Evidence map›Paper›PMID 29872622›Full record

ReviewActa pharmaceutica Sinica. B2018

Reconstituted high-density lipoproteins: novel biomimetic nanocarriers for drug delivery.

Xinyi Ma, Qingxiang Song, Xiaoling Gao

Abstract readReview
In one paragraph

Review in Acta pharmaceutica Sinica. B, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
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  15. Article
  16. Article
  17. HDLs extract lipophilic drugs from cells.Journal of cell science · 2022
    Article
  18. Biomimetic nanoparticles for tumor immunotherapy.Frontiers in bioengineering and biotechnology · 2022
    Review
  19. Cell-Free Membrane Protein Expression into Hybrid Lipid/Polymer Vesicles.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  20. Apolipoprotein mimetics in cancer.Seminars in cancer biology · 2021
    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

3 authors.

Xinyi MaDepartment of Pharmacology and Chemical Biology, Faculty of Basic Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Qingxiang SongDepartment of Pharmacology and Chemical Biology, Faculty of Basic Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Xiaoling GaoDepartment of Pharmacology and Chemical Biology, Faculty of Basic Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-density lipoproteins (HDL) are naturally-occurring nanoparticles that are biocompatible, non-immunogenic and completely biodegradable. These endogenous particles can circulate for an extended period of time and transport lipids, proteins and microRNA from donor cells to recipient cells. Based on their intrinsic targeting properties, HDL are regarded as promising drug delivery systems. In order to produce on a large scale and to avoid blood borne pollution, reconstituted high-density lipoproteins (rHDL) possessing the biological properties of HDL have been developed. This review summarizes the biological properties and biomedical applications of rHDL as drug delivery platforms. It focuses on the emerging approaches that have been developed for the generation of biomimetic nanoparticles rHDL to overcome the biological barriers to drug delivery, aiming to provide an alternative, promising avenue for efficient targeting transport of nanomedicine.

Indexed as

Biological barriersBiomimetic nanocarrierEfficient targetingNanodrug delivery systemsReconstituted high- density lipoprotein

Identifiers

PMID29872622
PMCPMC5985628

What OpenQuestion holds

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Registered trials

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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.