Loading Fluorescent Ca<sup>2+</sup> Indicators into Living Cells
Bibliographic record
Abstract
Small-molecule fluorescent Ca(2+) reporters are the most widely used tools in the field of Ca(2+) signaling. The excellent spatial and temporal resolution afforded by fluorescent reporters has driven the understanding of Ca(2+) as a messenger in many different cell types. In many situations, the cellular loading and monitoring of fluorescent Ca(2+) indicators is quite trivial. However, there are numerous pitfalls that require consideration to ensure that optimal data are recorded. Fluorescent Ca(2+) indicators have carboxylic acid groups for binding of Ca(2+). Because these "free-acid" forms of the indicators are hydrophilic they cannot readily cross cell membranes and need to be introduced into cells using techniques such as microinjection, pinocytosis, or diffusion from a patch pipette. However, the most convenient and widely used method for loading indicators into cells is as hydrophobic compounds in which the carboxylic acid groups are esterified (commonly as acetoxymethyl [AM] or acetate esters). The ester versions of the indicators permeate the plasma membrane. The Ca(2+)-sensitive, free-acid form of the indicator is liberated following hydrolysis of the ester groups by intracellular esterases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".