Pressurized liquid extraction of toxins from cyanobacterial cells
Bibliographic record
Abstract
The suitability of pressurized liquid extraction (PLE) of cyanotoxins from cells was investigated. The stability of cyanotoxins (MCYST-RR, MCYST-LR, and anatoxin-a) was evaluated at nine combinations of pressure and temperature (7, 10, and 14 MPa and 60 degrees C, 80 degrees C and 100 degrees C) using 75% (v/v) methanol in water (MeOH) as solvent. Additional experiments investigated the stability of cyanotoxins when water was used as solvent (at a pressure of 14 MPa and a temperature of 40 degrees C, 50 degrees C, 60 degrees C, 80 degrees C, or 100 degrees C). Results using 75% MeOH showed that the MCYST-RR and MCYST-LR were stable under the tested pressures up to 80 degrees C. At 100 degrees C MCYST recovery decreased by 10% to 17%. When water was used as the solvent, no differences in recovery were observed for MCYST-LR, whereas for MCYST-RR, maximum recovery was obtained at 60 degrees C, and degradation occurred at 100 degrees C. In contrast, anatoxin-a was labile under all experimental conditions; the best recoveries (ca. 50%) were obtained at 60 degrees C at the three pressures using 75% MeOH. However, only 17%-23% recovery was obtained with water extraction at all temperatures. The extraction of MCYST-LR and variants from cells (Microcystis aeruginosa, UTCC299) was studied using two solvents, 75% MeOH and 100% water, at 14 MPa and 60 degrees C and 100 degrees C. PLE extracts were compared with extracts obtained with 75% MeOH and ultrasonication. Complete extraction was achieved in both solvents in one 5-min cycle (at 100 degrees C). Although lower recovery was obtained using PLE (79%-105%), shorter extraction time and automation are advantageous over ultrasonication.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".