Pan-Cancer Prediction of Cell-Line Drug Sensitivity Using Network-Based Methods

The development of reliable predictive models for individual cancer cell lines to identify an optimal cancer drug is a crucial step to accelerate personalized medicine, but vast differences in cancer cell lines and drug characteristics make it quite challenging to develop predictive models that result in high predictive power and explain the similarity of cell lines or drugs. Our study proposes a novel network-based methodology that breaks the problem into smaller, more interpretable problems to improve the predictive power of anti-cancer drug responses in cell lines. For the drug-sensitivity study, we used the GDSC database for 915 cell lines and 200 drugs. The theory of optimal mass transport was first used to separately cluster cell lines and drugs, using gene-expression profiles and extensive cheminformatic drug features, represented in a form of data networks. To predict cell-line specific drug responses, random forest regression modeling was separately performed for each cell-line drug cluster pair. Post-modeling biological analysis was further performed to identify potential biological correlates associated with drug responses. The network-based clustering method resulted in 30 distinct cell-line drug cluster pairs. Predictive modeling on each cell-line-drug cluster outperformed alternative computational methods in predicting drug responses. We found that among the four drugs top-ranked with respect to prediction performance, three targeted the PI3K/mTOR signaling pathway. Predictive modeling on clustered subsets of cell lines and drugs improved the prediction accuracy of cell-line specific drug responses. Post-modeling analysis identified plausible biological processes associated with drug responses.     

Seismic microzonation and building vulnerability assessment based on site characteristic and geotechnical parameters by use of Fuzzy-AHP model (a case study for Kermanshah city)

ABSTRACT

On 12th November 2017, an earthquake with a magnitude of 7.3 Richter scale in the town of Sarpol-e Zahab took place that caused lots of human casualties and devastation. After the incident, issues related to the probability of an earthquake with equal intensity and extents of similar building destruction were raised in Kermanshah city. Therefore, a seismic microzonation map of Kermanshah city has been prepared based on the geotechnical, geological, and geophysical data, and the data were analysed using Fuzzy analytic hierarchy process (AHP). In the next step, the vulnerability analysis of city buildings was carried out based on the ground-shaking map, vulnerability curves, and statistical data regarding the buildings. The results of the vulnerability rate of residential buildings indicate that 80% of residential buildings would be exposed to vulnerability from low to moderate. However, other buildings would suffer 2% fully destruction (D1), 7% very high destruction (D2) and 11% high destruction (D3), respectively. Finally, according to the obtained results, the proposed model is verified with the help of the data and observations from the Sarpol-e Zahab earthquake, which reveals that the model is in good agreement with the actual earthquake data.     

Thermosensitive folic acid-targeted poly (ethylene-<Emphasis Type="Italic">co</Emphasis>-vinyl alcohol) hemisuccinate polymeric nanoparticles for delivery of epirubicin to breast cancer cells

A novel thermosensitive folic acid (FA)-targeted succinylated poly (ethylene-co-vinyl alcohol) (EVOH) (EVOHS-FA) nanocarrier was synthesized for the specific delivery of epirubicin (EPI) to MCF-7 breast cancer cell line. Three different ratios of synthesized EVOH-Suc were reacted with FA. The structure of the desired products (EVOHS₄₀-FA, EVOHS₆₀-FA and EVOHS₈₀-FA) was confirmed by ¹H NMR and FTIR techniques. Nanoparticles were obtained by nano-precipitation procedure using DMSO/H₂O as solvent/anti-solvent. The particle size, zeta potential, entrapment efficacy and in vitro release profile of the final formulations in different temperatures were measured. The optimized nanoparticles had the particle size of 214 ± 8.5 nm, zeta potential of ?29.6 mV, PDI of 0.198 ± 0.04, and a high encapsulation efficiency that released the drug efficiently within 450 h at the temperature of 40 °C compared to 37 °C. The morphology of nanoparticles was studied by scanning electron microscopy. The in vitro cytotoxicity was evaluated using the MTT assay on MCF-7 cell lines in response to temperatures of 37 and 40 °C. The MTT assay indicated that the targeted nanoparticles carrying EPI were significantly more cytotoxic than the non-targeted nanoparticles and the free drug at 40 °C.     

