A Differential Cytolocalization Assay for Analysis of Macromolecular Assemblies in the Eukaryotic Cytoplasm
Bibliographic record
Abstract
We have developed a differential cytolocalization assay (DCLA) that allows the observation of cytoplasmic protein/protein interactions in vivo. In the DCLA, interactions are visualized as a relocalization of a green fluorescent protein-tagged "prey" by a membrane-bound "bait." This assay was tested and utilized in Caenorhabditis elegans to probe interactions among proteins involved in RNA interference (RNAi) and nonsense-mediated decay (NMD) pathways. Several previously documented interactions were confirmed with DCLA, whereas uniformly negative results were obtained in several controls in which no interaction was expected. Novel interactions were also observed, including the association of SMG-5, a protein required for NMD, to several components of the RNAi pathway. The DCLA can be readily carried out under diverse conditions, allowing a dynamic assessment of protein interactions in vivo. We used this property to test a subset of the RNAi and NMD interactions in animals in which proteins central to each mechanism were mutated; several key associations in each machinery that can occur in vivo in the absence of a functional process were identified.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".