Hypoglycemic and Hypolipidemic Effects of Glucomannan Extracted from Konjac on Type 2 Diabetic Rats
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
Diabetes and its complications are one of the most concerned metabolic diseases worldwide and threaten human health severely. Hypoglycemic and hypolipidemic effects of glucomannan extracted from konjac on high-fat diet and streptozocin-induced type 2 diabetic rats were evaluated in this study. Administration of konjac glucomannan significantly decreased the levels of fasting blood glucose, serum insulin, glucagon-like peptide 1, and glycated serum protein. The concentrations of serum lipids, including total cholesterol, triacylglycerols, low-density lipoprotein cholesterol, and non-esterified fatty acid, were notably reduced by konjac glucomannan treatment. In addition, antioxidant capacity, pancreatic injury, and adipose cell hypertrophy were ameliorated by konjac glucomannan administration in type 2 diabetic rats. Besides, ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based lipidomics analysis was used to explore the improvement of lipid metabolic by konjac glucomannan treatment. The disturbance of glycerolipid (diacylglycerol, monoacylglycerol, and triacylglycerol), fatty acyl (acylcarnitine and hydroxyl fatty acid), sphingolipid (ceramide and sphingomyelin), and glycerophospholipid (phosphatidylcholine) metabolism were attenuated by the glucomannan treatment. This study provided new insights for investigating the anti-diabetic effects of konjac glucomannan and suggests that konjac glucomannan may be a promising nutraceutical for treating type 2 diabetes.
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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