Detection of immunolabels with multi‐isotope imaging mass spectrometry
Bibliographic record
Abstract
We have developed a method that combines the use of stable isotopes, multi‐isotope imaging mass spectrometry (MIMS) and antibody. We began with using well‐established antibodies, anti‐actin and anti‐synaptophysin, in mouse intestinal cells. We extended the method to an immunogold assay to specifically localize Ribeye, a major protein component of retina synaptic ribbons, or to localize a synaptic vesicle‐containing protein, synaptophysin. Both are localized in presynaptic nerve terminal of photoreceptors cells in retina. Our results show that by MIMS analysis of the Au signal, we can directly identify antibodies tagged with non amplified 1.4 nm gold nanoparticles. They also demonstrate that the gold nanoparticle‐tagged antibodies do not dilute the 15 N/ 14 N signal used for measuring protein turnover. Thus, we can simultaneously and directly use MIMS to measure protein turnover and to identify cell type or specific protein. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".