Mesenchymal stem cell conditioned medium increases glial reactivity and decreases neuronal survival in spinal cord slice cultures
Bibliographic record
Abstract
Ex vivo spinal cord slice cultures (SCSC) allow study of spinal cord circuitry, maintaining stimuli responses comparable to live animals. Previously, we have shown that mesenchymal stem/stromal cell (MSC) transplantation in vivo reduced inflammation and increased nerve regeneration but MSC survival was short-lived, highlighting that beneficial action may derive from the secretome. Previous in vitro studies of MSC conditioned medium (CM) have also shown increased neuronal growth. In this study, murine SCSC were cultured in canine MSC CM (harvested from the adipose tissue of excised inguinal fat) and cell phenotypes analysed via immunohistochemistry and confocal microscopy. SCSC in MSC CM displayed enhanced viability after propidium iodide staining. GFAP immunoreactivity was significantly increased in SCSC in MSC CM compared to controls, but with no change in proteoglycan (NG2) immunoreactivity. In contrast, culture in MSC CM significantly decreased the prevalence of βIII-tubulin immunoreactive neurites, whilst Ca2+ transients per cell were significantly increased. These ex vivo results contradict previous in vitro and in vivo reports of how MSC and their secretome may affect the microenvironment of the spinal cord after injury and highlight the importance of a careful comparison of the different experimental conditions used to assess the potential of cell therapies for the treatment of spinal cord injury.
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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".