Evidence map›Paper›PMID 41474269›Full record

ArticleAnalytical chemistry2026

Online Coupling of Field-Flow Fractionation with Raman Microspectroscopy Enables the Advanced Study of Nanoplastics Directly in Food.

Stefano Giordani, Maximilian J Huber, Isabel S Jüngling, Andrea Zattoni, Barbara Roda, Pierluigi Reschiglian, Valentina Marassi, Natalia P Ivleva

Abstract read
In one paragraph

Article in Analytical chemistry, 2026. 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. 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

8 authors.

Stefano GiordaniDepartment of Chemistry "Giacomo Ciamician", University of Bologna, 40129 Bologna, Italy.
Maximilian J HuberChair of Analytical Chemistry and Water Chemistry, School of Natural Sciences, Technical University of Munich, Garching 85748, Germany.ORCID 0000-0003-3734-2103
Isabel S JünglingChair of Analytical Chemistry and Water Chemistry, School of Natural Sciences, Technical University of Munich, Garching 85748, Germany.
Andrea ZattoniDepartment of Chemistry "Giacomo Ciamician", University of Bologna, 40129 Bologna, Italy.
Barbara RodaDepartment of Chemistry "Giacomo Ciamician", University of Bologna, 40129 Bologna, Italy.
Pierluigi ReschiglianDepartment of Chemistry "Giacomo Ciamician", University of Bologna, 40129 Bologna, Italy.
Valentina MarassiDepartment of Chemistry "Giacomo Ciamician", University of Bologna, 40129 Bologna, Italy.ORCID 0000-0001-8742-3708
Natalia P IvlevaChair of Analytical Chemistry and Water Chemistry, School of Natural Sciences, Technical University of Munich, Garching 85748, Germany.ORCID 0000-0002-7685-5166

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The detection and understanding of the behavior of nanoplastics (NPLs) in complex (in)organic systems is a growing concern and one of the major challenges in analytical chemistry today. Current analytical methods are limited in terms of sample flexibility and automation, often require laborious pretreatment, and usually only provide limited information about the presence of NPLs without assessing the behavior of the plastics in the matrix. Coupling an asymmetrical flow field-flow fractionation multidetector (AF4-MD) platform with Raman microspectroscopy (RM) represents a significant advancement in the field, offering a novel approach that combines the advantages of a highly flexible, automatable, and informative analytical system (AF4-MD) with a detector able to chemically identify NPLs (RM). Up to now, this pioneering technique has only been used to study different nanoparticles in an aqueous environment. Here, for the first time, we report the application of an AF4-MD-RM platform to detect NPLs in a real unprocessed matrix. The developed approach allowed for the separation, selective detection, and multiparametric characterization of milk components and NPLs (polystyrene, PS beads, 100-500 nm) in a short analytical time without sample pretreatment, while providing PS detection threshold values compatible with those of the currently exploited quantification approaches. These beyond the state-of-the-art results were proved with orthogonal techniques and highlight the game-changing potential of AF4-MD-RM for a straightforward detection of NPLs in complex matrices and the characterization of NPL-matrix interactions.

Indexed as

Food AnalysisFood ContaminationFractionation, Field FlowMicroplasticsMilkNanoparticlesSpectrum Analysis, RamanAnimalsMicroplastics

Identifiers

PMID41474269
PMCPMC12809650

What Socratic 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 Socratic graph.