A Six-Month Supplementation of Mulberry, Korean Red Ginseng, and Banaba Decreases Biomarkers of Systemic Low-Grade Inflammation in Subjects with Impaired Glucose Tolerance and Type 2 Diabetes
Bibliographic record
Abstract
We sought the long-term efficacy of traditionally used antidiabetic herbs in controlling blood glucose homeostasis and low-grade inflammation. Ninety-four subjects with either impaired glucose tolerance or mild T2D were randomized either to treatment arm or placebo arm and received 1 : 1 : 1 mixture of ginseng roots, mulberry leaf water extract, and banaba leaf water extract (6 g/d) for 24 weeks. Oral 75 g glucose tolerance test was performed to measure glucose and insulin responses. Blood biomarkers of low-grade inflammation were also determined. Results found no significant difference in glucose homeostasis control measure changes. However, plasma intracellular adhesion molecule-1 (ICAM-1) concentration was decreased showing a significant between-treatment changes (P = 0.037). The concentrations of vascular cell adhesion molecule-1 (VCAM-1) (P = 0.014) and ICAM-1 (P = 0.048) were decreased in the treatment group at week 24, and the oxidized low-density lipoprotein (ox-LDL) concentration was reduced at week 24 compared to the baseline value in the treatment group (P = 0.003). These results indicate a long-term supplementation of ginseng, mulberry leaf, and banaba leaf suppresses inflammatory responses in T2D.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".