LAR and PTPσ receptors are negative regulators of oligodendrogenesis and oligodendrocyte integrity in spinal cord injury
Bibliographic record
Abstract
Following spinal cord injury (SCI), the population of mature oligodendrocytes undergoes substantial cell death; promoting their preservation and replacement is a viable strategy for preserving axonal integrity and white matter repair in the injured spinal cord. Dramatic upregulation of matrix chondroitin sulfate proteoglycans (CSPGs) is shown to pose an obstacle to endogenous repair processes, and targeting CSPGs improves functional recovery after SCI. However, the cellular and molecular mechanisms underlying the inhibitory effects of CSPGs remain largely undefined. Modulation of CSPGs specific signaling receptors, leukocyte common antigen-related (LAR), and protein tyrosine phosphatase-sigma (PTPσ) allows us to uncover the role and mechanisms of CSPGs in regulating oligodendrocytes in SCI. Here, utilizing specific functionally blocking peptides in a clinically relevant model of contusive/compressive SCI in the rat, we demonstrate that inhibition of PTPσ and LAR receptors promotes oligodendrogenesis by endogenous precursor cells, attenuates caspase 3-mediated cell death in mature oligodendrocytes, and preserves myelin. In parallel in vitro systems, we have unraveled that CSPGs directly induce apoptosis in populations of neural precursor cells and oligodendrocyte progenitor cells and limit their ability for oligodendrocyte differentiation, maturation, and myelination. These negative effects of CSPGs are mediated through the activation of both LAR and PTPσ receptors and the downstream Rho/ROCK pathway. Thus, we have identified a novel inhibitory role for PTPσ and LAR in regulating oligodendrocyte differentiation and apoptosis in the injured adult spinal cord and a new feasible therapeutic strategy for optimizing endogenous cell replacement following SCI.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".