Effects of omeprazole treatment on nucleoside transporter expression and adenosine uptake in rat gastric mucosa
Bibliographic record
Abstract
Increased adenosine concentration inhibits gastric acid secretion in rat via adenosine A1 and A2A receptors, whereas achlorhydria suppresses A1 and A2A receptor gene expression. This study aimed to examine the effects of omeprazole-induced achlorhydria on the expression and functional activity of nucleoside transporters in rat gastric mucosa. Wistar rats were treated for either 1 or 3 days with 0.4 mmol/kg omeprazole via gavage; controls were treated with vehicle. The expression of nucleoside transporters at the transcript level was explored by quantitative real-time polymerase chain reaction assays; the functional activity of nucleoside transporters in gastric mucosa was explored by observing [3H]adenosine uptake in vitro. Gastric mucosa expressed rat equilibrative nucleoside transporter (rENT) 1 and 2, and rat concentrative nucleoside transporter (rCNT) 1, 2, and 3 at the transcript level, and the estimated values for the threshold cycles for target amplification (Ct) were 31.5 +/- 2, 28.5 +/- 2.1, 32.9 +/- 2.2, 29.1 +/- 2, and 28.9 +/- 2.5, respectively (n = 3 or 4). The Ct value for rat beta-actin was 21.9 +/- 1.8 (n = 4). In vitro uptake of [3H]adenosine by gastric mucosa samples consisted of Na+-dependent and Na+-independent components. One-day omeprazole treatment caused no change in nucleoside transporter mRNA levels or in [3H]adenosine uptake. Three-day omeprazole treatments, however, led to a 12-fold and 17-fold increase in rENT2 and rCNT1 mRNA levels, respectively. Samples taken after 3 days of treatment also took up significantly more [3H]adenosine than did samples from the corresponding control. In conclusion, the possible modification of nucleoside transport activities by changes in intraluminal acidity may have significance as part of a purinergic regulatory feedback mechanism in the control of gastric acid secretion.
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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 | 0.001 |
| 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".