Development and Application of a Quantitative Multiplexed Small GTPase Activity Assay Using Targeted Proteomics
Bibliographic record
Abstract
Small GTPases are a family of key signaling molecules that are ubiquitously expressed in various types of cells. Their activity is often analyzed by western blot, which is limited by its multiplexing capability, the quality of isoform-specific antibodies, and the accuracy of quantification. To overcome these issues, a quantitative multiplexed small GTPase activity assay has been developed. Using four different binding domains, this assay allows the binding of up to 12 active small GTPase isoforms simultaneously in a single experiment. To accurately quantify the closely related small GTPase isoforms, a targeted proteomic approach, i.e., selected/multiple reaction monitoring, was developed, and its functionality and reproducibility were validated. This assay was successfully applied to human platelets and revealed time-resolved coactivation of multiple small GTPase isoforms in response to agonists and differential activation of these isoforms in response to inhibitor treatment. This widely applicable approach can be used for signaling pathway studies and inhibitor screening in many cellular systems.
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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 | 0.003 | 0.002 |
| 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) | 0.001 | 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".