Simultaneous Analysis of a Non-Lipidated Protein and Its Lipidated Counterpart: Enabling Quantitative Investigation of Protein Lipidation’s Impact on Cellular Regulation
Bibliographic record
Abstract
Here, we introduce protein-lipidation quantitation (PLQ)-the first method for quantitative analysis of both a substrate and a product of protein lipidation in a biologically relevant context. Such analysis is required to study roles of protein lipidation in cellular regulation. In PLQ, the substrate is fused with a fluorescent protein to facilitate quantitative detection of both the nonlipidated substrate and the lipidated product. When expressed in cells with endogenous lipidation activity, the substrate is intracellularly lipidated. Following cell lysis and sampling crude cell lysate for analysis, the substrate and the product are separated by surfactant-mediated capillary electrophoresis (CE) and quantitated by integrating fluorescence intensity over respective CE peaks. In this work, we prove PLQ in principle and demonstrate its robustness to changes in structures of the substrate and lipid donor. Finally, PLQ analysis confirms a hypothesized link between a mutation in p53 and cellular prenylation activity.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".