Analysis of the effect of subcutaneous injection of omental-derived cells on the healing of third degree burns in rats: a preliminary study.
Bibliographic record
Abstract
Burn injury is considered a global health issue. Third degree burn wounds do not heal spontaneously and require skin grafts. Some factors could contribute to wound healing. In this study we assessed the effect of non-fatty omental cells in burn wound healing. Similar third degree burn wounds were induced on the back of 192 rats. Forty-eight of these rats were put in a control group that did not receive any treatment. The rest of the rats were put in 3 groups, each receiving a different treatment regime. Rats in group 2 had a daily application of silver sulfadiazine; group 3 rats were injected with omental cells, and group 4 rats were injected with phosphate buffer saline (PBS) once, followed by daily application of Vaseline to the burned region. Parameters such as open epidermis length, number of epidermal cell layers, granulation tissue thickness (GTT) and neutrophil density were evaluated in each group. The average open epidermis length in the omental cell group was less than in the other groups on days 10 and 20 (P<0.05). The thickness of epidermal cell layers in the group receiving cells was greater than in the other groups on all days. On the 20th day, there was a significant difference in GTT between the four groups (P<0.05). The injection of non-fatty omental cells has a positive effect on third degree burn wounds in rats.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".