A novel organotypic cortical slice culture model for traumatic brain injury: molecular changes induced by injury and mesenchymal stromal cell secretome treatment
Bibliographic record
Abstract
Traumatic brain injury (TBI) is a major worldwide neurological disorder with no neuroprotective treatment available. Three-dimensional (3D) in vitro models of brain contusion serving as a screening platform for drug testing are lacking. Here we developed a new in vitro model of brain contusion on organotypic cortical brain slices and tested its responsiveness to mesenchymal stromal cell (MSC) derived secretome. A focal TBI was induced on organotypic slices by an electromagnetic impactor. Compared to control condition, a temporal increase in cell death was observed after TBI by propidium iodide incorporation and lactate dehydrogenase release assays up to 48 h post-injury. TBI induced gross neuronal loss in the lesion core, with disruption of neuronal arborizations measured by microtubule-associated protein-2 (MAP-2) immunostaining and associated with MAP-2 gene down-regulation. Neuronal damage was confirmed by increased levels of neurofilament light chain (NfL), microtubule associated protein (Tau) and ubiquitin C-terminal hydrolase L1 (UCH-L1) released into the culture medium 48 h after TBI. We detected glial activation with microglia cells acquiring an amoeboid shape with less ramified morphology in the contusion core. MSC-secretome treatment, delivered 1 h post-injury, reduced cell death in the contusion core, decreased NfL release in the culture media, promoted neuronal reorganization and improved microglia survival/activation. Our 3D in vitro model of brain contusion recapitulates key features of TBI pathology. We showed protective effects of MSC-secretome, suggesting the model stands as a tractable medium/high throughput, ethically viable, and pathomimetic biological asset for testing new cell-based therapies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".