Comparative Assessment of Physical and Chemical Cyanobacteria Cell Lysis Methods for Total Microcystin-LR Analysis
Bibliographic record
Abstract
Standardization and validation of alternative cell lysis methods used for quantifying total cyanotoxins is needed to improve laboratory response time goals for total cyanotoxin analysis. In this study, five cell lysis methods (i.e., probe sonication, microwave, freeze-thaw, chemical lysis with Abraxis QuikLyseTM, and chemical lysis with copper sulfate) were assessed using laboratory-cultured Microcystis aeruginosa (M. aeruginosa) cells. Methods were evaluated for destruction of cells (as determined by optical density of the sample) and recovery of total microcystin-LR (MC-LR) using three M. aeruginosa cell densities (i.e., 1 × 105 cells/mL (low-density), 1 × 106 cells/mL (medium-density), and 1 × 107 cells/mL (high-density)). Of the physical lysis methods, both freeze-thaw (1 to 5 cycles) and pulsed probe sonication (2 to 10 min) resulted in >80% destruction of cells and consistent (>80%) release and recovery of intracellular MC-LR. Microwave (3 to 5 min) did not demonstrate the same decrease in optical density (<50%), although it provided effective release and recovery of >80% intracellular MC-LR. Abraxis QuikLyseTM was similarly effective for intracellular MC-LR recovery across the different M. aeruginosa cell densities. Copper sulfate (up to 500 mg/L Cu2+) did not lyse cells nor release intracellular MC-LR within 20 min. None of the methods appeared to cause degradation of MC-LR. Probe sonication, microwave, and Abraxis QuikLyseTM served as rapid lysis methods (within minutes) with varying associated costs, while freeze-thaw provided a viable, low-cost alternative if time permits.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".