Evidence map›Paper›PMID 39887143›Full record

ArticleAnnals of work exposures and health2025

The Nano Exposure Quantifier: a quantitative model for assessing nanoparticle exposure in the workplace.

Ruby Vermoolen, Remy Franken, Tanja Krone, Neeraj Shandilya, Henk Goede, Hasnae Ben Jeddi, Eelco Kuijpers, Calvin Ge, Wouter Fransman

Abstract read
In one paragraph

Article in Annals of work exposures and health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Ruby VermoolenTNO, Princetonlaan 6, PO Box 80015, Utrecht 3584 CB, The Netherlands.ORCID 0009-0005-5283-4757
Remy FrankenTNO, Princetonlaan 6, PO Box 80015, Utrecht 3584 CB, The Netherlands.ORCID 0000-0001-9382-3169
Tanja KroneTNO, Princetonlaan 6, PO Box 80015, Utrecht 3584 CB, The Netherlands.ORCID 0000-0003-4902-9907
Neeraj ShandilyaTNO, Princetonlaan 6, PO Box 80015, Utrecht 3584 CB, The Netherlands.ORCID 0000-0003-3328-8517
Henk GoedeTNO, Princetonlaan 6, PO Box 80015, Utrecht 3584 CB, The Netherlands.
Hasnae Ben JeddiTNO, Princetonlaan 6, PO Box 80015, Utrecht 3584 CB, The Netherlands.
Eelco KuijpersTNO, Princetonlaan 6, PO Box 80015, Utrecht 3584 CB, The Netherlands.ORCID 0000-0002-9033-7605
Calvin GeTNO, Princetonlaan 6, PO Box 80015, Utrecht 3584 CB, The Netherlands.ORCID 0000-0003-1748-5203
Wouter FransmanTNO, Princetonlaan 6, PO Box 80015, Utrecht 3584 CB, The Netherlands.ORCID 0000-0002-6602-3876

Funding

European Union's Horizon 2020 research 862195
6 · The paper itself

Abstract

Exposure to manufactured nanomaterials (MNs) is a growing concern for occupational health and safety. Reliable methods for assessing and predicting MN exposure are essential to mitigate associated risks. This study presents the development of the Nano Exposure Quantifier (NEQ), a mechanistic model designed to assess airborne MN exposure in the workplace. By utilizing a dataset of 128 MN measurements from existing exposure studies, the model demonstrates its effectiveness in estimating MN exposure levels for particles smaller than 10 µm. The NEQ provides estimates in terms of particle number concentration accompanied by a 95% confidence interval (CI), enabling a comprehensive assessment of MN exposure. The NEQ includes 2 quantitative models: a simplified tier 1 model and a more comprehensive tier 2 model. Both tier 1 and tier 2 models exhibit robust performance, with correlation coefficients (r) of 0.57 and 0.62, respectively. The models exhibit a moderate level of error, as indicated by residuals' standard deviation of 4.10 for tier 1 and 3.90 for tier 2. The tier 1 model demonstrates a slightly higher overestimation bias (1.15) compared to the tier 2 model (0.54). Overall, the NEQ offers a practical and reliable approach for estimating MN exposure in occupational settings. Future validation studies will investigate the impact of initial calibration efforts, heteroscedasticity, and further refine the model's accuracy.

Indexed as

Air Pollutants, OccupationalEnvironmental MonitoringNanoparticlesOccupational ExposureHumansInhalation ExposureModels, TheoreticalParticle SizeWorkplaceAir Pollutants, Occupationalemission potentialexposure assessmentexposure modelingmodifying factorsnanoparticlesrisk management

Identifiers

PMID39887143
PMCPMC11911509

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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.