Overexpression of BRCA1 in Neural Stem Cells Enhances Cell Survival and Functional Recovery after Transplantation into Experimental Ischemic Stroke
Bibliographic record
Abstract
Transplantation of neural stem cells (NSCs) is a promising therapy for ischemic stroke. However, the effectiveness of this approach is limited by grafted cell death. Breast cancer susceptibility protein 1 (BRCA1) could suppress apoptosis in neural progenitors and modulate oxidative stress in neurons. In this study, we found that BRCA1 was upregulated by oxygen-glucose deprivation/reoxygenation (OGD/R). Overexpression of BRCA1 in NSCs reduced cell apoptosis and oxidative stress after OGD/R insult. The molecule overexpression also stimulated cellular proliferation in OGD/R NSCs and increased the survival rate of grafted cells. Further, the transplantation of BRCA1-transfected NSCs into mice with ischemic stroke increased brain-derived neurotropic factor and nerve growth factor expression in the brain and elicited neurological function improvement. In addition, we found that RING finger domain and BRCT domain of BRCA1 could physically interact with p53 in NSCs. The cross talk between BRCA1 RING finger domain and p53 was responsible for p53 ubiquitination and degradation. Our findings indicate that modification with BRCA1 could enhance the efficacy of NSCs transplantation in ischemic 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 | 0.001 |
| 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".