Evidence map›Paper›PMID 39284812›Full record

ArticleScientific reports2024

In silico evaluation of cell therapy in acute versus chronic infarction: role of automaticity, heterogeneity and Purkinje in human.

Leto Luana Riebel, Zhinuo Jenny Wang, Hector Martinez-Navarro, Cristian Trovato, Julia Camps, Lucas Arantes Berg, Xin Zhou, Ruben Doste, Rafael Sachetto Oliveira, Rodrigo Weber Dos Santos 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 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. (Cardiac) complexity needs interaction.Scientific reports · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
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.

Leto Luana RiebelDepartment of Computer Science, University of Oxford, Oxford, UK. leto.riebel@gtc.ox.ac.uk.ORCID http://orcid.org/0000-0002-5774-2406
Zhinuo Jenny WangDepartment of Computer Science, University of Oxford, Oxford, UK.
Hector Martinez-NavarroDepartment of Computer Science, University of Oxford, Oxford, UK.
Cristian TrovatoDepartment of Computer Science, University of Oxford, Oxford, UK.
Julia CampsDepartment of Computer Science, University of Oxford, Oxford, UK.
Lucas Arantes BergDepartment of Computer Science, University of Oxford, Oxford, UK.
Xin ZhouDepartment of Computer Science, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0003-2814-3399
Ruben DosteDepartment of Computer Science, University of Oxford, Oxford, UK.
Rafael Sachetto OliveiraUniversidade Federal de São João del Rei, São João del Rei, Brazil.ORCID http://orcid.org/0000-0003-0800-5984
Rodrigo Weber Dos SantosUniversidade Federal de Juiz de Fora, Juiz de Fora, Brazil.
Jacopo BiasettiSystems Medicine, Clinical Pharmacology & Safety Science, R&D, AstraZeneca, Gothenburg, Sweden.
Blanca RodriguezDepartment of Computer Science, University of Oxford, Oxford, UK. blanca.rodriguez@cs.ox.ac.uk.

Funding

AstraZeneca R67719/CN001BHF Centre of Research Excellence, Oxford (BHF Centre of Research Excellence in Oxford) RE/13/1/30181CompBioMed project (European Commission Horizon 2020 research and innovation programme) grant agreements No. 675451CompBioMed project (European Commission Horizon 2020 research and innovation programme) No. 823712EPSRC project CompBioMed X (EP/X019446/1)National Centre for the Replacement Refinement and Reduction of Animals in Research (NC3Rs) NC/P001076/1Oxford-Bristol Myers Squibb Fellowship (R39207/CN063)Partnership for Advanced Computing in Europe AISBL (PRACE) icp019Partnership for Advanced Computing in Europe AISBL (PRACE) PRACE-ICEI icp013RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BB/V509395/1Wellcome TrustWellcome Trust (Wellcome) 214290/Z/18/Z
6 · The paper itself

Abstract

Human-based modelling and simulation offer an ideal testbed for novel medical therapies to guide experimental and clinical studies. Myocardial infarction (MI) is a common cause of heart failure and mortality, for which novel therapies are urgently needed. Although cell therapy offers promise, electrophysiological heterogeneity raises pro-arrhythmic safety concerns, where underlying complex spatio-temporal dynamics cannot be investigated experimentally. Here, after demonstrating credibility of the modelling and simulation framework, we investigate cell therapy in acute versus chronic MI and the role of cell heterogeneity, scar size and the Purkinje system. Simulations agreed with experimental and clinical recordings from ionic to ECG dynamics in acute and chronic infarction. Following cell delivery, spontaneous beats were facilitated by heterogeneity in cell populations, chronic MI due to tissue depolarisation and slow sinus rhythm. Subsequent re-entrant arrhythmias occurred, in some instances with Purkinje involvement and their susceptibility was enhanced by impaired Purkinje-myocardium coupling, large scars and acute infarction. We conclude that homogeneity in injected ventricular-like cell populations minimises their spontaneous beating, which is enhanced by chronic MI, whereas a healthy Purkinje-myocardium coupling is key to prevent subsequent re-entrant arrhythmias, particularly for large scars.

Indexed as

Cell- and Tissue-Based TherapyComputer SimulationMyocardial InfarctionAcute DiseaseArrhythmias, CardiacChronic DiseaseElectrocardiographyFemaleHumansMaleMiddle AgedModels, CardiovascularPurkinje Fibers

Identifiers

PMID39284812
PMCPMC11405404

What Socratic holds

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Registered trials

None linked

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 Socratic graph.