From cells to organism: Impact of dyslipidemia on inwardly rectifying K <sup>+</sup> channels and cerebral vascular function
Bibliographic record
Abstract
Evidence increasingly suggests that dyslipidemia diminishes dilatory function of resistance arteries by altering ion channel activity. Focusing on the cerebral vasculature, this study investigated whether inwardly rectifying K + 2.1 (K IR 2.1) channels are targeted early in dyslipidemia. Experiments began at the cellular level (patch-clamp electrophysiology), then progressed to isolated arteries (pressure myography) and whole animals (arterial spin-labeling magnetic resonance imaging). Lipid analysis confirmed dyslipidemia in Ldlr −/− (normal chow) and C57BL/6 mice fed a high-fat high-cholesterol (HFHC) diet for 8 weeks; no aortic plaques were observed. Patch-clamp electrophysiology revealed a marked reduction in endothelial but not smooth muscle K IR activity in both dyslipidemic models; this K IR activity was recoverable by plasma membrane cholesterol depletion. These cellular changes notably diminished flow-induced vasodilation in cerebral arteries isolated from both dyslipidemic models; such deficits were observed in endothelial Kir2.1 −/− arteries. A blood pressure challenge induced a perfusion phenotype in HFHC-C57BL/6 but not genetic deletion ( Ldlr −/− ) mice, consistent with reduced K IR activity and flow-mediated dilation. Our findings highlight that endothelial K IR 2.1 channels are targeted early in dyslipidemia, which was associated with attenuated flow-mediated dilation in our acute HFHC model. This change likely moderates the range of blood flow control and substrate delivery to active brain tissue.
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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 | 0.001 | 0.001 |
| 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".