Titanium dioxide (TiO2) nano- and submicrometric particles’ widespread use in differ- ent sectors raised concerns about human and environmental exposure. The validation of analytical methods is essential to ensure reliability in risk assessment studies. In this study, a single-particle inductively coupled plasma mass spectrometry (spICP-MS) method was validated for the detection, quantification, and dimensional characterization of TiO2 particles in biological tissues. Tissue samples collected after exposure to TiO2 particles underwent mild acidic digestion using a HNO3/H2O2 mixture to achieve complete matrix decomposition while preserving particle integrity. The resulting digests were analyzed by ICP-MS operated in single-particle mode to quantify and size TiO2 particles. Method validation was conducted according to ISO/IEC 17025:2017 and included linearity, repeata- bility, recovery, and detection limit assessments. The limit of detection for TiO2 particles was 0.04 µg/g, and 55.7 nm was the size the detection limit. Repeatability was within 0.5–11.5% for both TiO2 mass concentrations and particle size determination. The validated method was applied to tissues from inhalation-exposed subjects, showing TiO2 levels of 80 ±20 µg TiO2/g and particle number concentrations of 5.0 ×105 ±1.2 ×105 part. TiO2/mg. Detected TiO2 particles’ mean diameter ranged from 230 to 330 nm. The devel- oped and validated spICP-MS method provides robust and sensitive quantification of TiO2 particles in biological matrices, supporting its use in human biomonitoring and exposure assessment studies.

Single-particle ICP-MS method for the determination of TiO2 nano- and submicrometric particles in biological tissues / Sebastiani, Francesca; Tombolini, Francesca; Boccuni, Fabio; Natale, Claudio; Canepari, Silvia; Ferrante, Riccardo. - In: ANALYTICA. - ISSN 2673-4532. - 7:1(2026). [10.3390/analytica7010009]

Single-particle ICP-MS method for the determination of TiO2 nano- and submicrometric particles in biological tissues

Sebastiani, Francesca
;
Natale, Claudio;Canepari, Silvia;
2026

Abstract

Titanium dioxide (TiO2) nano- and submicrometric particles’ widespread use in differ- ent sectors raised concerns about human and environmental exposure. The validation of analytical methods is essential to ensure reliability in risk assessment studies. In this study, a single-particle inductively coupled plasma mass spectrometry (spICP-MS) method was validated for the detection, quantification, and dimensional characterization of TiO2 particles in biological tissues. Tissue samples collected after exposure to TiO2 particles underwent mild acidic digestion using a HNO3/H2O2 mixture to achieve complete matrix decomposition while preserving particle integrity. The resulting digests were analyzed by ICP-MS operated in single-particle mode to quantify and size TiO2 particles. Method validation was conducted according to ISO/IEC 17025:2017 and included linearity, repeata- bility, recovery, and detection limit assessments. The limit of detection for TiO2 particles was 0.04 µg/g, and 55.7 nm was the size the detection limit. Repeatability was within 0.5–11.5% for both TiO2 mass concentrations and particle size determination. The validated method was applied to tissues from inhalation-exposed subjects, showing TiO2 levels of 80 ±20 µg TiO2/g and particle number concentrations of 5.0 ×105 ±1.2 ×105 part. TiO2/mg. Detected TiO2 particles’ mean diameter ranged from 230 to 330 nm. The devel- oped and validated spICP-MS method provides robust and sensitive quantification of TiO2 particles in biological matrices, supporting its use in human biomonitoring and exposure assessment studies.
2026
single particle inductively coupled plasma mass spectrometry; analytical method validation; nanoparticles’ analysis in biological tissues
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Single-particle ICP-MS method for the determination of TiO2 nano- and submicrometric particles in biological tissues / Sebastiani, Francesca; Tombolini, Francesca; Boccuni, Fabio; Natale, Claudio; Canepari, Silvia; Ferrante, Riccardo. - In: ANALYTICA. - ISSN 2673-4532. - 7:1(2026). [10.3390/analytica7010009]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1759118
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