Early Intravenous Infusion of Mesenchymal Stromal Cells Exerts a Tissue Source Age-Dependent Beneficial Effect on Neurovascular Integrity and Neurobehavioral Recovery After Traumatic Cervical Spinal Cord Injury
Bibliographic record
Abstract
Localized vascular disruption after traumatic spinal cord injury (SCI) triggers a cascade of secondary events, including inflammation, gliosis, and scarring, that can further impact recovery. In addition to immunomodulatory and neurotrophic properties, mesenchymal stromal cells (MSCs) possess pericytic characteristics. These features make MSCs an ideal candidate for acute cell therapy targeting vascular disruption, which could reduce the severity of secondary injury, enhance tissue preservation and repair, and ultimately promote functional recovery. A moderately severe cervical clip compression/contusion injury was induced at C7-T1 in adult female rats, followed by an intravenous tail vein infusion 1 hour post-SCI of (a) term-birth human umbilical cord perivascular cells (HUCPVCs); (b) first-trimester human umbilical cord perivascular cells (FTM HUCPVCs); (c) adult bone marrow mesenchymal stem cells; or (d) vehicle control. Weekly behavioral testing was performed. Rats were sacrificed at 24 hours or 10 weeks post-SCI and immunohistochemistry and ultrasound imaging were performed. Both term and FTM HUCPVC-infused rats displayed improved (p < .05) grip strength compared with vehicle controls. However, only FTM HUCPVC-infusion led to significant weight gain. All cell infusion treatments resulted in reduced glial scarring (p < .05). Cell infusion also led to increased axonal, myelin, and vascular densities (p < .05). Although post-traumatic cavity volume was reduced with cell infusion, this did not reach significance. Taken together, we demonstrate selective long-term functional recovery alongside histological improvements with HUCPVC infusion in a clinically relevant model of cervical SCI. Our findings highlight the potential of these cells for acute therapeutic intervention after 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 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".