Host-specific differences in the physiology of acid secretion related to prostaglandins may play a role in gastric inflammation and injury
Bibliographic record
Abstract
Immune mediators are involved in strain-specific manifestations of Helicobacter pylori infection, and the type of immune response is associated with production of PGE(2), which in turn influences gastric acid secretion. Acid secretion plays a pivotal role, not only in the pattern of H. pylori-induced gastritis and its consequences, but also in nonsteroidal anti-inflammatory drug (NSAID)-induced gastropathies. Mice and their transgenic modifications are widely used in Helicobacter and eicosanoid research. Using [(14)C]aminopyrine accumulation and pylorus ligation, we aimed to study acid secretion in gastric gland preparations from the commonly used strains of BALB/c and C57BL/6 mice. We found that PGE(2) does not inhibit acid secretion in gastric glands from C57BL/6 mice, in contrast to the expected antisecretory effect of PGE(2) observed in BALB/c mice. In BALB/c mice the effect of histamine and carbachol was reduced by PGE(2), whereas in C57BL/6 mice dose-response curves to these secretagogues were not affected. EP(3) receptors are not involved in acid secretion in C57BL/6 mice, as confirmed by significantly lower expression of mRNA for the EP(3) receptor. These contrary findings are important to the interpretation of the antisecretory role of eicosanoids in BALB/c and C57BL/6 mouse strains and the involvement of prostanoids in the etiology of Helicobacter-induced inflammation and NSAID-induced gastropathies. We propose that the lack of antisecretory effect of PGE(2) observed in C57BL/6 mice could reflect the extent of Helicobacter-induced inflammation and status of acid secretion in response to anti-inflammatory drugs.
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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) | 0.002 | 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".