Prevalence and genotypic diversity of Canine Coronavirus in Shandong Province

Objective: To learn the prevalence and genotypic diversity of canine coronavirus(CCoV)in healthy and diarrhea dogs in Shandong Province.

A protein coupling and molecular simulation analysis of the clinical mutants of androgen receptor revealed a higher binding for Leupaxin, to increase the prostate cancer invasion and motility.

Recently a novel coactivator, Leupaxin (LPXN), has been reported to interact with Androgen receptor (AR) and play a significant role in the invasion and progression of prostate cancer. The interaction between AR and LPXN occurs in a ligand-dependent manner and has been reported that the LIM domain in the Leupaxin interacts with the LDB (ligand-binding domain) domain AR. However, no detailed study is available on how the LPXN interacts with AR and increases the (prostate cancer) PCa progression. Considering the importance of the novel co-activator, LPXN, the current study also uses state-of-the-art methods to provide atomic-level insights into the binding of AR and LPXN and the impact of the most frequent clinical mutations H874Y, T877A, and T877S on the binding and function of LPXN. Protein coupling analysis revealed that the three mutants favour the robust binding of LPXN than the wild type by altering the hydrogen bonding network. Further understanding of the binding variations was explored through dissociation constant prediction which demonstrated similar reports as the docking results. A molecular simulation approaches further revealed the dynamic features which reported variations in the dynamics stability, protein packing, hydrogen bonding network, and residues flexibility index. Furthermore, we also assessed the protein motion and free energy landscape which also demonstrated variations in the internal dynamics. The binding free energy calculation revealed -32.95 ± 0.17 kcal/mol for the wild type, for H874Y the total binding energy (BFE) was -36.69 ± 0.11 kcal/mol, for T877A the BFE was calculated to be -38.78 ± 0.17 kcal/mol while for T877S the BFE -41.16 ± 0.12 kcal/mol. This shows that the binding of LPXN is increased by these mutations which consequently increase the PCa invasion and motility. In conclusion, the current study helps in understanding the protein networks and particular the coupling of AR-LPXN in prostate cancer and is of great interest in deciphering the molecular mechanism of disease and therapeutics developments.

Many-Objective Evolutionary Algorithm With Reference Point-Based Fuzzy Correlation Entropy for Energy-Efficient Job Shop Scheduling With Limited Workers.

Because of COVID-19, factories are facing many difficulties, such as shortage of workers and social alienation. How to improve production performance under limited labor resources is an urgent problem for global manufacturing factories. This work studies an energy-efficient job-shop scheduling problem with limited workers. Those workers can have multiskills. A many-objective model with five objectives, that is: 1) makespan; 2) total tardiness; 3) total idle time; 4) total worker cost; and 5) total energy, is built. To solve this many-objective optimization problem (MaOP), a novel fitness evaluation mechanism (FEM) based on fuzzy correlation entropy (FCE) is adopted. Two construction methods for reference points are proposed to build the bridge between MaOP and a fuzzy set. Based on FCE and cluster methods, an environmental selection mechanism (ESM) is proposed to achieve a balance between solution convergence and diversity. With the proposed FEM and ESM, two many-objective evolutionary algorithms are proposed to solve MaOP. The effect of FCE-based FEM and ESM on the performance of algorithms is verified via experiments. The proposed algorithms are compared with four well-known peers to test their performance. The extensive experimental results show that they are very competitive for the considered many-objective scheduling problem.

Evaluation of organ function in patients with severe COVID-19 infections.

OBJECTIVE: The purpose of our study was to assess organ function in 102 patients with severe COVID-19 infections, using retrospective clinical analysis. MATERIAL AND METHODS: A retrospective analysis was conducted on 102 patients with severe COVID-19 infections. The patients were divided into a survival group (n=73) and a non-survival group (n=29) according to their prognosis. The age, sex, underlying diseases, clinical laboratory data within 48h (routine blood tests, ALT, AST, TBIL, ALB, BUN, CR, D-Dimer, PT, APTT, FIB, F VIII:C, CK-MB, CK, and LDH), and ventilation status were collected. The organ functions of these severe COVID-19 patients were assessed by comparing the differences between the two groups. RESULTS: AST, BUN, CR, CK-MB, LDH, and CK in the non-survival group were higher than those in the survival group, and the differences were statistically significant (P<0.05). D-Dimer, PT, FIB, and F VIII:C in the non-survival group were higher than the values observed in the survival group, and the differences were statistically significant (P<0.05). PLT, AST, BUN, CR, D-Dimer, PT, FIB, F VIII:C, CK-MB, CK, and LDH predicted the area under the ROC curve (AUC) of the COVID19 endpoint events and were 0.721, 0.854, 0.867, 0.757, 0.699, 0.679, 0.715, 0.811, 0.935, and 0.802, respectively. CONCLUSION: The results showed that there were different degrees of damage to the liver, kidneys, blood coagulation, and heart function in the non-survival group. In addition, PLT, AST, BUN, CR, D-Dimer, PT, FIB, F VIII:C, CK-MB, CK, and LDH had value in evaluating disease prognosis.