BNIP3 regulates mitophagy and apoptosis in delayed neuronal death in stroke
Bibliographic record
Abstract
Physiological level of autophagy promotes neuronal survival, while apoptosis contributes to delayed neuronal death in ischemic stroke. In this study, we show that the proapoptotic BCL‐2 family member BNIP3 is an upstream regulator for both processes. Specifically, deletion of BNIP3 gene is neuroprotective by affecting mitophagy and apoptosis pathways. We performed IHC, western blot, Co‐ip, ELISA, and cell transfection to analyze the BNIP3's regulation on mitophagy and apoptosis in cortical neurons and ischemic brains. Both BNIP3 wild‐type and knock‐out mice were used. In primary neurons exposed to OGD/reperfusion, BNIP3 was highly expressed, with the time course and expression levels of apoptosis‐related proteins (i.e. active caspase‐3, cytochrome C, and BAX) and autophagy‐related proteins (i.e. LC3, Beclin‐1, and LAMP‐2) positively regulated. Promoting or inhibiting autophagy pharmacologically didn't affect the expression patterns of BNIP3, indicating it is an upstream regulator. We also measured the brain damage of neonatal stroke in transgenic mice. TTC staining showed the infarct volume of ischemic brains was significantly reduced in BNIP3 KO mice compared to WT mice upon 3–7 days recovery. Silence of BNIP3 gene in cortical neurons of KO mice activated a robust autophagic response and decreased apoptosis, coordinately contributing to the neuroprotection in the KO animals after stroke. Grant Funding Source : Canadian Institute of Health Research, Canadian Stroke Network, Manitoba Health Research Council, Manitoba Institute of Child Health
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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) | 0.002 | 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".