Background And Purpose: Cyclophosphamide (CP) is a widely used antitumor and immunosuppressive drug, but it is highly cytotoxic and has carcinogenic and teratogenic potential. To reduce adverse effects of CP therapy and the frequency of its administration, the microencapsulation of CP into biodegradable polymeric matrices can be performed. However, according to the literature, only a few polymers were found suitable to encapsulate CP and achieve its' sustained release.
View Article and Find Full Text PDFPolyhydroxyalkanoates (PHAs) are used for various biomedical applications due to their biocompatibility. Surface properties, such as surface roughness, are crucial for PHAs performance. Traditional parameters used for the characterization of surface roughness, such as , are often insufficient to capture the complex and hierarchical (multiscale) topography of PHA films.
View Article and Find Full Text PDFSurface of polyhydroxyalkanoate (PHA) films of varying monomer compositions are analyzed using atomic force microscopy (AFM) and unsupervised machine learning (ML) algorithms to investigate and classify films based on global attributes such as the scan size, film thickness, and monomer type. The experiment provides benchmarked results for 12 of the most widely used clustering algorithms via a hybrid investigation approach while highlighting the impact of using the Fourier transform (FT) on high-dimensional vectorized data for classification on various pools of data. Our findings indicate that the use of a one-dimensional (1D) FT of vectorized data produces the most accurate outcome.
View Article and Find Full Text PDFThe needs of modern regenerative medicine for biodegradable polymers are wide and varied. Restoration of the viability of the vascular tree is one of the most important components of the preservation of the usefulness of organs and tissues. The creation of vascular implants compatible with blood is an important task of vascular bioengineering.
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