Potential Effect of Medicinal Plants on the Prevention of Gastric Ulcer: Mechanism of Actions
Bibliographic record
Abstract
Medicinal plants have been widely studied to identify plant-based anti-gastric ulcer medicines. The mechanism of gastroprotective action is important to discover the potential lead compounds for drug development. All relevant articles between 2011 and 2021 focusing on Malaysian plants were collected and analyzed to understand the underlying pathways. Keywords include peptic ulcer, gastric ulcer, NSAIDs (Non-Steroidal Anti-Inflammatory Drugs), Helicobacterpylori, medicinal plant, gastroprotection, antiulcer, acid secretion, cytoprotective, and digestion processes were applied in the search engines. Twenty-two of the plants had been reported based on the collected data. The review concludes that Malaysian plants could protect the gastric wall against necrotizing agents like ethanol and NSAIDs. This is mainly due to four critical defensive mechanisms: cytoprotective barriers, regulation of heat-shock protein 70 (HSP70) and pro-apoptotic protein (BAX), gastric acid secretion, and antioxidant capability. The mechanisms have been illustrated in the schematic diagrams for better understanding.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".