Rebelling against the (Insulin) Resistance: A Review of the Proposed Insulin-Sensitizing Actions of Soybeans, Chickpeas, and Their Bioactive Compounds
Bibliographic record
Abstract
Insulin resistance is a major risk factor for diseases such as type 2 diabetes and metabolic syndrome. Current methods for management of insulin resistance include pharmacological therapies and lifestyle modifications. Several clinical studies have shown that leguminous plants such as soybeans and pulses (dried beans, dried peas, chickpeas, lentils) are able to reduce insulin resistance and related type 2 diabetes parameters. However, to date, no one has summarized the evidence supporting a mechanism of action for soybeans and pulses that explains their ability to lower insulin resistance. While it is commonly assumed that the biological activities of soybeans and pulses are due to their antioxidant activities, these bioactive compounds may operate independent of their antioxidant properties and, thus, their ability to potentially improve insulin sensitivity via alternative mechanisms needs to be acknowledged. Based on published studies using in vivo and in vitro models representing insulin resistant states, the proposed mechanisms of action for insulin-sensitizing actions of soybeans, chickpeas, and their bioactive compounds include increasing glucose transporter-4 levels, inhibiting adipogenesis by down-regulating peroxisome proliferator-activated receptor-γ, reducing adiposity, positively affecting adipokines, and increasing short-chain fatty acid-producing bacteria in the gut. Therefore, this review will discuss the current evidence surrounding the proposed mechanisms of action for soybeans and certain pulses, and their bioactive compounds, to effectively reduce insulin resistance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".