Preparation, pungency and bioactivity of gingerols from ginger ( <i>Zingiber officinale</i> Roscoe): a review
Why this work is in the frame
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Bibliographic record
Abstract
Ginger has been widely used for different purposes, such as condiment, functional food, drugs, and cosmetics. Gingerols, the main pungent component in ginger, possess a variety of bioactivities. To fully understand the significance of gingerols in the food and pharmaceutical industry, this paper first recaps the composition and physiochemical properties of gingerols, and the major extraction and synthesis methods. Furthermore, the pungency and bioactivity of gingerols are reviewed. In addition, the food application of gingerols and future perspectives are discussed. Gingerols, characterized by a 3-methoxy-4-hydroxyphenyl moiety, are divided into gingerols, shogaols, paradols, zingerone, gingerdiones and gingerdiols. At present, gingerols are extracted by conventional, innovative, and integrated extraction methods, and synthesized by chemical, biological and in vitro cell synthesis methods. Gingerols can activate transient receptor potential vanilloid type 1 (TRPV1) and induce signal transduction, thereby exhibiting its pungent properties and bioactivity. By targeted mediation of various cell signaling pathways, gingerols display potential anticancer, antibacterial, blood glucose regulatory, hepato- and renal-protective, gastrointestinal regulatory, nerve regulatory, and cardiovascular protective effects. This review contributes to the application of gingerols as functional ingredients in the food and pharmaceutical industry.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it