Central Canal Ependymal Cells Proliferate Extensively in Response to Traumatic Spinal Cord Injury but Not Demyelinating Lesions
Bibliographic record
Abstract
The adult mammalian spinal cord has limited regenerative capacity in settings such as spinal cord injury (SCI) and multiple sclerosis (MS). Recent studies have revealed that ependymal cells lining the central canal possess latent neural stem cell potential, undergoing proliferation and multi-lineage differentiation following experimental SCI. To determine whether reactive ependymal cells are a realistic endogenous cell population to target in order to promote spinal cord repair, we assessed the spatiotemporal dynamics of ependymal cell proliferation for up to 35 days in three models of spinal pathologies: contusion SCI using the Infinite Horizon impactor, focal demyelination by intraspinal injection of lysophosphatidylcholine (LPC), and autoimmune-mediated multi-focal demyelination using the active experimental autoimmune encephalomyelitis (EAE) model of MS. Contusion SCI at the T9-10 thoracic level stimulated a robust, long-lasting and long-distance wave of ependymal proliferation that peaked at 3 days in the lesion segment, 14 days in the rostral segment, and was still detectable at the cervical level, where it peaked at 21 days. This proliferative wave was suppressed distal to the contusion. Unlike SCI, neither chemical- nor autoimmune-mediated demyelination triggered ependymal cell proliferation at any time point, despite the occurrence of demyelination (LPC and EAE), remyelination (LPC) and significant locomotor defects (EAE). Thus, traumatic SCI induces widespread and enduring activation of reactive ependymal cells, identifying them as a robust cell population to target for therapeutic manipulation after contusion; conversely, neither demyelination, remyelination nor autoimmunity appears sufficient to trigger proliferation of quiescent ependymal cells in models of MS-like demyelinating diseases.
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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) | 0.000 | 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) | 0.001 | 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 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".