India Ink staining after sodium dodecyl sulfate polyacrylamide gel electrophoresis and in conjunction with Western blots for peptide mapping by matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry
Bibliographic record
Abstract
We present an approach that allows matrix-assisted laser desorption/ionization time-of-flight mass spectrometric (MALDI-TOFMS) peptide mapping of proteins separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and electroblotted onto nitrocellulose (NC). After blocking the nitrocellulose membrane with polyvinylpyrrolidone-40 the immobilized proteins are visualized using India Ink staining which allows the detection of low nanogram amounts of protein. The utilization of a low concentration of Tween 20 (0.05%) in the India Ink staining solution does not negatively impair the quality of the mass spectra. Due to the virtual nondestructive nature of the stain proteolytic peptides could be recovered from the NC membrane. Taking into account minor precautions during the sample manipulation and concentration and by loading the sample onto a pre-crystallized matrix layer, high quality mass spectral data were obtained on <100 femtomoles of protein loaded onto the gel. Finally, the use of India Ink in conjunction with Western blot analysis is also demonstrated. A rat plasma protein, characterized by Western blot as a covalently modified protein-drug compound, was subjected to peptide mapping and post source decay (PSD) sequencing of peptides. The zomepirac-modified protein was identified as the alpha-subunit of fibrinogen.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".