Evidence map›Paper›PMID 32450105›Full record

ReviewAdvanced drug delivery reviews2020

Membrane-core nanoparticles for cancer nanomedicine.

Jianfeng Guo, Leaf Huang

Open access · greenAbstract readReview
In one paragraph

Review in Advanced drug delivery reviews, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.0field-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

22 citing papers in PubMed, 66 citations in OpenAlex.

  1. A sequentially programmed FeMaterials today. Bio · 2026
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  17. Advanced Nanotheranostics of CRISPR/Cas for Viral Hepatitis and Hepatocellular Carcinoma.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021
    Review
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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

2 authors at 1 institution in 2 countries.

Jianfeng GuoDivision of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599, USA; School of Pharmaceutical Sciences, Jilin University, Changchun 130021, China.
Leaf HuangDivision of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address: leafh@email.unc.edu.
University of North Carolina at Chapel Hill · US

Funding

Small Animal Imaging CoreU54CA198999 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LI, ZIBO · 2015 to 2019
$11.9M
NCI NIH HHS U54 CA198999
6 · The paper itself

Abstract

Cancer is one of the most severe disease burdens in modern times, with an estimated increase in the number of patients diagnosed globally from 18.1 million in 2018 to 23.6 million in 2030. Despite a significant progress achieved by conventional therapies, they have limitations and are still far from ideal. Therefore, safe, effective and widely-applicable treatments are urgently needed. Over the past decades, the development of novel delivery approaches based on membrane-core (MC) nanostructures for transporting chemotherapeutics, nucleic acids and immunomodulators has significantly improved anticancer efficacy and reduced side effects. In this review, the formulation strategies based on MC nanostructures for delivery of anticancer drug are described, and recent advances in the application of MC nanoformulations to overcome the delivery hurdles for clinical translation are discussed.

Indexed as

Cell MembraneDrug Delivery SystemsAnimalsAntineoplastic AgentsHumansNanomedicineNanoparticlesNeoplasmsAntineoplastic AgentsCombination therapyDrug deliveryHybrid nanostructured materialsNanoparticlesTumor microenvironment

Identifiers

PMID32450105
PMCPMC7680273
OpenAlexW3026546957

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.