Protection of Human Lens Epithelial Cells from Oxidative Stress Damage and Cell Apoptosis by KGF‐2 through the Akt/Nrf2/HO‐1 Pathway
Bibliographic record
Abstract
Oxidative stress exerts a significant influence on the pathogenesis of various cataracts by inducing degradation and aggregation of lens proteins and apoptosis of lens epithelial cells. Keratinocyte growth factor−2 (KGF‐2) exerts a favorable cytoprotective effect against oxidative stress in vivo and in vitro. In this work, we investigated the molecular mechanisms of KGF‐2 against hydrogen peroxide‐ (H2O2‐) induced oxidative stress and apoptosis in human lens epithelial cells (HLECs) and rat lenses. KGF‐2 pretreatment could reduce H2O2‐induced cytotoxicity as well as reactive oxygen species (ROS) accumulation. KGF‐2 also increases B‐cell lymphoma‐2 (Bcl‐2), quinine oxidoreductase‐1 (NQO‐1), superoxide dismutase (SOD2), and catalase (CAT) levels while decreasing the expression level of Bcl2‐associated X (Bax) and cleaved caspase‐3 in H2O2‐stimulated HLECs. LY294002, the phosphatidylinositol‐3‐kinase (PI3K)/Akt inhibitor, abolished KGF‐2’s effect to some extent, demonstrating that KGF‐2 protected HLECs via the PI3K/Akt pathway. On the other hand, KGF‐2 activated the Nrf2/HO‐1 pathway by regulating the PI3K/Akt pathway. Silencing nuclear factor erythroid 2‐related factor 2 (Nrf2) by targeted‐siRNA and inhibiting heme oxygenase‐1 (HO‐1) through zinc protoporphyrin IX (ZnPP) significantly decreased cytoprotection of KGF‐2. Furthermore, as revealed by lens organ culture assays, KGF‐2 treatment decreased H2O2‐induced lens opacity in a concentration‐dependent manner. As demonstrated by these data, KGF‐2 resisted H2O2‐mediated apoptosis and oxidative stress in HLECs through Nrf2/HO‐1 and PI3K/Akt pathways, suggesting a potential protective effect against the formation of cataracts.
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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".