BNIP3 Interacting with LC3 Triggers Excessive Mitophagy in Delayed Neuronal Death in Stroke
Bibliographic record
Abstract
INTRODUCTION: A basal level of mitophagy is essential in mitochondrial quality control in physiological conditions, while excessive mitophagy contributes to cell death in a number of diseases including ischemic stroke. Signals regulating this process remain unknown. BNIP3, a pro-apoptotic BH3-only protein, has been implicated as a regulator of mitophagy. AIMS: Both in vivo and in vitro models of stroke, as well as BNIP3 wild-type and knock out mice were used in this study. RESULTS: We show that BNIP3 and its homologue BNIP3L (NIX) are highly expressed in a "delayed" manner and contribute to delayed neuronal loss following stroke. Deficiency in BNIP3 significantly decreases both neuronal mitophagy and apoptosis but increases nonselective autophagy following ischemic/hypoxic insults. The mitochondria-localized BNIP3 interacts with the autophagosome-localized LC3, suggesting that BNIP3, similar to NIX, functions as a LC3-binding receptor on mitochondria. Although NIX expression is upregulated when BNIP3 is silenced, up-regulation of NIX cannot functionally compensate for the loss of BNIP3 in activating excessive mitophagy. CONCLUSIONS: NIX primarily regulates basal level of mitophagy in physiological conditions, whereas BNIP3 exclusively activates excessive mitophagy leading to cell death.
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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".