Rb <sup>+</sup> Efflux Assay for Assessment of Non-Selective Cation Channel Activities
Bibliographic record
Abstract
ABSTRACT Transient receptor potential (TRP) channels have been found to play important roles in cellular physiology and hold promise as therapeutic targets. These channels activate in response to a variety of chemical or physical stimuli and conduct non-selective cation currents (NSCC). Due to their unique activation properties, application of automated electrophysiology to measure the channel activity has been difficult. Using HEK293 cells stably expressing human TRP channels, hTRPC6 and hTRPA1, we developed and validated a high-throughput Rb(+) efflux assay for NSCC channels. The assay was performed in cell-based 96-well format. A significant increase in Rb(+) efflux can be detected upon channel activation by specific agonists, confirming that both TRPC6 and TRPA1 channels are permeable to Rb(+) ions. The agonists induced Rb(+) efflux can be blocked by known channel blockers and selected compounds from our high-throughput screening (HTS) hits. The assay is suitable for HTS with Z' factors of 0.53 and above. We also tested the Ca(2+) effect on channel activities in this assay. Both TRPC6 and TRPA1 channels were found to be inhibited by increasing the concentration of Ca(2+) in the assay buffer. However, Ca(2+) significantly reduced the potency of allyl isothiocyanate (AITC) on TRPA1 but did not affect the potency of carbochol on TRPC6. Using this assay for secondary confirmation screen, we successfully identified and confirmed the positive hits as TRPC6 inhibitors.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".