Comparison of two glutaraldehyde immobilization techniques for solid‐phase tryptic peptide mapping of human hemoglobin by capillary zone electrophoresis and mass spectrometry
Bibliographic record
Abstract
Stabilization of proteolytic enzymes, especially by immobilization, is of considerable interest because of their potential applications in medicine and the chemical and pharmaceutical industries. We report here a detailed comparison of two procedures for trypsin immobilization using the same homobifunctional agent, glutaraldehyde, for the purpose of peptide mapping. These methods include covalent coupling either to controlled pore glass (solid support) or via a cross-linking reaction (without any solid support). The immobilized trypsin preparations were characterized by the determination of immobilization efficiency, which ranged from 68 to > 95%, and measurement of apparent kinetic parameters toward a synthetic peptide-like substrate. Batch digestions of whole denaturated human normal adult hemoglobin (HbA) were performed to obtain peptide maps by capillary zone electrophoresis (CZE). Migration time reproducibility of the CZE maps was excellent, with a mean relative standard deviation of 1.5%. Moreover, the two immobilized enzyme preparations showed excellent reproducibility for repeated digestions. Matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry was also used for peptide mass mapping of denaturated HbA digested using the two immobilized trypsin preparations. Even though the two immobilized trypsin preparations do not behave identically, similar sequence coverages of 57% and 61% (for the two HbA chains merged) were achieved for the support-based and cross-linked trypsin preparations, respectively.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".