A genetically encoded Ca2+ indicator based on circularly permutated sea anemone red fluorescent protein eqFP578
Bibliographic record
Abstract
BACKGROUND: dynamics and neuronal activities in vitro and in vivo. Red fluorescent protein (RFP)-based GECIs have inherent advantages relative to green fluorescent protein-based GECIs due to the longer wavelength light used for excitation. Longer wavelength light is associated with decreased phototoxicity and deeper penetration through tissue. Red GECI can also enable multicolor visualization with blue- or cyan-excitable fluorophores. RESULTS: Here we report the development, structure, and validation of a new RFP-based GECI, K-GECO1, based on a circularly permutated RFP derived from the sea anemone Entacmaea quadricolor. We have characterized the performance of K-GECO1 in cultured HeLa cells, dissociated neurons, stem-cell-derived cardiomyocytes, organotypic brain slices, zebrafish spinal cord in vivo, and mouse brain in vivo. CONCLUSION: K-GECO1 is the archetype of a new lineage of GECIs based on the RFP eqFP578 scaffold. It offers high sensitivity and fast kinetics, similar or better than those of current state-of-the-art indicators, with diminished lysosomal accumulation and minimal blue-light photoactivation. Further refinements of the K-GECO1 lineage could lead to further improved variants with overall performance that exceeds that of the most highly optimized red GECIs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".