Antioxidant and antihypertensive activities of wonderful cola ( <i>Buchholzia coriacea</i>) seed protein and enzymatic protein hydrolysates
Bibliographic record
Abstract
The aim of this work was to produce wonderful cola protein hydrolysate fractions with in vitro antioxidant properties coupled with blood pressure-reducing ability when orally administered to spontaneously hypertensive rats (SHRs). Wonderful cola protein isolate (WCI) was hydrolyzed with pancreatin to produce a hydrolysate (WCH), which was subjected to ultrafiltration separation using 1, 3, 5, and 10 kDa molecular weight cut-off membranes to obtain <1, 1–3, 3–5 and 5–10 kDa peptide fractions, respectively. The <1 and 1–3 kDa fractions had higher contents of arginine when compared to the 3–5 and 5–10 kDa peptides. The WCH and <1 kDa peptide fraction had significantly (p < 0.05) better DPPH radical scavenging (55–67%) and metal chelation (83–93%) activities but lower hydroxyl radical scavenging power (10–32%) than the WCI (46, 46 and 63%, respectively). The <1 kDa had significantly (p < 0.05) higher in vitro inhibition (80%) of angiotensin converting enzyme (ACE) activity while the 5–10 kDa was the most active inhibitor (90%) of renin activity. All peptide fractions so produced had better systolic and diastolic blood pressure-lowering effects than WCH and WCI. However, the <1 kDa fraction produced significantly (p < 0.05) stronger systolic (−33 mmHg) and diastolic (−30 mmHg) blood pressure reductions 6 h after oral gavage to SHRs. Thus, wonderful cola proteins contain encrypted bioactive peptides that may be used to formulate antioxidant and antihypertensive products.
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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) | 0.001 | 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".