Microfluidic Selection and Retention of a Single Cardiac Myocyte, On-Chip Dye Loading, Cell Contraction by Chemical Stimulation, and Quantitative Fluorescent Analysis of Intracellular Calcium
Bibliographic record
Abstract
A microfluidic method to study the contraction of a single cardiac myocyte (heart muscle cell) has been developed. This method integrates various single-cell operations as well as on-chip dye loading, and quantitative analysis of intracellular calcium concentration, [Ca2+]i. After the channel enlargement by on-chip etching to accommodate large-sized cardiac myocytes, a single cell is selected and retained at a V-shaped cell retention structure within the microchip. Owing to the fragile property of the cardiac myocytes that could easily be damaged by centrifugation, the calcium-sensitive fluorescent dye was loaded in the cell by on-chip dye loading. This on-chip method minimized the damage to the cells from the use of a centrifuge in the conventional method and provided a way of cellular analysis of fragile cells. Subsequently, quantitative analysis of [Ca2+]i of a single cardiac myocyte by fluorescence measurement was achieved for the first time in a microfluidic chip, thanks to the intracellular calcium stimulant of ionomycin. The resting [Ca2+]i of the cardiomyocyte determined was consistent with the literature value. From the spontaneous contraction study, it was found that fluorescence intensity cannot represent the [Ca2+]i variation accurately, which implied the importance of the quantitative analysis of [Ca2+]i.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".