Necrostatin‐1 prevents the proapoptotic protein Bcl‐2/adenovirus E1B 19‐kDa interacting protein 3 from integration into mitochondria
Bibliographic record
Abstract
Necrostatin-1 (Nec-1) has previously been shown to protect neurons from death in traumatic and ischemic brain injuries. This study tests the hypothesis that Nec-1 protects neural cells against traumatic and ischemic brain injuries through inhibition of the Bcl-2/adenovirus E1B 19-kDa interacting protein 3 (BNIP3). We have used biochemical and morphological techniques to determine the inhibition of Nec-1 on BNIP3-induced cell death and to identify its mechanism of action in in vivo and in vitro models of neurodegeneration. Here we show that Nec-1 significantly increased neuronal viability following prolonged exposure to hypoxia in vitro, and attenuated myelin damage and neuronal death in traumatic brain injury and cerebral ischemia in Sprague-Dawley rats. Nec-1 alleviated traumatic brain injury-induced up-regulation of BNIP3 in mature oligodendrocytes. In isolated mitochondria, Nec-1 prevented BNIP3 from integrating into mitochondria by modifying its binding sites on the mitochondria. Consequently, Nec-1 robustly inhibited BNIP3-induced collapse of mitochondrial membrane potential and reduced the opening probability of mitochondrial permeability transition pores. Nec-1 also preserved mitochondrial ultrastructure and suppressed BNIP3-induced nuclear translocation of apoptosis-inducing factor. In conclusion, Nec-1 protects neurons and oligodendrocytes against traumatic and ischemic brain injuries by targeting the BNIP3-induced cell death pathway, and is a novel inhibitor for BNIP3. Cover Image for this issue: https://doi.org/10.1111/jnc.15056.
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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) | 0.003 | 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".