In-Capillary Protein Enrichment and Removal of Nonbuffering Salts Using Capillary Electrophoresis with Discontinuous Buffers
Bibliographic record
Abstract
Salt is abundant in biological samples and can cause problems in capillary electrophoresis (CE) due to excessive Joule heating and electrodispersion. Desalting with solid phase minibeds is currently most compatible with the small sample volumes of CE. They are however difficult to prepare and suffer from poor bed-to-bed reproducibility. Alternatively, enrichment of proteins and peptides was developed using CE, by trapping them at their isoelectric points with a discontinuous buffer of mismatched pH. Ionic salts, such as sodium chloride, do not possess isoelectric points and therefore are not retained by the discontinuous buffer. In this work, the removal of ionic salt during protein enrichment using CE with discontinuous buffers was investigated. Nonbuffering ions were found to electromigrate through the pH junction without disrupting the enrichment process and were eventually removed from the capillary. Mass spectral data obtained from the enriched and desalted sample confirmed a significant signal enhancement. Finally, a strong acid was introduced to remove the pH junction and thus facilitated a subsequent capillary zone electrophoresis separation. An integrated procedure of enrichment, desalting, and separation was demonstrated on a mixture of three protein standards.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".