Evidence map›Paper›PMID 27347092›Full record

ArticleOncology letters2016

Applications of nanoparticle drug delivery systems for the reversal of multidrug resistance in cancer.

Yinghong Huang, Susan P C Cole, Tiange Cai, Y U Cai

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
5.0field-weighted citation impact, top 5% 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

17 citing papers in PubMed, 63 citations in OpenAlex.

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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.

Yinghong HuangDepartment of Traditional Chinese Medicine, College of Pharmacy, Jinan University, Guangzhou, Guangdong 510632, P.R. China.
Susan P C ColeDepartment of Pathology and Molecular Medicine, Division of Cancer Biology and Genetics, Queen's University Cancer Research Institute, Kingston, ON K7L 3N6, Canada.
Tiange CaiDepartment of Biological Sciences, College of Life Sciences, Liaoning University, Shenyang, Liaoning 110036, P.R. China.
Y U CaiDepartment of Traditional Chinese Medicine, College of Pharmacy, Jinan University, Guangzhou, Guangdong 510632, P.R. China; Cancer Institute of Jinan University, Guangzhou, Guangdong 510632, P.R. China.
Jinan University · CNLiaoning University · CNQueen's University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multidrug resistance (MDR) to chemotherapy presents a major obstacle in the treatment of cancer patients, which directly affects the clinical success rate of cancer therapy. Current research aims to improve the efficiency of chemotherapy, whilst reducing toxicity to prolong the lives of cancer patients. As with good biocompatibility, high stability and drug release targeting properties, nanodrug delivery systems alter the mechanism by which drugs function to reverse MDR, via passive or active targeting, increasing drug accumulation in the tumor tissue or reducing drug elimination. Given the potential role of nanodrug delivery systems used in multidrug resistance, the present study summarizes the current knowledge on the properties of liposomes, lipid nanoparticles, polymeric micelles and mesoporous silica nanoparticles, together with their underlying mechanisms. The current review aims to provide a reliable basis and useful information for the development of new treatment strategies of multidrug resistance reversal using nanodrug delivery systems.

Indexed as

applicationscancerliposomesMDRMSNsnanoparticle drug delivery systemNLCphospholipid bilayerPLNpolymeric micellesSLN

Identifiers

PMID27347092
PMCPMC4907090
OpenAlexW2402558378

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.