In search of novel immune-modulatory compounds from British Columbia wild mushrooms and their effectiveness in inflammatory micro-circulation of mice
Bibliographic record
Abstract
Natural products have been an integral component of people's health and health outcomes for thousands of years. In particular, several mushroom species have demonstrated beneficial therapeutic potential. The goals of this research are to explore the immune-stimulatory and anti-inflammatory potential of wild mushrooms native to the North Central region of British Columbia. Out of 42 mushroom extracts examined, four exhibited strong immune-stimulatory activity as assessed by induction of tumor-necrosis factor alpha (TNF-a) production in macrophage cells. Out of thirty-three extracts tests, nineteen demonstrated potent anti-inflammatory activity as determined by inhibition of lipopolysaccharide-induced TNF-a production in macrophage cells. Sodium hydroxide extract of Echinodontium trinctorium exhibited potent anti-inflammatory activity and was selected for further study. A small molecular weight (~5-25 kDa) carbohydrate was successfully purified using sequential size-exclusion and ion-exchange chromatography. GC-MS analysis showed that the polysaccharide has glucose (89.7%) as the major back-bone monosaccharide, and also the presence of other monosaccharides such as mannose (3.1%), galactose (2.8%), fucose (2.4%), and xylose (2.0%). The study also revealed the presence of 1,3-linked glucose linkages. Both the semi-purified anti-inflammatory compound(s) from E. tinctorium and the methanol extract of Inonotus obliquus can ameliorate histamine-induced vasodilation in the 2A arterioles (gluteus maximus muscle) in mice. This is the first study to demonstrate the anti-inflammatory activity of purified compounds and extracts from mushroom in an animal microcirculation model using intravital microscopy.
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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 | 0.000 |
| 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".