Measuring Reaction Rate Constant in Individual Cells to Facilitate Accurate Analysis of Cell-Population Heterogeneity
Bibliographic record
Abstract
We propose Cytometry of Reaction Rate Constant (CRRC) for accurate analysis of cell-population heterogeneity with respect to a specific molecular reaction. Conceptually, in CRRC, the cells are loaded with a reaction substrate, and its conversion into a product is followed by time-lapse fluorescence microscopy at the single-cell level. A reaction rate constant is determined for every cell by using a known kinetic mechanism of the reaction, and a kinetic histogram “number of cells vs. the rate constant” is built. Finally, this histogram is used to determine parameters of reaction-based cell-population heterogeneity. Here, we studied a reaction of substrate extrusion from cells by ABC transporters. We proved that sizes of subpopulations with different extrusion rates could be accurately determined from the kinetic histogram, and this determination was not significantly affected by change in substrate concentration. We foresee that CRRC will facilitate the development of reliable disease biomarkers based on parameters of reaction-based cell-population heterogeneity.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".