New Method Development for Nanoparticle Extraction of Water-Soluble β-(1→3)-<scp>d</scp>-Glucan from Edible Mushrooms, <i>Sparassis crispa</i> and <i>Phellinus linteus</i>
Bibliographic record
Abstract
Sparassis crispa and Phellinus linteus are edible/medicinal mushrooms that have remarkably high contents of beta-(1-->3)-D-glucan, which acts as a biological response modifier, but difficulty in cultivating the fruiting bodies and extraction of beta-D-glucan have restricted detailed studies. Therefore, a novel process for nanoparticle extraction of Sparan, the beta-D-glucan from Sparassis crispa, and Phellin, the beta-D-glucan from Phellinus linteus, has been investigated using insoluble tungsten carbide as a model for nanoknife technology. This is the first report showing that the nanoknife method results in high yields of Sparan (70.2%) and Phellin (65.2%) with an average particle size of 150 and 390 nm, respectively. The extracted Sparan with beta-(1-->3) linkages showed a remarkably high water solubility of 90% even after 10 min of incubation at room temperature. Therefore, it is likely that this nanoknife method could be used to produce beta-D-glucan for food, cosmetic, and pharmaceutical industries.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".