Dried-droplet laser ablation ICP-MS of HPLC fractions for the determination of selenomethionine in yeast
Bibliographic record
Abstract
Offline coupling of high performance liquid chromatography (HPLC) to dried droplet laser ablation (LA) ICP-MS detection is described. The method is based on the offline spotting of HPLC fractions onto a substrate followed by LA introduction of the dried sample residues to an ICP-MS for elemental analysis. Quantitation of selenomethionine (SeMet) in yeast using species specific isotope dilution (ID) was achieved following digestion of samples in 4 M methanesulfonic acid and HPLC separation of species. Chromatographic fractions having retention times of 180–210 seconds were collected for each sample. Dried micro-droplets from each fraction were ablated from a polystyrene substrate and quantitated for SeMet. Concentrations of 3301 ± 18 and 3309 ± 24 μg g−1 (one standard deviation, n = 4) with RSDs of 0.55% and 0.73% were obtained based on measured 78Se/74Se and 82Se/74Se ratios, in good agreement with the values of 3309 ± 19 and 3305 ± 26 μg g−1 (one standard deviation, n = 4, RSDs of 0.58% and 0.79%), respectively, obtained by direct HPLC-ICP-MS analysis. The proposed method provides a satisfactory alternative technique for the quantitation of SeMet in yeast.
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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 | 0.001 | 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".