Speciation of selenium in cells by HPLC-ICP-MS after (on-chip) magnetic solid phase extraction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Elemental speciation in cells is significant for metallomics research. In this study, novel methods of (on-chip) magnetic solid phase extraction (MSPE) combined with high performance liquid chromatography (HPLC)-inductively coupled plasma mass spectrometry (ICP-MS) were proposed for selenium speciation in selenium-enriched yeast cells. An integrated microfluidic chip consisting of reaction, mixing, and extraction units was designed and fabricated for on-chip MSPE. Sulfonated polystyrene-coated magnetic nanoparticles (Fe3O4@PSS MNPs) were prepared as adsorption material for MSPE of selenoamino acids and selenopeptide. The factors affecting the extraction performance of the target selenium species by (on-chip) MSPE-HPLC-ICP-MS were systematically investigated. The analytical performance of the (on-chip) MSPE-HPLC-ICP-MS was evaluated under individual optimal conditions. The limits of detection for five target selenium species were 0.025 μg L−1 to 0.090 μg L−1 and 0.057 μg L−1 to 0.149 μg L−1 for MSPE-HPLC-ICP-MS and on-chip MSPE-HPLC-ICP-MS, respectively. The MSPE-HPLC-ICP-MS method is sensitive, fast, easy-to-operate, and economical. The on-chip MSPE-HPLC-ICP-MS method has the unique advantages of low sample consumption and high integration; thus, it is suitable for selenium speciation in a small number (∼800) of selenium-enriched yeast cells. A Certified Reference Material of SELM-1 yeast was used to validate the accuracy of the developed (on-chip) MSPE-HPLC-ICP-MS methods. The proposed methods were successfully applied to the speciation of selenium in selenium-enriched yeast cells. Analysis of approximately 800 cells by on-chip MSPE-HPLC-ICP-MS revealed that the average amounts of selenocystine (SeCys2) and selenomethionine (SeMet) in a single selenium-enriched yeast cell are in the order of subpicograms.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it