Evidence map›Paper›PMID 40189603›Full record

ArticleScientific reports2025

Assessing particle count in electron microscopy measurements of nanomaterials to support regulatory guidance.

Charlotte Wouters, Vikram Kestens, Eveline Verleysen, Jan Mast

Abstract read
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

4 authors.

Charlotte WoutersTrace Elements and Nanomaterials, Groeselenbergstraat 99, Sciensano, Uccle, 1180, Belgium. charlotte.wouters@sciensano.be.
Vikram KestensEuropean Commission, Joint Research Centre (JRC), Geel, Belgium.
Eveline VerleysenTrace Elements and Nanomaterials, Groeselenbergstraat 99, Sciensano, Uccle, 1180, Belgium.
Jan MastTrace Elements and Nanomaterials, Groeselenbergstraat 99, Sciensano, Uccle, 1180, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the European Union, nanomaterials are regulated through different pieces of sectoral legislation. This legislation often requires risk assessments and thus reliable characterization data, for which regulatory guidance generally recommend electron microscopy. The guidance provides best practices for measurements but lacks requirements on how many particles to measure. Using transmission electron microscopy data of nanomaterials, a strategy based on repeated subsampling is proposed to establish, for different particle size and shape measurands, mathematical relationships between particle count and precision, and subsequently to determine the minimum particle count. Our results confirm that the minimum particle count generally depends on the width of the size and shape distributions and that the median of the distribution can be determined with the highest precision compared to other percentiles. Upon combining the precision uncertainty related to particle number with uncertainties from other sources, such as sample preparation, calibration and trueness, we reach an optimal particle count above which additional particle measurements only yield negligible improvements to the combined measurement uncertainty. Our findings offer an experimental approach for determining the minimum particle count to measure particle size and shape by electron microscopy. It enables efficient analyses and facilitates compliance with legislation addressing nanomaterials across various application domains.

Indexed as

Electron microscopyNanomaterialParticle countParticle shapeParticle sizePrecisionRegulatory guidanceUncertainty

Identifiers

PMID40189603
PMCPMC11973222

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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.