Occurrence, dietary sources, quantification and bioactivities of natural antioxidant ergothioneine – A longavity vitamin?
Bibliographic record
Abstract
Abstract This review addresses the knowledge gap surrounding ergothioneine which is a naturally occurring antioxidant, by examining both its beneficial properties and the challenges associated with its study. Ergothioneine, often termed a ‘longevity vitamin’, is present in various foods such as mushrooms, grains and certain animal tissues and is synthesised by specific microorganisms. Despite its recognised potential in promoting healthier and extended lifespans, the mechanisms and full spectrum of its effects remain inadequately understood. This article provides a balanced overview of ergothioneine, covering its prevalence, methods for quantification and a wide range of bioactivities, while its antioxidant capabilities, including the neutralisation of free radicals and reactive oxygen species, highlight its promise for enhancing cellular health and preventing age-related diseases. In addition to that, this review also discusses the limitations and gaps in current research. Notably, ergothioneine's bioaccumulation in tissues vulnerable to oxidative stress suggests its significant role in longevity. Preliminary studies suggest benefits such as reduced inflammation, protection of mitochondrial function and support for brain health, yet comprehensive studies are required to fully understand its mechanisms. This review aims to present an unbiased and thorough understanding of ergothioneine, emphasising the need for further research to unlock its full potential in human health and ageing.
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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) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".