Evidence map›Paper›PMID 38196347›Full record

ReviewPhysical chemistry chemical physics : PCCP2024

Glycyrrhizic acid aggregates seen from a synthetic surfactant perspective.

Peter Fischer, Viviane Lutz-Bueno

Abstract readReview
In one paragraph

Review in Physical chemistry chemical physics : PCCP, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

2 authors.

Peter FischerInstitute of Food, Nutrition and Health, ETH Zurich, 8092 Zurich, Switzerland. peter.fischer@hest.ethz.ch.ORCID http://orcid.org/0000-0002-2992-5037
Viviane Lutz-BuenoLaboratory of Neutron Scattering and Imaging, Paul Scherrer Institut PSI, 5232 Villigen, Switzerland. viviane.lutz-bueno@psi.ch.ORCID http://orcid.org/0000-0001-9735-5470

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bio- or plant-based surfactants are a sustainable and renewable alternative to replace synthetic chemicals for environmental, drugs and food applications. However, these "green" surfactants have unique molecular structures, and their self-assembly in water might lead to complex morphologies and unexpected properties. The micellization of saponin molecules, such as glycyrrhizic acid (GA), differs significantly from those of conventional synthetic surfactants, yet these differences are often overlooked. Saponins self-assemble in complex hierarchical helical morphologies similar to bile salts, rather than the expected globular, ellipsoidal and wormlike micelles. Here, we review two potential routes for molecular self-assembly of GA, namely kinetics of crystallization and thermodynamic equilibrium, focusing on their structure as a function of concentration. Some uncertainty remains to define which route is followed by GA self-assembly, as well as the first type of aggregate formed at low concentrations, thus we review the state-of-the-art information about GA assembly. We compare the self-assembly of GA with conventional linear surfactants, and identify their key similarities and differences, from molecular and chemical perspectives, based on the critical packing parameter (CPP) theory. We expect that this work will provide perspectives for the unclear process of GA assembly, and highlight its differences from conventional micellization.

Indexed as

Glycyrrhizic AcidSurface-Active AgentsMicellesMolecular StructureWaterGlycyrrhizic AcidMicellesSurface-Active AgentsWater

Identifiers

PMID38196347
PMCPMC10806618

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.