Anti-Inflammatory Effect of Extracts of Inonotus obliquus and Microalgae
Bibliographic record
Abstract
Chaga mushroom (Inonotus obliquus) and marine microalgae are two emerging natural products with many potential physiological health benefits. The aim of this study was to investigate the anti-inflammatory effects of two extracts prepared from Chaga mushroom and microalgae using lipopolysaccharide-stimulated RAW 264.7 murine macrophage cell model. The Chaga mushroom extract dose-dependently reduced the production of proinflammatory biomarkers of interleukin (IL)-6 and tumor necrosis factor-alpha (TNF-α). At a high concentration of 500 µg/L, Chaga mushroom extract significantly suppressed cyclooxygenase-2 levels. Similarly, the extract of microalgae suppressed the secretion of IL-6 and TNF-α by lipopolysaccharide-induced macrophages. Both extracts had no significant impact on the secretion of anti-inflammatory IL-4 production. These results suggest that extracts of Chaga mushroom and microalgae can be used in developing anti-inflammatory natural health products.
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 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".