Application of capillary electrophoresis mass spectrometry to the characterization of bacterial lipopolysaccharides
Bibliographic record
Abstract
Capillary electrophoresis (CE) is a high-resolution technique for the separation of complex biological mixtures and has been widely applied to biological analyses. The coupling of capillary electrophoresis with mass spectrometry (MS) provides a powerful approach for rapid identification of target analytes present at trace levels in biological matrices, and for structural characterization of complex biomolecules. Here we review the analytical potential of combined capillary electrophoresis electrospray mass spectrometry (CE-MS) for the analysis of bacterial lipopolysaccharides (LPS). This hyphened methodology facilitates the determination of closely related LPS glycoform and isoform families by exploiting differences in their unique molecular conformations and ionic charge distributions by electrophoretic separation. On-line CE-MS also provides an additional avenue to improve detection limits, which has been successfully applied to directly probe oligosaccharide LPS glycoform populations of bacteria isolated from infected animal models without the need for further passage.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".