Bioengineering / Biyomühendislik

Permanent URI for this collectionhttps://hdl.handle.net/11147/4529

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  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    The Soft Nanodots as Fluorescent Probes for Cell Imaging: Analysis of Cell and Spheroid Penetration Behavior of Single Chain Polymer Dots
    (Wiley, 2024) Yücel, Müge; Onbaş, Rabia; Arslan Yıldız, Ahu; Yıldız, Ümit Hakan
    This study describes the formation, size control, and penetration behavior of polymer nanodots (Pdots) consisting of single or few chain polythiophene-based conjugated polyelectrolytes (CPEs) via nanophase separation between good solvent and poor solvent of CPE. Though the chain singularity may be associated with dilution nanophase separation suggests that molecules of a good solvent create a thermodynamically driven solvation layer surrounding the CPEs and thereby separating the single chains even in their poor solvents. This statement is therefore corroborated with emission intensity/lifetime, particle size, and scattering intensity of polyelectrolyte in good and poor solvents. Regarding the augmented features, Pdots are implemented into cell imaging studies to understand the nuclear penetration and to differentiate the invasive characteristics of breast cancer cells. The python based red, green, blue (RGB) color analysis depicts that Pdots have more nuclear penetration ability in triple negative breast cancer cells due to the different nuclear morphology in shape and composition and Pdots have penetrated cell membrane as well as extracellular matrix in spheroid models. The current Pdot protocol and its utilization in cancer cell imaging are holding great promise for gene/drug delivery to target cancer cells by explicitly achieving the very first priority of nuclear intake. The penetration capability of cationic soft nanodots in to tumor models of breast cancer is demonstrated. The image analysis based on fluorescence intensity variation reveals the characteristics of translocation of nanodots in dense mediums such as tumor models.image