Modulation of the ERG K+ Current by the Tyrosine Phosphatase, SHP-1
Bibliographic record
Abstract
We reported previously (Cayabyab, F. S., and Schlichter, L. C. (2002) J. Biol. Chem. 277, 13673-13681) a functional interaction between the ERG-1 K(+) channel and Src tyrosine kinase, which increased the current. We now show that the tyrosine phosphatase, SHP-1, which is present in microglia, is increased after brain damage, and is activated by colony-stimulating factor-1, associates with ERG-1 and regulates the current. Patch clamp recordings from the MLS-9 microglia cells were made with pipette solutions containing a recombinant SHP-1 protein: wild type (SHP-1 wild type (wt)), catalytically active (SHP-1 S6), or the substrate-trapping mutant (SHP-1 Cys --> Ser). SHP-1 wt and SHP-1 S6 proteins decreased the current, an effect that was reversed by the phosphatase inhibitor, pervanadate, whereas SHP-1 Cys --> Ser increased the current. Moreover, transient transfection with cDNA for SHP-1 wt or SHP-1 S6 decreased the ERG current without decreasing the protein level. Tyrosine phosphorylation of ERG-1 was decreased by transfection with SHP-1 wt and increased by SHP-1 Cys --> Ser. The decrease in current by active SHP-1 was partly attributed to changes in the voltage dependence of activation and steady-state conductance, whereas inactivation kinetics and voltage dependence were not affected. Our results show that ERG-1 is a SHP-1 substrate constituting the first report that an ion current is regulated by SHP-1.
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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".