A critical review of Luteolin's effects on glycolipid metabolism and the underlying molecular mechanisms
Bibliographic record
Abstract
The increasing global incidence of diabetes and obesity has heightened the desire for safer, more effective, and natural treatment agents. Luteolin, a flavonoid prevalent in fruits, vegetables, and herbs, has demonstrated potential antidiabetic and anti-obesity properties among dietary polyphenols. This article analyzes the molecular pathways that contribute to luteolin's therapeutic efficacy in the treatment of diabetes and obesity. Luteolin exhibits antidiabetic effects via diminishing oxidative stress, improving insulin sensitivity through modifications in insulin signaling pathways, and blocking enzymes like α-glucosidase and α-amylase that are integral to glucose metabolism. Concurrently, its anti-obesity actions encompass the suppression of adipogenesis, promotion of lipolysis, augmentation, improvement of gut microbiota composition, and mitigation of chronic inflammation and oxidative stress in adipose tissues. The poor bioavailability and the pharmacokinetics of luteolin are also examined. Moreover, many in vivo preclinical investigations validate luteolin's preventive effects in mitigating hyperglycemia, insulin resistance, hepatic steatosis, and inflammation generated by obesity. Luteolin is a promising natural supplement for the integrated control of diabetes and obesity through multi-targeted molecular pathways with minimal side effects. This narrative review encompasses around 19 in vivo animal studies and 3 human studies chosen for their mechanistic insights into the modulation of glycolipid metabolism by luteolin. Studies were included that evaluated the molecular mechanisms underlying the antidiabetic and anti-obesity effects of luteolin. The scarcity of human data and issues related to bioavailability underscore the necessity for clinical trials and formulation studies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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".