Bacterial DNA evokes epithelial IL‐8 production by a MAPK‐dependent, NFκB‐independent pathway
Bibliographic record
Abstract
ABSTRACT Recognition of bacterial products by the innate immune system is dependent on pattern‐recognition receptors: toll‐like receptor 9 (TLR‐9) in the case of bacterial DNA. We hypothesized that bacterial DNA can directly affect enteric epithelial cells. RT‐PCR revealed constitutive TLR‐9 mRNA expression in three human colonic epithelial cell lines (T84, HT‐29, Caco‐2) and THP‐1 monocytes. Epithelial cells, in six‐well culture plates or on filter supports, were exposed to E. coli DNA (1–50 µg/ml), synthetic CpG‐rich oligonucleotides, or calf thymus DNA for 6–48 h. Exposure to E. coli DNA resulted in an increase in IL‐8 mRNA, and a time‐and dose‐dependent increase in IL‐8 secretion. Also, CpG oligonucleotides induced epithelial IL‐8 production, whereas calf thymus DNA did not. Exposure to E. coli DNA resulted in phosphorylation of ERK 1/2 MAPK and inhibitors of ERK activity (PD98059, UO126) significantly reduced the evoked IL‐8 production. In contrast, inhibitors of NFκB activity (PDTC, SN50) did not block E. coli DNA‐induced IL‐8 production. Electrophoretic mobility shift assays revealed that E. coli DNA stimulated epithelial AP‐1 but not NFκB activation. The barrier (i.e., transepithelial resistance) and ion transport parameters of epithelial monolayers (assessed in Ussing chambers) were unaltered following E. coli DNA exposure. Thus model gut epithelia express TLR‐9 mRNA and, while maintaining their barrier function, can respond to E. coli DNA by increased IL‐8 production.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".