Design of a tripartite network for the prediction of drug targets

Drug-target networks have aided in many target prediction studies aiming at drug repurposing or the analysis of side effects. Conventional drug-target networks are bipartite. They contain two different types of nodes representing drugs and targets, respectively, and edges indicating pairwise drug-target interactions. In this work, we introduce a tripartite network consisting of drugs, other bioactive compounds, and targets from different sources. On the basis of analog relationships captured in the network and so-called neighbor targets of drugs, new drug targets can be inferred. The tripartite network was found to have a stable structure and simulated network growth was accompanied by a steady increase in assortativity, reflecting increasing correlation between degrees of connected nodes leading to even network connectivity. Local drug environments in the tripartite network typically contained neighbor targets and revealed interesting drug-compound-target relationships for further analysis. Candidate targets were prioritized. The tripartite network design extends standard drug-target networks and provides additional opportunities for drug target prediction.     

Acetone and perdeuterated acetone in UV-IMS

Measuring a mixture of acetone and perdeuterated acetone (acetone-d6) with an ultra-high resolution drift time ion mobility spectrometer (resolving power of R_p?=?235) and ultraviolet ionization (10.6 eV) at ambient pressure reveals three separated peaks. Two of the peaks can easily be associated with acetone and perdeuterated acetone. In a former publication several findings indicated an exchange of a methyl group and the formation of a H₃COCD₃ related peak. In this work the formed ion species were analyzed with a high resolution drift time ion mobility time of flight mass spectrometer. The mass spectra clearly show the formation of three proton-bound dimer peaks whereas the peak between acetone and acetone-d6 is a proton-bound mixed dimer consisting of one acetone and one acetone-d6 molecule.     

Noise induced transition in Josephson junction with second harmonic

We show a noise induced transition in Josephson junction with fundamental as well as second harmonic. A periodically modulated multiplicative colored noise can stabilize an unstable configuration in such a system. The stabilization of the unstable configuration has been captured in the effective potential of the system obtained by integrating out the high frequency components of the noise. This is a classical approach to understand the stability of an unstable configuration due to the presence of such stochasticity in the system and our numerical analysis confirms the prediction from the analytical calculation.     

Modelling the soundscape quality of urban waterfronts by artificial neural networks

The renewal of the urban waterfronts has become a major focus of attention for politicians and decision makers in the city’s management programs. The recognition of the patterns that define the waterfronts’ identity is essential to select new strategies of intervention for the environmental recovery. In order to create adequate environments for everyday life within a sustainable development, new links between human senses, human perception and design need to be created. Within this wide approach, the landscape and the soundscape play a significant role and can become a key driving force in the implementation of the changes. New techniques have to be tested to identify the sonic and visual parameters capable to explain the specificity of a waterfront. With this purpose, an artificial neural network (ANN) was developed, and the relative importance of the input variables was evaluated. The collected database was also analysed by multiple linear regression (MLR) to compare the outcomes of both models. The urban waterfront of Naples (Italy) was chosen as case study. The results obtained show that the performance of the neural network is better than the one of the linear regression (rANN = 0.949, rMLR = 0.639). The interpretation of the relative importance method is also quite satisfactory in the ANN.     

Vector and Cell Line Engineering Technologies Toward Recombinant Protein Expression in Mammalian Cell Lines

The rapid growth of global biopharmaceutical market in the recent years has been a good indication of its significance in biotechnology industry. During a long period of time in recombinant protein production from 1980s, optimizations in both upstream and downstream processes were launched. In this regard, one of the most promising strategies is expression vector engineering technology based on incorporation of DNA opening elements found in the chromatin border regions of vectors as well as targeting gene integration. Along with these approaches, cell line engineering has revealed convenient outcomes in isolating high-producing clones. According to the fact that more than 50% of the approved therapeutic proteins is being manufactured in mammalian cell lines, in this review, we focus on several approaches and developments in vector and cell line engineering technologies in mammalian cell culture.