Effect of Artemisia annua Linne callus induced by plant cell culture technology on wound healing
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Bibliographic record
Abstract
현재 많은 나라들은 자생식물을 활용한 산업소재를 개발하는 데 지대한 관심을 가지고 있다. 특히 화장품 산업은 친환경, 자연친화적인 소재를 찾는데 집중하고 있는 추세이다. 우수한 생리활성 물질을 포함한 식물을 식물세포배양기술을 이용하여 대량으로 배양하고 그 함유물을 고농도로 얻음으로 효과적인 소재로 개발하려고 노력하고 있다. 이에 본 연구는 항암, 항균, 항산화, 항염 등의 효능이 입증되어 세계적으로 주목받고 있는 개똥쑥을 선택하여 식물세포배양기술을 이용해 유도한 캘러스의 화장품 소재로서의 가능성을 확인하고자 하였다. 약 6개월 동안 식물세포배양기술로 개똥쑥 캘러스를 유도하였고, 유도된 캘러스를 얻어 열수 및 에탄올 추출하여 약 2개월간 다양한 효능을 시험하였다. HPLC 분석을 통하여 열수 및 에탄올 추출물의 유효성분에 차이를 보임을 확인하였다. 또한 효능평가에서도 차이를 보였다. 개똥쑥 캘러스 에탄올 추출물을 처리하였을 경우 항염관련 단백질인 COX-2의 발현을 50% 이상 감소시키고 wound healing assay를 통해 상처 치유능이 70%정도 증가함을 확인하였다. 이를 통해 개똥쑥 캘러스 추출물이 자연친화적, 친환경적인 소재로써 항염 및 상처치료 관련 제품에 기여할 것으로 예상된다. Currently, many countries have an interest in developing cosmetics materials using native plants. In this aspect, there is increasing need to develop cosmetics materials using native plants in our county. In the present study, calluses were induced from Artemisia annua Linne, which was highlighted because of its useful effects, such as anti-cancer, anti-fungal and anti-inflammation. Water and ethanol extractions were performed from the calluses of Artemisia annua Linne. After the mass production of Artemisia annua Linne's calluses, water and ethanol extraction was performed to examine its functional roles in healing wounds and inflammation. The differences in the effective elements were observed in the ethanol extract. The callus showed anti-inflammation activity through the suppression of the inflammation-related gene, COX-2, and ethanol extracts showed their ability to heal wounds. Overall, these results suggest that the extract of Artemisia annua Linne's calluses is a natural and environment-friendly material, and can be used as medical supplies associated with anti-inflammation and healing wounds.
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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 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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 it