Evidence map›Paper›PMID 42583167›Full record

ArticleNanoscale advances2026

SPAN 60 and TWEEN 60 surfactant-based niosomal vesicles: from preparation to molecular dynamics simulations.

Martina Ježková, Ashley H George, Mario Vazdar, Jiří Mikšátko, Jaroslav Hanuš, Miroslav Šoós

Abstract read
In one paragraph

Article in Nanoscale advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Martina JežkováDepartment of Chemical Engineering, University of Chemistry and Technology Prague Technická 5 166 28 Prague 6 Czech Republic miroslav.soos@vscht.cz.
Ashley H GeorgeDepartment of Chemical Engineering, University of Chemistry and Technology Prague Technická 5 166 28 Prague 6 Czech Republic miroslav.soos@vscht.cz.
Mario VazdarDepartment of Mathematics, Informatics, and Cybernetics, University of Chemistry and Technology Prague Technická 5 166 28 Prague 6 Czech Republic.
Jiří MikšátkoImaging Methods Core Facility, Charles University in Prague, Faculty of Science Prague Czech Republic.
Jaroslav HanušDepartment of Chemical Engineering, University of Chemistry and Technology Prague Technická 5 166 28 Prague 6 Czech Republic miroslav.soos@vscht.cz.
Miroslav ŠoósDepartment of Chemical Engineering, University of Chemistry and Technology Prague Technická 5 166 28 Prague 6 Czech Republic miroslav.soos@vscht.cz.ORCID https://orcid.org/0000-0002-9742-7160

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The role of vesicular systems in the field of drug delivery has led to increased research in the optimization of these novel delivery methods. Niosomes are bilayer structures that are capable of encapsulating lipophilic and hydrophilic compounds. In this study, niosomal systems formed from either Span 60 or Tween 60 non-ionic surfactants were investigated through experimental work and molecular dynamics simulations. Niosomes were prepared using thin-film hydration (TFH) and organic phase injection (OPI) methods and characterized in terms of particle size, polydispersity index, zeta potential, morphology, and encapsulation efficiency. A low-molecular-weight active pharmaceutical ingredient, tetracaine, and its water-soluble form, tetracaine HCl, were employed to understand the effect of pH on the encapsulation efficiency (EE) of the process. The molecular dynamics simulation of the niosomal system provided information on the distribution of Span 60 or Tween 60 surfactant molecules within the bilayer and the behavior of the tetracaine molecule.

Identifiers

PMID42583167
PMCPMC13459183

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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.