Effects of Nitric Oxide and Reactive Oxygen Species on HIF-1a Stabilization Following<b><i>Clostridium Difficile</i></b>Toxin Exposure of the Caco-2 Epithelial Cell Line
Bibliographic record
Abstract
BACKGROUND/AIMS: Stabilization of the hypoxia-inducible factor (HIF-1α) is proposed to provide a protective host-response to C. difficile intoxication. Here, we aimed to elucidate whether nitric oxide and/or reactive oxygen species produced during C. difficile toxin exposure could influence HIF-1α stability and initiate protection against epithelial cell damage. METHODS/RESULTS: HIF-1α and inducible nitric oxide synthase (iNOS) proteins were up-regulated whereas factor-inhibiting HIF-1 (FIH-1) protein was down-regulated in Caco-2 epithelial cell monolayers with in vitro toxin exposure. We demonstrate using the biotin-switch assay that the stabilization of HIF-1α protein occurred via iNOS-dependent nitrosylation. Inhibition of iNOS activity by selective inhibitor (1400W) attenuated HIF-1α stabilization and exacerbated toxin-dependent disruptions in Caco-2 monolayer morphology and tight junctional integrity in vitro. Treatment of Caco-2 cell monolayers with N-actylcysteine (NAC), a scavenger of reactive oxygen species (ROS), attenuated toxin-dependent increases in iNOS and HIF-1α protein levels but had no effect on FIH-1 responses. In addition, mice that were exposed to C. difficile toxin in vivo also demonstrated a significant increase in HIF-1α protein and nitrosylation levels. CONCLUSION: Taken together, these data suggest that important synergistic actions exist between nitric oxide and ROS to stabilize HIF-1α and its innate, protective actions in the context of C. difficile toxin-mediated epithelial injury.
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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".