Alterations of Mast Cells in the Esophageal Mucosa of the Patients With Non-Erosive Reflux Disease
Bibliographic record
Abstract
BACKGROUND: Mast cells (MCs) are widely distributed in the gastrointestinal tract, which could be involved in visceral hypersensitivity and gut dysmotility. Whether esophageal MCs play a role in non-erosive reflux disease (NERD) has yet to be determined. The aim of this study was to characterize esophageal MCs distribution, degranulation, and ultrastructure. METHODS: The esophageal mucosa at 5 cm above the end of esophagus was obtained from 26 NERD and 14 healthy volunteers (control) by gastroscopy. Immunohistochemistry was performed and average MC counts per high-power field (HPF) and the percentage of degranulated MCs were obtained. The ultrastructure of MCs was observed by transmission electron microscope (TEM). RESULTS: More MCs were observed in NERD (7.23 ± 2.41 cells/HPF) as compared with controls (3.79 ± 1.67 cells/HPF) (P < 0.01) and the percentage of degranulated MCs in NERD was also significantly higher than controls (26.85 ± 8.79% vs 11.5 ± 4.18%, P < 0.01). Under TEM, more Golgi apparatus, mitochondria and endoplasmic reticulum were found in MCs in patients with NERD. Special secreting particles were also found in cytoplasm, more vacuoles were left after MCs degranulation in patients with NERD. CONCLUSIONS: Our results indicate that increased numbers of MCs and MCs activation may be involved in the pathogenesis of NERD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".