A comparative study of ethylene polymerization by bis(aminotropone) Ti catalysts

A series of titanium aminotropone complexes bearing a pair of chelating [O–N] ligands have been synthesized and used for polymerization of ethylene successfully. Ethylene polymerization reactions were carried out at different conditions using the prepared catalysts. The activities for ethylene polymerization were significantly dependent on the catalyst structure. The polymerization activity increased with increasing of the both monomer pressure and [MAO]:[Ti] ratio. The highest activity of the catalysts was obtained at about 30–40 °C. It was demonstrated that unlike the high performance Ti–FI catalysts, bis(aminotropone) Ti catalysts do not require the presence of steric bulk in close proximity to the oxygen moiety. Introduction of the bulky alkyl substitution next to the oxygen moiety decreased the activity of the catalysts. Density Functional Theory (DFT) studies reveal that the active species derived from these catalysts normally possess higher electrophilicity nature compared with those produced using bis(phenoxy-imine) Ti catalysts (Ti–FI catalysts). Hydrogen was used as the chain transfer agent. The activities of the catalysts were increased with hydrogen concentration to some extent, but the M _v values of the obtained polymers were decreased. Crystallinity and melting point of the obtained polymer were between 42–62% and 102–124 °C, respectively. Higher pressure increased both the crystallinity and the M _v values of the resulting polymers. The catalyst 8a also produced PE with almost narrow polydispersities (1.10–2.55) as is typical for single-site catalysts. However, PDI was broadened by time.     

CuI Immobilized on Tricationic Ionic Liquid Anchored on Functionalized Magnetic Hydrotalcite (Fe3O4/HT-TIL-CuI) as a Novel,Magnetic and Efficient Nanocatalyst for Ullmann-Type C–N Coupling Reaction

One of the most important reactions in organic synthesis is Ullmann-type C–N coupling reaction which has been used for preparation of numerous biologically active compounds. In this work, CuI immobilized on tricationic ionic liquid anchored on functionalized magnetic hydrotalcite (Fe₃O₄/HT-TIL-CuI) has been successfully prepared and fully characterized by different techniques, including fourier-transform infrared spectroscopy, vibrating sample magnetometer, thermo gravimetric analysis, transmission electron microscopy, field-emission scanning electron microscopy, energy dispersive X-ray spectroscopy, elemental mapping, zeta potential, X-ray diffraction, temperature programmed desorption of ammonia (NH₃-TPD), temperature-programmed reduction and inductively coupled plasma. The results showed that the as-prepared nanocatalyst possesses plate-like morphology with approximate size of 50 nm and superparamagnetic behavior. Also, total acidity and total hydrogen consumption of the nanocatalyst were measured to be 8.5 and 1.41 mmol g^?1, respectively. This nanocatalyst exhibited favorable performance for C–N coupling reaction among a variety of aryl halides and N(H)-heterocycles (benzimidazoles, pyrazoles and triazoles) in the presence of 2.5 mol% of nanocatalyst without any additives under air atmosphere revealing high yields in all cases. Besides, it is noted that in the present system the desired product can be easily and quickly isolated and nanocatalyst also recovered magnetically from the reaction mixture employing a permanent magnet for at least six consecutive trials without a discernible decrease in catalytic activity which makes the proposed methodology appropriate for industrial. The findings demonstrated the advantages of the present method as no need for neutral atmosphere, appropriate times, recyclability of the catalyst, broad substrate scope, minimization of chemical waste, simple purification of products, easy workup process, and high yields.

     

Proposal of an equivalent linearization method to predict seismic hysteretic energy demand considering stiffness degradation effects

To overcome complexities and shortcomings of previous studies, a new method is proposed to derive an equivalent linear model for predicting seismic hysteretic energy demand of bilinear single degree of freedom (SDOF) models. A new displacement spectrum is defined, which represents hysteretic energy. It is found that by increasing initial period and damping of a nonlinear system in the correct proportion and defining a linear model with these characteristics, the new developed displacement can be achieved. Error minimization is applied through an algorithm to find the optimum equivalent period corresponding to an equivalent damping utilizing two sets of far‐field and near‐field earthquakes. To analyze the effects of stiffness degradation, the proposed algorithm has been implemented on modified Clough hysteretic model as well. Comparing the results, effects of stiffness degradation on the ratio of equivalent to initial period is evident in the short period range, while with increasing initial period, the effect can almost be neglected at higher values of ductility. Nonlinear regression analysis is carried out to provide the equations for predicting equivalent linear parameters as a function of ductility. Despite the previous predictive equations, the proposed model is independent of earthquake characteristics and response‐related parameters, which has increased efficiency as well as simplicity.