Hyperspectral imaging of nanoparticles in biological samples: Simultaneous visualization and elemental identification.
Microsc Res Tech
; 79(5): 349-58, 2016 May.
Article
em En
| MEDLINE
| ID: mdl-26864497
ABSTRACT
While engineered nanomaterials (ENMs) are increasingly incorporated into industrial processes and consumer products, the potential biological effects and health outcomes of exposure remain unknown. Novel advanced direct visualization techniques that require less time, cost, and resource investment than electron microscopy (EM) are needed for identifying and locating ENMs in biological samples. Hyperspectral imaging (HSI) combines spectrophotometry and imaging, using advanced optics and algorithms to capture a spectrum from 400 to 1000 nm at each pixel in an enhanced dark-field microscopic (EDFM) image. HSI-EDFM can be used to confirm the identity of the materials of interest in a sample and generate an image "mapping" their presence and location in a sample. Hyperspectral mapping is particularly important for biological samples, where ENM morphology is visually indistinct from surrounding tissue structures. While use of HSI (without mapping) is increasing, no studies to date have compared results from hyperspectral mapping with conventional methods. Thus, the objective of this study was to utilize EDFM-HSI to locate, identify, and map metal oxide ENMs in ex vivo histological porcine skin tissues, a toxicological model of cutaneous exposure, and compare findings with those of Raman spectroscopy (RS), energy-dispersive X-ray spectroscopy (EDS), and scanning electron microscopy (SEM). Results demonstrate that EDFM-HSI mapping is capable of locating and identifying ENMs in tissue, as confirmed by conventional methods. This study serves as initial confirmation of EDFM-HSI mapping as a novel and higher throughput technique for ENM identification in biological samples, and serves as the basis for further protocol development utilizing EDFM-HSI for semiquantitation of ENMs.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Nanopartículas
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Microsc Res Tech
Ano de publicação:
2016
Tipo de documento:
Article