Asymmetry between Sister Cells in a Cancer Cell Line Revealed by Chemical Cytometry
Bibliographic record
Abstract
We introduce instrumentation and methodology for two-channel chemical cytometry of sister cells-two cells born from division of the same mother cell. The method is based on capillary electrophoresis with laser-induced fluorescence detection and allows simultaneously probing multiple intracellular components in sister cells. To test the new technology, we compared the expression patterns of green fluorescent protein (GFP) between the sisters in cultured cancer cells stably transfected with a GFP-expressing construct. We found that all sister cells had detectable asymmetry in the GFP expression patterns with a confidence level of higher than 95%. To our best knowledge, this is the first reported observation of asymmetric patterns of protein expression in sister cells in a cancer cell line. The proposed technology can reliably detect minor differences in chemical contents between sister cells, which makes it a potentially indispensable tool in studying the molecular mechanisms of developmental processes. It will be especially valuable in quantitative studies of cells with complex proliferation kinetics (e.g., stem 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 | 0.001 |
| 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 | 0.001 | 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".