Comparison of St. John's wort oil and thiocilline ointment on wound healing in a diabetic rat model
Bibliographic record
Abstract
Aims: In diabetic patients, wound healing is impaired and wounds are often infected with multifactorial agents. This study aimed to compare the effectiveness of St. John’s wort and ointment containing bacitracin-neomycin (thiocilline) to improve wound healing in a diabetic infected wound model. Methods: Rats in which diabetes was induced by administering 60 mg/kg streptozotocin (STZ) were considered diabetic if their blood sugar levels were above 300 mg/dl 72 hours later. Group 1: Control (Non diabetic) group, Group 2: Diabetes group. During wound care, both groups were disinfected with povidone iodine (PI) and the right lumbar region of each rat was dressed with thiocilline and the left lumbar region was dressed with St. John’s wort oil. Considering the wound healing period, the study was terminated after an average of 20 days. In histopathological examination, ulceration, necrosis, epithelialization, congestion, edema, polymorphous nucleated leukocyte (PNL), monocyte, fibroblast, and neovascularization were evaluated. Results: In histopathological evaluation, there was a statistically significant decrease in ulceration and necrosis in the group treated with St. John’s wort oil compared to the group given thiocilline (p=0.04). In terms of epithelialization, there was a statistically significant increase in the group dressed with St. John’s wort oil compared to the group given thiocilline (p=0.03). There was a statistically significant decrease in congestion and edema in the group treated with St. John’s wort oil compared to the group given thiocilline (p=0.03). There was a statistically significant increase in fibroblast and neovascularization in the group treated with St. John’s wort oil compared to the group given thiocilline (p=0.02). Conclusion: Histopathologic ally, epithelialization, fibroblast, and neovascularization, which have important functions in the wound healing process, increased in diabetic rats administered St. John’s wort. Although it is used in traditional medicine due to its antidepressant effectiveness, we believe that St. John’s wort can be used in wounds that develop in diabetic patients, as it has the potential to increase the wound healing process.
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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 | 0.001 | 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) | 0.001 | 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".