The heart in lack of oxygen? A revisited method to improve cardiac performance ex vivo
Bibliographic record
Abstract
Isolated heart models have been used extensively to improve our understanding of heart physiology (27).The approach is of utmost value to investigate cardiac electrical/mechanical function, metabolism, and drug effects as well as pathophysiological studies, such as ischemia-reperfusion injury and diabetic cardiomyopathy (42).These study models were first introduced in 1895 by Oscar Langendorff, who performed retrograde perfusion (i.e., through the aorta) of the isolated mammalian heart (2, 25).Although the Langendorff technique remains a common approach in the field of cardiovascular research, the isolated contracting heart or perfused working heart models introduced subsequently by Otto Frank (11) and Neely and collaborators (31) are closer to in situ physiological conditions in terms of cardiac workload (i.e., preload and afterload).The introduction of ex vivo models not only offered greater environmental control but also opened the way to the development of important study techniques, such as imaging techniques based on endogenous fluorescence (i.e., NADH and myoglobin oxygenation) and fluorescent dyes (i.e., Ca 2ϩ dyes and voltage-sensitive dyes) that are widely used to study myocardial physiology (16,29).The possibility to image the whole heart surface has increased our understanding of cardiac dynamic electrical activity (19,29).Recent advances in data processing have enabled the transition from nonbeating tissue to working heart studies; for instance, optical mapping techniques allow simultaneous mapping of the optical action potential and mechanical contraction (3).However, there are variations in the characteristics of ex vivo models (e.g., O 2 consumption) (24) that could drastically influence experimental results.Ex vivo cardiac perfusion: the role of crystalloid buffers.Stable ex vivo heart models need constant perfusion to assure adequate substrate diffusion and O 2 delivery within the myocardium.A well-defined and controlled perfusate is key to experimental control and reproducibility.More than a century ago, in 1898, Rusch, a former Langendorff disciple, showed that blood could be replaced by a saline glucose-enriched medium as the perfusate in Langendorff-perfused hearts.His discovery was a stepping stone in determining the composition of mammalian tissue perfusate, which was elaborated later by Krebs and Henseleit (41).As such, the most common physio-
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".