Inhibitors of gap junctions attenuate myogenic tone in cerebral arteries
Bibliographic record
Abstract
The effects of two structurally distinct inhibitors of gap junction communication were studied by using three different forms of vasoconstriction in pressurized rat middle cerebral arteries. The sensitivity of myogenic tone (at 60 mmHg), vasopressin-induced tone (10 nM, at 20 mmHg), and depolarizing solution-induced tone (80 mM K(+), at 20 mmHg) to inhibition by heptanol (1.0 microM to 3.0 mM) or 18alpha-glycyrrhetinic acid (18alpha-GA, 1.0 to 50 microM) were determined. Pressure-induced myogenic tone was inhibited by heptanol (IC(50) = 0.75 +/- 0.09 mM) and 18alpha-GA ( approximately 30 microM). Vasopressin-induced vasoconstriction was also inhibited by heptanol (IC(50) = 0.4 +/- 0.3 mM) and 18alpha-GA (>1 microM). Depolarizing solution-induced vasoconstriction was less sensitive to inhibition by heptanol compared to vasopressin (P < 0.01) or pressure-induced constriction (P < 0.05). However, 18alpha-GA did not inhibit depolarization-induced constriction. Sharp microelectrode experiments on isolated arteries revealed stable membrane potentials, with no detectable effect of heptanol (1 mM) or 18alpha-GA (20-30 microM) on the average membrane potential at 20 mmHg. However, approximately 20% of impaled cells (5 of 28) exhibited uncharacteristic oscillations in membrane potential after pharmacological uncoupling. At 60 mmHg a approximately 7- to 9-mV hyperpolarization and corresponding vasodilation (approximately 50%) was observed, and the frequency of membrane potential oscillations doubled (9 of 23 cells). These data indicate that gap junctions play an important role in the maintenance and modulation of membrane potential and tone in cerebral resistance arteries.
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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 | 0.001 |
| 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".