Evidence map›Paper›PMID 17285739›Full record

ReviewThe AAPS journal2006

Optimizing targeted gene delivery: chemical modification of viral vectors and synthesis of artificial virus vector systems.

Sabine Boeckle, Ernst Wagner

Abstract readReview
In one paragraph

Review in The AAPS journal, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
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

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Innovations in gene and growth factor delivery systems for diabetic wound healing.Journal of tissue engineering and regenerative medicine · 2018
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Viral and nonviral delivery systems for gene delivery.Advanced biomedical research · 2012
    Article
  12. Article
  13. Building Cell Selectivity into CPP-Mediated Strategies.Pharmaceuticals (Basel, Switzerland) · 2010
    Review
  14. Article
  15. Article
  16. 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

2 authors.

Sabine BoecklePharmaceutical Biology--Biotechnology, Department of Pharmacy, Ludwig-Maximilians- Universität München, Germany.
Ernst Wagner

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In comparison to classical medicines, gene therapy has the potential to mediate the highest possible level of therapeutic specificity. Every normal or diseased cell can switch on or off a gene expression cassette in a tissue-, disease-, and time-dependent fashion, by use of specific transcription factors that are active only in a given unique situation. In practice, we face the problem in realizing the concept: the delivery of nucleic acids into target cells is very ineffective and presents a formidable challenge. Key issues for future developments include improved targeting, enhanced intracellular uptake, and reduced toxicity of gene vectors. The currently used classes of vectors have complementary characteristics, such as high intracellular efficiency of viral vectors on the one hand and low immunogenicity and greater flexibility of nonviral vectors on the other hand. The merge of viral and nonviral vector technologies is highlighted as an encouraging strategy for the future; concepts include chemically modified viral vectors ("chemo-viruses") and synthesis of virus-like systems ("synthetic viruses"). Examples for the development of vectors toward artificial synthetic viruses are presented.

Indexed as

Gene Transfer TechniquesAnimalsGene TargetingGenetic TherapyGenetic VectorsHumansViruses

Identifiers

PMID17285739
PMCPMC2751370

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.