Purification and identification of a polysaccharide from medicinal mushroom<i>Amauroderma rude</i>with immunomodulatory activity and inhibitory effect on tumor growth
Bibliographic record
Abstract
// Honghui Pan 1 , Yuanyuan Han 1 , Jiguo Huang 1 , Xiongtao Yu 1 , Chunwei Jiao 2 , Xiaobing Yang 1 , Preet Dhaliwal 3, 4 , Yizhen Xie 1 , Burton B. Yang 3, 4 1 Guangdong Institute of Microbiology, State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Guangzhou, China 2 Yuewei Edible Fungi Technology Co. Ltd., Guangzhou, China 3 Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Canada 4 Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada Correspondence to: Yizhen Xie, e-mail: 13622216490@126.com Burton B. Yang, e-mail: byang@sri.utoronto.ca Keywords: medicinal mushroom, herbal medicine, tumor growth, cytokine, amauroderma Received: April 28, 2015 Accepted: June 15, 2015 Published: June 27, 2015 ABSTRACT Medicinal mushrooms in recent years have been the subject of many experiments searching for anticancer properties. We previously screened thirteen mushrooms for their potential in inhibiting tumor growth, and found that the water extract of Amauroderma rude exerted the highest activity. Previous studies have shown that the polysaccharides contained in the water extract were responsible for the anticancer properties. This study was designed to explore the potential effects of the polysaccharides on immune regulation and tumor growth. Using the crude Amauroderma rude extract, in vitro experiments showed that the capacities of spleen lymphocytes, macrophages, and natural killer cells were all increased. In vivo experiments showed that the extract increased macrophage metabolism, lymphocyte proliferation, and antibody production. In addition, the partially purified product stimulated the secretion of cytokines in vitro , and in vivo . Overall, the extract decreased tumor growth rates. Lastly, the active compound was purified and identified as polysaccharide F212. Most importantly, the purified polysaccharide had the highest activity in increasing lymphocyte proliferation. In summary, this molecule may serve as a lead compound for drug development.
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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) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".