Direct targeted glycation of the free sulfhydryl group of cysteine residue (Cys‐34) of BSA. Mapping of the glycation sites of the anti‐tumor Thomsen–Friedenreich neoglycoconjugate vaccine prepared by Michael addition reaction
Bibliographic record
Abstract
We present in this manuscript the characterization of the exact glycation sites of the Thomsen-Friedenreich antigen-BSA vaccine (TF antigen:BSA) prepared using a Michael addition reaction between the saccharide antigen as an electrophilic acceptor and the nucleophilic thiol and L-Lysine ε-amino groups of BSA using different ligation conditions. Matrix laser desorption ionization time-of-flight mass spectrometry of the neoglycoconjugates prepared with TF antigen:protein ratios of 2:1 and 8:1, allowed to observe, respectively, the protonated molecules for each neoglycoconjugates: [M + H](+) at m/z 67,599 and 70,905. The measurements of these molecular weights allowed us to confirm exactly the carbohydrate:protein ratios of these two synthetic vaccines. These were found to be closely formed by a TF antigen:BSA ratios of 2:1 and 8:1, respectively. Trypsin digestion and liquid chromatography coupled with electrospray ionization mass spectrometry allowed us to identify the series of released glycopeptide and peptide fragments. De novo sequencing affected by low-energy collision dissociation tandem mass spectrometry was then employed to unravel the precise glycation sites of these neoglycoconjugate vaccines. Finally, we identified, respectively, three diagnostic and characteristic glycated peptides for the synthetic glycoconjugate possessing a TF antigen:BSA ratio 2:1, whereas we have identified for the synthetic glycoconjugate having a TF:BSA ratio 8:1 a series of 14 glycated peptides. The net increase in the occupancy sites of these neoglycoconjugates was caused by the large number of glycoforms produced during the chemical ligation of the synthetic carbohydrate antigen onto the protein carrier.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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 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".