Cell Staining: Fluorescent Labelling of the Golgi Apparatus
Bibliographic record
Abstract
Abstract Immunofluorescence has been the primary method for labelling the Golgi apparatus for light microscopic observation in fixed cells. The Golgi apparatus was initially labelled in living cells using the fluorescent ceramide analogue N ‐6[7‐nitro‐2,1,3‐benzoxadiazol‐4‐yl] aminocaproyl sphingosine or by microinjection of fluorescently conjugated antibodies to exposed Golgi epitopes. With the common availability of the green fluorescent protein (GFP) and advanced fluorescence microscopes including confocal microscopes, imaging of the Golgi apparatus in living cells is now a major experimental approach. Time‐lapse imaging of living cells has also been combined with photobleach techniques in order to study the dynamics of transient protein association with the Golgi apparatus. Similar live‐cell imaging approaches have been used to study the dynamics of the cargo transport through the exocytic pathway. Recent advances in microscopy have allowed bypassing the diffraction limit which has traditionally limited image resolution. These new methods may be applied to fluorescence imaging of the Golgi apparatus, although they are not easily applied to living cells at present. Key Concepts Immunofluorescence can be used to visualise proteins in the Golgi apparatus or its subdomains. Live‐cell visualisation of the Golgi apparatus is possible with GFP‐tagged proteins. Fluorescence images can be quantitated in a rigorous way. Photobleaching and photoactivation techniques permit visualisation of protein dynamics and flux through the Golgi apparatus in living cells. Super‐resolution imaging promises a new generation of imaging approaches to the Golgi apparatus.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".