Unlocking the paradoxical endogenous stem cell response after spinal cord injury
Bibliographic record
Abstract
Nearly a century ago, the concept of the secondary injury in spinal cord trauma was first proposed to explain the complex cascade of molecular and cellular events leading to widespread neuronal and glial cell death after trauma. In recent years, it has been established that the ependymal region of the adult mammalian spinal cord contains a population of multipotent neural stem/progenitor cells (NSPCs) that are activated after spinal cord injury (SCI) and likely play a key role in endogenous repair and regeneration. How these cells respond to the various components of the secondary injury remains poorly understood. Emerging evidence suggests that many of the biochemical components of the secondary injury cascade which have classically been viewed as deleterious to host neuronal and glial cells may paradoxically trigger NSPC activation, proliferation, and differentiation thus challenging our current understanding of secondary injury mechanisms in SCI. Herein, we highlight new findings describing the response of endogenous NSPCs to spinal cord trauma, redefining the secondary mechanisms of SCI through the lens of the endogenous population of stem/progenitor cells. Moreover, we outline how these insights can fuel novel stem cell-based therapeutic strategies to repair the injured spinal cord.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".