Evidence map›Paper›PMID 27387837›Full record

ArticleScientific reports2016

Assembly PCR synthesis of optimally designed, compact, multi-responsive promoters suited to gene therapy application.

H Mohamed, Y Chernajovsky, D Gould

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 19% 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

2 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. 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 2 institutions in 1 country.

H MohamedQueen Mary University of London, William Harvey Research Institute, Bone &Joint Research Unit, United Kingdom.
Y ChernajovskyQueen Mary University of London, William Harvey Research Institute, Bone &Joint Research Unit, United Kingdom.
D GouldQueen Mary University of London, William Harvey Research Institute, Bone &Joint Research Unit, United Kingdom.
William Harvey Research Institute · GBQueen Mary University of London · GB

Funding

Medical Research Council
6 · The paper itself

Abstract

Gene therapy has the potential to provide innovative treatments for genetic and non-genetic diseases, with the ability to auto-regulate expression levels of therapeutic molecules so that they are produced locally and in direct response to disease activity. Generating disease responsive gene therapy vectors requires knowledge of the activation profile of transcription factors (TFs) during active disease, in order to assemble binding sites for these TFs into synthetic promoters, which can be appropriately activated by the disease process. In this study, we optimised a PCR random assembly approach to generate promoters with optimal spacing between TF binding sites (TFBSs) and their distance from the TATA box. In promoters with optimal spacing, it was possible to demonstrate activation by individual transcription pathways and either additive or synergistic promoter activation when transfected cells were treated with combined stimuli. The kinetics and sensitivity of promoter activation was further explored in transduced cells and when lentivirus was directly delivered to mouse paws a synthetic promoter demonstrated excellent activation by real-time imaging in response to local inflammation.

Indexed as

Promoter Regions, GeneticAnimalsBinding SitesGenetic TherapyGenetic VectorsHumansLentivirusMicePolymerase Chain ReactionTATA BoxTranscriptional ActivationTranscription FactorsTranscription Factors

Identifiers

PMID27387837
PMCPMC4937410
OpenAlexW2469373669

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.