Axon Degeneration Is Rescued with Human Umbilical Cord Perivascular Cells: A Potential Candidate for Neuroprotection After Traumatic Brain Injury
Bibliographic record
Abstract
Traumatic brain injury (TBI) leads to delayed secondary injury events consisting of cellular and molecular cascades that exacerbate the initial injury. Human umbilical cord perivascular cells (HUCPVCs) secrete neurotrophic and prosurvival factors. In this study, we examined the effects of HUCPVC in sympathetic axon and cortical axon survival models and sought to determine whether HUCPVC provide axonal survival cues. We then examined the effects of the HUCPVC in an in vivo fluid percussion injury model of TBI. Our data indicate that HUCPVCs express neurotrophic and neural survival factors. They also express and secrete relevant growth and survival proteins when cultured alone, or in the presence of injured axons. Coculture experiments indicate that HUCPVCs interact preferentially with axons when cocultured with sympathetic neurons and reduce axonal degeneration. Nerve growth factor withdrawal in axonal compartments resulted in 66 ± 3% axon degeneration, whereas HUCPVC coculture rescued axon degeneration to 35 ± 3%. Inhibition of Akt (LY294002) resulted in a significant increase in degeneration compared with HUCPVC cocultures (48 ± 7% degeneration). Under normoxic conditions, control cultures showed 39 ± 5% degeneration. Oxygen glucose deprivation (OGD) resulted in 58 ± 3% degeneration and OGD HUCPVC cocultures reduced degeneration to 34 ± 5% (p < 0.05). In an in vivo model of TBI, immunohistochemical analysis of NF200 showed improved axon morphology in HUCPVC-treated animals compared with injured animals. These data presented in this study indicate an important role for perivascular cells in protecting axons from injury and a potential cell-based therapy to treat secondary injury after TBI.
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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".