Identification of the angiotensin-converting enzyme inhibitory\nactivity peptide of the germinated brown rice sake-lees by\nLC-MS analysis using ACD/MS Workbook Suite
Bibliographic record
Abstract
Until now, we have made low-salt bread using the germinated brown rice sake-lees. We would like to utilize the germinated brown rice sake-lees for making bread, which is in future. Angiotensin-Converting Enzyme (ACE) inhibitory activities were measured in germinated brown rice sake-lees, germinated brown rice liquor, and refined sake in vitro. As a result, the ACE inhibitory activities (germinated brown rice sake-lees, germinated brown rice liquor and refined sake) were 0.15 mg/ml, 1.15 mg/ml and 1.55 mg/ml with an IC50 level, respectively. Since ACE inhibitory activity of the germinated brown rice liquor was higher than that of the refined sake, the germinated brown rice-derived ingredients was suggested to have some ACE inhibitory activity. In addition, the ACE inhibitory activity of the germinated brown rice sake-lees was higher than that of the germinated brown rice liquor. Taken together, the germinated brown rice sake-lees were expected to remain more inhibitory activity than the liquor. As a method to easily search and identify the functional ingredients of the food, we conducted an examination to develop a method for identification of the functional-dipeptide from germinated brown rice sake-lees extract. From the LC-MS analysis results, we searched dipeptide with the ACE inhibitory activity using the software ACD/MS Workbook Suite (Advanced Chemistry Development, Inc., Canada) with IntelliTarget function and MS Match function. Comparing the two functions, MS Match function showned that dipeptide Val-Pro with the hypotensive effect was present in germinated brown rice sakelees. The effective dipeptide was identified easily by using MS Match function from LC-MS results
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".