Eugenol attenuates inflammatory response and enhances barrier function during lipopolysaccharide-induced inflammation in the porcine intestinal epithelial cells
Why this work is in the frame
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Bibliographic record
Abstract
Eugenol (4-allyl-2-methoxyphenol) is an essential oil component, possessing antimicrobial, anti-inflammatory, and antioxidative properties; however, the effect of eugenol on porcine gut inflammation has not yet been investigated. In this study, an in vitro lipopolysaccharide (LPS)-induced inflammation model in porcine intestinal epithelial cells (IPEC-J2) has been set up. Cells were pretreated with 100 μM (16.42 mg/L) eugenol for 2 h followed by 10 μg/mL LPS stimulation for 6 h. Proinflammatory cytokine secretion; reactive oxygen species; gene expression of proinflammatory cytokines, tight junction proteins, and nutrient transporters; the expression and distribution of zonula occludens-1 (ZO-1); transepithelial electrical resistance (TEER); and cell permeability were measured to investigate the effect of eugenol on inflammatory responses and gut barrier function. The results showed that eugenol pretreatment significantly suppressed the LPS-stimulated interleukin-8 level and the mRNA abundance of tumor necrosis factor-α and restored the LPS-stimulated decrease of the mRNA abundance of tight junction proteins, such as ZO-1 and occludin, and the mRNA abundance of nutrient transporters, such as B0 1 system ASC sodium-dependent neutral amino acid exchanger 2, sodium-dependent glucose transporter 1, excitatory amino acid transporter 1, and peptide transporter 1. In addition, eugenol improved the expression and even redistribution of ZO-1 and tended to increase TEER value and maintained the barrier integrity. In conclusion, a low dose of eugenol attenuated inflammatory responses and enhanced selectively permeable barrier function during LPS-induced inflammation in the IPEC-J2 cell line.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it