Evidence map›Paper›PMID 39107282›Full record

ArticleNature communications2024

Heterogeneously deacetylated chitosans possess an unexpected regular pattern favoring acetylation at every third position.

Margareta J Hellmann, Dominique Gillet, Stéphane Trombotto, Sonja Raetz, Bruno M Moerschbacher, Stefan Cord-Landwehr

Abstract read
In one paragraph

Article in Nature communications, 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. Article
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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

6 authors.

Margareta J HellmannInstitute for Biology and Biotechnology of Plants, University of Münster, 48143, Münster, Germany.ORCID 0000-0002-3500-9465
Dominique GilletGillet Chitosan SAS, La Ville Es Comte, 22350, Plumaudan, France.
Stéphane TrombottoIngénierie des Matériaux Polymères (IMP), UMR 5223, Université Claude Bernard Lyon 1, CNRS, INSA Lyon, Université Jean Monnet Saint-Etienne, F-69622, Villeurbanne, France.
Sonja RaetzInstitute for Biology and Biotechnology of Plants, University of Münster, 48143, Münster, Germany.ORCID 0009-0000-0896-8700
Bruno M MoerschbacherInstitute for Biology and Biotechnology of Plants, University of Münster, 48143, Münster, Germany. moersch@uni-muenster.de.ORCID 0000-0001-6067-3205
Stefan Cord-LandwehrInstitute for Biology and Biotechnology of Plants, University of Münster, 48143, Münster, Germany.ORCID 0000-0003-1915-1936

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chitosans are promising biopolymers for diverse applications, with material properties and bioactivities depending i.a. on their pattern of acetylation (PA). Commercial chitosans are typically produced by heterogeneous deacetylation of chitin, but whether this process yields chitosans with a random or block-wise PA has been debated for decades. Using a combination of recently developed in vitro assays and in silico modeling surprisingly revealed that both hypotheses are wrong; instead, we found a more regular PA in heterogeneously deacetylated chitosans, with acetylated units overrepresented at every third position in the polymer chain. Compared to random-PA chitosans produced by homogeneous deacetylation of chitin or chemical N-acetylation of polyglucosamine, this regular PA increases the elicitation activity in plants, and generates different product profiles and distributions after enzymatic and chemical cleavage. A regular PA may be beneficial for some applications but detrimental for others, stressing the relevance of the production process for product development.

Indexed as

ChitinChitosanAcetylationChitinChitosan

Identifiers

PMID39107282
PMCPMC11303684

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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.