Enrichment of high‐purity nervonic acid ethyl ester from <i>Acer truncatum</i> <scp>B</scp> unge seed oil by combination method of urea inclusion and molecular distillation
Bibliographic record
Abstract
Abstract Acer truncatum Bunge is a type of maple that is unique to China. Its fruit setting rate and seed oil content are both high. The oil is mainly composed of C16–C24 fatty acids and contains 5%–7% nervonic acid (NA). NA and its derivatives can delay ageing and prevent and treat disorders such as senile dementia and Alzheimer's disease. The content of NA ethyl ester prepared by the seed oil of A. truncatum Bunge is 5.84%. We report a new process for the enrichment of NA ethyl ester by urea inclusion (UI) and molecular distillation (MD), with the aim of obtaining highly pure NA ethyl ester. First, based on the difference in fatty acid ethyl ester saturation and carbon chain length, unwanted compounds such as oleic acid ethyl ester, linoleic acid ethyl ester, and sterol were removed by one‐stage UI, the content of NA ethyl ester was increased to 18.69%. The oil in the UI compound was used as a feed, and differences in the mean molecular free paths between the components were exploited to separate the C16–C20 fatty acid ethyl esters (FAEEs) by two‐stage MD. The total content of C16–C20 FAEEs decreased to 3.69% and the purity of NA ethyl ester increased to 47.47%. A new purification process of UI‐MD‐UI was established and NA ethyl ester could be purified to 91.8%. The combination of MD and UI has an important reference value for the industrialization of producing high‐purity NA ethyl ester.
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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 | 0.000 | 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".