Evidence map›Paper›PMID 35013350›Full record

ArticleScientific reports2022

High-throughput formation and image-based analysis of basal-in mammary organoids in 384-well plates.

Soojung Lee, Jonathan Chang, Sung-Min Kang, Eric Parigoris, Ji-Hoon Lee, Yun Suk Huh, Shuichi Takayama

Open access · goldAbstract readVideo-Audio Media
In one paragraph

Article in Scientific reports, 2022. 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
2.4field-weighted citation impact, top 12% 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, 31 citations in OpenAlex.

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  16. Biomimetic Gland Models with Engineered Stratagems.Research (Washington, D.C.) · 2023
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  19. Better In Vitro Tools for ExploringLife (Basel, Switzerland) · 2022
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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

7 authors at 4 institutions in 2 countries.

Soojung Lee *Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Jonathan Chang *Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Sung-Min KangDepartment of Green Chemical Engineering, Sangmyung University, Cheonan, Chungnam, 31066, Republic of Korea.
Eric ParigorisWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Ji-Hoon LeeWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Yun Suk HuhDepartment of Biological Engineering, NanoBio High-Tech Materials Research Center, Inha University, 100 Inha-ro, Incheon, 22212, Republic of Korea.
Shuichi TakayamaWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA. takayama@gatech.edu.
Georgia Institute of Technology · USThe Wallace H. Coulter Department of Biomedical Engineering · USInha University · KRSangmyung University · KR

Funding

Systems Bioengineering of Cancer Cell MigrationR01CA196018 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LINDERMAN, JENNIFER JEAN, LUKER, GARY D · 2015 to 2019
$2.2M
NCI NIH HHS R01 CA196018NIH HHS R01CA196018
6 · The paper itself

Abstract

This manuscript describes a new method for forming basal-in MCF10A organoids using commercial 384-well ultra-low attachment (ULA) microplates and the development of associated live-cell imaging and automated analysis protocols. The use of a commercial 384-well ULA platform makes this method more broadly accessible than previously reported hanging drop systems and enables in-incubator automated imaging. Therefore, time points can be captured on a more frequent basis to improve tracking of early organoid formation and growth. However, one major challenge of live-cell imaging in multi-well plates is the rapid accumulation of large numbers of images. In this paper, an automated MATLAB script to handle the increased image load is developed. This analysis protocol utilizes morphological image processing to identify cellular structures within each image and quantify their circularity and size. Using this script, time-lapse images of aggregating and non-aggregating culture conditions are analyzed to profile early changes in size and circularity. Moreover, this high-throughput platform is applied to widely screen concentration combinations of Matrigel and epidermal growth factor (EGF) or heparin-binding EGF-like growth factor (HB-EGF) for their impact on organoid formation. These results can serve as a practical resource, guiding future research with basal-in MCF10A organoids.

Indexed as

Cell ProliferationHigh-Throughput Screening AssaysImage Processing, Computer-AssistedMicroscopy, FluorescenceOrganoidsTime-Lapse ImagingAlgorithmsCell Culture Techniques, Three DimensionalCell LineCollagenDrug CombinationsEpidermal Growth FactorFemaleHeparin-binding EGF-like Growth FactorHumansLamininCollagenDrug CombinationsEpidermal Growth FactorHeparin-binding EGF-like Growth FactorLamininmatrigelProteoglycans

Identifiers

PMID35013350
PMCPMC8748891
OpenAlexW4206061533

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.