of graft survival was displayed in 66.7% of the surviving, grafted animals. Fibre outgrowth, greatest in the bridge and triple grafts, was observed in both rostral and caudal directions essentially bridging the lesion. Double grafts were smaller, displaying less fibre outgrowth, which did not cross the lesion. Long fibre outgrowth was evident up to 2 cm from the graft as assessed by tracing and immunohistochemical studies. CONCLUSIONS: Bridge and triple grafts displayed greater growth and enabled the hNT graft to essentially bridge the lesion. This suggests that hNT neurons have the potential to structurally reconnect the proximal and distal spinal cord across the region of injury.
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 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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".