Oxidative stress enhances IL-8 and inhibits CCL20 production from intestinal epithelial cells in response to bacterial flagellin
Bibliographic record
Abstract
Intestinal epithelial cells act as innate immune sentinels, as the first cells that encounter diarrheal pathogens. They use pattern recognition molecules such as the Toll-like receptors (TLRs) to identify molecular signals found on microbes but not host cells or food components. TLRs cannot generally distinguish the molecular signals on pathogenic bacteria from those found in commensals, yet under healthy conditions epithelial immune responses are kept in check. We hypothesized that, in the setting of tissue damage or stress, intestinal epithelial cells would upregulate their responses to TLR ligands to reflect the greater need for immediate protection against pathogens. We treated Caco-2 cells with the TLR5 agonist flagellin in the presence or absence of H(2)O(2) and measured chemokine production and intracellular signaling pathways. H(2)O(2) increased flagellin-induced IL-8 (CXCL8) production in a dose-dependent manner. This was associated with synergistic phosphorylation of p38 MAP kinase and with prolonged I-kappaB degradation and NF-kappaB activation. The H(2)O(2)-mediated potentiation of IL-8 production required the activity of p38, tyrosine kinases, phospholipase Cgamma, and intracellular calcium, but not protein kinase C or protein kinase D. H(2)O(2) prolonged and augmented NF-kappaB activation by flagellin. In contrast to IL-8, CCL20 (MIP3alpha) production by flagellin was reduced by H(2)O(2), and this effect was not calcium dependent. Oxidative stress biases intestinal epithelial responses to flagellin, leading to increased production of IL-8 and decreased production of CCL20. This suggests that epithelial cells are capable of sensing the extracellular environment and adjusting their antimicrobial responses accordingly.
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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) | 0.001 | 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".