Förster Resonance Energy Transfer-Based Biosensors for Multiparameter Ratiometric Imaging of Ca<sup>2+</sup> Dynamics and Caspase-3 Activity in Single Cells
Bibliographic record
Abstract
As one of the principal cytoplasmic second messengers, the calcium ion (Ca(2+)) is central to a variety of intracellular signal transduction pathways. Accordingly, there is a sustained interest in methods for spatially- and temporally resolved imaging of the concentration of Ca(2+) in live cells using noninvasive methods such as genetically encoded biosensors based on Förster resonance energy transfer (FRET) between fluorescent proteins (FPs). In recent years, protein-engineering efforts have provided the research community with FRET-based Ca(2+) biosensors that are dramatically improved in terms of enhanced emission ratio change and optimized Ca(2+) affinity for various applications. We now report the development and systematic optimization of a pair of spectrally distinct FRET-based biosensors that enable the simultaneous imaging of Ca(2+) in two compartments of a single cell without substantial spectral crosstalk between emission channels. Furthermore, we demonstrate that these new biosensors can be used in conjunction with previously reported caspase-3 substrates based on the same set of FRET pairs.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".