Endogenous and Exogenous CNS Derived Stem / Progenitor Cell Approaches for Neurotrauma
Bibliographic record
Abstract
Neural stem/progenitor cells capable of generating new neurons and glia, reside in specific areas of the adult mammalian central nervous system (CNS), including the ependymal region of the spinal cord and the subventricular zone (SVZ), hippocampus, and dentate gyrus of the brain. Much is known about the neurogenic regions in the CNS, and their response to various stimuli including injury, neurotrophins (NFs), morphogens, and environmental factors like learning, stress, and aging. This work has shaped our current views about the CNS's potential to recover lost tissue and function post-traumatically and the therapies to support the intrinsic regenerative capacity of the brain or spinal cord. Recently, intensive research has explored the potential of harvesting, culturing, and transplanting neural stem/progenitors as a therapeutic intervention for spinal cord injury (SCI) and traumatic brain injury (TBI). Another strategy has focused on maximizing the potential of this endogenous population of cells by stimulating their recruitment, proliferation, migration, and differentiation in vivo following traumatic lesions to the CNS. The promise of such experimental treatments has prompted tissue and biomaterial engineers to implant synthetic three-dimensional biodegradable scaffolds seeded with neural stem/progenitors into CNS lesions. Although there is no definitive answer about the ideal cell type for transplantation, strong evidence supports the use of region specific neural stem/progenitors. The technical and logistic considerations for transplanting neural stem/progenitors are extensive and crucial to optimizing and maintaining cell survival both before and after transplantation, as well as for tracking the fate of transplanted cells. These issues have been systematically addressed in many animal models, that has improved our understanding and approach to clinical therapeutic paradigms.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".