Effects of human neural stem cell transplantation in canine spinal cord hemisection
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Previous works have reported that the transplantation of neural stem cells (NSCs) may improve functional recovery after spinal cord injury (SCI), but these results have been mainly obtained in rat models. In the present work, the authors sought to determine whether the transplantation of human NSCs improves functional outcome in a canine SCI model and whether transplanted NSCs survive and differentiate. METHODS: Human NSCs (HB1. F3 clone) were used in this work. Lateral hemisection at the L2 level was performed in dogs and either (1) Matrigel (200 microl) alone as a growth-promoting matrix or (2) Matrigel seeded with human NSCs (10(7) cells/200 microl) were transplanted into hemisected gaps. Using a canine hind limb locomotor scale, functional outcomes were assessed over 12 weeks. Immunofluorescence staining was performed to examine cell survival, differentiation and axonal regeneration. RESULTS: Compared with dogs treated with Matrigel alone, dogs treated with Matrigel + human NSCs showed significantly better functional recovery (10.3 +/- 0.7 versus 15.6 +/- 0.7, respectively, at 12 weeks; p<0.05). Human nuclei-positive cells were found mainly near hemisected areas in dogs treated with Matrigel + NSCs. In addition, colocalization of human nuclei and neuronal nuclei or myelin basic protein was clearly observed. Moreover, the Matrigel + NSC group showed more ascending sensory axon regeneration. CONCLUSIONS: The transplantation of human NSCs has beneficial effects on functional recovery after SCI, and these NSCs were found to differentiate into mature neurons and/or oligodendrocytes. These results provide baseline data for future clinical applications.
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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 | 0.001 |
| 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) | 0.000 | 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 it