Total Analysis of Microcystins in Fish Tissue Using Laser Thermal Desorption–Atmospheric Pressure Chemical Ionization–High-Resolution Mass Spectrometry (LDTD-APCI-HRMS)
Bibliographic record
Abstract
Microcystins (MCs) are cyanobacterial toxins encountered in aquatic environments worldwide. Over 100 MC variants have been identified and have the capacity to covalently bind to animal tissue. This study presents a new approach for cell-bound and free microcystin analysis in fish tissue using sodium hydroxide as a digestion agent and Lemieux oxidation to obtain the 2-methyl-3-methoxy-4-phenylbutyric acid (MMPB) moiety, common to all microcystin congeners. The use of laser diode thermal desorption-atmospheric pressure chemical ionization coupled with Q-Exactive mass spectrometry (LDTD-APCI-HRMS) led to an analysis time of approximately 10 s per sample and high-resolution detection. Digestion/oxidation and solid phase extraction recoveries ranged from 70 to 75% and from 86 to 103%, respectively. Method detection and quantification limits values were 2.7 and 8.2 μg kg(-1), respectively. Fish samples from cyanobacteria-contaminated lakes were analyzed, and concentrations ranging from 2.9 to 13.2 μg kg(-1) were reported.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".