Biophysical characterization of light-gated ion channels using planar automated patch clamp
Bibliographic record
Abstract
Channelrhodopsins (ChRs) are proteins that guide phototaxis in protists and exhibit light-gated channel conductance when their genes are heterologously expressed in mammalian cells. ChRs are widely used as molecular tools to control neurons and cardiomyocytes with light (optogenetics). Cation- and anion-selective ChRs (CCRs and ACRs, respectively) enable stimulation and inhibition of neuronal activity by depolarization and hyperpolarization of the membrane, respectively. More than 400 natural ChR variants have been identified so far, and high-throughput polynucleotide sequencing projects add many more each year. However, electrophysiological characterization of new ChRs lags behind because it is mostly done by time-consuming manual patch clamp (MPC). Here we report using a high-throughput automated patch clamp (APC) platform, SyncroPatch 384i from Nanion Technologies, for ChR research. We find that this instrument can be used for determination of the light intensity dependence and current-voltage relationships in ChRs and discuss its advantages and limitations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".