Cationic Geminoid Peptide Amphiphiles Inhibit DENV2 Protease,Furin, and Viral Replication

Dengue is an important arboviral infectious disease for which there is currently no specific cure. We report gemini-like (geminoid) alkylated amphiphilic peptides containing lysines in combination with glycines or alanines (C₁₅H₃₁C(O)-Lys-(Gly or Ala)_nLys-NHC₁₆H₃₃, shorthand notation C₁₆-KX_nK-C₁₆ with X = A or G, and n = 0–2). The representatives with 1 or 2 Ala inhibit dengue protease and human furin, two serine proteases involved in dengue virus infection that have peptides with cationic amino acids as their preferred substrates, with IC₅₀ values in the lower µM range. The geminoid C₁₆-KAK-C₁₆ combined inhibition of DENV2 protease (IC₅₀ 2.3 µM) with efficacy against replication of wildtype DENV2 in LLC-MK2 cells (EC₅₀ 4.1 µM) and an absence of toxicity. We conclude that the lysine-based geminoids have activity against dengue virus infection, which is based on their inhibition of the proteases involved in viral replication and are therefore promising leads to further developing antiviral therapeutics, not limited to dengue.     

A new approach for quantitative risk analysis

Project risk management aims to provide insight into the risk profile of a project as to facilitate decision makers to mitigate the impact of risks on project objectives such as budget and time. A popular approach to determine where to focus mitigation efforts, is the use of so-called ranking indices (e.g., the criticality index, the significance index etc.). Ranking indices allow the ranking of project activities (or risks) based on the impact they have on project objectives. A distinction needs to be made between activity-based ranking indices (those that rank activities) and risk-driven ranking indices (those that rank risks). Because different ranking indices result in different rankings of activities and risks, one might wonder which ranking index is best. In this article, we provide an answer to this question. Our contribution is threefold: (1) we set up a large computational experiment to assess the efficiency of ranking indices in the mitigation of risks, (2) we develop two new ranking indices that outperform existing ranking indices and (3) we show that a risk-driven approach is more effective than an activity-based approach.     

Determination of geometrical factors in Layerwise Laser Melting using optical process monitoring

Layerwise Laser Melting (LLM) is a layerwise production technique enabling the production of complex metallic parts. In the process a thin layer of powder is first deposited on a base plate. With the energy of a scanning laser beam this layer is melted at selected places, according to a predefined scanning pattern. After scanning, a new layer of powder is deposited on top of the previous layer and selectively melted. This sequence of depositing and scanning is repeated until the complete part is built. The local geometry surrounding the melt pool has a large influence on the processing behavior. For process control issues, this influence must be known and quantified, in order to determine a priori optimal processing conditions and to interpret measured melt pool radiation. In order to study the melt pool behavior, optical process monitoring of LLM has been applied using a high speed near-infrared CMOS camera and a large area silicon photodiode sensor. Data processing rates up to 10 kHz and real-time process monitoring are achieved using image and signal processing on a Field Programmable Gate Array (FPGA). Several case studies will be presented showing that the geometric influencing factors can be studied and quantified by analyzing the melt pool sensor output.     

Liquid phase separation of polyaromatics on [Cu2(BDC)2(dabco)

The porous coordination polymer (PCP) [Cu(2)(BDC)(2)(dabco)] is capable of selectively adsorbing up to 25 wt % of either 1-methylnaphthalene or 2-methylnaphthalene. Uptakes of unsubstituted naphthalene and 1,4-dimethylnaphthalene are significantly lower (7-13 wt %), suggesting that monomethyl substituted polyaromatics can be separated from the other fractions. Furthermore, this PCP can perform the difficult separation of 1-methylnaphthalene from 2-methylnaphthalene with separation factors as high as 2.6, proving that specific interactions of the methyl group with the lattice play an important role in determining the adsorption selectivity.