Different methods of membrane domains isolation result in similar 2-D distribution patterns of membrane domain proteins
Bibliographic record
Abstract
Membrane domains are highly specialized parts of the cell plasma membrane, carrying on and augmenting the incoming signals. To study their structural and functional properties, it is crucial to find the least damaging mode of their isolation. Using two different cell lines, epithelial HEK cells (clone E2M11) and S49 lymphoma cells, three methods of membrane domain isolation (i.e., detergent extraction, alkaline treatment, and "drastic" homogenization) were tested for similarity and reproducibility by 2-D electrophoresis. Our data show that the protein composition of membrane domains obtained by different isolation methods is similar and that approximately 60% of the spots are present in all membrane domain preparations. Furthermore, the same degree of similarity of 2-D profiles of the most intensively silver stained spots found in membrane domains of the two cell lines derived from different tissues suggests that the composition of a large part of membrane domains proteins is conservative. We suggest that these proteins may either be involved in the organization of membrane domain structure or represent the conservative component of signal transduction machinery.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".