Evidence map›Paper›PMID 29180863›Full record

ArticleInternational journal of nanomedicine2017

Paclitaxel and quercetin nanoparticles co-loaded in microspheres to prolong retention time for pulmonary drug delivery.

Kang Liu, Weijuan Chen, Tingting Yang, Baofang Wen, Dejun Ding, Michael Keidar, Jinbao Tang, Weifen Zhang

Open access · goldAbstract read
In one paragraph

Article in International journal of nanomedicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
4.1field-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

23 citing papers in PubMed, 77 citations in OpenAlex.

  1. Quercetin Hybrids and their Biological Potential.Mini reviews in medicinal chemistry · 2026
    Review
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  16. Nanoparticle Delivery Systems with Cell-Specific Targeting for Pulmonary Diseases.American journal of respiratory cell and molecular biology · 2021
    Review
  17. Review
  18. Review
  19. Application of quercetin flavonoid based hybrid nanocomposites: A review.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2020
    Review
  20. Delivery of natural phenolic compounds for the potential treatment of lung cancer.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2019
    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

8 authors at 3 institutions in 2 countries.

Kang LiuCollege of Pharmacy, Weifang Medical University, Weifang.
Weijuan ChenDepartment of Pathology, People's Hospital of Shouguang, Shouguang, People's Republic of China.
Tingting YangCollege of Pharmacy, Weifang Medical University, Weifang.
Baofang WenCollege of Pharmacy, Weifang Medical University, Weifang.
Dejun DingCollege of Pharmacy, Weifang Medical University, Weifang.
Michael KeidarDepartment of Mechanical and Aerospace Engineering, School of Engineering and Applied Science, The George Washington University, Washington, DC, USA.
Jinbao TangCollege of Pharmacy, Weifang Medical University, Weifang.
Weifen ZhangCollege of Pharmacy, Weifang Medical University, Weifang.
Weifang Medical University · CNGeorge Washington University · USShougang (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High drug resistance, poor water solubility, short half-life, and low local drug concentration are obstacles for successful delivery of chemotherapeutic drugs for lung cancer. A new method involving the use of nanoparticles (NPs) for pulmonary delivery is proposed. However, use of NPs is limited by the particle size range for pulmonary drug delivery considering that NPs cannot be deposited directly into the lungs. NPs polymerized into microspheres (polymeric microspheres, PMs) will result in suitable particle sizes and retain the advantages of nanodrugs after redispersion when applied in pulmonary delivery. We report the development of novel NPs in the form of PMs loaded with paclitaxel (PTX) and quercetin (QUE) double drugs based on the synthesis of oleic acid-conjugated chitosan (OA-CTS) for pulmonary delivery. This approach is aimed toward prolonging PTX retention time in the presence of QUE and bypassing P-glycoprotein drug efflux pumps. NPs loaded with PTX or QUE were prepared with 11% substitution degree using OA-CTS as the carrier by ionic cross-linking method, which NPs loaded with PTX or QUE were used in the preparation of PMs by spray-drying. The diameters of the PMs ranged from 1 to 5 μm which had uniform size range. Scanning electron microscopy showed that PMs were polymers formed by a large number of NPs and readily redispersed (after redispersion, size of NPs ranged between 250 and 350 nm) in water within 1 h. PMs displayed slow-release characteristics at pH 4.5 and 7.4. The in vivo pharmacokinetic and biodistribution studies suggested that PMs exhibit prolonged circulation time and a markedly high accumulation in the lung. The obtained results indicate that PMs can serve as a promising pulmonary delivery system for combined pharmacotherapy using hydrophobic anticancer drugs.

Indexed as

AnimalsAntineoplastic AgentsATP Binding Cassette Transporter, Subfamily BATP Binding Cassette Transporter, Subfamily B, Member 1ChitosanDrug Delivery SystemsDrug LiberationFemaleHalf-LifeLungMaleMicrospheresNanoparticlesOleic AcidPaclitaxelParticle SizeAntineoplastic AgentsATP Binding Cassette Transporter, Subfamily BATP Binding Cassette Transporter, Subfamily B, Member 1ChitosanOleic AcidPaclitaxelQuercetinnanoparticlesoleic acid-conjugated chitosanpaclitaxelpolymeric microspherespulmonary deliveryquercetin

Identifiers

PMID29180863
PMCPMC5691910
OpenAlexW2770147253

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.