Synthetic phosphoserine dimer attenuates lipopolysaccharide‐induced inflammatory response in human intestinal epithelial cells via activation of NF‐κB and MAPKs cell signalling pathways
Bibliographic record
Abstract
Summary Previous studies have shown that phosvitin phosphopeptides could exert anti‐inflammatory activity in lipopolysaccharide (LPS)‐stimulated small intestine epithelial cells. However, the role of phosphopeptides in inflammation‐related cell signalling pathways remains to be elucidated. Here, the anti‐inflammation effect of a synthetic phosphoserine dimer (2PS) in cell signalling pathways were evaluated by PCR array and immunoblotting assays. Our results showed that 2PS led to reduced secretion of LPS‐induced IL‐8 in a dose‐dependent manner, and downregulation of the mRNA expression of pro‐inflammation cytokines in HT‐29 cell cultures, including IL‐8, IL‐6, IL‐12, TNF‐α and MCP‐1. Compared to LPS alone, treatment with 2PS + LPS exerted downregulation of gene expression in the TLR4‐related cell signalling pathway, including MyD88, IRAK1, IKKε and IKKγ, as well as transcription factors RELs, JUN, and FOS. At the protein level, cell treatment with 2PS led to a decline in LPS‐induced phosphorylation of IκB, ERK1/2, and p‐38 MAPKs. Our results indicate that 2PS attenuates LPS‐induced inflammation through down‐regulation of NF‐κB pathway and inhibition of MAPKs phosphorylation.
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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".