Iron chelation acutely stimulates fetal human intestinal cell production of IL-6 and VEGF while decreasing HGF: the roles of p38, ERK, and JNK MAPK signaling
Bibliographic record
Abstract
Bacteria have developed mechanisms to sequester host iron via chelators such as deferoxamine (DFO). Interestingly, DFO has been shown to stimulate acute intestinal epithelial cell inflammatory cytokine production in the absence of bacteria; however, this mechanism has not been elucidated. Intestinal epithelial cell production of IL-6 and TNF-alpha is elevated in various gastrointestinal pathologies, including acute intestinal ischemia. Similarly, VEGF and HGF are essential to intestinal epithelial cell integrity. Therapeutic strategies that decrease IL-6 and TNF-alpha while increasing VEGF and HGF therefore have theoretical appeal. We hypothesized that 1) fetal human intestinal epithelial cells acutely produce increased IL-6, TNF-alpha, VEGF, and HGF during iron chelation and 2) the MAPK pathway mediates these effects. Fetal human intestinal epithelial cells were stimulated by iron chelation (1 mM DFO) with and without p38 MAPK, ERK, or JNK inhibition. Supernatants were harvested after 24 h of incubation, and IL-6, TNF-alpha, VEGF, and HGF levels were quantified by ELISA. Activation of MAPK pathways was confirmed by Western blot analysis. DFO stimulation resulted in a significant increase in epithelial cell IL-6 and VEGF production while yielding a decrease in HGF production (P<0.05). Unexpectedly, TNF-alpha was not detectable. p38 MAPK, ERK, and JNK inhibition significantly decreased IL-6, VEGF, and HGF production (P<0.05). In conclusion, DFO acutely increases fetal human intestinal epithelial cell IL-6 and VEGF expression while causing an unexpected decrease in HGF expression and no detectable TNF-alpha production. Furthermore, chelator-induced intestinal epithelial cell cytokine expression depends on p38, ERK, and JNK MAPK pathways.
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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".