A general method for the rapid characterization of tyrosine-phosphorylated proteins by mini two-dimensional gel electrophoresis
Bibliographic record
Abstract
Our preliminary results are reported in the investigation of the tyrosine phosphorylation cascade triggered by the stimulation of the insulin receptor in the adipocyte cell line 3T3-L1 using a mini two-dimensional gel electrophoresis approach. The minigel format, 8 x 10 cm, was found sufficiently resolving and reproducible to study complex biological samples while considerably increasing throughput and lowering costs compared to larger gel formats. Consequently, we used the minigel format to rapidly screen a large number of samples, of which only the most relevant were then analyzed by optimized, preparative two-dimensional gels. The accurate localization and relative quantification of tyrosine-phosphorylated proteins was performed using a nonradioactive triple labeling method. After transfer onto polyvinylidene difluoride (PVDF) membranes, proteins were stained with Sypro Ruby to verify the separation quality and to localize the general region of interest for immunostaining. The membranes were subsequently blocked with polyvinylpyrrolidone-40 and probed with the relevant antibodies for visualization of the phosphorylated proteins by chemiluminescence. Finally, membranes were stained with colloidal gold to obtain a pattern reminiscent of the silver staining of a polyacrylamide gel. We believe that the presented strategy can be generalized for any gel application in which a protein has to be detected and identified based on its immunoreactivity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.010 |
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".