Toxicity of a traditional Chinese medicine, Ganoderma lucidum, in children with cancer.
Bibliographic record
Abstract
BACKGROUND: Cancer is one of the most common severe diseases in Canadian children, and chemotherapy treatment leads to numerous, potentially fatal, adverse side effects including febrile neutropenia and leukopenia. In an attempt to prevent opportunistic infections, Ganoderma lucidum, a mushroom that has been used in Traditional Chinese Medicine for thousands of years, is being used by some people as an adjunctive to chemotherapy to help boost the immune system. Although extensive research is being conducted to determine its immunostimulatory properties, there is essentially no data on toxicity. OBJECTIVES AND METHODS: The purpose of this study was to determine toxicity of low and high concentrations of 3 different extracts of G. lucidum (GL, Reishi and PSGL) on the viability of 1) Jurkat E6.1 cells, 2) LG2 cells, and 3) PBMCs isolated from a) healthy adults, b) healthy children, and c) paediatric patients undergoing chemotherapy. RESULTS: When Jurkat E6.1 and LG2 cells were treated with increasing concentrations of the 3 extracts, both time- and concentration- dependent decreases in cell viability were observed. However, when human PBMCs were treated with the same extracts, variable results were obtained. Although there was no consistent pattern, toxicity was observed in PBMCs. CONCLUSION: This is the first study that examines the toxicity of 3 different extracts of G. lucidum in both adultsâ and children's PBMCs. Contrary to previous belief, our results suggest that extracts of G. lucidum should be used with caution as there appears to be potential for toxicity.
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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".