Using a Modified Ferrous Oxidation−Xylenol Orange (FOX) Assay for Detection of Lipid Hydroperoxides in Plant Tissue
Bibliographic record
Abstract
The ferrous oxidation-xylenol orange (FOX) assay was adapted for quantifying lipid hydroperoxides (LOOHs) in plant extracts. Excised pieces of several fruit and vegetable species were exposed to 83 kJ m(-2) day(-1) of biologically effective ultraviolet B irradiance (UV-B(BE)) for 10-12 days to induce cellular oxidation. The LOOH and thiobarbituric acid reactive substance (TBARS) concentrations of these plant tissues were assessed with the FOX and iodometric assays for the former and a modified TBARS assay for the latter. There was generally good agreement between the FOX and iodometric methods both prior to and following the UV exposure. However, the iodometric assay appeared to have some difficulty in consistently quantifying lower LOOH levels (<11 microM), whereas the FOX assay measured LOOH concentrations as low as 5 microM. All tissues exhibited UV-induced increases in TBARS, indicating a marked degree of cellular oxidation in the exposed tissue segments. Compared with the iodometric assay, the FOX method consistently generated less variable LOOH values. The presence of authentic linoleic acid-OOHs in spiked avocado and spinach samples (11 microM) was identified with liquid chromatography-mass spectrometry techniques, which validated corresponding FOX assay results. The FOX method is inexpensive, is not sensitive to ambient O2 or light levels, and can rapidly generate LOOH measurements. The physiological value of the FOX assay resides in its ability to measure initial rather than more advanced fatty acid oxidation; hence, early membrane-associated stress events in plant tissue can be detected.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".