Isolation and Identification of Sialylated Glycopeptides from Bovine α<sub>1</sub>-Acid Glycoprotein by Off-Line Capillary Electrophoresis MALDI-TOF Mass Spectrometry
Bibliographic record
Abstract
Sialylated glycopeptides contained in liquid chromatographic fractions of bovine alpha1-glycoprotein tryptic digests were isolated from asialo peptides using capillary electrophoresis (CE). CE effluents were deposited directly onto a metallic target and analyzed using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. This method allowed the characterization of four N-glycosylation sites in the glycoprotein, and each site was observed as a set of sialylated peptide glycoforms. Tandem mass spectrometry was used to confirm peptide sequences and glycan content in glycoforms. The CE method developed for this study resulted in a very clear separation of the sialylated from the asialo content of glycoprotein digests and proved very useful in the determination of the nature and location of sialylated glycans along the protein chain. This article is the first report describing the use of on-target CE fraction collection using a MALDI removable sample concentrator.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| 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 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".