Prostaglandin E<sub>2</sub>Produced by<i>Entamoeba histolytica</i>Binds to EP4 Receptors and Stimulates Interleukin-8 Production in Human Colonic Cells
Bibliographic record
Abstract
Entamoeba histolytica pathogenesis in the colon occurs in a stepwise fashion. It begins with colonization of the mucin layer, which is followed by stimulation of a proinflammatory response that causes nonspecific tissue damage that may facilitate parasite invasion of the underlying colonic mucosa. Unfortunately, the parasite and/or host factors that stimulate a proinflammatory response in the gut are poorly understood. In this study, we found that live E. histolytica or secretory or proteins (SP) and soluble ameba components (SAP) can markedly increase interleukin-8 (IL-8) mRNA expression and protein production in colonic epithelial cells. The IL-8-stimulating molecule produced by live amebae was identified as prostaglandin E(2) (PGE(2)) as trophozoites treated with cyclooxygenase inhibitors inhibited the biosynthesis of PGE(2) and eliminated IL-8 production induced by live parasites or ameba components. Moreover, using specific prostaglandin EP2 and EP4 receptor agonists and antagonists, we found that PGE(2) binds exclusively through EP4 receptors in colonic epithelial cells to stimulate IL-8 production. Silencing of EP4 receptors with EP4 small interfering RNA completely eliminated SP- and SAP-induced IL-8 production. These studies identified bioactive PGE(2) as a one of the major virulence factors produced by E. histolytica that can stimulate the potent neutrophil chemokine and activator IL-8, which can trigger an acute host inflammatory response. Thus, the induction of IL-8 production in response to E. histolytica-derived PGE(2) may be a mechanism that explains the initiation and amplification of acute inflammation associated with intestinal amebiasis.
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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".