Copper toxicity has been a selective pressure on the sea-ice bacteria due to its widespread occur-rence in Antarctica. Here, with a combined biochemical and metabolomic approach, the Cu2+ ad-aptation mechanisms of Antarctic bacteria were analyzed. Heavy metal resistance pattern of Pb2+ > Cu2+ > Cd2+ > Hg2+ > Zn2+ was observed. Copper treatment did increase the activity of antioxidants and enzymes, maintaining cellular redox state balance and normal cell division and growth. Metabolomics analysis demonstrated that fatty acids, amino acids, and carbohydrates played dominant roles in copper stress adaptation. The results indicated that the adaptation mechanisms of strain O5 to copper stress included protein synthesis and repair, accumulation of organic per-meable substances, up-regulation of energy metabolism, and formation of fatty acids. This study increases the resistance mechanism understanding of Antarctic strains to heavy metals in extreme environments.

The GLUT members belong to a family of glucose transporter proteins that facilitate glucose transport across the cell membrane. The mammalian GLUT family consists of thirteen members (GLUTs 1-12 and HMIT). Humans have a recently duplicated GLUT member, GLUT14. Avians express the majority of GLUT members. The arrangement of multiple GLUTs across all somatic tissues signifies the important role of glucose across all organisms. Defects in glucose transport have been linked to metabolic disorders, insulin resistance and diabetes. Despite the essential importance of these transporters, our knowledge regarding GLUT members in avians is fragmented. It has been clear that there are no chicken orthologs of mammalian GLUT4 and GLUT7. Our examination of GLUT members in the chicken revealed that some chicken GLUT members do not have corresponding orthologs in mammals. We review the information regarding GLUT orthologs and their function and expression in mammals and birds, with emphasis on chickens and humans.

Crash prediction of the sharp horizontal curve segment (SHCS) of a freeway is an important tool in analyzing safety of SHCSs and in building a crash prediction model (CPM). The design and crash report data of 88 SHCSs from different institutions were surveyed and three negative binomial (NB) regression models and three generalized negative binomial (GNB) regression models were built to prove that the interactive influence of explanatory variables plays an important role in fitting goodness. The study demonstrates the effective use of the GNB model in analyzing the interactive influence of explanatory variables and in predicting freeway basic segments. Traffic volume, highway horizontal radius, and curve length have been formulated as explanatory variables. Subsequently, we performed statistical analysis to determine the model parameters and conducted sensitivity analysis. Among the six models, the result of model 6, which considered interactive influence, is much better than those of the other models by fitting rules. We also compared the actual results from crashes of 88 SHCSs with those predicted by models 1, 3, and 6. Results demonstrate that model 6 is much more reasonable than models 1 and 3.