Human neural stem cells promote proliferation of endogenous neural stem cells and enhance angiogenesis in ischemic rat brain
Bibliographic record
Abstract
Transplantation of human neural stem cells into the dentate gyrus or ventricle of rodents has been reportedly to enhance neurogenesis. In this study, we examined endogenous stem cell proliferation and angiogenesis in the ischemic rat brain after the transplantation of human neural stem cells. Focal cerebral ischemia in the rat brain was induced by middle cerebral artery occlusion. Human neural stem cells were transplanted into the subventricular zone. The behavioral performance of human neural stem cells-treated ischemic rats was significantly improved and cerebral infarct volumes were reduced compared to those in untreated animals. Numerous transplanted human neural stem cells were alive and preferentially localized to the ipsilateral ischemic hemisphere. Furthermore, 5-bromo-2'-deoxyuridine-labeled endogenous neural stem cells were observed in the subventricular zone and hippocampus, where they differentiated into cells immunoreactive for the neural markers doublecortin, neuronal nuclear antigen NeuN, and astrocyte marker glial fibrillary acidic protein in human neural stem cells-treated rats, but not in the untreated ischemic animals. The number of 5-bromo-2'-deoxyuridine-positive ⁄ anti-von Willebrand factor-positive proliferating endothelial cells was higher in the ischemic boundary zone of human neural stem cells-treated rats than in controls. Finally, transplantation of human neural stem cells in the brains of rats with focal cerebral ischemia promoted the proliferation of endogenous neural stem cells and their differentiation into mature neural-like cells, and enhanced angiogenesis. This study provides valuable insights into the effect of human neural stem cell transplantation on focal cerebral ischemia, which can be applied to the development of an effective therapy for stroke.
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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".