Vascular Dysfunction after Modeled Traumatic Brain Injury Is Preserved with Administration of Umbilical Cord Derived Mesenchymal Stromal Cells and Is Associated with Modulation of the Angiogenic Response
Bibliographic record
Abstract
Vascular dysfunction arising from blood-brain barrier (BBB) breakdown after traumatic brain injury (TBI) can adversely affect neuronal health and behavioral outcome. Pericytes and endothelial cells of the neurovascular unit (NVU) function collectively to maintain strict regulation of the BBB through tight junctions. Secondary injury mechanisms, such as pro-angiogenic signals that contribute to pericyte loss, can prolong and exacerbate primary vascular injury. Human umbilical cord perivascular cells (HUCPVCs) are a source of mesenchymal stromal cells (MSCs) that have been shown to reduce vascular dysfunction after neurotrauma. We hypothesized that the perivascular properties of HUCPVCs can reduce vascular dysfunction after modeled TBI by preserving the pericyte-endothelial interactions. Rats were subjected to a moderate fluid percussion injury (FPI) and intravenously infused with 1,500,000 HUCPVCs post-injury. At acute time points (24 h and 48 h) quantitative polymerase chain reaction (qPCR) analysis demonstrated that the gene expression of angiopoietin-2 was increased with FPI and reduced with HUCPVCs. Immunofluorescent assessment of RECA-1 (endothelial cells) and platelet-derived growth factor receptors (PDGFR-β) (pericytes) revealed that capillary and pericyte densities as well as the co-localization of the two cells were decreased with FPI and preserved with HUCPVC administration. These acute HUCPVC-mediated protective effects were associated with less permeability to Evan's blue dye and increased expression of the tight junction occludin, suggesting less vascular leakage. Further, at 4 weeks post-injury, HUCPVC administration was associated with reduced anxiety and decreased β-amyloid precursor protein (β-APP) accumulation. In summary, HUCPVCs promoted pericyte-endothelial barrier function that was associated with improved long-term outcome.
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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".