Processing and storage of ratite oils affects primary oxidation status and radical scavenging ability
Bibliographic record
Abstract
Treatments for diseases such as coronary artery disease and gastrointestinal disorders seek to minimise oxidative damage by free radicals through the use of antioxidants. Oils derived from ratites (flightless birds) have therapeutic potential, with varying fatty acid composition between species. The current study investigated the influence of farm location, rendering method, duration and storage mode on radical scavenging activity (RSA) and primary oxidation status of ratite oils. Emu Oil (n = 8; EO1, EO2a/b, EO3–7; varying processing and storage factors), Ostrich Oil (OsO), Rhea Oil (RO) and olive oil (OlO) were tested for free RSA against 2,2-diphenyl-1-picryl hydracyl (expressed as 1/IC50 g/mL) and primary oxidation (peroxide mEqO2/kg). RSA (g/mL) of EO1 (558 ± 22) was greater than EO2a (8 ± 0.6), EO5 (413 ± 26), EO6 (16 ± 0.3) and EO7 (2 ± 0.2), OsO (313 ± 12), RO (32 ± 12) and OlO (196 ± 4), and less than EO3 (717 ± 32; P < 0.001). Antioxidant properties of OsO were more pronounced than RO (P < 0.001). Primary oxidation (mEqO2/kg) of EO1 (97 ± 0.6) was greater than EO2a (57 ± 0.6), EO2b (28 ± 0.2), EO5 (11 ± 0.6), OsO (50 ± 0.9) and OlO (61 ± 0.9). The wide variability in RSA of oils highlights the need for standardisation of farm location, diet composition, rendering procedures, time of render and duration of storage. Regulatory control of these parameters is recommended in order to minimise differences in therapeutic efficacy of ratite oils.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".