Optimization of extraction and purification process of lycopene from engineered Saccharomyces cerevisiae and structure identification
Bibliographic record
Abstract
In order to explore the extraction and purification method and structure of lycopene produced by engineered Saccharomyces cerevisiae, the extraction and purification technology of lycopene was optimized by single factor and orthogonal tests, and its structure was identified by nuclear magnetic resonance (NMR). The results showed that the optimum extraction conditions of lycopene were acid heat breaking wall: hydrochloric acid concentration 3.0 mol/L, hydrochloric acid dosage 3.0 ml/0.1 g yeast, acidification time 60 min, and temperature 45 ℃. NaOH degreasing: NaOH concentration 0.10 mol/L, NaOH dosage 2.0 ml/0.1 g yeast, saponification time 30 min, water bath temperature 40 ℃ after saponification. Acetone extraction∶ material-liquid ratio 1∶20 (g∶ml), extraction temperature 40 ℃, and time 50 min. The optimal purification process was n-hexane crystallization: crude extract was dissolved and filtered with n-hexane at 40 ℃ and crystallized at -20 ℃ for 12 h. Under the optimum extraction and purification conditions, the extraction rate of lycopene was 76% and the purity of lycopene was 96.7%. NMR results showed that the structure of lycopene was all-trans lycopene, which was consistent with plant-derived lycopene.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".