Evidence map›Paper›PMID 24013011›Full record

ReviewBiotechnology advances

Rigid nanoparticle-based delivery of anti-cancer siRNA: challenges and opportunities.

Zhiyong Wang, Gang Liu, Hairong Zheng, Xiaoyuan Chen

Abstract readReview
In one paragraph

Review in Biotechnology advances. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

26 citing papers in PubMed, 81 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Self-assembled Viral Nanoparticles as Targeted Anticancer Vehicles.Biotechnology and bioprocess engineering : BBE · 2021
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. The Daniel K. Inouye College of Pharmacy Scripts: Targeted Nanocarrier Based Systems for the Treatment of Lung Cancer.Hawai'i journal of medicine & public health : a journal of Asia Pacific Medicine & Public Health · 2017
    Review
  18. Review
  19. Ligand-targeted theranostic nanomedicines against cancer.Journal of controlled release : official journal of the Controlled Release Society · 2016
    Review
  20. 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 3 institutions in 2 countries.

Zhiyong WangCenter for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen, Fujian 361102, China; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Key Laboratory for MRI, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Gang LiuCenter for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen, Fujian 361102, China; State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen 361102, China; MOE key Lab of Spectrochemical Analysis & Instrumentation, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China. Electronic address: gangliu.cmitm@xmu.edu.cn.
Hairong ZhengPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Key Laboratory for MRI, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Xiaoyuan ChenLaboratory of Molecular Imaging and Nanomedicine (LOMIN), National Institute of Biomedical Imaging and Bioengineering (NIBIB), National Institutes of Health (NIH), Bethesda, MD 20892, USA. Electronic address: shawn.chen@nih.gov.
Xiamen University · CNNational Institute of Biomedical Imaging and Bioengineering · USShenzhen Institutes of Advanced Technology · CN

Funding

Laboratory of Molecular Imaging and NanomedicineZIAEB000073 · NIBIB · NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING · PI CHEN, XIAOYUAN · 2010 to 2020
$32.8M
Intramural NIH HHS Z99 EB999999Intramural NIH HHS ZIA EB000073
6 · The paper itself

Abstract

Gene therapy is a promising strategy to treat various genetic and acquired diseases. Small interfering RNA (siRNA) is a revolutionary tool for gene therapy and the analysis of gene function. However, the development of a safe, efficient, and targetable non-viral siRNA delivery system remains a major challenge in gene therapy. An ideal delivery system should be able to encapsulate and protect the siRNA cargo from serum proteins, exhibit target tissue and cell specificity, penetrate the cell membrane, and release its cargo in the desired intracellular compartment. Nanomedicine has the potential to deal with these challenges faced by siRNA delivery. The unique characteristics of rigid nanoparticles mostly inorganic nanoparticles and allotropes of carbon nanomaterials, including high surface area, facile surface modification, controllable size, and excellent magnetic/optical/electrical properties, make them promising candidates for targeted siRNA delivery. In this review, recent progresses on rigid nanoparticle-based siRNA delivery systems will be summarized.

Indexed as

Antineoplastic AgentsBiomarkersCalcium PhosphatesCell MembraneFerric CompoundsGene SilencingGenetic TherapyGene Transfer TechniquesGoldHumansImmunity, InnateLigandsNanoparticlesNanotechnologyNanotubes, CarbonNeoplasmsAntineoplastic AgentsBiomarkerscalcium phosphateCalcium PhosphatesFerric Compoundsferric oxideGoldLigandsNanotubes, CarbonRNA, Small InterferingSilicon DioxideGene deliveryGene therapyNanoparticlesRNA interference (RNAi)Small-interfering RNA (siRNA)

Identifiers

PMID24013011
PMCPMC3947394
OpenAlexW2058333505

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.