On-Membrane Digestion Technology for Muscle Proteomics
Why this work is in the frame
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Bibliographic record
Abstract
High-resolution two-dimensional gel electrophoresis and in-gel digestion are routinely used for large-scale protein separation and peptide generation in mass spectrometry-based proteomics, respectively. However, the combination of isoelectric focusing in the first dimension and polyacrylamide slab gel electrophoresis in the second dimension is not suitable for the proper separation of integral proteins and high-molecular-mass proteins. In addition, in-gel trypsination may not result in a high degree of efficient digestion levels for the production of large numbers of peptides in the case of certain protein species. The application of gradient one-dimensional gel electrophoresis and on-membrane digestion can overcome these technical problems and be extremely helpful for the comprehensive identification of proteins that are underrepresented in routine two-dimensional gel electrophoretic approaches. This review critically examines the general application of on-membrane digestion techniques in proteomics and its recent application for the identification of very large integral membrane proteins from skeletal muscle by mass spectrometry. This includes the discussion of proteomic studies that have focused on the proteomic characterization of the membrane cytoskeletal protein dystrophin from sarcolemma vesicles and the ryanodine receptor calcium release channel of the sarcoplasmic reticulum from skeletal muscle.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it