A simple method for methylmercury, inorganic mercury and ethylmercury determination in plasma samples by high performance liquid chromatography-cold-vapor-inductively coupled plasma mass spectrometry
Bibliographic record
Abstract
A simple and sensitive method with a fast sample preparation procedure is proposed for the determination of mercury species in plasma/serum. The method combines online high-performance liquid chromatography separation, Hg cold-vapor formation and inductively coupled plasma mass spectrometry detection. Prior to analysis, plasma (250 mu L) was accurately pipetted into 15 mL conical tubes. Then, an extractant solution containing mercaptoethanol, L-cysteine and HCl was added to the samples following sonication for 10 min. Quantitative mercury extraction was achieved with the proposed procedure. Separation of mercury species was accomplished in less than 8 min on a C8 reverse phase column with a mobile phase containing 3% v/v methanol + 97% v/v (0.5% v/v 2-mercaptoethanol + 0.05% v/v formic acid). The method detection limits were found to be 12 ng L-1, 5 ng L-1 and 4 ng L-1 for inorganic mercury, ethylmercury and methylmercury, respectively. Method accuracy is traceable to Standard Reference Material (SRM) 966 Toxic Metals in Bovine Blood from NIST. Additional validation was provided by the analysis of a secondary reference serum sample from the INSQ-Canada. Finally, the method was successfully applied for the speciation of mercury in plasma samples collected from volunteers exposed to methylmercury through fish consumption. For the first time to our knowledge, levels of different species of Hg in plasma samples from riverside populations exposed to MeHg were determined. (C) 2012 Elsevier B.V. All rights reserved.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".