Supercharging metabolic health with <i>Lycium barbarum</i> L.: A review of the therapeutic potential of this functional food for managing metabolic syndrome
Bibliographic record
Abstract
Abstract Metabolic syndrome (MetS) is a common disorder involving a cluster of metabolic abnormalities, such as abdominal obesity, hypertension, dyslipidemia, insulin resistance, and atherogenic profile. MetS is characterized by an increase in oxidative stress and a chronic proinflammatory state, which are directly related to the development and progression of this pathology. It has been seen how a healthy lifestyle and good dietary practices are key to improving the different metabolic parameters and, therefore, play a fundamental role in reducing the risk of developing diabetes. The present review focuses on the research evidence related to the therapeutic properties of Lycium barbarum L. in MetS gathered in the last years. Several preclinical studies suggest that L. barbarum extracts are a good dietary supplement for the prevention of cardiovascular diseases in people with MetS. This compound has been used for years in traditional Chinese medicine for the treatment of atrophic gastritis, problems related to the lungs, kidneys, and liver, and as a supplement for eye health. In addition, different in vitro and in vivo studies have been carried out that support the properties attributed to metabolites derived from L. barbarum, such as polysaccharides that have been shown diverse biological activities. In conclusion, L. barbarum extracts have multiple benefits to increase general well‐being and immune function. However, there are a limited number of studies related to effect of L. barbarum in MetS, but they demonstrated effectiveness in the treatment of obesity, diabetes mellitus type 2, and prevention of diabetes mellitus type 2 complication.
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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 | 0.001 |
| 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 | 0.001 | 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".