Evidence map›Paper›PMID 38151495›Full record

ArticleScientific reports2023

Exploring the infiltrative and degradative ability of Fusarium oxysporum on polyethylene terephthalate (PET) using correlative microscopy and deep learning.

Flavio Cognigni, Marta Elisabetta Eleonora Temporiti, Lidia Nicola, Nicolas Gueninchault, Solveig Tosi, Marco Rossi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
5.4field-weighted citation impact, top 5% 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

4 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
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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 at 4 institutions in 2 countries.

Flavio CognigniDepartment of Basic and Applied Sciences for Engineering (SBAI), University of Rome LA SAPIENZA, 00185, Rome, Italy.
Marta Elisabetta Eleonora TemporitiLaboratory of Mycology, Department of Earth and Environmental Sciences, University of Pavia, 27100, Pavia, Italy.
Lidia NicolaLaboratory of Mycology, Department of Earth and Environmental Sciences, University of Pavia, 27100, Pavia, Italy. lidia.nicola@unipv.it.
Nicolas GueninchaultCarl Zeiss X-ray Microscopy, Inc, 5300 Central Parkway, Dublin, CA, 94568, USA.
Solveig TosiLaboratory of Mycology, Department of Earth and Environmental Sciences, University of Pavia, 27100, Pavia, Italy.
Marco RossiDepartment of Basic and Applied Sciences for Engineering (SBAI), University of Rome LA SAPIENZA, 00185, Rome, Italy.
Sapienza University of Rome · ITCarl Zeiss (United States) · USUniversity of Palermo · ITUniversity of Pavia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Managing the worldwide steady increase in the production of plastic while mitigating the Earth's global pollution is one of the greatest challenges nowadays. Fungi are often involved in biodegradation processes thanks to their ability to penetrate into substrates and release powerful catabolic exoenzymes. However, studying the interaction between fungi and plastic substrates is challenging due to the deep hyphal penetration, which hinders visualisation and evaluation of fungal activity. In this study, a multiscale and multimodal correlative microscopy workflow was employed to investigate the infiltrative and degradative ability of Fusarium oxysporum fungal strain on polyethylene terephthalate (PET) fragments. The use of non-destructive high-resolution 3D X-ray microscopy (XRM) coupled with a state-of-art Deep Learning (DL) reconstruction algorithm allowed optimal visualisation of the distribution of the fungus on the PET fragment. The fungus preferentially developed on the edges and corners of the fragment, where it was able to penetrate into the material through fractures. Additional analyses with scanning electron microscopy (SEM), Raman and energy dispersive X-ray spectroscopy (EDX) allowed the identification of the different phases detected by XRM. The correlative microscopy approach unlocked a more comprehensive understanding of the fungus-plastic interaction, including elemental information and polymeric composition.

Indexed as

Deep LearningFusariumFungiMicroscopy, Electron, ScanningPolyethylene TerephthalatesPolyethylene Terephthalates

Identifiers

PMID38151495
PMCPMC10752890
OpenAlexW4390264404

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.