Effect of Alpina Officinarum Ethanol Extract on Immunoregulatory Activities in the Mice
Bibliographic record
Abstract
본 연구는 면역억제 마우스에서 양강 에탄올 추출물이 면역증강에 미치는 영향을 평가해보았다. 마우스에 cyclophosphamide를 2회 복강 주사한 후 양강 추출물을 30, 100, 300 mg/kg 용량으로 4주간 경구투여 한 후, 체중 및 면역장기 무게, 비장세포수, 혈청 사이토카인 농도 및 혈청 면역글로불린의 농도를 측정하였다. 실험 결과 체중과 비장세포수는 양강 추출물 투여 시 대조군과 비교하여 유의한 차이를 보이지 않았다. 혈청의 IL-2, TGF-<TEX>${\beta}$</TEX> 및 IFN-<TEX>${\gamma}$</TEX> 농도는 AO 100군에서 대조군에 비해 유의적인 증가를 보였고(p<0.05) IL-4 농도는 실험군에서 유의한 차이를 보이지 않았다. 혈청 내 IgM의 농도는 대조군에 비해 양강 추출물 투여군 모두에서 유의적으로 증가하였고 (p<0.05), IgA의 농도는 양강 추출물 투여군에서 증가하는 경향을 보였는데 특히 AO100군에서 유의성 있게 증가하였다(p<0.05). 본 연구 결과는 양강 에탄올 추출물은 혈청 내 사이토카인 농도와 면역글로불린 농도를 증가시켜 면역력 증강에 기여할 것으로 보이며 특히 100 mg/kg을 투여하였을 때 효과가 가장 큰 것으로 나타났다. The purpose of this study was to investigate the immunomodulatory effects of Alpina officinarum (AO) ethanol extract on immunocompromised mice. The mice were injected intraperitoneally with an immunosuppressive drug, cyclophosphamide, and then administrated orally with 30, 100, and 300 mg/kg of ethanol extract of AO (AO 30, AO 100, and AO 300, respectively). The concentrations of cytokines and immunoglobulins (IgM, IgA, IgG) in serum were measured. The body weight of the mice and spleen cell number of the AO-fed group showed no significant difference compared to a control group. The concentrations of several cytokines, including IL-2, IFN-<TEX>${\gamma}$</TEX>, and TGF-<TEX>${\beta}$</TEX>, in serum showed a significant increase in the AO 100 group compared to the control and other groups (p<0.05). The IL-4 level showed no significant difference in the experimental groups. The supplementation of AO (30, 100, 300 mg/kg) significantly increased the concentration of IgM (p<0.05). The concentration of IgA was significantly increased in the AO 100 group (p<0.05) compared to the control group. It can be concluded that AO ethanol extract enhances immune function by promoting the production of cytokines and immunoglobulins.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".