Evidence map›Paper›PMID 24504928›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2014

Multifunction co-culture model for evaluating cell-cell interactions.

Danielle R Bogdanowicz, Helen H Lu

Open access · greenAbstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

14 citing papers in PubMed, 32 citations in OpenAlex.

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  7. Consistent Inclusion of Mesenchymal Stem Cells into In Vitro Tumor Models.Methods in molecular biology (Clifton, N.J.) · 2021
    Review
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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

2 authors at 1 institution in 1 country.

Danielle R BogdanowiczDepartment of Biomedical Engineering, Columbia University, New York, NY, USA.
Helen H Lu
Columbia University · US

Funding

Interface Tissue Engineering for Soft Tissue-to-Bone IntegrationR01AR055280 · NIAMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI LU, HELEN H · 2008 to 2014
$1.9M
NIAMS NIH HHS R01 AR055280NIAMS NIH HHS R01-AR055280
6 · The paper itself

Abstract

Interactions within the same cell population (homotypic) and between different cell types (heterotypic) are essential for tissue development, repair, and homeostasis. To elucidate the underlying mechanisms of these cellular interactions, co-culture models have been used extensively to investigate the role of cell-cell physical contact, autocrine and/or paracrine interactions on cell function, as well as stem cell differentiation. Specifically, the mixed co-culture model is often optimal for interpreting the effects of cell-cell contact on cellular behavior in vitro, while indirect co-culture can be used to study the effects of paracrine signaling on cell reactions. Additionally, cell-cell contact can be controlled by establishing physical barriers, which are used to regulate spatial and temporal cell distribution patterns in co-culture. In this chapter, we describe a method for forming a removable permeable divider for temporally and spatially controlling cellular interactions. This model can be used to study the impact of both cell-cell contact and paracrine signaling on the behavior of the mixed population as a whole and on the response of each subpopulation of cells in co-culture.

Indexed as

Cell CommunicationModels, BiologicalAnimalsCell MembraneCoculture TechniquesHumansHydrogel, Polyethylene Glycol DimethacrylateStaining and LabelingHydrogel, Polyethylene Glycol Dimethacrylate

Identifiers

PMID24504928
PMCPMC4077974
OpenAlexW2205195858

What OpenQuestion holds

Textmetadata
LicenceTDM
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.