Chrysin Modulates Genes Related to Inflammation, Tissue Remodeling, and Cell Proliferation in the Gastric Ulcer Healing
Bibliographic record
Abstract
Chrysin exhibits anti-inflammatory and antioxidant activities. Here, the gastroprotective effect of chrysin was investigated in mouse models of gastric ulcer induced by absolute ethanol, acetic acid, and ischemia-reperfusion injury. The gastric-healing effect was evaluated at 7 and 14 days after treatment; the mechanism of action was verified using the expression of metalloproteinase 2 (MMP-2) and 9 (MMP-9), caspase-3, cyclooxygenase 1 (COX-1) and 2 (COX-2), epidermal growth factor (EGF), and interleukin-10. Chrysin (10 mg/kg) inhibited macroscopic lesions and increased catalase activity in the mouse model established using absolute ethanol. It ameliorated the gastric ulcer caused by acetic acid by improving the expression of inflammatory genes such as COX-2, inhibiting negative remodeling promoted by MMP-9, increasing cell proliferation effect via EGF, and reducing cellular apoptosis by modulating caspase-3. A faster healing effect was evident in the first 7 days of treatment compared to 14 days of treatment, indicating the pharmacological potential of chrysin. Overall, these results demonstrate the potent effect of chrysin in the gastrointestinal tract and elucidate the genes involved in the healing of gastric ulcers. Moreover, an increase in the levels of gastric mucosa defensive factors is involved in the activity of chrysin in the gastric mucosa.
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) | 0.001 | 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".