Structure and Biochemical Study of Nanocomposite Bioconstruction for Restoration of Bone-cartilaginous Defects

Porous and strong nanocomposite bioconstructions were formed by laser evaporation of an aqueous dispersion of carbon nanotubes in a protein matrix. The homogeneous dispersion was exposed to laser irradiation to create solid constructions. Continuous laser radiation with a wavelength of 970 nm and a power of 5-7 W was used. The porosity of nanocomposite bioconstructions was studied by the method of lowtemperature nitrogen porosimetry and X-ray microtomography, the tensile strength and relative elongation of bioconstructions were evaluated, and their biocompatibility was tested in vitro. It was found that with an increase of the carbon nanotube’s concentration, a slight decrease in strength (3-15 %), a decrease in the pore size (20- 40 %), and an increase in the degree of deformation (10-12 %) were observed. At the same time, the mechanical parameters of the bioconstructions met the requirements for the materials for the restoration of bone-cartilaginous defects. Using optical microscopy and the MTT-test, proliferative activity and structural features of bone tissue cells on the surface of nanocomposite bioconstructions were evaluated. Studies have shown no toxic or inhibitory effect on cells. The results of the studies can talk about the advantage of nanocomposite bioconstructions using as an implant material for improving the growth of biological cells and regenerating damaged biotissues. Keywords: Nanocomposites, laser radiation, mechanical properties, porosity, X-ray microtomography, biocompatibilit

Predicting response to cancer immunotherapy using noninvasive radiomic biomarkers

Introduction Immunotherapy is regarded as one of the major breakthroughs in cancer treatment. Despite its success, only a subset of patients responds-urging the quest for predictive biomarkers. We hypothesize that artificial intelligence (AI) algorithms can automatically quantify radiographic characteristics that are related to and may therefore act as noninvasive radiomic biomarkers for immunotherapy response.Patients and methods In this study, we analyzed 1055 primary and metastatic lesions from 203 patients with advanced melanoma and non-small-cell lung cancer (NSCLC) undergoing anti-PD1 therapy. We carried out an AI-based characterization of each lesion on the pretreatment contrast-enhanced CT imaging data to develop and validate a noninvasive machine learning biomarker capable of distinguishing between immunotherapy responding and nonresponding. To define the biological basis of the radiographic biomarker, we carried out gene set enrichment analysis in an independent dataset of 262 NSCLC patients.Results The biomarker reached significant performance on NSCLC lesions (up to 0.83 AUC, PConclusions These results indicate that radiographic characteristics of lesions on standard-of-care imaging may function as noninvasive biomarkers for response to immunotherapy, and may show utility for improved patient stratification in both neoadjuvant and palliative settings.</p