FoxO3 transcription factor promotes autophagy after oxidative stress injury in HT22 cells
Bibliographic record
Abstract
Autophagy has been implicated in neurodegenerative diseases. Forkhead box O3 (FoxO3) transcription factors promote autophagy in heart and inhibit oxidative damage. Here we investigate the role of FoxO3 transcription factors in regulating autophagy after oxidative stress injury in immortalized mouse hippocampal cell line (HT22). The present study confirms that hydrogen peroxide (H2O2) injury could induce autophagy and FoxO3 activation in HT22 cells. In addition, overexpression of FoxO3 enhanced H2O2-induced autophagy activation and suppressed neuronal cell damage, while knockdown of FoxO3 reduced H2O2-induced autophagy activation and exacerbated neuronal cell injury. Inhibition of autophagy by 3-methyladenine (3-MA) resulted in reduced cell viability, increased production of reactive oxygen species (ROS), promoted nuclear condensation, and decreased expression of antiapoptotic and autophagy-related proteins, indicating that autophagy may have protective effects on H2O2-induced injury in HT22 cells. Moreover, overexpression of FoxO3 prevented exacerbation of brain damage induced by 3-MA. Taken together, these results show that activation of FoxO3 could induce autophagy and inhibit H2O2-induced damage in HT22 cells. Our study demonstrates the critical role of FoxO3 in regulating autophagy in brain.
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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 | 0.000 |
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".