Evidence map›Paper›PMID 41266800›Full record

ArticleAnalytical and bioanalytical chemistry2026

In vitro dosimetry of multi-walled carbon nanotubes on human bronchial epithelial cells (BEAS-2B) using UV-Vis-NIR spectrophotometry and chemical digestion.

Frédéric Cosnier, Emmy Joubert, Marlène Mascherin, Christian Darne, Carole Seidel

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Article in Analytical and bioanalytical chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Frédéric CosnierFrench Research and Safety Institute for the Prevention of Occupational Accidents and Diseases (INRS), Toxicology and Biomonitoring Division, 1 Rue Morvan, 54519, Vandœuvre Les Nancy, France. frederic.cosnier@inrs.fr.ORCID http://orcid.org/0000-0002-8596-927X
Emmy JoubertFrench Research and Safety Institute for the Prevention of Occupational Accidents and Diseases (INRS), Toxicology and Biomonitoring Division, 1 Rue Morvan, 54519, Vandœuvre Les Nancy, France.
Marlène MascherinFrench Research and Safety Institute for the Prevention of Occupational Accidents and Diseases (INRS), Toxicology and Biomonitoring Division, 1 Rue Morvan, 54519, Vandœuvre Les Nancy, France.
Christian DarneFrench Research and Safety Institute for the Prevention of Occupational Accidents and Diseases (INRS), Toxicology and Biomonitoring Division, 1 Rue Morvan, 54519, Vandœuvre Les Nancy, France.
Carole SeidelFrench Research and Safety Institute for the Prevention of Occupational Accidents and Diseases (INRS), Toxicology and Biomonitoring Division, 1 Rue Morvan, 54519, Vandœuvre Les Nancy, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interpreting in vitro toxicology results with nanomaterials requires precise knowledge of the amount of materials actually delivered to cells. This dose is particularly challenging to accurately measure or estimate for carbon nanotubes (CNTs) due to difficulties quantifying inorganic carbon within an organic matrix. In addition, existing deposition models often assume spherical particles, and may thus not adequately reflect the behaviour of fibrous CNTs. We present a method to quantify the amounts of CNTs remaining in suspension, loosely bound to cells, or strongly bound/internalized. The approach uses UV-Vis-NIR spectroscopy, preceded by chemical digestion or lyophilization as necessary depending on the fractions investigated. The method was implemented and validated with three CNT types-MWNT-7 (long and thick), NM-403 (short and thin), and A2-6-COOH (short, thin, and functionalized with carboxyl groups)-dispersed at six exposure concentrations in cell culture medium. Human bronchial epithelial cells (BEAS-2B) were exposed to CNTs for 96 h. The analytical method was validated for selectivity, linearity, detection and quantification limits, lyophilization yield, bias, and precision (within- and between-run). This method successfully estimated delivered and cellular amounts, which did not always match the nominal exposure concentration. CNT distribution across fractions varies depending on the type of CNT. For functionalized nanotubes, the amount delivered equals the amount applied, whereas for non-functionalized nanotubes, a significant proportion (up to 20-30%) remains suspended in the medium at the highest exposure concentrations. This method also highlighted levels of cell death, as reflected by the release of dead cells containing nanotubes suspended in the culture medium.

Indexed as

BronchiEpithelial CellsNanotubes, CarbonCell LineHumansLimit of DetectionSpectrophotometry, UltravioletSpectroscopy, Near-InfraredNanotubes, CarbonCarbon nanotubesDelivered doseDosimetryLung toxicityMethodValidation

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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.