Deoxycholic acid causes DNA damage while inducing apoptotic resistance through NF-κB activation in benign Barrett's epithelial cells
Bibliographic record
Abstract
Gastroesophageal reflux is associated with adenocarcinoma in Barrett's esophagus, but the incidence of this tumor is rising, despite widespread use of acid-suppressing medications. This suggests that refluxed material other than acid might contribute to carcinogenesis. We looked for potentially carcinogenetic effects of two bile acids, deoxycholic acid (DCA) and ursodeoxycholic acid (UDCA), on Barrett's epithelial cells in vitro and in vivo. We exposed Barrett's (BAR-T) cells to DCA or UDCA and studied the generation of reactive oxygen/nitrogen species (ROS/RNS); expression of phosphorylated H2AX (a marker of DNA damage), phosphorylated IkBα, and phosphorylated p65 (activated NF-κB pathway proteins); and apoptosis. During endoscopy in patients, we took biopsy specimens of Barrett's mucosa before and after esophageal perfusion with DCA or UDCA and assessed DNA damage and NF-κB activation. Exposure to DCA, but not UDCA, resulted in ROS/RNS production, DNA damage, and NF-κB activation but did not increase the rate of apoptosis in BAR-T cells. Pretreatment with N-acetyl-l-cysteine (a ROS scavenger) prevented DNA damage after DCA exposure, and DCA did induce apoptosis in cells treated with NF-κB inhibitors (BAY 11-7085 or AdIκB superrepressor). DNA damage and NF-κB activation were detected in biopsy specimens of Barrett's mucosa taken after esophageal perfusion with DCA, but not UDCA. These data show that, in Barrett's epithelial cells, DCA induces ROS/RNS production, which causes genotoxic injury, and simultaneously induces activation of the NF-κB pathway, which enables cells with DNA damage to resist apoptosis. We have demonstrated molecular mechanisms whereby bile reflux might contribute to carcinogenesis in Barrett's esophagus.
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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".