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Record W1967455904 · doi:10.1093/ehjci/jeu083

These abstracts have been selected for presentation in 4 sessions throughout the meeting. Please refer to the PROGRAM for more details.

2014· article· en· W1967455904 on OpenAlexaff
Francis J. Munch, J. Retel, S. Jeuthe, B. van Rossum, D. Oh-Ici, Frances R. Berger, Titus Kühne, Hartmut Oschkinat, Daniel Messroghli, José F. Rodríguez‐Palomares, L. Gutierrez Garcia Moreno, G. Maldonado, G. Garcia, Imanol Otaegui, Bruno García del Blanco, J. Barrabes, M. Gonzalez Alujas, A. Evangelista, David García Dorado, A. Barison, Alberico Del Torto, S. Chiappino, N. Pugliese, Giovanni Donato Aquaro, Vincenzo Positano, Claudio Passino, Michele Emdin, Pier Giorgio Masci, Katherine Fischer, Dominik P. Guensch, N. Shie, Matthias G. Friedrich, Gaby Captur, Filip Zemrak, Vivek Muthurangu, Lin Chunming, Steffen B. Petersen, Nadine Kawel‐Boehm, Patrick F. Bassett, Perry Elliott, Jozéli Fernandes de Lima, David A. Bluemke, James Moon, Gianluca Pontone, E. Bertella, M. Loguercio, Andrea Baggiano, S. Mushtaq, Sara Salerni, Carlo Riccardo Rossi, D. Andreini, E. Arroyo Ucar, R Hinojar Baydes, N. Ngah, Y. Kuo, Darius Dabir, C. Cummins, Debra Higgins, Tobias Schaeffter, N. Gaddum, Phil Chowienczyk, G Carr-White, Michael Marber, Sema Kalkan Uçar, Sebastian J. Reinstadler, Günter Klug, H. Feistritzer, K. Greber, Jonathan Mair, M. Schocke, W Franz, Barbara U. Metzler-Zebeli, Karine Moschetti, G. Pilz, Jean‐Blaise Wasserfallen, M. Lombardi, Grigorios Korosoglou, Annemarie M. C. van Rossum, Oliver Bruder, Heiko Mahrholdt, Juerg Schwitter, Ignacio Ferreira González, Víctor Pineda, R. Ruiz Salmeron, A. San Roman, Arturo Evangelista, Francisco Fernández‐Avilés, Stanley Winkler, Thomas Allison, Howard F. Conn, Peter A. Bandettini, Satish Shanbhag, Philip J. Kellman, Leslie Hsu, Andrea Gevurtz Arai, B. Pernter, Silvia Pica, Daniel Sado, Viviana Maestrini, Marie‐Christine Fontana, Stephen D. White, Thomas A. Treibel, Sarah Anderson, Stefan K. Piechnik, M. Robson, Robert Lachmann, Eamonn Murphy, Atharva Mehta, D. Hughes, Victor S. Ferreira, Erica Dall’Armellina, Theodoros D. Karamitsos, John Francis, Romit Roy Choudhury, Adrian Banning, Keith M. Channon, Rajesh Kharbanda, Colin Forfar, Oliver Ormerod, Bernard Prendergast, Attila Kardos, J Newton, Martin Friedrich, Stefan Neubauer, A. Barison, Giuseppe Vergaro, G. Mirizzi, C. Passino, A. Florian, Allen C. Ludwig, Stephanie Rösch, Udo Sechtem, Ahmet YILMAZ, Simon Greulich, D. Kitterer, Joerg Latus, Kerstin Bentz, Stefan Birkmeier, Mark Dominik Alscher, N. Braun, F. Perfetto, F. Secchi, Mario Petrini, Paola Maria Cannaò, Giuseppe Di Leo, Francesco Sardanelli, Hiroyuki Yoshihara, Jessica Bastiaansen, Corinne Berthonneche, Arnaud Comment, Brian L. Gerber, G. Noppe, N. Marquet, P. Buchlin, Jean‐Louis Vanoverschelde, Lewis Bertrand, S. Horman, Piekutowska-Abramczuk Dorota, Witczak Piotr, GerardJ. Marek, A. Almeida, Nuno Cortez‐Dias, Jéssica de Lyra Sousa, L Carpinteiro, A. Magalhães, Gil Silva, Ana Bernardes, Fausto J. Pinto, A. Nunes Diogo

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Imaging · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPresentation (obstetrics)Computer scienceInformation retrievalPsychologyMathematics educationWorld Wide WebMedicineSurgery

Abstract

fetched live from OpenAlex

Background: Altered metabolism is thought to play an important role in the pathogenesis of heart failure.Study of the metabolism may provide insights into the pathology of heart failure and may provide new diagnostic tools.Proton magnetic resonance spectroscopy (MRS) allows us to quantify total creatine, which plays an essential role in the transport of energy from the mitochondria to the myofibrils.Experimental autoimmune myocarditis (EAM) in rodents is an accepted model of myocarditis and dilated cardiomyopathy.As of yet, proton MRS has not been used to study the changes occurring in this model of heart failure.We aimed to study the metabolic changes occurring in an animal model of EAM, and compare these to the findings in healthy animals.Methods: Myocardial tissue of 10 male young Lewis rats with EAM (35 days after immunization with 0.25 mg porcine myocardial myosine) was analysed using 1H-MAS-MRS (Bruker 600 MHz).The metabolic profile was compared to fresh (n ¼ 7) and frozen (n ¼ 8) healthy controls and to the results from histology and immunohistochemistry (CD68).For fresh control samples the spectra were taken less than 10 min after death.Frozen control samples and myocarditis samples were shock-frozen in liquid nitrogen and stored for 4-6 months at -808C before measurements.Myocardial tissue from a basalcavity slice of the the left ventricle (30-40 mg) excluding epicardial tissue was placed in a 4 mm zirconium rotor, packed homogeneously using a spacer and spun at 4 kHz at 293 K.A water suppression pulse sequence was applied to obtain the proton spectrum (ns ¼ 128, t ¼ 7 min).Spectra were phased and baseline correction using polynomial fit to the region of interest was applied before integration of the peaks.Results: The metabolic ratio of taurine to creatine obtained by spectral analysis proved to be a significant biomarker for diagnosis of myocarditis compared to healthy controls (taurine/creatine ratio in myocarditis: 4.47(+0.83),fresh control: 2.59(+0.09),frozen control: 2.59(+0.28);P , 0.001).Myocarditis was confirmed histologically with an inflammatory cellular infiltrate and CD68 positive staining.Conclusions: Myocardial taurine/creatine ratio as detected by proton MRS is able to differentiate between healthy myocardium and myocardium from rats with EAM.This variation may occur due to creatine depletion as described in heart failure and/or an increase in taurine due to its antioxidant activity in inflammatory reactions.1237

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.366
Threshold uncertainty score0.522

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0050.002
Open science0.0030.005
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.6340.487

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 head0.033
GPT teacher head0.351
Teacher spread0.317 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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