K<sup>+</sup> currents regulate the resting membrane potential, proliferation, and contractile responses in ventricular fibroblasts and myofibroblasts
Bibliographic record
Abstract
Despite the important roles played by ventricular fibroblasts and myofibroblasts in the formation and maintenance of the extracellular matrix, neither the ionic basis for membrane potential nor the effect of modulating membrane potential on function has been analyzed in detail. In this study, whole cell patch-clamp experiments were done using ventricular fibroblasts and myofibroblasts. Time- and voltage-dependent outward K(+) currents were recorded at depolarized potentials, and an inwardly rectifying K(+) (Kir) current was recorded near the resting membrane potential (RMP) and at more hyperpolarized potentials. The apparent reversal potential of Kir currents shifted to more positive potentials as the external K(+) concentration ([K(+)](o)) was raised, and this Kir current was blocked by 100-300 muM Ba(2+). RT-PCR measurements showed that mRNA for Kir2.1 was expressed. Accordingly, we conclude that Kir current is a primary determinant of RMP in both fibroblasts and myofibroblasts. Changes in [K(+)](o) influenced fibroblast membrane potential as well as proliferation and contractile functions. Recordings made with a voltage-sensitive dye, DiBAC(3)(4), showed that 1.5 mM [K(+)](o) resulted in a hyperpolarization, whereas 20 mM [K(+)](o) produced a depolarization. Low [K(+)](o) (1.5 mM) enhanced myofibroblast number relative to control (5.4 mM [K(+)](o)). In contrast, 20 mM [K(+)](o) resulted in a significant reduction in myofibroblast number. In separate assays, 20 mM [K(+)](o) significantly enhanced contraction of collagen I gels seeded with myofibroblasts compared with control mechanical activity in 5.4 mM [K(+)](o). In combination, these results show that ventricular fibroblasts and myofibroblasts express a variety of K(+) channel alpha-subunits and demonstrate that Kir current can modulate RMP and alter essential physiological 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".