A mixture of St. John's wort and sea buckthorn oils regresses endometriotic implants and affects the levels of inflammatory mediators in peritoneal fluid of the rat: A surgically induced endometriosis model
Bibliographic record
Abstract
OBJECTIVE: Sea buckthorn (Hippophae rhamnoides L.) and St. John's wort (Hypericum perforatum L.) are used as an emmenagog and for the treatment of other gynecological disorders including uterus inflammation and endometriosis. The aim of the present study is to investigate the potential of a mixture of sea buckthorn and St. John's wort oils (HrHp oil) in the treatment of endometriosis. MATERIALS AND METHODS: The activity was assessed in surgically induced endometriosis in rats. A 15-mm piece of endometrium was sutured into the abdominal wall. Twenty-eight days later, a second laparotomy was performed to calculate the endometrial foci areas and to score intra-abdominal adhesions. The rats were treated with either vehicle, HrHp oil formulation, or the reference (buserelin acetate). At the end of the experiment all rats were sacrificed and endometriotic foci areas and intra-abdominal adhesions were re-evaluated. The tissue sections were analyzed histopathologically. Peritoneal fluids of the experimental animals were collected in order to detect the levels of tumor necrosis factor-α, vascular endothelial growth factor, and interleukin-6, which might be involved in the etiology of endometriosis. RESULTS: , p<0.001) without any adhesion (0.0±0.0, p<0.001) when compared to the control group (3.1±0.9). The levels of tumor necrosis factor-α decreased from 7.02±1.33 pg/mL to 4.78±1.02 pg/mL (p<0.01); vascular endothelial growth factor from 17.39±8.52 pg/mL to 9.67±5.04 pg/mL (p<0.01); and interleukin-6 from 50.95±22.84 pg/mL to 29.11±7.45 pg/mL (p<0.01), respectively, after HrHp oil treatment. CONCLUSION: HrHp oil may be a promising alternative for the treatment of endometriosis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".