Evidence map›Paper›PMID 41436592›Full record

ArticleScientific reports2025

Co-staining microplastics with Nile Red and Rose Bengal for improved optical quantification.

Benedetta Villa, Gaia Bolla, Isabella Gambino, Elisa Terzaghi, Ginevra Boldrocchi, Enrica Baldini, Filippo Brusa, Stefania Federici, Serena Ducoli, Giovanni Bergna and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. 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
–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

4 citing papers in PubMed.

  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

14 authors.

Benedetta VillaDepartment of Science and High Technology, University of Insubria, Via Valleggio 11, Como, Italy.
Gaia BollaDepartment of Science and High Technology, University of Insubria, Via Valleggio 11, Como, Italy.
Isabella GambinoDepartment of Science and High Technology, University of Insubria, Via Valleggio 11, Como, Italy.
Elisa TerzaghiDepartment of Science and High Technology, University of Insubria, Via Valleggio 11, Como, Italy.
Ginevra BoldrocchiDepartment of Human Sciences, Innovation and Territory, University of Insubria, Via Valleggio, 11, Como, Italy.
Enrica BaldiniCentro Tessile Serico Sostenibile (CTSS), Via Castelnuovo 3, Como, 22100, Italy.
Filippo BrusaCentro Tessile Serico Sostenibile (CTSS), Via Castelnuovo 3, Como, 22100, Italy.
Stefania FedericiDepartment of Mechanical and Industrial Engineering, INSTM Unit of Brescia, University of Brescia, Via Branze 38, Brescia, 25123, Italy.
Serena DucoliDepartment of Mechanical and Industrial Engineering, INSTM Unit of Brescia, University of Brescia, Via Branze 38, Brescia, 25123, Italy.
Giovanni BergnaLariana Depur S.p.a, Via Laghetto 1, 22073 Fino Mornasco, Como, Italy.
Alberto ZoccaliDepartment of Civil and Environmental Engineering (DICA) - Environmental Section, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milano, 20133, Italy.
Francesca MalpeiDepartment of Civil and Environmental Engineering (DICA) - Environmental Section, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milano, 20133, Italy.
Antonio Di GuardoDepartment of Science and High Technology, University of Insubria, Via Valleggio 11, Como, Italy.
Roberta BettinettiDepartment of Human Sciences, Innovation and Territory, University of Insubria, Via Valleggio, 11, Como, Italy. roberta.bettinetti@uninsubria.it.

Funding

European Commission LIFE22-ENV - LIFE CASCADE contract no. 101113942
6 · The paper itself

Abstract

Accurate assessment of microplastic (MP) contamination in environmental samples is crucial not only for understanding the scope of this growing environmental threat but also for quantifying its magnitude and enabling proper risk assessment. However, current methodologies for MP quantification often suffer from inaccuracies due to the difficulty in distinguishing plastic particles from natural organic matter, also due to incomplete digestion of natural polymers during sample treatment. Moreover, the techniques commonly employed are highly time-consuming, further limiting their routine application. This research presents an innovative solution for optical microscopy evaluation: a sequential co-staining technique employing Nile Red (NR) and Rose Bengal (RB) to identify natural vs. synthetic polymer fragments as well as false positives. Two experiments were implemented staining natural polymers (cellulose, protein, lignin, and chitin) and synthetic polymers (Polyvinyl Chloride (PVC), Polystyrene (PS), Polyethylene Terephthalate (PET), Polypropylene (PP), Nylon (NY), High-Density Polyethylene (HDPE) and Low-Density Polyethylene (LDPE)) with the two dyes. The results showed that co-staining is an effective way of separating natural and synthetic fragments and a significant improvement in the accuracy of visual MP identification. Additionally, co-staining the same filter allows to obtain relevant time saving as well as reducing counting and identification errors, since no sample exchange is needed. Application of this novel technique will allow for more reliable monitoring of MP concentrations in various environmental matrices, leading to better-informed risk assessments and mitigation strategies.

Indexed as

Digital microscopeMicroplasticsNile redOptical quantificationRose bengalVisual analysis

Identifiers

PMID41436592
PMCPMC12830938

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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.