Evidence map›Paper›PMID 39616208›Full record

ArticleScientific reports2024

Deep phenotyping the right ventricle to establish translational MRI biomarkers for characterization of adaptive and maladaptive states in pulmonary hypertension.

Nicoleta Baxan, Lin Zhao, Ali Ashek, Marili Niglas, Dingyi Wang, Fatemeh Khassafi, Farah Sabrin, Olivier Dubois, Chien-Nien Chen, Soni Savai Pullamsetti and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Nicoleta BaxanNational Heart and Lung Institute, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, UK.
Lin ZhaoNational Heart and Lung Institute, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, UK.
Ali AshekNational Heart and Lung Institute, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, UK.
Marili NiglasNational Heart and Lung Institute, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, UK.
Dingyi WangNational Heart and Lung Institute, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, UK.
Fatemeh KhassafiDepartment of Lung Development and Remodeling, Max Planck Institute for Heart and Lung Research, Member of the German Center for Lung Research (DZL), Member of the Cardio-Pulmonary Institute (CPI), Bad Nauheim, Germany.
Farah SabrinBiological Imaging Centre, Imperial College London, Hammersmith Hospital, London, UK.
Olivier DuboisBiological Imaging Centre, Imperial College London, Hammersmith Hospital, London, UK.
Chien-Nien ChenNational Heart and Lung Institute, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, UK.
Soni Savai PullamsettiDepartment of Lung Development and Remodeling, Max Planck Institute for Heart and Lung Research, Member of the German Center for Lung Research (DZL), Member of the Cardio-Pulmonary Institute (CPI), Bad Nauheim, Germany.
Martin WilkinsNational Heart and Lung Institute, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, UK.
Lan ZhaoNational Heart and Lung Institute, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, UK. l.zhao@imperial.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep phenotyping the right ventricle (RV) is essential for understanding the mechanisms of adaptive and maladaptive RV responses to pulmonary hypertension (PH). In this study, feature selection coupled with machine learning classification/ranking of specific cardiac magnetic resonance imaging (MRI) features from cine-MRI, flow-sensitized, and extracellular-volume techniques were used to assess RV remodelling in monocrotaline (MCT) and Sugen hypoxia (SuHx) PH rats. Early physiological changes associated with RV adaptation were detected along with prediction of RV maladaptive outcomes. Key adaptation features included haemodynamic alterations of pulmonary blood flow ejection and wave reflection, mild RV dilatation, progressive RV hypertrophy with subtle extracellular volume growth of RV wall. A dominant component of maladaptation was the extracellular matrix increase at RV insertion points and septum, observations compatible with histopathologic and RNA-sequencing results. The upregulation of mammalian target of rapamycin (mTOR) paralleled by AMP-activated protein kinase (AMPK) deactivation was seen at 4-week MCT and 8-week SuHx, along with reduced sarcoplasmic/endoplasmic reticulum Ca

Indexed as

BiomarkersHeart VentriclesHypertension, PulmonaryMagnetic Resonance ImagingAdaptation, PhysiologicalAnimalsDisease Models, AnimalHypertrophy, Right VentricularMaleMonocrotalinePhenotypeRatsRats, Sprague-DawleyTOR Serine-Threonine KinasesVentricular RemodelingBiomarkersMonocrotalineTOR Serine-Threonine KinasesAdaptive/maladaptive right ventricleMRIMyocardial extracellular matrixPulmonary artery blood flowPulmonary hypertensionRV phenotyping

Identifiers

PMID39616208
PMCPMC11608234

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.