Kinetics of Enzyme Inhibition and Antihypertensive Effects of Hemp Seed (<i>Cannabis sativa</i> L.) Protein Hydrolysates
Bibliographic record
Abstract
Abstract The aim of this study was to determine the antihypertensive effects of enzymatic hemp seed protein hydrolysate (HPH) and its peptide fractions. Hemp seed protein isolate was digested by the sequential action of pepsin and pancreatin to mimic gastrointestinal digestion in human beings. The resultant HPH was separated by membrane ultrafiltration into peptide fractions with different sizes (<1 and 1–3 kDa). The HPH led to significantly higher ( P < 0.05) in vitro inhibition of the activities of angiotensin I‐converting enzyme (ACE) and renin, the two main enzymes involved in abnormal blood pressure elevation (hypertension). Kinetic studies showed that HPH and peptide fractions inhibited renin and ACE activities in a mixed‐type pattern, indicating binding to areas other than the active site. Oral administration of HPH (200 mg/kg body weight) to spontaneously hypertensive rats led to significant reductions ( P < 0.05) in systolic blood pressure (SBP) that reached a maximum of −30 mmHg after 8 h. In contrast, the hypotensive effects of peptide fractions (<1 and 1–3 kDa) had a maximum value of about −15 mmHg after 6–8 h post oral administration. The results suggest a synergistic antihypertensive effect of the peptides present within HPH; this effect was reduced significantly ( P < 0.05) upon separation into peptide fractions.
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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".