Effect of Manitoba-Grown Red-Osier Dogwood Extracts on Recovering Caco-2 Cells from H2O2-Induced Oxidative Damage
Bibliographic record
Abstract
Red-osier dogwood, a native species of flowering plant in North America, has been reported to have anti-oxidative properties because of abundant phenolic compounds; this could be promising as a functional food or a feed additive. In the present study, an oxidative damage model using 1.0 mM hydrogen peroxide (H2O2) in Caco-2 cells was established to evaluate the antioxidative effects of red-osier dogwood extracts (RDE). The results showed that 1.0 mM H2O2 pre-exposure for 3 h significantly decreased cell viability, and increased interleukin 8 (IL-8) secretion and the intracellular reactive oxygen species (ROS) level. Caco-2 cells were treated with 100 µg/mL RDE for 24 h after pre-exposure to H2O2. It was found that the decreased cell viability caused by H2O2 was significantly restored by a subsequent 100 µg/mL RDE treatment. Furthermore, the IL-8 secretion and ROS level were significantly blocked by RDE, accompanied by the enhanced gene expression of hemeoxygenase-1 (HO-1), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px), and the enhanced protein expression of the nuclear factor (erythroid-derived 2)-like 2 (Nrf-2). Moreover, RDE improved barrier functions in Caco-2 cells. Using RDE reduced the diffusion of fluorescein isothiocyanate (FITC)-dextran and increased the transepithelial resistance (TEER) value. The relative mRNA level of tight junction claudin-1, claudin-3, and occludin was elevated by RDE. These extracts also repaired the integrity of zonula occludens-1 (ZO-1) damaged by H2O2 and increased the protein expressions of ZO-1 and claudin-3 in the H2O2-pretreated cells. These results illustrated that RDE reduced the ROS level and enhanced the barrier function in oxidative-damaged epithelial cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".