title: Statistical detection of nanoparticles in cells by darkfield microscopy.
abstract: In the fields of nanomedicine, biophotonics and radiation therapy, nanoparticle (NP) detection in cell models often represents a fundamental step for many in vivo studies. One common question is whether NPs have or have not interacted with cells. In this context, we propose an imaging based technique to detect the presence of NPs in eukaryotic cells. Darkfield images of cell cultures at low magnification (10×) are acquired in different spectral ranges and recombined so as to enhance the contrast due to the presence of NPs. Image analysis is applied to extract cell-based parameters (i.e. mean intensity), which are further analyzed by statistical tests (Student's t-test, permutation test) in order to obtain a robust detection method. By means of a statistical sample size analysis, the sensitivity of the whole methodology is quantified in terms of the minimum cell number that is needed to identify the presence of NPs. The method is presented in the case of HeLa cells incubated with gold nanorods labeled with anti-CA125 antibodies, which exploits the overexpression of CA125 in ovarian cancers. Control cases are considered as well, including PEG-coated NPs and HeLa cells without NPs.
authors.affiliation: Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, viale Pieraccini 6, I-50139 Florence, Italy. Electronic address: alessio.gnerucci@unifi.it.
authors.forename: Alessio
authors.initials: A
authors.lastname: Gnerucci
authors.affiliation: Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, viale Pieraccini 6, I-50139 Florence, Italy. Electronic address: giovanni.romano@unifi.it.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Romano
authors.affiliation: Institute of Applied Physics "Nello Carrara", National Research Council, via Madonna del Piano 10, I-50019 Sesto Fiorentino, Italy.
authors.forename: Fulvio
authors.initials: F
authors.lastname: Ratto
authors.affiliation: Institute of Applied Physics "Nello Carrara", National Research Council, via Madonna del Piano 10, I-50019 Sesto Fiorentino, Italy.
authors.forename: Sonia
authors.initials: S
authors.lastname: Centi
authors.affiliation: Department of Statistics, Informatics, Applications "G. Parenti", University of Florence, viale Morgagni 59, I-50134 Florence, Italy.
authors.forename: Michela
authors.initials: M
authors.lastname: Baccini
authors.affiliation: Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, I-50134 Florence, Italy.
authors.forename: Ugo
authors.initials: U
authors.lastname: Santosuosso
authors.affiliation: Institute of Applied Physics "Nello Carrara", National Research Council, via Madonna del Piano 10, I-50019 Sesto Fiorentino, Italy.
authors.forename: Roberto
authors.initials: R
authors.lastname: Pini
authors.affiliation: Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, viale Pieraccini 6, I-50139 Florence, Italy.
authors.forename: Franco
authors.initials: F
authors.lastname: Fusi
mesh_terms: D000906:Antibodies / Q000737:chemistry / Q000276:immunology; D001692:Biological Transport; D018394:CA-125 Antigen / Q000276:immunology; D003624:Darkness; D006046:Gold / Q000737:chemistry; D006367:HeLa Cells; D006801:Humans; D007425:Intracellular Membranes / Q000378:metabolism; D008565:Membrane Proteins / Q000276:immunology; D008853:Microscopy / Q000379:methods*; D053758:Nanoparticles / Q000737:chemistry / Q000378:metabolism*; D011092:Polyethylene Glycols / Q000737:chemistry
chemical_list: D000906:Antibodies; D018394:CA-125 Antigen; C451759:MUC16 protein, human; D008565:Membrane Proteins; D011092:Polyethylene Glycols; D006046:Gold
keywords: Darkfield microscopy; Gold nanoparticles; Image analysis; Statistical test