Evidence map›Paper›PMID 32294992›Full record

ArticlePolymers2020

Binary Solutions of Hyaluronan and Lactose-Modified Chitosan: The Influence of Experimental Variables in Assembling Complex Coacervates.

Federica Vecchies, Pasquale Sacco, Eleonora Marsich, Giuseppe Cinelli, Francesco Lopez, Ivan Donati

Abstract read
In one paragraph

Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Effect of α-Amylase on the Structure of Chia Seed Mucilage.Biomimetics (Basel, Switzerland) · 2022
    Article
  3. 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

6 authors.

Federica VecchiesUniversity of Trieste, Department of Life Science, Via Licio Giorgieri, 5, 34127, Trieste, Italy.
Pasquale SaccoUniversity of Trieste, Department of Life Science, Via Licio Giorgieri, 5, 34127, Trieste, Italy.
Eleonora MarsichDepartment of Medicine, Surgery, and Health Sciences, University of Trieste, Piazza dell'Ospitale 1, I-34129 Trieste, Italy.
Giuseppe CinelliDepartment of Agricultural, Environmental and Food Sciences (DiAAA), Università degli Studi del Molise, Via De Sanctis, I-86100 Campobasso, Italy.
Francesco LopezDepartment of Agricultural, Environmental and Food Sciences (DiAAA), Università degli Studi del Molise, Via De Sanctis, I-86100 Campobasso, Italy.
Ivan DonatiUniversity of Trieste, Department of Life Science, Via Licio Giorgieri, 5, 34127, Trieste, Italy.

Funding

Interreg 1472551605
6 · The paper itself

Abstract

A miscibility study between oppositely charged polyelectrolytes, namely hyaluronic acid and a lactose-modified chitosan, is here reported. Experimental variables such as polymers' weight ratios, pH values, ionic strengths and hyaluronic acid molecular weights were considered. Transmittance analyses demonstrated the mutual solubility of the two biopolymers at a neutral pH. The onset of the liquid-liquid phase separation due to electrostatic interactions between the two polymers was detected at pH 4.5, and it was found to be affected by the overall ionic strength, the modality of mixing and the polymers' weight ratio. Thorough Dynamic Light Scattering (DLS) measurements were performed to check the quality of the formed coacervates by investigating their dimensions, homogeneity and surface charge. The whole DLS results highlighted the influence of the hyaluronic acid molecular weight in affecting coacervates' dispersity and size.

Indexed as

characterizationcomplex coacervationexperimental variableshyaluronic acidlactose-modified chitosan

Identifiers

PMID32294992
PMCPMC7240600

What OpenQuestion holds

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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.