Liquid Chromatography Online with Selected Reaction Monitoring Electrospray Mass Spectrometry for the Determination of Organoarsenic Species in Crude Extracts of Marine Reference Materials
Bibliographic record
Abstract
The large number of arsenic species known to be present in marine samples and their broad range of chemical properties pose a significant challenge for arsenic speciation analysis. The predominantly used ICPMS detection online with HPLC only provides element-selective information, which is not sufficient for the identification of arsenic species without standards. However, electrospray tandem mass spectrometry in the selected reaction monitoring (SRM) mode enables molecule-selective detection with high sensitivity for quantification. A new HPLC-ES-SRM method was developed for the determination of more than 20 organoarsenic species. Two chromatographic systems were compared, an anion exchange method and a combined cation anion exchange method. Collision-induced dissociation breakdown curves were constructed for all arsenic species investigated and used to optimize the SRM conditions. External calibration was performed with mixed standard solutions containing 21 arsenic species. Two SRM transitions were monitored for most of the analytes, and their intensity ratio was used for quality control. The developed methods were applied for the quantification of arsenic species in extracts of four marine reference materials. Spiking experiments revealed, especially for the early-eluting analytes on the anion exchange system, significant signal suppression by coeluting matrix constituents. Therefore, the standard addition approach was used for quantification. AsB, the major arsenic species in tuna CRM 627 and DORM-2, was accurately quantified with the combined cation anion exchange ES-SRM method.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".