Tetrahydroxylated bile acids prevents malignant progression of Barret esophagus <i>in vitro</i> by inhibiting the interleukin-1β-nuclear factor kappa-B pathway
Bibliographic record
Abstract
BACKGROUND: Barrett esophagus (BE), a metaplastic adaptive process to gastrointestinal reflux, is associated with a higher risk of developing esophageal adenocarcinoma. However, the factors and mechanism that drive the malignant progression of BE is not well understood. AIM: To investigate the role of bile acids, a component of the reflux fluid, in the malignant progression of BE. METHODS: Using engineered green fluorescent protein- labeled adult tissue-resident stem cells isolated from BE clinical biopsies (BE-ASCs) as the target, we studied the effect of hydrophobic deoxycholic acid (DCA) and hydrophilic tetrahydroxylated bile acids (THBA) on cell viability by fluorescence intensity analysis, mucin production by dark density measurement, tissue structure by pathology analysis, expression of different pro-inflammatory factors gene by quantitative polymerase chain reaction and proteins by Western blot. RESULTS: We found that hydrophobic DCA has cytotoxic and proinflammatory effects through activation of interleukin-1β (IL-1β)-nuclear factor kappa-B (NF-κB) inflammatory pathway on BE-ASCs. This action results in impaired cell viability, tissue intactness, reduced mucin production, and increased transition to disorganized atypical cells without intestinal features. In contrast, co-culture with hydrophilic THBA inhibited the IL-1β-NF-κB inflammatory pathway with maintenance of mature intestinal type cellular and histomorphology. CONCLUSION: Our data indicates that the hydrophilic bile acid THBA can counteract the cytotoxic and proinflammatory effect of hydrophobic DCA and prevent the malignant progression of BE by inhibiting the IL-1β-NF-κB pathway.
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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".