The effect of oral Aphanizomenon flos-aquae extract on excisional wound healing
Bibliographic record
Abstract
Background: Aphanizomenon flos-aquae (AFA) is a type of blue-green algae and contains a source of biological compounds. These microalgae have many beneficial health effects. Recently, fucoidan, known sulfated polysaccharide component of AFA algae, has been claimed to stimulate stem-cell mobilization in animal models. Stem cells play an essential role in tissue repair process. In this study, we use excisional full thickness wound model to investigate the effectiveness of trademark AFA extract on skin wound repair process. Methods: In this experimental study, 21 adult male Wistar rats (weighing 200-250 g) were used and under general anesthesia (intraperitoneally with a ketamine/xylazine solution), two round excisional wounds were created under sterile conditions by a 6 mm punch on the dorsum (paravertebral area) of all rats. Animals were randomly assigned into 3 groups. In groups 1 and 2 (SE-200, SE-400), StemEnhance© (StemTech Health Sciences Inc. British Columbia, Canada) were given respectively 200 or 400 mg/kg by oral gavage once daily and in group 3 (Sham), distilled water (DW) was given to all subjects. Post-wounding gavage of StemEnhance or DW started from 1st day and continued to 7th day. The wound surface area was monitored daily by digital camera and assessed by Image Tool™ software, version 3.5 (UTHSCSA, San Antonio, TX, USA). At 9th day post-wounding animals were sacrificed and repaired tissues were harvested by and assessed by a 8 mm punch. Repaired skin areas were processed for hematoxylin and eosin (H&E). Histopathological parameters of healing including inflammatory cell infiltration, angiogenesis, and fibroblast count were assessed by pathologist. Our study was conducted in the Physiology Department of Medical School, Bushehr University of Medical Sciences, Iran, from October 2016 to March 2016. Results: Macroscopic imaging of wound area revealed that there was statistically significant difference in wound area reduction between SE-200 group and sham group on day 6 post wounding (P=0.032). Moreover, histological findings showed that the number of neutrophils, macrophages, fibroblasts, and microvessel density decreased in both StemEnhace-treated groups. There were no significant differences between two treatment groups. Conclusion: According to the obtained results it seems that the extract of Aphanizomenon flos-aquae algae positively affects wound healing process by ameliorating inflammatory response in early healing phases.
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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 | 0.000 |
| 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 | 0.001 |
| 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".