Genetically encoded ratiometric indicators for potassium ion
Bibliographic record
Abstract
Abstract Potassium ion (K + ) homeostasis and dynamics play critical roles in regulating various biological activities, and the ability to monitor K + spatial-temporal dynamics is critical to understanding these biological functions. Here we report the design and characterization of a Förster resonance energy transfer (FRET)-based genetically encoded K + indicator, KIRIN1, constructed by inserting a bacterial cytosolic K + binding protein (Kbp) between a fluorescent protein (FP) FRET pair, mCerulean3 and cp173Venus. Binding of K + induces a conformational change in Kbp, resulting in an increase in FRET efficiency. KIRIN1 was able to detect K + at physiologically relevant concentrations in vitro and is highly selective toward K + over Na + . We further demonstrated that KIRIN1 allowed real-time imaging of pharmacologically induced depletion of cytosolic K + in live cells, and KIRIN1 also enabled optical tracing of K + efflux and reuptake in neurons upon glutamate stimulation in cultured primary neurons. These results demonstrate that KIRIN1 is a valuable tool to detect K + in vitro and in live cells.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".