Microenvironmental regulation of oligodendrocyte replacement and remyelination in spinal cord injury
Bibliographic record
Abstract
Myelin is a proteolipid sheath enwrapping axons in the nervous system that facilitates signal transduction along the axons. In the central nervous system (CNS), oligodendrocytes are specialized glial cells responsible for myelin formation and maintenance. Following spinal cord injury (SCI), oligodendroglia cell death and myelin damage (demyelination) cause chronic axonal damage and irreparable loss of sensory and motor functions. Accumulating evidence shows that replacement of damaged oligodendrocytes and renewal of myelin (remyelination) are promising approaches to prevent axonal degeneration and restore function following SCI. Neural precursor cells (NPCs) and oligodendrocyte progenitor cells (OPCs) are two main resident cell populations in the spinal cord with innate capacities to foster endogenous oligodendrocyte replacement and remyelination. However, due to the hostile microenvironment of SCI, the regenerative capacity of these endogenous precursor cells is conspicuously restricted. Activated resident glia, along with infiltrating immune cells, are among the key modulators of secondary injury mechanisms that create a milieu impermissible to oligodendrocyte differentiation and remyelination. Recent studies have uncovered inhibitory roles for astrocyte-associated molecules such as matrix chondroitin sulfate proteoglycans (CSPGs), and a plethora of pro-inflammatory cytokines and neurotoxic factors produced by activated microglia/macrophages. The quality of axonal remyelination is additionally challenged by dysregulation of the supportive growth factors required for maturation of new oligodendrocytes and axo-oligodendrocyte signalling. Careful understanding of factors that modulate the activity of endogenous precursor cells in the injury microenvironment is a key step in developing efficient repair strategies for remyelination and functional recovery following 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".