Lactoferrin attenuates fatty acid-induced lipotoxicity via Akt signaling in hepatocarcinoma cells
Bibliographic record
Abstract
Nonalcoholic fatty liver disease (NAFLD) describes a spectrum of lesions ranging from simple steatosis to non-alcoholic steatohepatitis (NASH). The excess influx of fatty acids (FAs) into the liver is recognized as a main cause of simple steatosis formation and progression to NASH. Recently, administration of lactoferrin (LF), a glycoprotein present in milk, was suggested to prevent NAFLD development. However, the effect of LF on the contribution of FA to NAFLD development remains unclear. In this study, the effects of LF on FA mixture (FAm)-induced lipotoxicity using human hepatocarcinoma G2 cells were assessed. FAm significantly decreased cell viability and increased intracellular lipid accumulation, whereas LF significantly recovered cell viability without affecting lipid accumulation. FAm-induced lactic dehydrogenase (LDH) and caspase-3/7 activities were significantly decreased by LF and SP600125, a c-Jun N-terminal kinase (JNK) specific inhibitor. We also found that LF added to FAm-treated cells induced Akt phosphorylation, which contributed to inhibition of JNK signaling pathway-dependent apoptosis. Akt inhibitor VIII, an allosteric Akt inhibitor, significantly attenuated the effect of LF on LDH activity and abrogated the ones on cell viability and caspase-3/7 activity. In summary, the present study has revealed that LF has a protective effect on FAm-induced lipotoxicity in a HepG2 model of NAFLD and identified the activation of the Akt signaling pathway as a possibly major mechanism.
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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 | 0.001 |
| 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".