Apoptosis-Inducing Factor Is a Key Factor in Neuronal Cell Death Propagated by BAX-Dependent and BAX-Independent Mechanisms
Bibliographic record
Abstract
Mitochondria release proteins that propagate both caspase-dependent and caspase-independent cell death pathways. AIF (apoptosis-inducing factor) is an important caspase-independent death regulator in multiple neuronal injury pathways. Presently, there is considerable controversy as to whether AIF is neuroprotective or proapoptotic in neuronal injury, such as oxidative stress or excitotoxicity. To evaluate the role of AIF in BAX-dependent (DNA damage induced) and BAX-independent (excitotoxic) neuronal death, we used Harlequin (Hq) mice, which are hypomorphic for AIF. Neurons carrying double mutations for Hq/Apaf1-/- (apoptosis proteases-activating factor) are impaired in both caspase-dependent and AIF-mediated mitochondrial cell death pathways. These mutant cells exhibit extended neuroprotection against DNA damage, as well as glutamate-induced excitotoxicity. Specifically, AIF is involved in NMDA- and kainic acid- but not AMPA-induced excitotoxicity. In vivo excitotoxic studies using kainic acid-induced seizure showed that Hq mice had significantly less hippocampal damage than wild-type littermates. Our results demonstrate an important role for AIF in both BAX-dependent and BAX-independent mechanisms of neuronal injury.
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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) | 0.002 | 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".