Role of food-derived opioid peptides in the central nervous and gastrointestinal systems
Bibliographic record
Abstract
Opioid receptors are widely distributed in central nervous system and peripheral tissues. Endogenous opioid receptor ligands are involved in many physiological processes. Exogenous peptides, derived from food proteins with gastrointestinal proteases, also exert opioid-like activities, and they include gluten exorphins (wheat), casomorphins (milk), rubiscolins (spinach), and soymorphins (soybean). Milk-derived opioid peptides play both agonistic and antagonistic roles, and most of the opioid peptides exert regulatory functions in the central nervous system, related to nociception, emotion and memory after oral, intracerebroventricular, or intraperitoneal administration. This indicates that the peptides may have crossed the blood-brain barrier or acted peripherally. Furthermore, some food-derived opioid peptides influence gastrointestinal functions such as gut motility, hormone release, appetite, mucus production, and local immunity. In healthy states, food-derived opioid peptides could benefit both the nervous and digestive systems, whereas in pathological conditions, the gastrointestinal permeability change and opioid excess may contribute to pathogenesis of some disorders. PRACTICAL APPLICATIONS: Opioid receptors are important biological targets for the treatment of multiple diseases. Traditional opiate compounds, such as alkaloids, are demonstrated to exert numerous side effects, thereby limiting their clinical effectiveness. It is thought that food-derived opioid peptides may be safer than the alkaloids, and therefore can be applied in functional food development. In this review, we summarized the already discovered food opioid peptides from different sources, and elaborated their physiological functions on the central nervous and gastrointestinal systems. These effects support further exploration of the opioid peptides as therapeutic agents or as functional food ingredient for human health promotion.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".