A Voltammetric Assay of Antioxidants and Inhibitors of Soybean Lipoxygenase
Bibliographic record
Abstract
Abstract Antioxidant activity and/or the inhibition of lipoxygenases may contribute to the cell and tissue protective properties of flavonoids. Soybean lipoxygenase‐1 (LOX‐1), is a useful paradigm for lipoxygenases isolated from different sources, and can be used to devise assays of oxygenase inhibitors and antioxidants. Here we describe the voltammetric detection of methylene blue (MB) to assay for antioxidant and lipoxygenase inhibition activity. MB is formed by the catalytic action of hydroperoxide, produced by soybean lipoxygenase reaction on linoleic acid, on benzoyl‐leuco methylene blue (BLMB). Every compound which blocks either the enzymatic reaction, lipoxygenase inhibitors, or the oxidation of BLMB, antioxidants, can thus be detected using this method. The assay involves reaction for a period of one hour of linoleic acid, lipoxygenase, BLMB and inhibitor, followed by injection into a flow‐injection system and detection by square‐wave voltammetry of the methylene blue produced. The problem of irreproducibility induced by adsorption at the solid platinum working electrode is alleviated using the method of alternate injections of control and assay solutions. Assays of several known lipoxygenase inhibitors were undertaken. All of these inhibitors were also, however, shown to be antioxidants. Extension of the assay to the rapid evaluation of novel therapeutic antioxidants and lipoxygenase inhibitors is proposed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".