The effect of apelin-13 on gastric ischemia/reperfusion injury: the roles of sensory nerves and vagus nerve
Bibliographic record
Abstract
Apelin is a peptide that plays a role in physiological processes such as angiogenesis, apoptosis, and proliferation. The aim of this study was to investigate the role of capsaicin-sensitive afferent neurons and vagus in the effect of apelin against ischemia/reperfusion (I/R) injury. The experimental groups were (1) control, (2) I/R, (3) apelin + I/R, (4) vagotomy + I/R, (5) vagotomy + apelin + I/R, (6) capsaicin + I/R, (7) capsaicin + apelin + I/R, (8) lorglumide + I/R, and (9) lorglumide + apelin + I/R. To test the potential gastroprotective effect of apelin-13, apelin-13 (2 mg/kg i.v.) was administered just before both ischemia and reperfusion. A vagotomy was performed 1 week before I/R in the vagotomized groups; capsaicin (125 mg/kg s.c.) was administrated 2 weeks before I/R in the capsaicin-treated groups and lorglumide (5 mg/kg i.p.) was administered 30 min before I/R in the lorglumide-treated groups. After I/R, a variety parameters in gastric tissue were analyzed. cfos expression was determined in brainstem samples. In the I/R group, the lesion index, myeloperoxidase activity, lipid peroxidation, nitric oxide, and tumor necrosis factor-α increased, and mucosal blood flow, prostaglandin-E2, and calcitonin gene related peptide decreased. Apelin prevented the damaging effects of I/R and increased cfos expression in brainstem areas. Vagotomy, capsaicin, and lorglumide largely eliminated the gastroprotective effects of apelin-13. This study showed that sensory nerves and the vagus play regulatory roles in apelin-induced gastroprotection. Cholecystokinin may play a role in the effect of apelin through sensory neurons.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".