Bioactive Peptides: From Basic Research to Clinical Trials and Commercialization
Bibliographic record
Abstract
Chronic diseases, including metabolic diseases, have become a worldwide public health issue. Research regarding the use of bioactive peptides or protein hydrolysates derived from food, as the diet-based strategies for the prevention and mitigation of chronic diseases, has increased exponentially in the past decades. Numerous in vitro and in vivo studies report the efficacy and safety of food-derived bioactive peptides and protein hydrolysates as antihypertensive, anti-inflammatory, antidiabetic, and antioxidant agents. However, despite promising preclinical results, an inadequate understanding of their mechanisms of action and pharmacokinetics restrict their clinical translation. Commercialization of bioactive peptides can be further hindered due to scarce information regarding their efficacy, safety, bitter taste, as well as the lack of a cost-effective method of production. This review provides an overview of the current clinical evidence and challenges to commercial applications of food-derived bioactive peptides and protein hydrolysates for the prevention and alleviation of chronic diseases.
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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 | 0.003 | 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 | 0.001 |
| 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".