The Effect of Aloe vera (Linn) On Cutaneous Wound Healing and Wound Contraction Rate in Adult Rabbits
Bibliographic record
Abstract
Background: In the present research study, the rate of cutaneous wound healing and contraction rate in healthy rabbits using Aloe vera pulp was studied.Methods: Ten healthy rabbits were used for the study. They were divided into two groups consisting of five rabbits each. Cutaneous wounds were made on the lumbar region of each rabbit using a template which ensured that the wounds were of the same size in all the rabbits. 5ml of Aloe vera gel was applied to the wounds of the animals in the test group, while nothing was applied to the wound area of the animals in the control group. The wound area in each group was measured for a period of 21 days, using a venire caliper and tracing paper which was used to trace the wound area. Tissue samples were removed from the wound area in both experimental and control groups and subjected to routine histological analysis, also, morphometric analysis was performed.Results: The rate of wound contraction and mean centripetal contraction was calculated in both groups and graphically represented using Microsoft Excel. The results showed that animals who were treated with Aloe vera gel had a greater wound contraction rate, as well as rapid wound closure. The micrographs showed a thicker epithelial layer, with thinner collagen fibers in the dermis of experimental animals compared to the control group. There was also an abundant capillary bed at the dermal-epidermal junction in the experimental group, compared to the control group.Conclusion: Aloe vera may increase the rate of wound healing by accelerating epithelial migration, and may also play a role in neo-vascularization of the newly healed area.Keywords: Aloe vera, Cutaneous Wounds, Rabbits, Wound Contraction, Wound Healing
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".