Evidence map›Paper›PMID 29163792›Full record

ArticleOncotarget2017

Dual-targeting nanoparticles with excellent gene transfection efficiency for gene therapy of peritoneal metastasis of colorectal cancer.

Ling Li, Rui Deng, Yi Su, Cheng Yang

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 31% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. In vivo gene delivery mediated by non-viral vectors for cancer therapy.Journal of controlled release : official journal of the Controlled Release Society · 2020
    Review
  3. Review
  4. Article
  5. 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

4 authors at 2 institutions in 1 country.

Ling Li *The Key Laboratory of Food Colloids and Biotechnology, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi 214122, China.
Rui Deng *Hematology Department and Hematopoietic Stem Cell Transplantation Center, Cheng Du Military General Hospital of PLA, Chengdu 610083, China.
Yi SuHematology Department and Hematopoietic Stem Cell Transplantation Center, Cheng Du Military General Hospital of PLA, Chengdu 610083, China.
Cheng YangThe Key Laboratory of Food Colloids and Biotechnology, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi 214122, China.
Chengdu Military General Hospital · CNJiangnan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer has been one of the most common cancers in the worldwide. Poor patient compliance and serious side effects often associated with conventional therapy (e.g. surgery, radiation, and chemotherapy). Gene therapy may be an alternative strategy. Herein, we developed a dual-targeting nanoparticle with excellent gene transfection efficiency for gene therapy of peritoneal metastasis of colorectal cancer. This nanoparticle can facilitate efficient cellular uptake and promote penetration into nucleus. Meanwhile, this nanoparticle mediated efficient gene transfection in medium with or without serum, which significantly surpassed that of commercial transfection reagents, Lipofectamine 2000 and Lipofectamine 3000. After systemic administration, this nanoparticle loaded with hTRAIL plasmid significantly inhibited peritoneal metastasis of colorectal cancer

Indexed as

colorectal cancerdual-targeting nanoparticlegene therapyperitoneal metastasis

Identifiers

PMID29163792
PMCPMC5685713
OpenAlexW2757870176

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.