Identification of Selenium-Containing Glutathione S-Conjugates in a Yeast Extract by Two-Dimensional Liquid Chromatography with Inductively Coupled Plasma MS and Nanoelectrospray MS/MS Detection
Why this work is in the frame
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Bibliographic record
Abstract
An approach for the identification of unknown selenium-containing biomolecules was developed, enabling the identification of selenodiglutathione (GS-Se-SG) and the mixed selenotrisulfide of glutathione and cysteinylglycine (GS-Se-SCG) in aqueous yeast extracts. The method consists of two-dimensional liquid chromatography, inductively coupled plasma mass spectrometry (ICPMS) and nanoelectrospray tandem mass spectrometry. Analytes were separated by size-exclusion chromatography followed by preconcentration and separation on a porous graphitic carbon HPLC column. The HPLC effluent was monitored for selenium by ICPMS, and two selenium-containing fractions were isolated and analyzed by nanoelectrospray MS. The nanoelectrospray technique has a low sample consumption of approximately 80 nL/min, enabling a preconcentration of the sample to a few microliters. Mass spectra of the two fractions showed the characteristic Se isotopic pattern centered at m/z 693.1 and 564.0 for the [M + H]+ 80Se ions. MS/MS spectra of adjacent parent ions confirmed the presence of Se. The two selenium species were identified as GS-Se-SG and GS-Se-SCG by collision induced dissociation (CID). The accurately measured masses of the most abundant 691 and 693 u parent ions are in good agreement (differences = 3 ppm) with the theoretical masses. To our knowledge, this is the first identification of GS-Se-SG and GS-Se-SCG in biological matrixes by MS/MS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 it