Therapeutic Roles of Goji Berry and Ginseng in Traditional Chinese
Bibliographic record
Abstract
Background: Goji berries (Lycium barbarum), widely used in traditional Chinese medicine, can be applied as a dietary supplement. They are classified as nutraceutical food due to their long and safe traditional use. Ginseng has been increasingly used in the last decades and has become well known for its significant role in preventing and treating many diseases. Methods: The keywords of Goji berry, Ginseng, Traditional Chinese medicine were searched in Google Scholar, Scopus, Research Gate, and PubMed in both English and Chinese languages. Results: Goji berry significantly inhibited the generation and spread of cancer cells, improved eyesight, and increased reserves of muscle glycogen and liver glycogen, which may increase human energy and has anti-fatigue effect. Usage of Goji berries improved brain function and enhanced learning and memory. It had positive effects on anti-cancer, anti-oxidant activities, retinal function preservation, anti-diabetes, immune function, and anti-fatigue. Pharmacological activities of ginseng extracts affected the central nervous system, antipsychotic action, tranquilizing effects, protection from stress ulcers, increase of gastrointestinal motility, anti-fatigue action, endocrinological effects, enhancement of sexual behavior, acceleration of metabolism, or synthesis of carbohydrates, lipids, RNA, and proteins. In Traditional Chinese Medicine, ginseng helps to maintain a healthy immune system. Conclusions: In this review article we found that Goji berries and Ginseng were sources of compounds with valuable nutritional and bioactive properties. Therefore, they could be incorporated into foods with functional properties. More clinical studies are necessary to uncover the numerous substances and their effects in goji berries and ginseng that contribute to public health.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".