Hemp seed protein and its hydrolysate compared with casein protein consumption in adults with hypertension: a double-blind crossover study
Bibliographic record
Abstract
BACKGROUND: The effects of consuming hemp seed protein (HSP) as well as its hydrolysate-derived bioactive peptide (HSP+) on blood pressure (BP) has not, to our knowledge, been investigated in humans. OBJECTIVES: We aimed to investigate how consumption of HSP and its hydrolysate modulates 24-h systolic (SBP) and diastolic BP (DBP) and plasma biomarkers of BP compared with casein. METHODS: In a double-blind, randomized, crossover design trial, 35 adults who had mild hypertension with SBP between 130 and 160 mmHg and DBP ≤110 mmHg were recruited. Participants were randomly assigned to varying sequences of 3 6-wk treatments, 50 g casein/d, 50 g HSP/d, or 45 g HSP plus 5 g HSP-derived bioactive peptides/d (HSP+), separated by a 2-wk washout period. Treatment effects were assessed with a linear mixed model with repeated measures. RESULTS: Compared with casein, after HSP+ consumption, 24-h SBP and 24-h DBP decreased from 135.1 and 80.0 mmHg to 128.1 ± 1.6 (P < 0.0001) and 76.0 ± 1.4 mmHg (P < 0.0001), respectively, whereas these values were 133.5 ± 1.6 and 78.9 ± 1.4 mmHg after HSP consumption (P < 0.0001). There were no differences between the HSP and HSP+ consumption in plasma angiotensin-converting enzyme (ACE) activity, renin, or nitric oxide (NO) concentrations. However, these 2 treatments were able to lower both ACE and renin activities and raise NO concentration in plasma compared with casein. CONCLUSIONS: These results suggest that hemp protein consumption, as well as in combination with bioactive peptides, may have a role in the dietary management of hypertension. This trial was registered at clinicaltrials.gov as NCT03508895.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".