Activation of the Akt/FoxO3 signaling pathway enhances oxidative stress-induced autophagy and alleviates brain damage in a rat model of ischemic stroke
Bibliographic record
Abstract
Autophagy has been implicated in stroke. Our previous study showed that the FoxO3 transcription factor promotes autophagy after transient cerebral ischemia/reperfusion (I/R). However, whether the Akt/FoxO3 signaling pathway plays a regulatory role in autophagy in cerebral I/R-induced oxidative stress injury is still unclear. The present study aims to investigate the effects of the Akt/FoxO3 signaling pathway on autophagy activation and neuronal injury in vitro and in vivo. By employing LY294002 or insulin to regulate the Akt/FoxO3 signaling pathway, we found that insulin pretreatment increased cell viability, decreased reactive oxygen species production, and enhanced the expression of antiapoptotic and autophagy-related proteins following H2O2 injury in HT22 cells. In addition, insulin significantly decreased neurological deficit scores and infarct volume and increased the expression of antiapoptotic and autophagy-related proteins following I/R injury in rats. However, LY294002 showed the opposite effects under these conditions. Altogether, these results indicate that Akt/FoxO3 signaling pathway activation inhibited oxidative stress-mediated cell death through activation of autophagy. Our study supports a critical role for the Akt/FoxO3 signaling pathway in autophagy activation in stroke.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".