Grafts of Brain-Derived Neurotrophic Factor and Neurotrophin 3-Transduced Primate Schwann Cells Lead to Functional Recovery of the Demyelinated Mouse Spinal Cord
Bibliographic record
Abstract
Experimental studies provided overwhelming proof that transplants of myelin-forming cells achieve efficient remyelination in the CNS. Among cellular candidates, Schwann cells can be used for autologous transplantation to ensure robust remyelination of lesions and to deliver therapeutic factors in the CNS. In the present study, macaque Schwann cells expressing green fluorescent protein (GFP) were infected with human immunodeficiency virus-derived vectors overexpressing brain-derived neurotrophic factor (BDNF) or Neurotrophin 3 (NT-3), two neurotrophins that also modulate glial cell biology. The ability of transgenic Schwann cells to secrete growth factors was assessed by ELISA and showed 35- and 62-fold increases in BDNF and NT-3, respectively, in transduced macaque Schwann cell supernatants. Conditioned media of BDNF- and NT-3-transduced Schwann cells reduced Schwann cell proliferation and favored their differentiation in vitro. Transgenic cells were grafted in demyelinated spinal cords of adult nude mice. Two behavioral assays showed that NT-3- and BDNF-transduced Schwann cells promoted faster and stronger functional recovery than GFP-transduced Schwann cells. Morphological analysis indicated that functional recovery correlated with enhanced proliferation and differentiation of resident oligodendrocyte progenitors and enhanced oligodendrocyte and Schwann cell differentiation. Moreover, NT-3-transduced Schwann cells provided neuroprotection and reduced astrogliosis. These results underline the potential therapeutic benefit of combining neuroprotection and activation of myelin-forming cells to restore altered functions in demyelinating diseases of the CNS.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".