Evidence map›Paper›PMID 34841289›Full record

ArticleCell reports. Medicine2021

C-MORE: A high-content single-cell morphology recognition methodology for liquid biopsies toward personalized cardiovascular medicine.

Jennifer Furkel, Maximilian Knoll, Shabana Din, Nicolai V Bogert, Timon Seeger, Norbert Frey, Amir Abdollahi, Hugo A Katus, Mathias H Konstandin

Abstract read
In one paragraph

Article in Cell reports. Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Jennifer FurkelDepartment of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, 69120 Heidelberg, Germany.
Maximilian KnollGerman Cancer Consortium (DKTK) Core Center Heidelberg, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
Shabana DinDepartment of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, 69120 Heidelberg, Germany.
Nicolai V BogertDepartment of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, 69120 Heidelberg, Germany.
Timon SeegerDepartment of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, 69120 Heidelberg, Germany.
Norbert FreyDepartment of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, 69120 Heidelberg, Germany.
Amir AbdollahiGerman Cancer Consortium (DKTK) Core Center Heidelberg, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
Hugo A KatusDepartment of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, 69120 Heidelberg, Germany.
Mathias H KonstandinDepartment of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, 69120 Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cellular morphology has the capacity to serve as a surrogate for cellular state and functionality. However, primary cardiomyocytes, the standard model in cardiovascular research, are highly heterogeneous cells and therefore impose methodological challenges to analysis. Hence, we aimed to devise a robust methodology to deconvolute cardiomyocyte morphology on a single-cell level: C-MORE (cellular morphology recognition) is a workflow from bench to data analysis tailored for heterogeneous primary cells using our R package cmoRe. We demonstrate its utility in proof-of-principle applications such as modulation of canonical hypertrophy pathways and linkage of genotype-phenotype in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). In our pilot study, exposure of cardiomyocytes to blood plasma prior to versus after aortic valve replacement allows identification of a disease fingerprint and reflects partial reversibility following therapeutic intervention. C-MORE is a valuable tool for cardiovascular research with possible fields of application in basic research and personalized medicine.

Indexed as

AlgorithmsLiquid BiopsyPrecision MedicineSingle-Cell AnalysisAnimalsAortic Valve StenosisCardiovascular DiseasesCell CycleGreen Fluorescent ProteinsHumansHypertrophyInduced Pluripotent Stem CellsMyocytes, CardiacPhenotypeRatsReproducibility of ResultsGreen Fluorescent Proteinscellular morphologyhigh-content imaginghigh-throughput screeninghuman induced pluripotent stem cell-derived cardiomyocyteshypertrophic cardiomyopathyneonatal rat cardiomyocytespattern recognitionphenoprintphenotypeprimary cells

Identifiers

PMID34841289
PMCPMC8606902

What OpenQuestion holds

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Registered trials

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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.