Antioxidant Isoflavones in Osage Orange, <i>Maclura pomifera</i> (Raf.) Schneid
Bibliographic record
Abstract
Recent findings that many human chronic diseases are associated with oxidative stresses have instigated the search for dietary antioxidants. Many phytochemicals, particularly phenolic compounds, have been found to possess strong antioxidant activity and reduce the risks of those diseases. Isoflavones, a special phenolic group found in soybean, have been found to act as antioxidants in some model systems. This study investigated the isoflavone content in a unique nonedible tree fruit, Osage orange [Maclura pomifera (Raf.) Schneid], and methods for the extraction, identification, and quantification of the two major isoflavones, osajin and pomiferin, were developed. The ethyl acetate extract contained 25.7% osajin and 36.2% pomiferin, and the two isoflavones were at 9.5 g kg(-1) of fresh Osage orange. Two model systems, FRAP and beta-CLAMS, were used to measure the antioxidant activity of these two isoflavones. Pomiferin was found to be a strong antioxidant in both systems, comparable to the antioxidant vitamins C and E and the synthetic antioxidant BHT. Osajin and the two soybean isoflavones (genistein and daidzein) showed no antioxidant activity. Although the Osage orange fruit is not a food source, it is considered to be safe and, therefore, a potentially good source of an antioxidant nutraceutical and functional food ingredient.
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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 | 0.001 | 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) | 0.000 | 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 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".