Potentiometric platform for the quantification of cellular potassium efflux
Bibliographic record
Abstract
Renewed interest in the measurement of cellular K(+) effluxes has been prompted by the observation that potassium plays an active and important role in numerous key cellular events, in particular cell necrosis and apoptosis. Although necrosis and apoptosis follow different pathways, both induce intracellular potassium effluxes. Here, we report the use of potassium-selective microelectrodes located in a microfluidic platform for cell culture to monitor and quantify such effluxes in real time. Using this platform, we observed and measured the early signs of cell lysis induced by a modification of the extracellular osmolarity. Furthermore, we were able to quantify the number of dying cells by evaluating the extracellular potassium concentration. A comparison between the potentiometric measurement with a fluorescent live-dead assay performed under similar conditions revealed the delay between potassium effluxes and cell necrosis. These results suggest that such platforms may be exploited for applications, such as cytotoxicological screening assays or tumor cell proliferation assays, by using extracellular K(+) as cell death marker.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".