Regulation of an ERG K+ Current by Src Tyrosine Kinase
Bibliographic record
Abstract
The human "ether-a-go-go"-related gene (HERG) K(+) channel, and its homologues are present in heart, neuronal tissue, some cancer cells, and the MLS-9 rat microglia cell line (Zhou, W., Cayabyab, F. S., Pennefather, P. S., Schlichter, L. C., and DeCoursey, T. E. (1998) J. Gen. Physiol. 111, 781-794). Despite its importance, there are few studies of ERG modulation. In this first report of regulation by tyrosine phosphorylation we show that MLS-9 cells express transcripts for r-erg1 (rat homologue of HERG) and r-erg2, and an immunoreactive doublet was identified using an anti-HERG antibody. The constitutive tyrosine phosphorylation of the ERG1 protein, detected by co-immunoprecipitation, was reduced by the protein-tyrosine kinase inhibitors, lavendustin A, herbimycin A, or genistein (but not daidzein). The whole cell ERG current was reduced by protein-tyrosine kinase inhibitors or the Src-selective inhibitory peptide, src40-58, but not by a scrambled peptide. Conversely, the current was increased by the Src-activating peptide, srcpY, but not by an inactive analogue. Activating endogenous Src or transfecting constitutively active v-Src altered the voltage dependence and deactivation kinetics to produce more current at negative potentials. Co-immunoprecipitation identified an association between the channel protein and Src. Thus, r-ERG1 and Src tyrosine kinase appear to exist in a signaling complex that is well positioned to modulate this K(+) channel and affect its contribution to cellular functions.
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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".