Enzymatic pre‐treatment of microalgae cells for enhanced extraction of proteins
Bibliographic record
Abstract
Crude proteins and pigments were extracted from different microalgae strains, both marine and freshwater. The effectiveness of enzymatic pre‐treatment prior to protein extraction was evaluated and compared to conventional techniques, including ultrasonication and high‐pressure water extraction. Enzymatic pre‐treatment was chosen as it could be carried out at mild shear conditions and does not subject the proteins to high temperatures, as with the ultrasonication approach. Using enzymatic pre‐treatment, the extracted proteins yields of all tested microalgae strains were approximately 0.7 mg per mg of dry cell weight. These values were comparable to those achieved using a commercial lytic kit. Ultrasonication was not very effective for proteins extraction from Chlorella sp ., and the extracted proteins yields did not exceed 0.4 mg per mg of dry cell weight. For other strains, similar yields were achieved by both treatment methods. The time‐course effect of enzymatic incubation on the proteins extraction efficiency was more evident using laccase compared to lysozyme, which suggested that the former enzyme has a slower rate of cell disruption. The crude extracted proteins were fractionated using an ion exchange resin and were analyzed by the electrophoresis technique. They were further tested for their antioxidant activity, the highest of which was about 60% from Nannochloropsis sp . The total phenolic contents in the selected strains were also determined, with Chlorella sp . showing the highest content reaching 17 mg/g. Lysozyme was also found to enhance the extraction of pigments, with Chlorella sp. showing the highest pigments contents of 16.02, 4.59 and 5.22 mg/g of chlorophyll a, chlorophyll b and total carotenoids, respectively.
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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 | 0.000 | 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 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".