<i>Momordica charantia</i> (bitter melon) reduces plasma apolipoprotein B-100 and increases hepatic insulin receptor substrate and phosphoinositide-3 kinase interactions
Bibliographic record
Abstract
Aqueous extracts or juice from unripened fruit of Momordica charantia (bitter melon) has traditionally been used in the treatment of diabetes and its complications. Insulin resistance is characterized by significant down-regulation of hepatic insulin signalling as documented by attenuated phosphorylation of insulin receptor (IR), IR substrates 1 and 2, phosphoinositide-3 kinase, protein kinase B, and over-expression of phosphotyrosine phosphatase 1B. We recently demonstrated that bitter melon juice (BMJ) is a potent inhibitor of apoB secretion and TAG synthesis and secretion in human hepatoma cells, HepG2, that may be involved in plasma lipid- and VLDL-lowering effects observed in animal studies. The aim of this study was to evaluate the effects of BMJ on plasma apoB levels and hepatic insulin signalling cascade in mice fed high-fat diet (HFD). Female C57BL/6 mice (4-6 weeks old) were randomized into three groups receiving regular rodent chow, HFD and HFD+BMJ. The data indicate that BMJ not only improves glucose and insulin tolerance but also lowers plasma apoB-100 and apoB-48 in HFD-fed mice as well as modulates the phosphorylation status of IR and its downstream signalling molecules. Investigating the biochemical and molecular mechanisms involved in amelioration of diabetic dyslipidaemia by BMJ may lead to identification of new molecular targets for dietary/alternative therapies.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".