This work focuses on the experimental measurement and modeling of solid− liquid equilibria containing continuous binary solid solutions crystallized from solvent mixtures for the usage in antisolvent crystallization. The newly constructed quaternary phase diagrams of L-valine/L-leucine in water/2-propanol and water/acetone systems are analyzed and compared to those of water/ethanol mixtures. Experimental data sets are determined via highperformance liquid chromatography, while the formation of solid solutions is confirmed with powder X-ray diffraction. Our validated modeling approach for the ternary L-valine/L-leucine/ water mixture is extended to the aforementioned quaternary systems. The modeling combines the Perturbed Chain-Statistical Associating Fluid Theory and the Non-Random Two-Liquid model to describe the liquid and solid phases, respectively. Additionally, two modeling approaches (predictive and semi-predictive) are proposed. Both models show good agreement with the experimental solubility data sets of the binary solutions. However, larger deviations were observed in three-and four-component systems, especially toward the solubility maxima. Therefore, the modeling approach should be used for qualitative initial antisolvent screenings for the separation of solid solutions using counter-current crystallization.

The biodesulfurization activity of bacteria through the 4S pathway in aqueous‐oil emulsions is affected by various operational factors. These factors also demonstrate interacting effects that influence the potential for field applications of biodesulfurization technology and can solely be deciphered through multi‐variable experiments. In this study, the effects of the influential factors and their interactions on the desulfurizing activity of a newly identified desulfurizing bacterium, Rhodococcus sp, FUM94 were quantitatively investigated. The capacity improvement achieved through optimized values obtained in this study is significant due to its simple implementation to large scale processes. This is the most simple and the most cost‐effective way to scale‐up a biodesulfurization process.Using response surface methodology (RSM). Optimum values of the factors were identified with the objective of maximizing biodesulfurization activity. Results revealed that the desulfurization activity of the biocatalyst increased from 0.323 ± 0.072 to 46.57 ± 4.556 mmol 2‐Hydroxybiphenyl (kg dry cell weight)−1h−1 at the optimized conditions of 6 h reaction time, 2 g.L−1 biocatalyst concentration, 0.54 mM (100 ppm) dibenzothiophene (DBT) concentration (sulfur source), and 25% oil phase fraction. Desirability analysis proved that the selected conditions are the most desirable combination of factors (desirability value = 0.896) to achieve the highest biodesulfurization activity of the biocatalyst. A comparison between the biodesulfurization capacity achieved in this study and the capacities reported in similar studies published in the past two decades revealed that biodesulfurization under optimized operational conditions outperforms previously proposed techniques.

Introduction: Changes in the expression of pseudogenes have been demonstrated to play a role in the pathogenesis of various malignancies in studies. The goal of this study was to find pseudogenes with significant expression alterations in gastric cancer (GC) that could be implicated in the disease's development via the competing endogenous RNAs (ceRNAs) network. Methods: Pseudogenes, mRNAs, and microRNAs whose expression changes considerably in GC specimens were identified using the cancer genome atlas (TCGA) data. The ceRNAs network was constructed using the miRWalk, miRTarBase, and DIANA-LncBase databases. The cox regression test was performed to assess the correlation between candidate genes and patient prognosis using TCGA-derived GC clinical data. Finally, using the RT-qPCR method, the in silico results were evaluated using GC samples and adjacent normals. Results: The ceRNA network revealed that pseudogenes such as RCN1P2, TPM3P9, and HSP90AB3P were most connected to changed mRNAs and microRNAs in GC. The findings of subnet enrichment for each of the pseudogenes mentioned revealed that the related mRNAs are involved in cell proliferation, inflammation, and metastatic pathways. Furthermore, elevated expression of several mRNAs linked to potential pseudogenes was linked to a poor prognosis. The results of RCN1P2, TPM3P9and HSP90AB3P expression levels in TCGA and tissue samples showed that their expression increased significantly in GC. Conclusion: The expression of RCN1P2, TPM3P9, and HSP90AB3P is dramatically enhanced in GC. They can also influence the survival rate of GC patients by regulating pathways involved in cell proliferation, inflammation, and metastasis via the ceRNAs network.