Longitudinal study of esophageal mucosal damage after esophagectomy and gastric interposition: relationship between reflux-related mucosal injury and Notch signaling
Bibliographic record
Abstract
Background: Esophagectomy with gastric interposition could serve as a good human reflux model to study the molecular pathogenesis of esophageal mucosal damage induced by gastroesophageal reflux. This study was to investigate the role of Notch signaling in reflux injury of esophageal mucosa. Methods: Patients undergoing Ivor-Lewis esophagectomy for early stage esophageal squamous cell carcinoma were included. Follow-ups were scheduled at 6, 18, 36 and 48 months postoperatively, including reflux symptom assessment, endoscopic and histological evaluation of esophageal mucosal damage. The expressions of Notch1 and its downstream target gene Hes1 were evaluated by real-time polymerase chain reaction (PCR) and immunohistochemistry (IHC). Results: Forty-four out of 48 patients completed four follow-ups. Injuries of esophageal remnant confirmed by endoscopical and histological examinations were both more often with a longer postoperative period (P<0.05). The mRNA expression levels of Notch1 and Hes1 were decreased in a time-dependent manner after operation (P<0.001). Notch1 and Hes1 mRNA levels were significantly higher in normal squamous mucosa than in esophagitis, and higher in esophagitis than in metaplasia (P<0.05). Immunohistochemical study also demonstrated a similar protein expression pattern. Samples with endoscopic evidence of mucosal damage exhibited lower expression of Notch1 mRNA levels as compared to biopsies without visualized damage (P=0.035). Conclusions: This is the first longitudinal study on Notch signaling in human esophagectomy model, our preliminary findings suggest decreased Notch signaling might be involved in the development of mucosa damage caused by gastroesophageal reflux.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".