Bone Marrow-Derived Endothelial Progenitor Cells Protect Postischemic Axons after Traumatic Brain Injury
Bibliographic record
Abstract
White matter sparing after traumatic brain injury (TBI) is an important predictor of survival and outcome. Blood vessels and axons are intimately associated anatomically and developmentally. Neural input is required for appropriate vascular patterning, and vascular signaling is important for neuron development and axon growth. Owing to this codependence between endothelial cells and axons during development and the contribution of endothelial progenitor cells (EPCs) in ischemic injury, we hypothesized that EPCs are important in axonal survival after TBI. We examined the effects of allogenic-cultured EPCs on white matter protection and microvascular maintenance after midline fluid percussion injury in adult Sprague-Dawley rats. We used two in vitro models of injury, mechanical stretch and oxygen-glucose deprivation (OGD), to examine the effects of EPCs on the mechanical and ischemic components of brain trauma, respectively. Our results indicate that EPCs improve the white matter integrity and decrease capillary breakdown after injury. Cultured cortical neurons exposed to OGD had less axon degeneration when treated with EPC-conditioned media, whereas no effect was seen in axons injured by mechanical stretch. The results indicate that EPCs are important for the protection of the white matter after trauma and represent a potential avenue for therapy.
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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".