Evidence map›Paper›PMID 30108260›Full record

ArticleScientific reports2018

Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice.

Dushan N Wadduwage, Jennifer Kay, Vijay Raj Singh, Orsolya Kiraly, Michelle R Sukup-Jackson, Jagath Rajapakse, Bevin P Engelward, Peter T C So

Abstract readValidation Study
In one paragraph

Article in Scientific reports, 2018. 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

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

8 authors.

Dushan N WadduwageDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. dushanw@mit.edu.
Jennifer KayDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID 0000-0001-5891-0689
Vijay Raj SinghBioSystems and Micromechanics (BioSyM), Singapore MIT Alliance for Research and Technology (SMART) Centre, 1 CREATE Way, #04-13/14 Enterprise Wing, Singapore, 138602, Singapore.ORCID 0000-0001-6880-9509
Orsolya KiralyDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Michelle R Sukup-JacksonDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Jagath RajapakseBioSystems and Micromechanics (BioSyM), Singapore MIT Alliance for Research and Technology (SMART) Centre, 1 CREATE Way, #04-13/14 Enterprise Wing, Singapore, 138602, Singapore.
Bevin P EngelwardDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Peter T C SoDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.

Funding

TOXICOLOGY CORE UNITP30ES002109 · NIEHS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LEVINE, STUART S · 1985 to 2020
$25.6M
Reaction and Diffusion of NO in Biological SystemsP01CA026731 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI TANNENBAUM, STEVEN R · 1985 to 2018
$25.4M
TRAINING GRANTS IN ENVIROMENTAL TOXICOLOGYT32ES007020 · NIEHS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI ESSIGMANN, JOHN M · 1985 to 2024
$13.1M
Wide-Field Short-Wave Infrared (SWIR) multiphoton (MP) tissue imagingP41EB015871 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI SO, PETER T. · 2012 to 2021
$11.3M
Characterizing mechanisms of sickle cell crisis via dynamic optical assayR01HL121386 · NHLBI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI SO, PETER T. · 2014 to 2016
$1.7M
Regenerative Healing Using ECM Based ScaffoldsR01NS051320 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI YANNAS, IOANNIS V · 2006 to 2009
$1.6M
High Throughput Manufacturing for Three-Dimensional Microfluidic DevicesR44EB012415 · NIBIB · FEMTOFAB, INC. · PI JANG, YUN-HO · 2011 to 2013
$849k
NCI NIH HHS P01 CA026731NHLBI NIH HHS R01 HL121386NIBIB NIH HHS P41 EB015871NIBIB NIH HHS R44 EB012415NIEHS NIH HHS P30 ES002109NIEHS NIH HHS T32 ES007020NINDS NIH HHS R01 NS051320
6 · The paper itself

Abstract

Homologous recombination (HR) events are key drivers of cancer-promoting mutations, and the ability to visualize these events in situ provides important information regarding mutant cell type, location, and clonal expansion. We have previously created the Rosa26 Direct Repeat (RaDR) mouse model wherein HR at an integrated substrate gives rise to a fluorescent cell. To fully leverage this in situ approach, we need better ways to quantify rare fluorescent cells deep within tissues. Here, we present a robust, automated event quantification algorithm that uses image intensity and gradient features to detect fluorescent cells in deep tissue specimens. To analyze the performance of our algorithm, we simulate fluorescence behavior in tissue using Monte Carlo methods. Importantly, this approach reduces the potential for bias in manual counting and enables quantification of samples with highly dense HR events. Using this approach, we measured the relative frequency of HR within a chromosome and between chromosomes and found that HR within a chromosome is more frequent, which is consistent with the close proximity of sister chromatids. Our approach is both objective and highly rapid, providing a powerful tool, not only to researchers interested in HR, but also to many other researchers who are similarly using fluorescence as a marker for understanding mammalian biology in tissues.

Indexed as

Models, GeneticAnimalsCarcinogenesisChromatidsChromosomes, MammalianComputer SimulationFluorescenceGenes, ReporterHomologous RecombinationImage Processing, Computer-AssistedLuminescent ProteinsMiceMice, TransgenicMolecular ImagingMonte Carlo MethodMutationLuminescent Proteins

Identifiers

PMID30108260
PMCPMC6092416

What OpenQuestion 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 OpenQuestion graph.