Astrocytes originated from neural stem cells drive the regenerative remodeling of pathologic CSPGs in spinal cord injury
Bibliographic record
Abstract
Neural degeneration is a hallmark of spinal cord injury (SCI). Multipotent neural precursor cells (NPCs) have the potential to reconstruct the damaged neuron-glia network due to their tri-lineage capacity to generate neurons, astrocytes, and oligodendrocytes. However, astrogenesis is the predominant fate of resident or transplanted NPCs in the SCI milieu adding to the abundant number of resident astrocytes in the lesion. How NPC-derived astrocytes respond to the inflammatory milieu of SCI and the mechanisms by which they contribute to the post-injury recovery processes remain largely unknown. Here, we uncover that activated NPC-derived astrocytes exhibit distinct molecular signature that is immune modulatory and foster neurogenesis, neuronal maturity, and synaptogenesis. Mechanistically, NPC-derived astrocytes perform regenerative matrix remodeling by clearing inhibitory chondroitin sulfate proteoglycans (CSPGs) from the injury milieu through LAR and PTP-σ receptor-mediated endocytosis and the production of ADAMTS1 and ADAMTS9, while most resident astrocytes are pro-inflammatory and contribute to the pathologic deposition of CSPGs. These novel findings unravel critical mechanisms of NPC-mediated astrogenesis in SCI repair.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".