Confocal Microscopy-based Linescan Methodologies for Intra-Golgi Localization of Proteins
Bibliographic record
Abstract
Localization of resident Golgi proteins to earlier (cis) or later (trans) Golgi compartments has traditionally required quantitative immunocytochemistry and electron microscopy, which are inaccessible to many researchers. For this reason, light microscopy has often been used, initially for localization of Golgi glycotransferases and, more recently, for other Golgi proteins (e.g., Arf1, GBF1, Rab6). Quantitation of light microscopic intra-Golgi localization can be problematic. We describe here a novel quantitative light microscopic methodology using linescans crossing the Golgi ribbon. Our method determines a localization for the unknown protein in a one-dimensional coordinate system in which 0.0 corresponds to localization of a cis marker and 1.0 to localization of a trans marker. We also describe a variant of this methodology in which Golgi morphology is simplified by nocodazole-induced dispersal into ministacks, allowing a fully automated analysis. In our assay, beta1,4-galactosyltransferase-YFP and Golgin97 localize similarly to trans markers, whereas p115, GBF1, and p58-YFP are similarly near other cis markers. The medial Golgi protein alpha1,3-1,6-mannosidase II gives an intermediate localization in this assay. These methodologies may prove useful in instances where electron microscopy is technically difficult as well as when rapid analysis of large numbers of samples is required.
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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 | 0.001 | 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".