The Damaged Spinal Cord Is a Suitable Target for Stem Cell Transplantation
Bibliographic record
Abstract
Background. Given individuals with spinal cord injury (SCI) approaching 2 million, viable options for regenerative repair are desperately needed. Human central nervous system stem cells (HuCNS-SC) are self-renewing, multipotent adult stem cells that engraft, migrate, and differentiate in appropriate regions in multiple animal models of injured brain and spinal cord. Preclinical improved SCI locomotor function provided rationale for the first-in-human SCI clinical trial of HuCNS-SC cells. Evidence of feasibility and long-term safety of cell transplantation into damaged human cord is needed to foster translational progression of cellular therapies. Methods. A first-ever, multisite phase I/IIa trial involving surgical transplantation of 20 million HuCNS-SC cells into the thoracic cord in 12 AIS A or B subjects (traumatic, T2-T11 motor-complete, sensory-incomplete), aged 19 to 53 years, demonstrated safety and preliminary efficacy. Six-year follow-up data were collected (sensory thresholds and neuroimaging augmenting clinical assessments). Findings. The study revealed short- and long-term surgical and medical safety (well-tolerated immunosuppression in population susceptible to infections). Preliminary efficacy measures identified 5/12 with reliable sensory improvements. Unfortunately, without thoracic muscles available for manual muscle examination, thoracic motor changes could not be measured. Lower limb motor scores did not change during the study. Cervical cord imaging revealed, no tumor formation or malformation of the lesion area, and secondary supralesional structural changes similar to SCI control subjects. Interpretation. Short- and long-term safety and feasibility support the consideration of cell transplantation for patients with complete and incomplete SCI. This report is an important step to prepare, foster, and maintain the therapeutic development of cell transplantation for human SCI.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".