Effects of flow and energy metabolism on injury and Rb<sup>+</sup> uptake in pig hearts: An <sup>87</sup>Rb and <sup>31</sup>P NMR study
Bibliographic record
Abstract
In this work the roles of coronary flow (CF) and metabolism in Rb(+) (K(+) congener) uptake were studied. In isolated pig hearts the left anterior descending artery (LAD) was cannulated to maintain adequate perfusion of the LAD bed. Rb(+) loading was initiated and the LAD flow was either completely stopped (no flow (NF)) or reduced to 12% (low flow (LF)), or buffer was deoxygenated without change in flow (hypoxic flow (HYP)) for 2 h. CF through the LAD was then restored to normal, or perfusion was switched to oxygenated buffer. Serial (87)Rb MR images or localized (31)P spectra were acquired to compare the Rb(+) uptake and energetics in the left ventricular (LV) anterior (ischemic/hypoxic) and posterior (normal) walls. End-ischemic/hypoxic (87)Rb signal intensities in the anterior wall were higher and the fluxes were greater in the HYP and LF groups than in the NF group. Phosphocreatine and ATP decreased less significantly and recovered better in the HYP and LF groups. Upon reperfusion/reoxygenation, the HYP and LF groups showed higher (87)Rb signal intensities and smaller or no infarctions in the anterior wall compared to those in the NF group. Ischemia reduces Rb(+) uptake due to both flow limitations and metabolic inhibition of cellular transport. (87)Rb MRI has a potential for distinguishing necrotic and reversibly damaged 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".