Anti-ENG monoclonal antibody, clone 3I7G22 [OC515]

Drawing from psychological contract, job demands-resources, and affective events theories, this paper proposes and tests a research model where employee engagement (ENG) mediates the impact of psychological contract breach (PCB) on task-related pro-environmental behaviors (TPEBs), proactive pro-environmental behaviors (PPEBs), and intent to remain with the organization (IRO). The linkages given above were assessed via structural equation modeling. Based on data obtained from hotel customer-contact employees in three waves and their immediate supervisors in China, the findings reveal that PCB is a stressor eroding employee ENG, TPEBs, PPEBs, and proclivity to remain with the organization. Employees with high ENG display pro-environmental behaviors at high levels and exhibit elevated IRO. These findings implicitly illustrate that employee ENG partly mediates the impact of PCB on TPEBs, PPEBs, and proclivity to remain with the organization. Implications of these findings are discussed, as are the limitations and avenues for future research.

Significant advancements in the field of protein structure prediction have necessitated the need for objective and robust evaluation of protein structural models by comparing predicted models against the experimentally determined native structures to quantitate their structural similarities. Existing protein model versus native similarity metrics either consider the distances between alpha carbon (C alpha) or side-chain atoms for computing the similarity. However, side-chain orientation of a protein plays a critical role in defining its conformation at the atomic-level. Despite its importance, inclusion of side-chain orientation in structural similarity evaluation has not yet been addressed. Here, we present SPECS, a side-chain-orientation-included protein model-native similarity metric for improved evaluation of protein structural models. SPECS combines side-chain orientation and global distance based measures in an integrated framework using the united-residue model of polypeptide conformation for computing model-native similarity. Experimental results demonstrate that SPECS is a reliable measure for evaluating structural similarity at the global level including and beyond the accuracy of C alpha positioning. Moreover, SPECS delivers superior performance in capturing local quality aspect compared to popular global C alpha positioning-based metrics ranging from models at near-experimental accuracies to models with correct overall folds-making it a robust measure suitable for both high- and moderate-resolution models. Finally, SPECS is sensitive to minute variations in side-chain chi angles even for models with perfect C alpha trace, revealing the power of including side-chain orientation. Collectively, SPECS is a versatile evaluation metric covering a wide spectrum of protein modeling scenarios and simultaneously captures complementary aspects of structural similarities at multiple levels of granularities. SPECS is freely available at http://watson.cse.eng.auburn.edu/SPECS/.