Evidence map›Paper›PMID 19015958›Full record

ReviewPharmaceutical research2009

Antisense makes sense in engineered regenerative medicine.

Yongchang Yao, Chunming Wang, Rohan R Varshney, Dong-An Wang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Pharmaceutical research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

10 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Article
  3. Technologies for controlled, local delivery of siRNA.Journal of controlled release : official journal of the Controlled Release Society · 2015
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Localized, targeted, and sustained siRNA delivery.Chemistry (Weinheim an der Bergstrasse, Germany) · 2011
    Article
  9. Article
  10. siRNA applications in nanomedicine.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology
    Review
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

4 authors at 1 institution in 1 country.

Yongchang YaoDivision of BioEngineering, School of Chemical and Biomedical Engineering, Nanyang Technological University, 70 Nanyang Drive, N1.3-B2-13, Singapore, 637457, Singapore.
Chunming Wang
Rohan R Varshney
Dong-An Wang
Nanyang Technological University · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of antisense strategies such as ribozymes, oligodeoxynucleotides (ODNs) and small interfering RNA (siRNA) in gene therapy, in conjunction with the use of stem cells and tissue engineering, has opened up possibilities in curing degenerative diseases and injuries to non-regenerating organs and tissues. With their unique ability to down-regulate or silence gene expression, antisense oligonucleotides are uniquely suited in turning down the production of pathogenic or undesirable proteins and cytokines. Here, we review the antisense strategies and their applications in regenerative medicine with a focus on their efficacies in promoting cell viability, regulating cell functionalities as well as shaping an optimal microenvironment for therapeutic purposes.

Indexed as

Genetic TherapyStem Cell TransplantationTissue EngineeringApoptosisArthritis, RheumatoidCardiovascular DiseasesCell DifferentiationCell ProliferationCell SurvivalGene Expression RegulationGene Transfer TechniquesHumansNerve DegenerationOligonucleotides, AntisenseRegenerationRegenerative MedicineOligonucleotides, AntisenseRNA, CatalyticRNA, Small Interfering

Identifiers

PMID19015958
OpenAlexW1988771204

What OpenQuestion holds

Textmetadata
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.