Phytoglycoproteins and Human Health: Current Knowledge and Future Applications
Bibliographic record
Abstract
Over the years, humans have relied on plants as sources of nutrients and bioactive compounds that promote health and wellness. Interestingly, drug discovery has benefitted immensely from the use of bioactive phytochemicals derived from food and medicinal plants. Phytoglycoproteins (PGPs) are plant-derived proteins with sugar moieties covalently linked to amino acid side chains, formed by glycosylation during posttranslational modification of polypeptides. Several studies in the last two decades, including cell culture and animal studies, have documented a variety of health-beneficial effects of PGPs, including hypolipidemic, wound healing, antioxidant, anti-inflammatory, immunomodulatory, and anticancer properties. Despite the prospects, there is a dearth of information on the pharmacokinetics and toxicity of PGPs, including possible induction of immune reactions, and the potential effects of stereospecific variation in PGPs isomers on their physiological functions. Further exploration of the multifunctional glycoproteins will position them as strong candidates for the development of nutraceuticals and functional foods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".