Pharmacological Activities and Safety of Ganoderma lucidum Spores: A Systematic Review
Bibliographic record
Abstract
Ganoderma lucidum is traditionally used to prevent and treat some diseases such as liver disorders, hypertension, insomnia, diabetes, and cancer. G. lucidum spore extracts are also reported to share similar bioactivities as extracts from its other parts. However, there is no systematic review that elucidates its pharmacological effect. Our aim is to comprehensively summarise current evidence of G. lucidum spore extracts to clarify its benefits to be applied in further studies. We searched five primary databases: PubMed, Virtual Health Library (VHL), Global Health Library (GHL), System for Information on Grey Literature in Europe (SIGLE), and Google Scholar on September 13, 2021. Articles were selected according to inclusion and exclusion criteria. A manual search was applied to find more relevant articles. Ninety studies that reported the pharmacological effects and/or safety of G. lucidum spores were included in this review. The review found that G. lucidum spore extracts showed quite similar effects as other parts of this medicinal plant including anti-tumor, anti-inflammatory, antioxidant effects, and immunomodulation. G. lucidum sporoderm-broken extract demonstrated higher efficiency than unbroken spore extract. G. lucidum extracts also showed their effects on some genes responsible for the body's metabolism, which implied the benefits in metabolic diseases. The safety of G. lucidum should be investigated in depth as high doses of the extract could increase levels of cancer antigen (CA)72-4, despite no harmful effect shown on body organs. Generally, there is a lot of potential in the studies of compounds with pharmacological effects and new treatments. Sporoderm breaking technique could contribute to the production of extracts with more effective prevention and treatment of diseases. High doses of G. lucidum spore extract should be used with caution as there was a concern about the increase in CA.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".