Messenger RNA Detection in Leukemia Cell lines by Novel Metal-Tagged in situ Hybridization using Inductively Coupled Plasma Mass Spectrometry.
Bibliographic record
Abstract
Conventional gene expression profiling relies on using fluorescent detection of hybridized probes. Physical characteristics of fluorophores impose limitations on achieving a highly multiplex gene analysis of single cells. Our work demonstrates the feasibility of using metal-tagged in situ hybridization for mRNA detection by inductively coupled plasma mass spectrometry (ICP-MS). ICP-MS as an analytical detector has a number of unique and relevant properties: 1) metals and their stable isotopes generate non-overlapping distinct signals that can be detected simultaneously; 2) these signals can be measured over a wide dynamic range; 3) ICP-MS is quantitative and very sensitive. We used commercial antibodies conjugated to europium (Eu) and gold together with biotinylated oligonucleotide probes reacted with terbium-labeled streptavidin to demonstrate simultaneous mRNA and protein detection by ICP-MS in leukemia cells.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".