Evidence map›Paper›PMID 23209767›Full record

ArticlePloS one2012

Unique reporter-based sensor platforms to monitor signalling in cells.

Meesbah Jiwaji, Rónán Daly, Abdullah Gibriel, Gráinne Barkess, Pauline McLean, Jingli Yang, Kshama Pansare, Sarah Cumming, Alisha McLauchlan, Piotr J Kamola and 6 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 46% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

16 authors at 4 institutions in 2 countries.

Meesbah JiwajiInstitute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom.
Rónán Daly
Abdullah Gibriel
Gráinne Barkess
Pauline McLean
Jingli Yang
Kshama Pansare
Sarah Cumming
Alisha McLauchlan
Piotr J Kamola
Musab S Bhutta
Adam G West
Katherine L West
Walter Kolch
Mark A Girolami
Andrew R Pitt
University of Glasgow · GBUniversity College Dublin · IEUniversity College London · GBUniversity of Strathclyde · GB

Funding

Medical Research Council G0400180
6 · The paper itself

Abstract

introductionIn recent years much progress has been made in the development of tools for systems biology to study the levels of mRNA and protein, and their interactions within cells. However, few multiplexed methodologies are available to study cell signalling directly at the transcription factor level.

methodsHere we describe a sensitive, plasmid-based RNA reporter methodology to study transcription factor activation in mammalian cells, and apply this technology to profiling 60 transcription factors in parallel. The methodology uses two robust and easily accessible detection platforms; quantitative real-time PCR for quantitative analysis and DNA microarrays for parallel, higher throughput analysis.

findingsWe test the specificity of the detection platforms with ten inducers and independently validate the transcription factor activation.

conclusionsWe report a methodology for the multiplexed study of transcription factor activation in mammalian cells that is direct and not theoretically limited by the number of available reporters.

Indexed as

Blotting, WesternCadmium ChlorideCell LineColforsinDexamethasoneHumansOligonucleotide Array Sequence AnalysisPlasmidsReal-Time Polymerase Chain ReactionSystems BiologyTranscription FactorsCadmium ChlorideColforsinDexamethasoneTranscription Factors

Identifiers

PMID23209767
PMCPMC3510088
OpenAlexW2124945391

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.