A Review of the Potential and Versatility of Colloidal Gold Cytochemical Labeling for Molecular Morphology
Bibliographic record
Abstract
In the present article we review several postembedding cytochemical techniques using the colloidal gold marker. Owing to the high atomic number of gold, the colloidal gold particles are electron dense. They are spherical in shape and can be prepared in sizes from 1 to 25 nm, which renders this marker among the best for electron microscopy. In addition, because it can be bound to several molecules, this marker has the advantage of being extremely versatile. Combined to immunoglobulins or immunoglobulin-binding proteins (protein A), it has been applied successfully in immunocytochemistry. Colloidal gold particles 5-15 nm in size are excellent for postembedding cytochemistry. Particles of smaller size, such as 1 nm, must be silver enhanced to be visualized by transmission electron microscopy. We have elected to review the superiority of indirect immunocytochemical approaches using IgG-gold or protein A-gold (protein G-gold and protein AG-gold). Lectins or enzymes can be tagged with colloidal gold particles, and the corresponding lectin-gold and enzyme-gold techniques have specific advantages and great potential. Using an indirect digoxigenin-tagged nucleotide and an antidigoxigenin probe, colloidal gold technology can also be used for in situ hybridization at the electron microscope level. Affinity characteristics lie behind all cytochemical techniques and several molecules displaying high affinity properties can also be beneficial for colloidal gold electron microscopy cytochemistry. All of these techniques can be combined in various ways to produce multiple labelings of several binding sites on the same tissue section. Colloidal gold is particulate and can easily be counted; thus the cytochemical signal can be evaluated quantitatively, introducing further advantages to the use of the colloidal gold marker. Finally, several combinations and multiple step procedures have been designed to amplify the final signal which renders the techniques more sensitive. The approaches reviewed here have been applied successfully in different fields of cell and molecular biology, cell pathology, plant biology and pathology, microbiology and virology. The potential of the approaches is emphasized in addition to different ways to assess specificity, sensitivity and accuracy of results.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".