Formation of a border ischemic zone depends on plasma potassium concentration
Bibliographic record
Abstract
Extracellular potassium concentration might modify electrophysiological properties in the border zone of ischemic myocardium. We evaluated the depolarization and repolarization characteristics across the ischemic–normal border under [K+] variation. Sixty-four-lead epicardial mapping was performed in 26 rats ([K+] 2.3–6.4 mM) in a model of acute ischemia/reperfusion. The animals with [K+] < 4.7 mM (low–normal potassium) had an ischemic zone with ST-segment elevation and activation delay, a border zone with ST-segment elevation and no activation delay, and a normal zone without electrophysiological abnormalities. The animals with [K+] >4.7 mM (normal-high potassium) had only the ischemic and normal zones and no transitional area. Activation–repolarization intervals and local conduction velocities were inversely associated with [K+] in linear regression analysis with adjustment for the zone of myocardium. The reperfusion extrasystolic burden (ESB) was greater in the low–normal as compared to normal-high potassium animals. Ventricular tachycardia/fibrillation incidence did not differ between the groups. In patch-clamp experiments, hypoxia shortened action potential duration at 5.4 mM but not at 1.3 mM of [K+]. IK(ATP) current was lower at 1.3 mM than at 5.4 mM of [K+]. We conclude that the border zone formation in low–normal [K+] was associated with attenuation of IK(ATP) response to hypoxia and increased reperfusion ESB.
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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".