Evidence map›Paper›PMID 38480810›Full record

ArticleCommunications biology2024

OrgaSegment: deep-learning based organoid segmentation to quantify CFTR dependent fluid secretion.

Juliet W Lefferts, Suzanne Kroes, Matthew B Smith, Paul J Niemöller, Natascha D A Nieuwenhuijze, Heleen N Sonneveld van Kooten, Cornelis K van der Ent, Jeffrey M Beekman, Sam F B van Beuningen

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
11.7field-weighted citation impact, top 1% of its field
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

21 citing papers in PubMed, 28 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Juliet W LeffertsDepartment of Pediatric Respiratory Medicine, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, 3584 EA, Utrecht, The Netherlands.
Suzanne KroesDepartment of Pediatric Respiratory Medicine, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, 3584 EA, Utrecht, The Netherlands.
Matthew B SmithDepartment of Pediatric Respiratory Medicine, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, 3584 EA, Utrecht, The Netherlands.
Paul J NiemöllerDepartment of Pediatric Respiratory Medicine, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, 3584 EA, Utrecht, The Netherlands.
Natascha D A NieuwenhuijzeDepartment of Pediatric Respiratory Medicine, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, 3584 EA, Utrecht, The Netherlands.
Heleen N Sonneveld van KootenDepartment of Pediatric Respiratory Medicine, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, 3584 EA, Utrecht, The Netherlands.
Cornelis K van der EntDepartment of Pediatric Respiratory Medicine, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, 3584 EA, Utrecht, The Netherlands.
Jeffrey M BeekmanDepartment of Pediatric Respiratory Medicine, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, 3584 EA, Utrecht, The Netherlands. j.beekman@umcutrecht.nl.ORCID 0000-0003-4886-3756
Sam F B van BeuningenDepartment of Pediatric Respiratory Medicine, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, 3584 EA, Utrecht, The Netherlands. s.vanbeuningen@umcutrecht.nl.ORCID 0000-0001-6166-196X
Utrecht University · NLUniversity of Applied Sciences Utrecht · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial ion and fluid transport studies in patient-derived organoids (PDOs) are increasingly being used for preclinical studies, drug development and precision medicine applications. Epithelial fluid transport properties in PDOs can be measured through visual changes in organoid (lumen) size. Such organoid phenotypes have been highly instrumental for the studying of diseases, including cystic fibrosis (CF), which is characterized by genetic mutations of the CF transmembrane conductance regulator (CFTR) ion channel. Here we present OrgaSegment, a MASK-RCNN based deep-learning segmentation model allowing for the segmentation of individual intestinal PDO structures from bright-field images. OrgaSegment recognizes spherical structures in addition to the oddly-shaped organoids that are a hallmark of CF organoids and can be used in organoid swelling assays, including the new drug-induced swelling assay that we show here. OrgaSegment enabled easy quantification of organoid swelling and could discriminate between organoids with different CFTR mutations, as well as measure responses to CFTR modulating drugs. The easy-to-apply label-free segmentation tool can help to study CFTR-based fluid secretion and possibly other epithelial ion transport mechanisms in organoids.

Indexed as

Cystic FibrosisDeep LearningCystic Fibrosis Transmembrane Conductance RegulatorHumansIntestinesOrganoidsCFTR protein, humanCystic Fibrosis Transmembrane Conductance Regulator

Identifiers

PMID38480810
PMCPMC10937908
OpenAlexW4392748137

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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.