<scp>l</scp>-carnitine protects human hepatocytes from oxidative stress-induced toxicity through Akt-mediated activation of Nrf<sub>2</sub> signaling pathway
Bibliographic record
Abstract
In our previous study, l-carnitine was shown to have cytoprotective effect against hydrogen peroxide (H2O2)-induced injury in human normal HL7702 hepatocytes. The aim of this study was to investigate whether the protective effect of l-carnitine was associated with the nuclear factor erythroid 2 (NFE2)-related factor 2 (Nrf2) pathway. Our results showed that pretreatment with l-carnitine augmented Nrf2 nuclear translocation, DNA binding activity and heme oxygenase-1 (HO-1) expression in H2O2-treated HL7702 cells, although l-carnitine treatment alone had no effect on them. Analysis using Nrf2 siRNA demonstrated that Nrf2 activation was involved in l-carnitine-induced HO-1 expression. In addition, l-carnitine-mediated protection against H2O2 toxicity was abrogated by Nrf2 siRNA, indicating the important role of Nrf2 in l-carnitine-induced cytoprotection. Further experiments revealed that l-carnitine pretreatment enhanced the phosphorylation of Akt in H2O2-treated cells. Blocking Akt pathway with inhibitor partly abrogated the protective effect of l-carnitine. Moreover, our finding demonstrated that the induction of Nrf2 translocation and HO-1 expression by l-carnitine directly correlated with the Akt pathway because Akt inhibitor showed inhibitory effects on the Nrf2 translocation and HO-1 expression. Altogether, these results demonstrate that l-carnitine protects HL7702 cells against H2O2-induced cell damage through Akt-mediated activation of Nrf2 signaling pathway.
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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".