Simulated microgravity increases myocardial susceptibility to ischemia–reperfusion injury via a deficiency of AMP-activated protein kinase
Bibliographic record
Abstract
Gravitation is an important factor in maintaining cardiac contractility. Our study investigated whether simulated microgravity increases myocardial susceptibility to ischemia-reperfusion (IR) injury. Using the Langendorff-perfused heart model with 300 beats/min pacing, 4-week tail suspension (SUS) and control (CON) male Sprague-Dawley rats (n = 10 rats/group) were subjected to 60 min of left anterior descending coronary artery (LAD) occlusion followed by 120 min of reperfusion. Left ventricular end-systolic pressure (LVESP), left ventricular end-diastolic pressure (LVEDP), creatine kinase (CK) and lactate dehydrogenase (LDH) activity, and infarct size were assessed. Data demonstrated that there were significantly increased LVEDP, CK, LDH, and infarct size in SUS compared with CON (P < 0.05), accompanied by decreased LVESP (P < 0.05). Furthermore, TUNEL-positive cardiomyocytes were higher in SUS than that in CON (P < 0.01), and AMP-activated protein kinase (AMPK) phosphorylation and Bcl-2/Bax in SUS were less compared with CON (P < 0.05). Similarly, isolated hearts pre-treated with A-769662 exhibited better recovery of cardiac function, increased AMPK phosphorylation, and reduced necrosis and apoptosis. Furthermore, AMPKα protein showed a significant suppression in 4-week hindlimb unweighting rats. These results suggest that AMPK deficiency increases myocardial susceptibility to IR injury in rats subjected to simulated microgravity.
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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) | 0.001 | 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".