Investigation of different combinations of derivatization, separation methods and electrospray ionization mass spectrometry for standard oligosaccharides and glycans from ovalbumin
Bibliographic record
Abstract
Derivatization procedures using 1-phenyl-3-methyl-5-pyrazolone (PMP) and 2-aminonaphthalene trisulfone (ANTS) were selected among a number of well known methods for labelling carbohydrates. PMP derivatives were selected owing to our laboratory's previous high-performance liquid chromatography/electrospray ionization mass spectrometry (HPLC/ESI-MS) experience with these, whereas the ANTS-labelled compounds were prepared for fluorophore-assisted carbohydrate electrophoresis (FACE) separation. ANTS-oligosaccharide standards were characterized to study their ionization patterns. Reversed-phase and normal-phase HPLC systems were coupled on-line with ESI-MS. Each necessitated its own mobile phase system which, in turn, imposed some important changes in the ionization conditions used and/or on the ionization patterns and spectra obtained. Following characterization of the intact glycoprotein ovalbumin with ESI-MS, its glycans were detached using the enzyme PNGase-F. The glycans were subjected to PMP and ANTS derivatization. It was very difficult to separate ANTS derivatives by reversed-phase HPLC owing to lack of retention, and normal-phase HPLC offered reasonable retention with limited separation. PMP compounds overall yielded better normal- and reversed-phase separations and improved sensitivity over the ANTS-labelled sugars, for which negative mode ESI had to be used. The combination of ESI of intact ovalbumin and ESI of PMP-glycans gave rise to the detection of over 20 different glycoforms, excluding the possible presence of structural isomers for each sugar composition detected.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".