Antioxidative stress effect of phosphoserine dimers is mediated via activation of the Nrf2 signaling pathway
Bibliographic record
Abstract
SCOPE: Phosphoserine-containing peptides have been shown to exert antioxidative stress effects, by lowering lipid peroxidation, increasing intracellular glutathione, and increasing the expression of antioxidant enzymes in human intestinal epithelial cells. However, the role of phosphoserine residues in antioxidative stress activity, and their mechanism of action, remains unknown. METHODS AND RESULTS: The antioxidative stress activity of phosphoserine and phosphoserine peptides was examined using an in vitro model of hydrogen peroxide (H2 O2 )-induced oxidative stress in Caco-2 cells. Phosphoserine dimers (2PS) reduced IL-8 secretion in H2 O2 -treated Caco-2 cells, and reduced H2 O2 -induced expression of genes involved in inflammation and generation of reactive oxygen species (ROS), including chemokine (C-C motif) ligand 5 (CCL5), lactoperoxidase (LPO), myeloperoxidase (MPO), neutrophil cytosolic factor 1/2 (NCF1/2), and nitric oxide synthase 2A (NOS2), and upregulated metallothionein 3 (MT3), peroxiredoxin 3 (PRDX3), and surfactant, pulmonary-associated protein D (SFTPD), which are involved in protection against oxidative stress and activation of the Nrf2 signaling pathway. At the protein level, 2PS reduced H2 O2 -induced phosphorylation of the ERK1/2 and JNK MAPKs, and increased Nrf2 expression. Moreover, the ability of 2PS to reduce H2 O2 -induced IL-8 secretion, a marker of inflammation and oxidative stress, was abrogated in Nrf2 knockdown cells. CONCLUSION: These results suggest that 2PS reduce H2 O2 -induced oxidative stress via the Nrf2 signaling pathway, and reveal a potential mechanism for the antioxidative stress activity of phosphoserine-containing peptides.
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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) | 0.001 | 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) | 0.003 | 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".