Konjac-Mannan and American Ginsing: Emerging Alternative Therapies for Type 2 Diabetes Mellitus
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite significant achievements in treatment modalities and preventive measures, the prevalence of diabetes has risen exponentially in the last decade. Because of these limitations there is a continued need for new and more effective therapies. An increasing number of people are using dietary and herbal supplements, even though there is a general lack of evidence for their safety and efficacy. Consequently, science based medical and government regulators are calling for more randomized clinical studies to provide evidence of efficacy and safety. Our research group has selected two such promising and functionally complementary therapies for further investigation as potentially emerging alternative therapies for type 2 diabetes: Konjac-mannan (KJM) and American ginseng (AG). We have generated a mounting body of evidence to support the claim that rheologically-selected, highly-viscous KJM, and AG with a specific composition may be useful in improving diabetes control, reducing associated risk factors such as hyperlipidemia and hypertension, and ameliorating insulin resistance. KJM has a demonstrated ability to modulate the rate of absorption of nutrients from the small bowel, whereas AG has post-absorptive effects. Consequently, it appears that KJM and AG are acting through different, yet complementary, mechanisms: KJM by increasing insulin sensitivity and AG likely by enhancing insulin secretion. Before the therapeutic potential of KJM and AG as novel prandial agents for treatment of diabetes can be fully realized, further controlled trials with larger sample sizes and of longer duration are required. A determination of the active ingredients in AG, and the rheology-biology relationship of KJM are also warranted.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it