Myocardial function following cold ischemic storage is improved by cardiac-specific overexpression of A<sub>1</sub>-adenosine receptors
Bibliographic record
Abstract
Cold ischemic storage of hearts for transplantation is limited to 4-6 h, and therefore the development of strategies to extend preservation time may increase the donor pool of hearts. Overexpression of A1-adenosine receptors (A1AR) can protect hearts from acute ischemic injury, and the purpose of this study was to test the hypothesis that overexpression of A1AR will improve tolerance to longer periods of cold ischemic preservation. Hearts from 18 wild type and 16 transgenic mice with overexpression of A1AR (A1AR Trans) were isolated and perfused, and then subjected to 18 h of preservation in 5 degrees C University of Wisconsin solution followed by 2 h of reperfusion. Left ventricular end diastolic pressure and left ventricular developed pressure were measured as indices of ventricular function. Cell viability was assessed by determination of infarct size and myocardial cell apoptosis. A1AR Trans hearts showed improved function following 18 h of ischemia, as shown by lower end diastolic pressure (p < 0.05) and higher recovery of left ventricular developed pressure (p < 0.05) during reperfusion. A1AR Trans hearts had markedly reduced infarct size (p < 0.05) and decreased apoptosis (p < 0.05). Overexpression of cardiac A1AR imparts cardioprotection during long-term cold ischemic preservation.
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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".