The differential polarizability of CHO cells can be used to monitor changes in metabolism
Bibliographic record
Abstract
Background A healthy cell has a well-balanced ionic content. Changes in the ionic content, flux, membrane and mitochondrial capacitance within the cells have been correlated to physiological and metabolic changes linked to early stages of apoptosis [1]. The ionic content and structure of individual cells allow them to be polarized in an applied electrical field with an alternating current in the radiofrequency range [2]. Any changes in the ionic content will then lead to changes in the response of the cells to the applied electric field. Hence, methods based on dielectric measurements are particularly promising for identifying early emerging subpopulations of apoptotic cells. We have developed a prototype cytometer, which measures the dielectrophoretic properties of individual cells. This tracks the trajectory of individual cells as they pass through a bank of electrodes designed to differentially perturb the cells according to their polarizability. Cells are analyzed in the instrument (DEP cytometer) by their displacement in an electrical field with sensitivity of 0.1 μm and at a rate of 5 cells per second [3]. Bulk average capacitance measurements of a bioreactor cell population have been made possible by commercially available sterilizable probes. However, the analysis of single cells allows a unique insight into the metabolism and energy flow within cells. By using single cell analysis discoveries can be made that might otherwise be masked by the overall response of a cell population.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".