Development and Validation of a Predictive Model to Evaluate the Risk of Bone Metastasis in Kidney Cancer.

BACKGROUND: Bone is a common target of metastasis in kidney cancer, and accurately predicting the risk of bone metastases (BMs) facilitates risk stratification and precision medicine in kidney cancer. METHODS: Patients diagnosed with kidney cancer were extracted from the Surveillance, Epidemiology, and End Results (SEER) database to comprise the training group from 2010 to 2017, and the validation group was drawn from our academic medical center. Univariate and multivariate logistic regression analyses explored the statistical relationships between the included variables and BM. Statistically significant risk factors were applied to develop a nomogram. Calibration plots, receiver operating characteristic (ROC) curves, probability density functions (PDF), and clinical utility curves (CUC) were used to verify the predictive performance. Kaplan-Meier (KM) curves demonstrated survival differences between two subgroups of kidney cancer with and without BMs. A convenient web calculator was provided for users via "shiny" package. RESULTS: A total of 43,503 patients were recruited in this study, of which 42,650 were training group cases and 853 validation group cases. The variables included in the nomogram were sex, pathological grade, T-stage, N-stage, sequence number, brain metastases, liver metastasis, pulmonary metastasis, histological type, primary site, and laterality. The calibration plots confirmed good agreement between the prediction model and the actual results. The area under the curve (AUC) values in the training and validation groups were 0.952 (95% CI, 0.950-0.954) and 0.836 (95% CI, 0.809-0.860), respectively. Based on CUC, we recommend a threshold probability of 5% to guide the diagnosis of BMs. CONCLUSIONS: The comprehensive predictive tool consisting of nomogram and web calculator contributes to risk stratification which helped clinicians identify high-risk cases and provide personalized treatment options.

Porous Carbon Membrane-Supported Atomically Dispersed Pyrrole-Type FeN4 as Active Sites for Electrochemical Hydrazine Oxidation Reaction.

The rational design of catalytically active sites in porous materials is essential in electrocatalysis. Herein, atomically dispersed Fe-Nx sites supported by hierarchically porous carbon membranes are designed to electrocatalyze the hydrazine oxidation reaction (HzOR), one of the key techniques in electrochemical nitrogen transformation. The high intrinsic catalytic activity of the Fe-Nx single-atom catalyst together with the uniquely mixed micro-/macroporous membrane support positions such an electrode among the best-known heteroatom-based carbon anodes for hydrazine fuel cells. Combined with advanced characterization techniques, electrochemical probe experiments, and density functional theory calculation, the pyrrole-type FeN4 structure is identified as the real catalytic site in HzOR.

ß-Cyclodextrin-derived Room Temperature Macromolecular Ionic Liquids by PEGylated Anions.

A series of cyclodextrin-derived room temperature macromolecular ionic liquids carrying rather low glass transition temperatures of -20 to -40 °C are synthesized via sequential esterification, quaternization, and anion metathesis reactions. In addition to being ionic in nature, they are viscous liquids at room temperature with more fluidic behavior at elevated temperatures. They serve as a solvent for organic dyes or iodine separation via a liquid-liquid extraction approach. This strategy is useful for the development of various sugar (macro)molecule-based functional ionic liquids as well as macromolecular ionic liquids.

Aqueous Biphasic Systems Containing Customizable Poly(Ionic Liquid)s for Highly Efficient Extractions.

Ionic liquid (IL)-based aqueous biphasic systems (ABSs) provide a sustainable and efficient alternative to conventional liquid-liquid extraction techniques and can be used for the extraction, recovery, and purification of diverse solutes. However, the construction of a high-performance ABS that has both excellent phase separation ability and extraction performance remains challenging. This study concerns the preparation of a family of novel ABSs based on poly(ionic liquid)s (PILs) with customized structure and controllable molecular weight for the extraction of bioactive compounds. Several tailor-made PILs consisting of a hydrophobic backbone, hydrophilic imidazolium pendant groups and strong hydrogen bonding basic counteranions are prepared by reversible addition fragmentation chain-transfer polymerization. The PILs have a perfect balance of hydrophobicity/hydrophilicity and functionality, affording outstanding phase separation, which was better than with either the IL monomer poly(1-butyl-3-vinylimidazolium bromide ([BVIm]Br) or the normal free-radical polymer P[BVIm]Br*. More importantly, PIL-based ABSs exhibited unprecedented high partition coefficients for six bioactive compounds including tryptophan, phenylalanine, and caffeine, as well as high extraction yields. The performance of the PIL-based ABSs could also be tuned by changing the molecular weight and anionic character of the PILs. This work shows that tailor-made PIL-based ABSs are a promising platform for bioactive compound extraction and provides significant clues for the design of new ABSs for various applications.

Enhanced self-assembly for the solubilization of cholesterol in molecular solvent/ionic liquid mixtures.

The development of new solvents combining greatly enhanced solubility for sparingly soluble compounds and good kinetic properties is challenging. In this study, we constructed a family of new molecular solvent/ionic liquid (IL) mixtures with amphiphilic, anionic functional long-chain carboxylate ionic liquids (LCC-ILs) as a key component for the solubilization of sparingly soluble compounds, using cholesterol as a model solute. Polarized optical microscopy (POM), wide angle X-ray diffraction (WAXD), Fourier-transform infrared (FTIR) spectra and 1H NMR showed that ordered mesoscopic structures, such as liquid crystals (LCs), were formed when cholesterol was dissolved in the mixtures, presenting a self-assembly induced dissolution mechanism driven by H-bond interaction and van der Waals forces in the mixtures. A synergistic effect between the molecular solvents and LCC-ILs was revealed, which contributed to enhanced solute-solvent self-assembly in dissolution over pure LCC-ILs and thus elevated solubility. Additionally, the effect of IL concentration, solvent type and anionic alkyl-chain length on self-assembly and solubility was investigated. These mixtures showed unparalleled solubilities for cholesterol, while maintaining a low viscosity. The quantitative solubilities (g g-1) of cholesterol were as high as 0.70, 0.84 and 0.82, respectively, at 25 °C in ethyl acetate/[P4444][C15H31COO] (50 wt%), n-heptane/[P4444][C15H31COO] (40 wt%) and ethyl acetate/[P4444][C17H35COO] (50 wt%) mixtures, which were the highest solubilities of cholesterol ever reported, six- to 980-fold higher than traditional molecular solvents and even one- to seven-fold higher compared to pure LCC-ILs. These results demonstrated the considerable potential of molecular solvent/LCC-ILs mixtures as promising solvents for solubilization and advanced separation processes.