MétaCan
Menu
← Back to cohort
Record W2771915543 · doi:10.1152/ajpheart.00699.2017

The heart in lack of oxygen? A revisited method to improve cardiac performance ex vivo

2018· letter· en· W2771915543 on OpenAlexaff
Matthieu Ruiz, Philippe Comtois

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2018
Typeletter
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsEx vivoOxygenCardiologyInternal medicineIn vivoMedicineChemistryBiology

Abstract

fetched live from OpenAlex

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-

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0020.002

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.

Opus teacher head0.014
GPT teacher head0.297
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Physiology-Heart and Circulatory Physiology→Same topicCardiac Arrest and Resuscitation→French-language works237,207→