Inward Rectifier Potassium Channels: Membrane Lipid-Dependent Mechanosensitive Gates in Brain Vascular Cells
Bibliographic record
Abstract
Cerebral arteries contain two primary and interacting cell types, smooth muscle (SMCs) and endothelial cells (ECs), which are each capable of sensing particular hemodynamic forces to set basal tone and brain perfusion. These biomechanical stimuli help confer tone within arterial networks upon which local neurovascular stimuli function. Tone development is intimately tied to arterial membrane potential (V M ) and changes in intracellular [Ca 2+ ] driven by voltage-gated Ca 2+ channels (VGCCs). Arterial V M is in turn set by the dynamic interplay among ion channel species, the strongly inward rectifying K + (Kir) channel being of special interest. Kir2 channels possess a unique biophysical signature in that they strongly rectify, display negative slope conductance, respond to elevated extracellular K + and are blocked by micromolar Ba 2+ . While functional Kir2 channels are expressed in both smooth muscle and endothelium, they lack classic regulatory control, thus are often viewed as a simple background conductance. Recent literature has provided new insight, with two membrane lipids, phosphatidylinositol 4,5-bisphosphate (PIP 2 ) and cholesterol, noted to (1) stabilize Kir2 channels in a preferred open or closed state, respectively, and (2) confer, in association with the cytoskeleton, caveolin-1 (Cav1) and syntrophin, hemodynamic sensitivity. It is these aspects of vascular Kir2 channels that will be the primary focus of this review.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".