Activity of Inwardly Rectifying K <sup>+</sup> Channels in Cerebral Arteries is Diminished in Dyslipidemia Without Overt Effects on Cerebral Blood Flow
Bibliographic record
Abstract
Endothelial dysfunction associated with dyslipidemia is a major contributor to cardiovascular disease. Dilatory function of resistance arteries is diminished in dyslipidemia through altered activity of ion channels that set membrane potential. We examined whether inwardly rectifying K + (K IR ) channels are targeted early in dyslipidemia and if alterations impact cerebral blood flow control. Experiments began at the cellular level (patch‐clamp electrophysiology) and then were extended to isolated arteries (pressure myography) and whole animals (arterial spin‐labelling magnetic resonance imaging). Initial lipid analysis confirmed the dyslipidemic state of LDLR ‐/‐ (normal chow) and C57BL/6 mice fed a high‐cholesterol high‐fat (HFHC) diet for 8 weeks; note aortic plaque formation was absent in these animal models. Patch‐clamp electrophysiology revealed a marked reduction in endothelial but not smooth muscle K IR activity in both dyslipidemic models. Flow activation of K IR was also reduced in endothelial cells from LDLR ‐/‐ and HFHC mice. However, endothelial K IR activity was recovered in dyslipidemic mice by depleting the plasma membrane of cholesterol. Consistent with these cellular changes, we observed diminished shear‐induced vasodilation in cerebral arteries isolated from dyslipidemic animals. However, these cellular and tissue level changes did not alter cerebral blood flow at baseline or in response to a blood pressure challenge (phenylephrine injection through a peritoneal catheter, 0.816 mg/kg). The maintenance of blood flow control was observed across a full range of structures including the cortex, cerebral nuclei, hippocampus, thalamus, hypothalamus and midbrain. Our findings highlight that while K IR channel function is targeted early on in dyslipidemia, compensatory mechanisms can maintain brain blood flow to preserve neurological function.
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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) | 0.003 | 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".