Notch Signaling Pathway Is Inhibited in the Development of Barrett’s Esophagus: An In Vivo and In Vitro Study
Bibliographic record
Abstract
Objective: To explore the role of Notch signaling in the development of Barrett's esophagus. Methods: Patients with esophagectomy and gastric interposition were recruited as a human model of gastroesophageal reflux disease. The expressions of Notch signaling genes in normal esophagus from surgical specimen and columnar metaplasia in the esophageal remnant after esophagectomy were evaluated by real time quantitative Polymerase Chain Reaction (RT-qPCR) and immunohistochemistry (IHC). For in vitro experiments, Het-1A cells were treated with hydrochloric acid, deoxycholic acid, mixture of hydrochloric acid and deoxycholic acid, or Notch1-siRNA, and expressions of Notch1, Hes1, MUC2, and K13 were evaluated via RT-qPCR and western blot. Results: Samples were obtained from 36 patients with columnar metaplasia in the esophageal remnant. Both IHC and RT-qPCR indicated that Notch1 and Hes1 expressions were significantly higher in normal esophagus than that in metaplasia. Hydrochloric acid and deoxycholic acid suppressed Notch1, Hes1, and K13 expressions, in concert with increasing MUC2 expressions. Notch inhibition by Notch1-siRNA contributed to the downregulation of Notch1, Hes1, and K13 expressions, whereas MUC2 expression was enhanced. Conclusions: Both hydrochloric acid and deoxycholic acid could suppress Notch signaling pathway in esophageal epithelial cells, and inhibited Notch signaling has important functions in the development of Barrett's esophagus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".