Nutritional and Functional Properties of Edible Mushrooms: A Food with Promising Health Claims
Bibliographic record
Abstract
Over the past two decades, there has been a steady flow of publications about the health effects related to mushrooms consumption. They represent a valuable source of protein, present high levels of fiber, some vitamins and minerals, and they also have reduced amount of fat and sodium. In addition, their complex carbohydrates profile can strengthen considerably the immune system.Edible mushrooms have been related to significant functional properties due to their bioactive compounds, such as eritadenine, phenolic compounds, sterols (as ergosterol), chitosan, etc., These substances are considered as important agents in the prevention and treatment of different health conditions like obesity, diabetes, or cardiovascular disease. However, it is important to remember that most of scientific studies are made in animal models and, therefore, some evidences regarding mushroom consumption have yet to be confirmed in clinical trials.Despite of the growing appeal for humans by their medicinal effects and nutritional value, mushrooms are also very appreciated for their texture, flavor, and versatility in culinary. They can be easily incorporated into any kind of dish, improving the dietary diversity without adding many calories.The information presented in this review point out that the positive effect of mushrooms on health is beyond basic nutrition. Therefore, it is very valuable expanding our knowledge about mushrooms, in order to identify all their active principles and the mechanisms involved in each health benefit, getting aware about the doses required to achieve that, in a safe range for humans.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".