SPARC from Olfactory Ensheathing Cells Stimulates Schwann Cells to Promote Neurite Outgrowth and Enhances Spinal Cord Repair
Bibliographic record
Abstract
Olfactory ensheathing cells (OECs) transplanted into the lesioned CNS can stimulate reportedly different degrees of regeneration, remyelination, and functional recovery, but little is known about the mechanisms OECs may use to stimulate endogenous repair. Here, we used a functional proteomic approach, isotope-coded affinity tagging and mass spectrometry, to identify active components of the OEC secreteome that differentially stimulate outgrowth. SPARC (secreted protein acidic rich in cysteine) (osteonectin) was identified as an OEC-derived matricellular protein that can indirectly enhance the ability of Schwann cells to stimulate dorsal root ganglion outgrowth in vitro. SPARC stimulates Schwann cell-mediated outgrowth by cooperative signal with laminin-1 and transforming growth factor beta. Furthermore, when SPARC-null OECs were transplanted into lesioned rat spinal cord, the absence of OEC-secreted SPARC results in an attenuation of outgrowth of specific subsets of sensory and supraspinal axons and changes the pattern of macrophage infiltration in response to the transplanted cells. These data provide the first evidence for a role for SPARC in modulating different aspects of CNS repair and indicate that SPARC can change the activation state of endogenous Schwann cells, resulting in the promotion of outgrowth in vitro, and in vivo.
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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 | 0.000 |
| 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".