Evidence map›Paper›PMID 33340353›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2021

Reconstitution of Morphogen Signaling Gradients in Cultured Cells.

Julia S Kim, Michael Pineda, Pulin Li

Open access · greenAbstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 74% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Julia S KimWhitehead Institute for Biomedical Research, Cambridge, MA, USA.
Michael PinedaWhitehead Institute for Biomedical Research, Cambridge, MA, USA.
Pulin LiWhitehead Institute for Biomedical Research, Cambridge, MA, USA. pli@wi.mit.edu.
Whitehead Institute for Biomedical Research · US

Funding

Spatio-Temporal Signaling Dynamics in Neuronal Cell Fate Decision and PatterningR00HD087532 · NICHD · WHITEHEAD INSTITUTE FOR BIOMEDICAL RES · PI LI, PULIN · 2019 to 2021
$736k
NICHD NIH HHS R00 HD087532
6 · The paper itself

Abstract

Development of multicellular organisms depends on the proper establishment of signaling information in space and time. Secreted molecules called morphogens form concentration gradients in space and provide positional information to differentiating cells within the organism. Although the key molecular components of morphogen pathways have been identified, how the architectures and key parameters of morphogen pathways control the properties of signaling gradients, such as their size, speed, and robustness to perturbations, remains challenging to study in developing embryos. Reconstituting morphogen gradients in cell culture provides an alternative approach to address this question. Here we describe the methodology for reconstituting Sonic Hedgehog (SHH) signaling gradients in mouse fibroblast cells. The protocol includes the design of morphogen sending and receiving cell lines, the setup of radial and linear gradients, the quantitative time-lapse imaging, and the data analysis. Similar approaches could potentially be applied to other cell-cell communication pathways.

Indexed as

Microscopy, FluorescenceMicroscopy, VideoTime-Lapse ImagingAnimalsFibroblastsGene Expression Regulation, DevelopmentalGenes, ReporterHedgehog ProteinsLuminescent ProteinsMiceMorphogenesisNIH 3T3 CellsSignal TransductionTime FactorsHedgehog ProteinsLuminescent ProteinsShh protein, mouseMorphogen gradientsQuantitative imagingReconstitutionTissue patterning

Identifiers

PMID33340353
PMCPMC8112896
OpenAlexW3117647929

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.