Background: TP53 mutations are the most frequent mutations in hepatocellular carcinoma (HCC) and affect the occurrence and development of this cancer type. Therefore, it is essential to clarify the function and mechanism of TP53 mutations in HCC.Methods: We performed a sequence of bioinformatic analyses to elucidate the characteristics of TP53 mutations in HCC. We downloaded the data of hepatocellular carcinoma from The Cancer Genome Atlas database and used different R packages for serial analyses, including gene mutation analysis, copy number variation analysis, analysis of the tumor mutational burden and microsatellite instability, differential gene expression analysis, and functional enrichment analysis of TP53 mutations, and performed gene set enrichment analysis. We established a protein-protein interaction network using the STRING online database and used the Cytoscape software for network visualization, and hub gene screening. In addition, we performed anticancer drug sensitivity analysis using data from the Genomics of Drug Sensitivity in Cancer. Immune infiltration and prognosis analyses were also performed.Results: Missense mutations accounted for a great proportion of HCC mutations, the frequency of single nucleotide polymorphisms was high, and C > T was the most common form of single nucleotide variations. TP53 had a mutation rate of 30% and was the most commonly mutated gene in HCC. In the TP53 mutant group, the tumor mutational burden (p < 0.001), drug sensitivity (p < 0.05), ESTIMATE score (p = 0.038), and stromal score (p < 0.001) dramatically decreased. The Cytoscape software screened ten hub genes, including CT45A1, XAGE1B, CT55, GAGE2A, PASD1, MAGEA4, CTAG2, MAGEA10, MAGEC1, and SAGE1. The prognostic model showed a poor prognosis in the TP53 mutation group compared with that in the wild-type group (overall survival, p = 0.023). Univariate and multivariate cox regression analyses revealed that TP53 mutation was an independent risk factor for the prognosis of HCC patients (p <0.05). The constructed prognostic model had a favorable forecast value for the prognosis of HCC patients at 1 and 3 years (1-year AUC = 0.752, 3-years AUC = 0.702).Conclusion: This study further deepened our understanding of TP53-mutated HCC, provided new insights into a precise individualized therapy for HCC, and has particular significance for prognosis prediction.

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Extractive distillation is often used to separate difficult separation systems so as to realize the recovery and utilization of resources in industry. Based on the separation of ethylene glycol (EG), isoamyl alcohol, and water, the separation of ternary azeotropic mixtures by extractive distillation was studied. The study of extraction mechanism is very important for solvent screening and molecular design. To compare the selectivity of solvents, the interaction energies between solvent–water, solvent–EG, and solvent–isoamyl alcohol were calculated by the quantum chemical method. Atoms in molecules, reduced density gradient, and electrostatic potential were used to study the microextraction mechanism of solvents in the water–EG–isoamyl alcohol system. In extractive distillation, vapor–liquid equilibrium (VLE) data is used as the basic data for designing and optimizing the process. In order to solve the problem of lack of VLE data between N,N-dimethylformamide, dimethyl sulfoxide, choline-based deep eutectic solvents, and azeotropes, the VLE experiment of the solvent and azeotrope system was carried out. In this work, the selectivity of different solvents was compared by the quantum chemical method, the microextraction mechanism of solvents was explored, and the lack of VLE experimental data was supplemented, which provided theoretical guidance for the selection and design of solvent molecules with excellent performance.

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Separation of methanol−isopropyl acetate (IPAC) obtained via isopropanol synthesis is essential. Deep eutectic solvents (DESs) have garnered extensive attention in the field of azeotropic separation owing to their advantages such as biodegradability, ecofriendliness, and cost-effectiveness. In this work, three cholinebased DESs were prepared. Then, the experimental data of the synthesized DESs with methanol and IPAC were measured, which were linearly correlated with Hand and Othmer−Tobias equations. The G M /RT surface obtained using GUI-MATLAB software was used to determine the reliability of the fitting data based on the NRTL model. Choline chloride and ethylene glycol DES with a molar ratio of 1:2 exhibited the best methanol affinity. The effect of the solvent structure was studied using a combination of experimental and quantum chemistry and molecular dynamics (MD) calculations. Through electrostatic potential distribution, atoms-in-molecules, and independent gradient model analytical methods, the three DEEs were primarily extracted via a hydrogen bond interaction and van der Waals interaction, wherein the former played a dominant role in separation. MD simulation was used to reveal the effect of the structures of hydrogen bond acceptors (HBAs) and hydrogen bond donors (HBDs) on the extraction process at the molecular level. The analysis results indicated that HBA was the main influencing factor in the separation, and the electrostatic interaction of Cl − and methanol was dominant in the separation. Additionally, HBDs were the secondary factor during the separation process. In this work, the reasons for the differences in the separation performances of different DESs were analyzed from a microscopic perspective, offering theoretical support for selecting suitable DESs for separating alcohol-containing azeotropic systems.

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