Transcriptome signatures in Helicobacter pylori-infected mucosa identifies acidic mammalian chitinase loss as a corpus atrophy marker
Bibliographic record
Abstract
BACKGROUND: The majority of gastric cancer cases are believed to be caused by chronic infection with the bacterium Helicobacter pylori, and atrophic corpus gastritis is a predisposing condition to gastric cancer development. We aimed to increase understanding of the molecular details of atrophy by performing a global transcriptome analysis of stomach tissue. METHODS: Biopsies from patients with different stages of H. pylori infection were taken from both the antrum and corpus mucosa and analyzed on microarrays. The stages included patients without current H. pylori infection, H. pylori-infected without corpus atrophy and patients with current or past H. pylori-infection with corpus-predominant atrophic gastritis. RESULTS: Using clustering and integrated analysis, we found firm evidence for antralization of the corpus mucosa of atrophy patients. This antralization harbored gain of gastrin expression, as well as loss of expression of corpus-related genes, such as genes associated with acid production, energy metabolism and blood clotting. The analyses provided detailed molecular evidence for simultaneous intestinal metaplasia (IM) and spasmolytic polypeptide expressing metaplasia (SPEM) in atrophic corpus tissue. Finally, acidic mammalian chitinase, a chitin-degrading enzyme produced by chief cells, was shown to be strongly down-regulated in corpus atrophy. CONCLUSIONS: Transcriptome analysis revealed several gene groups which are related to development of corpus atrophy, some of which were increased also in H. pylori-infected non-atrophic patients. Furthermore, loss of acidic chitinase expression is a promising marker for corpus atrophy.
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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 | 0.001 | 0.001 |
| 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".