Hypoxic fetoplacental vasoconstriction in humans is mediated by potassium channel inhibition
Bibliographic record
Abstract
Fetal to maternal blood flow matching in the placenta, necessary for optimal fetal blood oxygenation, may occur via hypoxic fetoplacental vasoconstriction (HFPV). We hypothesized that HFPV is mediated by K(+) channel inhibition in fetoplacental vascular smooth muscle, as occurs in several other O(2)-sensitive tissues. With the use of an isolated human placental cotyledon perfused at a constant flow rate, we found that hypoxia reversibly increased perfusion pressure by >20%. HFPV was unaffected by cyclooxygenase or nitric oxide synthase inhibition. HFPV and 4-aminopyridine, an inhibitor of voltage-dependent K(+) (K(v)) channels, increased pressure in a nonadditive manner, suggesting they act via a common mechanism. Iberiotoxin, a large conductance Ca(2+)-sensitive K(+) (BK(Ca)) channel inhibitor, had little effect on normoxic pressure. Immunoblotting and RT-PCR showed expression of several putative O(2)-sensitive K(+) channels in peripheral fetoplacental vessels. In patch-clamp experiments with smooth muscle cells isolated from peripheral fetoplacental arteries, hypoxia reversibly inhibited K(v) but not BK(Ca) or ATP-dependent currents. We conclude that human fetoplacental vessels constrict in response to hypoxia. This response is largely mediated by hypoxic inhibition of K(v) channels in the smooth muscle of small fetoplacental 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 | 0.000 |
| 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".