Phytochemicals targeting genes relevant for type 2 diabetes
Bibliographic record
Abstract
Nutrigenomic approaches based on ethnopharmacology and phytotherapy concepts have revealed that type 2 diabetes mellitus (T2DM) may be susceptible to dietary intervention. Interaction between bioactive food components and the genome may influence cell processes and modulate the onset and progression of the disease. T2DM, characterized by insulin resistance and beta cell dysfunction, is one of the leading causes of death and disability. Despite the great advances that have been made in the understanding and management of this complex, multifactorial disease, T2DM has become a worldwide epidemic in the 21st century. Population and family studies have revealed a strong genetic component of T2DM, and a number of candidate genes have been identified in humans. Variations in the gene sequences such as single nucleotide polymorphisms, explain the individual differences in traits like disease susceptibility and response to treatment. A clear understanding of how nutrients affect the expression of genes should facilitate the development of individualized intervention and, eventually, treatment strategies for T2DM. Review of the literature identified many phytochemicals/extracts from traditional medicinal plants that can target diabetogenic genes. This review focuses on the genetic aspects of T2DM, nutrient modification of genes relevant for diabetes, and future prospects of nutritional therapy of T2DM.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.001 |
| 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".