Strategies for the real-time detection of Ca<sup>2+</sup>channel events of single cells: recent advances and new possibilities
Bibliographic record
Abstract
Ca(2+) ion channels play key roles in cell physiology and they are important drug targets. The Ca(2+) channel events are mainly measurable by fluorescent and patch clamp methods. This review summarizes the recent advances of these techniques for the detection of Ca(2+) channel events and the prospect of their new directions in the near future. Conventional bulk fluorescent methods are amenable to high-throughput applications, but they are not real-time single-cell measurements, which provide kinetic data on individual cells and offer unparalleled sensitive data for rare cells. Recent advances on real-time single-cell fluorescent measurements are conducted on microfluidic chips with scalable cell-retention sites, integrated with electrical stimulation and fluorescent measuring features. Patch clamp techniques are real-time measurements conducted on single cells, but the measurements are of low throughput. Recent advances are conducted on microfluidic patch clamp chips for high-throughput applications. Future real-time single-cell Ca(2+) channel event measurements will be conducted in a multiparametric manner in an integrated and automated microfluidic chip.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".