H <sub>2</sub> S‐RELEASING ASPIRIN EXERTS PROTECTIVE EFFECT IN ESOPHAGEAL AND GASTRIC MUCOSAL STRESS‐ASSOCIATED INJURY
Bibliographic record
Abstract
Aspirin is one of the widely prescribed antiplatelet and anti‐inflammatory drugs and last data expanded its role into complex biological processes such as cancerogenesis, tissue repair, and aging, despite that well know its effects for peptic ulcer or gastrointestinal (GI) bleeding which can develop even in an achlorhydric environment. Recent extensive research of activities of hydrogen sulfide (H 2 S) has proven that the addition of H 2 S‐releasing moiety to the classical non‐steroidal anti‐inflammatory drugs (NSAID) results with GI cytoprotective activity. The objective of this study was to evaluate the effects of novel NSAID‐H 2 S compound ‐ ATB 340 (Antibe Therapeutics Inc), hydrogen sulfide‐releasing derivative of aspirin (H 2 S‐aspirin) in esophageal and gastric mucosal defence in a rat model of stress injury. Methods Rats were treated with vehicle (control), classical aspirin (10 mg/kg), ATB‐340 (17,5 mg/kg) with or without being subjected to injury according to the University Ethical Committee Approval (21.05.2014, N o 5). The damage of the esophageal mucosa (EM) and gastric mucosa (GM) was estimated via scoring lesion index by histomorphological analysis. Serological levels of VCAM‐1, IL‐6 by ELISA Kits (Cedarlane, Canada) were evaluated. Results Treatment by ATB‐340 resulted in protective effect and lower grade of EM & GM lesions in twice by damage index. The basal levels of VCAM‐1, IL‐6 from aspirin‐treated rats and suspected to stress‐injury were higher that of control animal. Pre‐treatment by ATB‐340 exerted an anti‐inflammatory effect by decreasing VCAM‐1 and IL‐6 vs classical aspirin. Conclusion These results indicate that inhibiting inflammation and improving endothelial functions modulate protective effect of H2S‐aspirin.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".