Soybean Bioactive Peptides and Their Functional Properties
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Soy consumption has been associated with many potential health benefits in reducing chronic diseases such as obesity, cardiovascular disease, insulin-resistance/type II diabetes, certain type of cancers, and immune disorders. These physiological functions have been attributed to soy proteins either as intact soy protein or more commonly as functional or bioactive peptides derived from soybean processing. These findings have led to the approval of a health claim in the USA regarding the ability of soy proteins in reducing the risk for coronary heart disease and the acceptance of a health claim in Canada that soy protein can help lower cholesterol levels. Using different approaches, many soy bioactive peptides that have a variety of physiological functions such as hypolipidemic, anti-hypertensive, and anti-cancer properties, and anti-inflammatory, antioxidant, and immunomodulatory effects have been identified. Some soy peptides like lunasin and soymorphins possess more than one of these properties and play a role in the prevention of multiple chronic diseases. Overall, progress has been made in understanding the functional and bioactive components of soy. However, more studies are required to further identify their target organs, and elucidate their biological mechanisms of action in order to be potentially used as functional foods or even therapeutics for the prevention or treatment of chronic diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it