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Record W2942299761 · doi:10.3791/59197

A Pre-Clinical Porcine Model of Orthotopic Heart Transplantation

2019· article· en· W2942299761 on OpenAlexaff
Roberto Vanin Pinto Ribeiro, Juglans Alvarez, Frank Yu, M. Adamson, Naoto Fukunaga, Cyril Serrick, V. Bissoondath, Massimiliano Meineri, Mitesh Badiwala, Vivek Rao

Bibliographic record

VenueJournal of Visualized Experiments · 2019
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineTransplantationHeart transplantationAnimal modelClinical trialHeart failureIntensive care medicineGold standard (test)IschemiaCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Fifty-years following the first successful report, cardiac transplantation remains the gold-standard treatment for eligible patients with advanced heart failure. Multiple small-animal models of heart transplantation have been used to study the acute and long-term effects of novel therapies. However, few are tested and demonstrated success in clinical trials. It is of critical importance to evaluate new therapies in a clinically relevant large-animal model for efficient and reliable translation of basic studies' findings. Here, we describe a pre-clinical large-animal (porcine) model of orthotopic heart transplantation that has been firmly established and previously used to investigate novel cardioprotective strategies. This procedure focuses on acute ischemia-reperfusion injury and is a reliable method to investigate novel interventions which have been tested and validated in smaller experimental models, such as the murine model. We demonstrate its usefulness in assessing cardiac performance during the early post-transplantation period and other potential possibilities enabled by the model.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.089
GPT teacher head0.532
Teacher spread0.443 · 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 teacher head, 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

Citations6
Published2019
Admission routes1
Has abstractyes

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