Voltage-clamp Fluorometry in <em>Xenopus</em> Oocytes Using Fluorescent Unnatural Amino Acids
Bibliographic record
Abstract
Voltage-Clamp Fluorometry (VCF) has been the technique of choice to investigate the structure and function of electrogenic membrane proteins where real-time measurements of fluorescence and currents simultaneously report on local rearrangements and global function, respectively1. While high-resolution structural techniques such as cryo-electron microscopy or X-ray crystallography provide static images of the proteins of interest, VCF provides dynamic structural data that allows us to link the structural rearrangements (fluorescence) to dynamic functional data (electrophysiology). Until recently, the thiol-reactive chemistry used for site-directed fluorescent labeling of the proteins restricted the scope of the approach because all accessible cysteines, including endogenous ones, will be labeled. It was thus required to construct proteins free of endogenous cysteines. Labeling was also restricted to sites accessible from the extracellular side. This changed with the use of Fluorescent Unnatural Amino Acids (fUAA) to specifically incorporate a small fluorescent probe in response to stop codon suppression using an orthogonal tRNA and tRNA synthetase pair2. The VCF improvement only requires a two-step injection procedure of DNA injection (tRNA/synthetase pair) followed by RNA/fUAA co-injection. Now, labelling both intracellular and buried sites is possible, and the use of VCF has expanded significantly. The VCF technique thereby becomes attractive for studying a wide range of proteins and – more importantly – allows investigating numerous cytosolic regulatory mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".