One Filter, One Sample, and the <i>N</i>- and O-Glyco(proteo)me: Toward a System to Study Disorders of Protein Glycosylation
Bibliographic record
Abstract
Abstract A method has been developed for release/isolation of O-glycans from glycoproteins in whole cell lysates for mass spectrometric analysis. Cells are lysed in SDS, which is then exchanged for urea and ammonium bicarbonate in a centrifugal filter, before treating with NH4OH to release O-glycans. Following centrifugation, O-glycans are recovered in the filtrate. Sonication achieves O-glycan release in 1 h. Combining the established protocol for filter-aided N-glycan separation, here optimized for enhanced PNGase F efficiency, with the developed O-glycan release method allows analysis of both N- and O-glycans from one sample, in the same filter unit, from 0.5 to 1 million cells. The method is compatible with subsequent analysis of the residual protein by liquid chromatography–mass spectrometry (LC–MS) after glycan release. The medium throughput approach is amenable to analysis of biological replicates, offering a simple way to assess the often subtle changes to glycan profiles accompanying differentiation and disease progression, in a statistically robust way.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".