Characterization of the antihypertensive and antioxidant properties of hemp seeds (Cannabis sativa L.) and protein-derived peptides in individuals with high blood pressure
Bibliographic record
Abstract
The purpose of this study was to produce bioactive peptides in the form of a hemp seed protein hydrolysate (HPH) and assess the antihypertensive and antioxidant properties in comparison to whole hemp seed protein and casein using a clinical trial design. Bioactive peptides were generated using a previously established method utilizing gastrointestinal enzymes (pepsin and pancreatin) and optimized time, temperature, and pH conditions. Thirty-one individuals with hypertension participated in the study, following a randomized crossover design. They consumed the three treatments (50 g casein, 50 g hemp seed protein, or 45 g hemp seed protein + 5 g HPH) for six weeks each with 2 weeks washout period in between treatments. During the study, 24-hr blood pressure (BP) was measured at various timepoints and blood samples were collected to determine the level of enzymes and biomarkers involved in the BP regulation. The treatment containing HPH showed greater BP lowering effect compared to whole hemp protein and casein. This hypotensive effect was observed for both 24-hr systolic and diastolic BP. Although, we could not differentiate the effects of hemp protein and HPH on angiotensin converting enzyme, renin and nitric oxide, the peptides demonstrated an ability to enhance the levels of superoxide dismutase and catalase while reducing plasma total peroxides and reactive oxygen species to a greater extent than hemp protein and casein. Furthermore, the attenuation of 24-hrBP was correlated with the increased level of epoxy oxylipins, which are involved in the relaxation of smooth muscle cells and subsequently vasorelaxation. These findings propose, for the first time from a clinical trial that hemp seed bioactive peptides may have a potential role as hypotensive and antioxidant agents as an alternative therapy for individuals with hypertension.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".