Preservation of Myocardial Perfusion and Function by Keeping Hypertrophied Heart Empty and Beating for Valve Surgery: An In Vivo MR Study of Pig Hearts
Bibliographic record
Abstract
Objectives . Normothermic hyperkalemic cardioplegia arrest (NHCA) may not effectively preserve hypertrophied myocardium during open-heart surgery. Normothermic normokalemic beating perfusion (NNBP), keeping hearts empty-beating, was utilized as an alternative to evaluate its cardioprotective role. Materials and Methods . Twelve hypertrophied pig hearts at 58.6 ± 7.2 days after ascending aorta banding underwent NNBP and NHCA, respectively. Near infrared myocardial perfusion imaging with indocyanine green (ICG) was conducted to assess myocardial perfusion. Left ventricular (LV) contractile function was assessed by cine MRI. TUNEL staining and western blotting for caspase-3 cleavage and cardiac troponin I (cTnI) degradation were conducted in LV tissue samples. Results . Ascending aortic diameter was reduced by 52.7 % ± 0.4 % at approximately fifty-eight days after banding. LV wall thickness was significantly higher in aorta banding than in sham operation. Myocardial blood flow reflected by maximum ICG absorbance value was markedly higher in NNBP than in NHCA. The amount of apoptotic cardiomyocyte was significantly lower in NNBP than in NHCA. NNBP alleviated caspase-3 cleavage and cTnI degradation associated with NHCA. NNBP displayed a substantially increased postoperative ejection fraction relative to NHCA. Conclusions . NNBP was better than NHCA in enhancing myocardial perfusion, inhibiting cardiomyocyte apoptosis, and preserving LV contractile function for hypertrophied hearts.
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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".