Stoichiometry of molecular complexes at adhesions in living cells
Bibliographic record
Abstract
We describe a method to detect molecular complexes and measure their stoichiometry in living cells from simultaneous fluctuations of the fluorescence intensity in two image channels, each detecting a different kind of protein. The number and brightness (N&B) analysis, namely, the use of the ratio between the variance and the average intensity to obtain the brightness of molecules, is extended to the cross-variance of the intensity fluctuations in two channels. We apply the cross-variance method to determine the stoichiometry of complexes containing paxillin and vinculin or focal adhesion kinase (FAK) in disassembling adhesions in mouse embryo fibroblasts expressing FAK, vinculin, and paxillin-tagged with EGFP and mCherry. We found no complexes of these proteins in the cytoplasm away from the adhesions. However, at the adhesions, large aggregates leave, forming a hole, during their disassembly. This hole shows cross-correlation between FAK and paxillin and vinculin and paxillin. From the amplitude of the correlated fluctuations we determine the composition of the aggregates leaving the adhesions. These aggregates disassemble rapidly in the cytoplasm because large complexes are found only in very close proximity to the adhesions or at their borders.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".