Evidence map›Paper›PMID 34960834›Full record

ArticlePolymers2021

Electrospun Structural Hybrids of Acyclovir-Polyacrylonitrile at Acyclovir for Modifying Drug Release.

He Lv, Shiri Guo, Gaoyi Zhang, Wanli He, Yonghui Wu, Deng-Guang Yu

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In one paragraph

Article in Polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

He LvSchool of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai 200093, China.
Shiri GuoSchool of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai 200093, China.
Gaoyi ZhangSchool of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Wanli HeSchool of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai 200093, China.
Yonghui WuThe Department of Mechanical Engineering, Guangxi Technological College of Machinery and Electricity, Nanning 530007, China.
Deng-Guang YuSchool of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai 200093, China.ORCID 0000-0001-7825-4498

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In traditional pharmaceutics, drug-crystalline nanoparticles and drug-polymer composites are frequently explored for their ability to modify drug release profiles. In this study, a novel sort of hybrid with a coating of acyclovir crystalline nanoparticles on acyclovir-polyacrylonitrile composites was fabricated using modified, coaxial electrospinning processes. The developed acyclovir-polyacrylonitrile at the acyclovir nanohybrids was loaded with various amounts of acyclovir, which could be realized simply by adjusting the sheath fluid flow rates. Compared with the electrospun composite nanofibers from a single-fluid blending process, the nanohybrids showed advantages of modifying the acyclovir release profiles in the following aspects: (1) the initial release amount was more accurately and intentionally controlled; (2) the later sustained release was nearer to a zero-order kinetic process; and (3) the release amounts at different stages could be easily allocated by the sheath fluid flow rate. X-ray diffraction results verified that the acyclovir nanoparticles were in a crystalline state, and Fourier-transform infrared spectra verified that the drug acyclovir and the polymer polyacrylonitrile had a good compatibility. The protocols reported here could pave the way for developing new types of functional nanostructures.

Indexed as

coaxial electrospinningmedicated nanomaterialsmodified releasepolymeric nanocompositesstructural hybrids

Identifiers

PMID34960834
PMCPMC8708694

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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.