The effects of alpha lipoic acid in preventing oxidative stress-induced retinal pigment epithelial cell injury
Bibliographic record
Abstract
This study evaluated the protective effect of alpha lipoic acid (ALA) in human adult retinal pigment epithelium cells (ARPE-19). An RPE oxidative stress model was established in ARPE-19 cells. Cell apoptosis was detected by Annexin V/PI staining and Hoechst33342 staining. Autophagy activation was evaluated by formation of acidic vesicular organelles (AVO) as well as protein expression of Atg5 and LC3. Akt phosphorylation and Bax protein expression were measured using western blot. Exogenous H2O2 significantly increased intracellular ROS concentration and decreased the viability of ARPE-19 cells in a dose-dependent way. H2O2 (12.5 μmol/L) induced early stage apoptosis, significantly decreased Akt phosphorylation, and increased Bax protein level 4 h after stimulation. H2O2 (12.5 μmol/L) significantly increased AVO formation, mRNA and protein levels of Atg-5, and protein expression of LC3 I and II. Treatment of ARPE-19 cells with 37.5 μmol/L ALA significantly blocked increased intracellular ROS level, apoptosis, AVO formation, as well as elevation of Atg5, LC3 I, and II protein levels induced by 12.5 μmol/L H2O2. Exogenous H2O2 induces apoptosis and activation of autophagy in human adult retinal pigment epithelium cells through Akt-Bax signaling. ALA is effective in protecting RPE cells from H2O2-induced 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".