Biophysical and electrochemical studies of protein-nucleic acid interactions

This review is devoted to biophysical and electrochemical methods used for studying protein-nucleic acid (NA) interactions. The importance of NA structure and protein-NA recognition for essential cellular processes, such as replication or transcription, is discussed to provide background for description of a range of biophysical chemistry methods that are applied to study a wide scope of protein-DNA and protein-RNA complexes. These techniques employ different detection principles with specific advantages and limitations and are often combined as mutually complementary approaches to provide a complete description of the interactions. Electrochemical methods have proven to be of great utility in such studies because they provide sensitive measurements and can be combined with other approaches that facilitate the protein-NA interactions. Recent applications of electrochemical methods in studies of protein-NA interactions are discussed in detail

Examination and comparison of cognitive and executive functions in patients with schizophrenia and bipolar disorders

Background: Schizophrenia and bipolar disorders are associated with impaired cognitive and executive functions. Cognitive and executive profile of these two disorders is similar. However, cognitive and executive deficits in these patients may follow different paths. The purpose of the present study is to examination and comparison of different paths of cognitive and executive function in patients with schizophrenia and bipolar disorders. Methods: This was a descriptive study on patients with schizophrenia and bipolar disorders from 2016 to 2017. Thirty-four patients with schizophrenia, 52 patients with bipolar disorder, and 72 healthy individuals participated in the present study. This research was performed in Kargarnejad psychiatric hospital located in Kashan City, Iran. In this study, Positive and Negative Symptom Scale (PANSS), Young Mania Rating Scale (YMRS), Beck Depression Inventory-II (BDI-II), Tower of London task, Wisconsin card sorting task, Trial Making Test (TMT), and Four-Choice reaction time test (Four-Choice) were used. Findings: The MANOVA test showed a significant difference between the schizophrenia, bipolar disorder, and healthy groups in all scales of cognitive and executive functions. Altogether, performance of patients with schizophrenia in cognitive and executive functions were better than those with bipolar disorder; but schizophrenia and bipolar disorder groups have weaker performance than healthy persons (P < 0.001). Conclusion: This study show that cognitive and executive functions are destructed in schizophrenia and bipolar disorders, and they have weaker cognitive and executive functions than healthy controls. Moreover, cognitive and executive functions in patients with bipolar disorder are weaker than patients with schizophrenia, and follow different paths from schizophrenia. © 2019, Isfahan University of Medical Sciences(IUMS). All rights reserved

Agile optimization for a real‐time facility location problem in Internet of Vehicles networks

The uncapacitated facility location problem (UFLP) is a popular NP-hard optimization problem that has been traditionally applied to logistics and supply networks, where decisions are difficult to reverse. However, over the years, many new application domains have emerged, in which real-time optimization is needed, such as Internet of Vehicles (IoV), virtual network functions placement, and network controller placement. IoV scenarios take into account the presence of multiple roadside units (RSUs) that should be frequently assigned to operating vehicles. To ensure the desired quality of service level, the allocation process needs to be carried out frequently and efficiently, as vehicles' demands change. In this dynamic environment, the mapping of vehicles to RSUs needs to be reoptimized periodically over time. Thus, this article proposes an agile optimization algorithm, which is tested using existing benchmark instances. The experiments show that it can efficiently generate high-quality and real-time results in dynamic IoV scenarios