Combination therapy for mCRPC with immune checkpoint inhibitors, ADT and vaccine: A mathematical model

Metastatic castration resistant prostate cancer (mCRPC) is commonly treated by androgen deprivation therapy (ADT) in combination with chemotherapy. Immune therapy by checkpoint inhibitors, has become a powerful new tool in the treatment of melanoma and lung cancer, and it is currently being used in clinical trials in other cancers, including mCRPC. However, so far, clinical trials with PD-1 and CTLA-4 inhibitors have been disappointing. In the present paper we develop a mathematical model to assess the efficacy of any combination of ADT with cancer vaccine, PD-1 inhibitor, and CTLA-4 inhibitor. The model is represented by a system of partial differential equations (PDEs) for cells, cytokines and drugs whose density/concentration evolves in time within the tumor. Efficacy of treatment is determined by the reduction in tumor volume at the endpoint of treatment. In mice experiments with ADT and various combinations of PD-1 and CTLA-4 inhibitors, tumor volume at day 30 was always larger than the initial tumor. Our model, however, shows that we can decrease tumor volume with large enough dose; for example, with 10 fold increase in the dose of anti-PD-1, initial tumor volume will decrease by 60%. Although the treatment with ADT in combination with PD-1 inhibitor or CTLA-4 inhibitor has been disappointing in clinical trials, our simulations suggest that, disregarding negative effects, combinations of ADT with checkpoint inhibitors can be effective in reducing tumor volume if larger doses are used. This points to the need for determining the optimal combination and amounts of dose for individual patients.

DESTRUCTION OF DYES IN WASTES OF TEXTILE PRODUCTS

The results of wastewater treatment of textile enterprises in the electrolyzer with insoluble anodes and separation of electrode spaces with an inert membrane are presented. The influence of time, current density, concentration of sodium chloride, the initial concentration of dyes on the process of electrochemical destruction is determined. The developed technology makes it possible to ensure the effectiveness of the destruction of dyes and organic substances, which is necessary to obtain water quality that meets the standards for discharge into the municipal sewage system and reduce the cost of water treatment due to the lack of reagent facilities, septic tanks and dewatering equipment.

MATHEMATICAL MODELING THE ELECTROCHEMICAL DEPOSITION PROCESS OF Ni–Mo THIN FILMS

To avoid the numerous experiments for determining optimal conditions and electrolyte composition at co-deposition of two metals we have cleated the regression equation. Mathematical calculations have been carried out using the Optum ME package program with the study of some factors as current density, concentration of main components, temperature, etc. which effect on the co-deposition process. Three independent variables have been selected. The amount of molybdenum in the deposit has been chosen as the dependent variable. The developed regression equation quite adequately describes the co-deposition process of nickel with molybdenum and can be used at planning the works on obtaining alloys with the required composition by the electrochemical method

On The Stability of Triangular Janus MoSSe Quantum-Dots: Shape and Size Effects

Asymmetric Janus transition metal dichalcogenide MoSSe is a promising catalytic material due to the intrinsic in-plane dipole of its opposite faces. The atomic description of the structures observed by experimental techniques is relevant to tune and optimize the reaction processes on its surfaces. Furthermore, the experimentally observed triangular morphologies in MoSSe suggest that an analysis of the chemical environment of its edges is vital to understand its reactivity. Here we analyze the size-shape stability among different triangular structures-quantum dots-proposed from the ideal S(-1010) and Mo(10-10) terminations. Our stability analysis evidenced that the S-Se termination is more stable than Mo; moreover, as the size of the quantum dot increases, its stability increases as well. Besides, a trend is observed, with the appearance of elongated Mo-S/Se bonds at symmetric positions of the edges. Tersoff-Hamann scanning tunneling microscopy images for both faces of the stablest models are presented. Electrostatic potential isosurfaces denote that the basal plane on the S face of both configurations remains the region with more electron density concentration. These results point toward the differentiated activity over both faces. Finally, our study denotes the exact atomic arrangement on the edges of MoSSe quantum dots corresponding with the formation of S/Se dimmers who decorates the edges and their role along with the faces as catalytic sites.

Autofluorescence imaging for human pluripotent stem cell differentiation into cardiomyocytes

Human pluripotent stem cell (hPSC)-derived cardiomyocytes provide a promising regenerative cell therapy for cardiovascular patients and an important model system to accelerate drug discovery. However, cost-effective and time-efficient platforms must be developed to evaluate the quality of hPSC-derived cardiomyocytes during biomanufacturing. Here, we develop a non-invasive label-free live cell imaging platform to predict the efficiency of hPSC differentiation into cardiomyocytes. Autofluorescence imaging of metabolic co-enzymes is performed under varying differentiation conditions (cell density, concentration of Wnt signaling activator) across three hPSC lines.

Label-free imaging for quality control of cardiomyocyte differentiation

Human pluripotent stem cell (hPSC)-derived cardiomyocytes provide a promising regenerative cell therapy for cardiovascular patients and an important model system to accelerate drug discovery. However, cost-effective and time-efficient platforms must be developed to evaluate the quality of hPSC-derived cardiomyocytes during biomanufacturing. Here, we develop a non-invasive label-free live cell imaging platform to predict the efficiency of hPSC differentiation into cardiomyocytes. Autofluorescence imaging of metabolic co-enzymes is performed under varying differentiation conditions (cell density, concentration of Wnt signaling activator) across five hPSC lines. Live cell autofluorescence imaging and multivariate classification models provide high accuracy to separate low (< 50%) and high (≥ 50%) differentiation efficiency groups (quantified by cTnT expression on day 12) within 1 day after initiating differentiation (area under the receiver operating characteristic curve, 0.91). This non-invasive and label-free method could be used to avoid batch-to-batch and line-to-line variability in cell manufacturing from hPSCs.

Label-free imaging for cardiomyocyte differentiation from human pluripotent stem cells

Human pluripotent stem cell (hPSC)-derived cardiomyocytes provide a promising regenerative cell therapy for cardiovascular patients and an important model system to accelerate drug discovery. However, cost-effective and time-efficient platforms must be developed to evaluate the quality of hPSC-derived cardiomyocytes during biomanufacturing. Here, we develop a non-invasive label-free live cell imaging platform to monitor hPSC differentiation into cardiomyocytes. Autofluorescence imaging of metabolic co-enzymes is performed under varying differentiation conditions (cell density, concentration of Wnt signaling activator) across five hPSC lines.

Label-free imaging for quality control of cardiomyocyte differentiation

Human pluripotent stem cell (hPSC)-derived cardiomyocytes provide a promising regenerative cell therapy for cardiovascular patients and an important model system to accelerate drug discovery. However, cost-effective and time-efficient platforms must be developed to evaluate the quality of hPSC-derived cardiomyocytes during biomanufacturing. Here, we developed a non-invasive label-free live cell imaging platform to predict the efficiency of hPSC differentiation into cardiomyocytes. Autofluorescence imaging of metabolic co-enzymes was performed under varying differentiation conditions (cell density, concentration of Wnt signaling activator) across three hPSC lines. Live cell autofluorescence imaging and multivariate classification models provided high accuracy to separate low (< 50%) and high (≥ 50%) differentiation efficiency groups (quantified by cTnT expression on day 12) within 1 day after initiating differentiation (area under the receiver operating characteristic curve, 0.98). This non-invasive and label-free method could be used to avoid batch-to-batch and line-to-line variability in cell manufacturing from hPSCs.