Evidence map›Paper›PMID 23201315›Full record

ArticleAntiviral research2013

Novel polymeric inhibitors of HCoV-NL63.

Aleksandra Milewska, Justyna Ciejka, Kamil Kaminski, Anna Karewicz, Dorota Bielska, Slawomir Zeglen, Wojciech Karolak, Maria Nowakowska, Jan Potempa, Berend Jan Bosch and 2 more

Open access · greenAbstract read
In one paragraph

Article in Antiviral research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

49 citing papers in PubMed, 82 citations in OpenAlex.

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  17. Polymeric Materials as Potential Inhibitors Against SARS-CoV-2.Journal of polymers and the environment · 2022
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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

12 authors at 4 institutions in 3 countries.

Aleksandra MilewskaMicrobiology Department, Faculty of Biochemistry Biophysics and Biotechnology, Jagiellonian University, Krakow, Poland.
Justyna Ciejka
Kamil Kaminski
Anna Karewicz
Dorota Bielska
Slawomir Zeglen
Wojciech Karolak
Maria Nowakowska
Jan Potempa
Berend Jan Bosch
Krzysztof Pyrc
Krzysztof Szczubialka
Jagiellonian University · PLSilesian Center for Heart Disease · PLUniversity of Louisville · USUtrecht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human coronavirus NL63 is generally classified as a common cold pathogen, though the infection may also result in severe lower respiratory tract diseases, especially in children, patients with underlying disease, and elderly. It has been previously shown that HCoV-NL63 is also one of the most important causes of croup in children. In the current manuscript we developed a set of polymer-based compounds showing prominent anticoronaviral activity. Polymers have been recently considered as promising alternatives to small molecule inhibitors, due to their intrinsic antimicrobial properties and ability to serve as matrices for antimicrobial compounds. Most of the antimicrobial polymers show antibacterial properties, while those with antiviral activity are much less frequent. A cationically modified chitosan derivative, N-(2-hydroxypropyl)-3-trimethylammonium chitosan chloride (HTCC), and hydrophobically-modified HTCC were shown to be potent inhibitors of HCoV-NL63 replication. Furthermore, both compounds showed prominent activity against murine hepatitis virus, suggesting broader anticoronaviral activity.

Indexed as

AnimalsAntiviral AgentsCationsCell LineChitosanCoronavirus NL63, HumanHumansMacaca mulattaMurine hepatitis virusVirus ReplicationAntiviral AgentsCationsChitosan

Identifiers

PMID23201315
PMCPMC7114096
OpenAlexW1977129657

What OpenQuestion holds

Textmetadata
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.