Evidence map›Paper›PMID 30377872›Full record

ArticleNanoscale research letters2018

Novel Delivery of Mitoxantrone with Hydrophobically Modified Pullulan Nanoparticles to Inhibit Bladder Cancer Cell and the Effect of Nano-drug Size on Inhibition Efficiency.

Xiaojun Tao, Ting Tao, Yi Wen, Jiajin Yi, Lihua He, Zixuan Huang, Yu Nie, Xiaoyan Yao, Yingying Wang, Chunlian He and 1 more

Open access · goldAbstract read
In one paragraph

Article in Nanoscale research letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

9 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. 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

11 authors at 1 institution in 1 country.

Xiaojun TaoKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China.
Ting TaoKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China.
Yi WenKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China.
Jiajin YiKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China.
Lihua HeKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China.
Zixuan HuangKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China.
Yu NieKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China.
Xiaoyan YaoKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China.
Yingying WangKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China.
Chunlian HeKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China.
Xiaoping YangKey Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province and Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, 410013, China. xiaoping.yang@hunnu.edu.cn.ORCID http://orcid.org/0000-0002-3451-9850
Hunan Normal University · CN

Funding

Hunan Provincial Health Commission General Project B2017073Key Project of Hunan Province 2016 2016JC2036Natural Science Foundation of Hunan Province (CN) 2016JJ2187Start-up Funds of the Key Laboratory of Study and Discovery of Targeted Small Molecules of Hunan Province 2017TP020
6 · The paper itself

Abstract

Reducing the dosage of chemotherapeutic drugs via enhancing the delivery efficiency using novel nanoparticles has great potential for cancer treatment. Here, we focused on improving mitoxantrone delivery by using cholesterol-substituted pullulan polymers (CHPs) and selected a suitable nano-drug size to inhibit the growth of bladder cancer cells. We synthesized three kinds of CHPs, named CHP-1, CHP-2, CHP-3. Their chemical structures were identified by NMR, and the degree of cholesterol substitution was 6.82%, 5.78%, and 2.74%, respectively. Their diameters were 86.4, 162.30, and 222.28 nm. We tested the release rate of mitoxantrone in phosphate-buffered saline for 48 h: the release rate was 38.73%, 42.35%, and 58.89% for the three CHPs. The hydrophobic substitution degree in the polymer was associated with the self-assembly process of the nanoparticles, which affected their size and therefore drug release rate. The release of the three drug-loaded nanoparticles was significantly accelerated in acid release media. The larger the nanoparticle, the greater the drug release velocity. At 24 h, the IC

Indexed as

Bladder cancerCholesterol-substituted pullulanHydrophobicNanoparticleSize

Identifiers

PMID30377872
PMCPMC6207605
OpenAlexW2899507986

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.