Enrichment-Free Identification of Native Definitive (EnFIND) O-glycoproteome of antibodies in autoimmune diseases
Bibliographic record
Abstract
Abstract The detection of O-glycosylation at the proteome level has long been a challenging task and a roadblock for O-linked protein glycosylation research. We report an Enrichment-Free Identification of Native Definitive (EnFIND) O-glycoproteome using Trapped Ion Mobility Spectrometry coupled to TOF Mass Spectrometry (TIMS-TOF MS) for direct analysis of protein O-glycosylation in native samples with minimum sample requirement. This approach enabled separation of O-glycopeptide isomers, resolution of O-glycosites and O-glycoform, reduction of sample complexity, and increased sensitivity, thus greatly enhancing analysis of the O-glycoproteome of cell lysates, human serum and exosomes. In addition, we found that antibodies in human serum are highly O-glycosylated on variable, especially hypervariable regions and constant regions, which significantly increases antibody diversity. This method was used to successfully identify characteristic O-glycosylation features of autoimmune diseases.
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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) | 0.000 | 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".