Enteroaggregative <i>Escherichia coli</i> flagellin‐induced interleukin‐8 secretion requires Toll‐like receptor 5‐dependent p38 MAP kinase activation
Bibliographic record
Abstract
Enteroaggregative Escherichia coli (EAEC) is an emerging enteric pathogen that causes acute and chronic diarrhoea in a number of clinical settings. EAEC diarrhoea involves bacterial aggregation, adherence to intestinal epithelial cells and elaboration of several toxigenic bacterial mediators. Flagellin (FliC-EAEC), a major bacterial surface protein of EAEC, causes interleukin (IL)-8 release from several epithelial cell lines. The host response to flagellins from E. coli and several other bacteria is mediated by Toll-like receptor 5 (TLR5), which signals through nuclear factor kappa B (NF-kappaB) to induce transcription of pro-inflammatory cytokines. p38 mitogen-activating protein (MAP) kinase (MAPK) is a member of a family of stress-related kinases that influences a diverse range of cellular functions including host inflammatory responses to microbial products. We studied the role of p38 MAPK in FliC-EAEC-induced IL-8 secretion from Caco-2 human intestinal epithelial cells and THP-1 human monocytic cells. We found that IL-8 secretion from both cell types is dependent on p38 MAPK, which is phospho-activated in response to FliC-EAEC. The role of TLR5 in p38 MAPK-dependent IL-8 secretion was verified in HEp-2 cells transiently transfected with a TLR5 expression construct. Activation of interleukin-1 receptor-associated kinase (IRAK) was also observed in Caco-2 and TLR5-transfected HEp-2 cells after exposure to FliC-EAEC. Finally, we demonstrated that pharmacological inhibition of p38 MAPK reduced IL-8 transcription and mRNA levels, but did not affect NF-kappaB activation. Collectively, our results suggest that TLR5 mediates p38 MAPK-dependent IL-8 secretion from epithelial and monocytic cells incubated with FliC-EAEC, and that this effect requires IL-8 promoter activation independent of NF-kappaB nuclear migration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".