Mushroom-Derived Medicine? Preclinical Studies Suggest Potential Benefits of Ergothioneine for Cardiometabolic Health
Bibliographic record
Abstract
Medicinal use of mushrooms has been documented since ancient times, and in the modern world, mushrooms have a longstanding history of use in Eastern medicine. Recent interest in plant-based diets in Westernized countries has brought increasing attention to the use of mushrooms and mushroom-derived compounds in the prevention and treatment of chronic diseases. Edible mushrooms are the most abundant food sources of the modified amino acid, ergothioneine. This compound has been shown to accumulate in almost all cells and tissues, but preferentially in those exposed to oxidative stress and injury. The demonstrated cytoprotectant effect of ergothioneine has led many to suggest a potential therapeutic role for this compound in chronic conditions that involve ongoing oxidative stress and inflammation, including cardiovascular and metabolic diseases. However, the in vivo effects of ergothioneine and its underlying therapeutic mechanisms in the whole organism are not as clear. Moreover, there are no well-defined, clinical prevention and intervention trials of ergothioneine in chronic disease. This review highlights the cellular and molecular mechanisms of action of ergothioneine and its potential as a Traditional, Complementary and Alternative Medicine for the promotion of cardiometabolic health and the management of the most common manifestations of cardiometabolic disease.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".