Decision Support for the Comparative Evaluation and Selection of Analytical Methods: Detection of Genetically Modified Organisms as an Example

The selection of the best-fit-for-purpose analytical method to be implemented in the laboratory is difficult due to availability of multiple methods, targets, aims of detection, and different kinds and sources of more or less reliable information. Several factors, such as method performance, practicability, cost of setup, and running costs need to be considered together with personnel training when selecting the most appropriate method. The aim of our work was to prepare a flexible multicriteria decision analysis model suitable for evaluation and comparison of analytical methods used for the purpose of detecting and/or quantifying genetically modified organisms, and to use this model to evaluate a variety of changing analytical methods. Our study included selection of PCR-, isothermal-, protein-, microarray-, and next-generation sequencing-based methods in simplex and/or multiplex formats. We show that the overall result of their fitness for purpose is relatively similar; however, individual criteria or a group of related criteria exposed more substantial differences between the methods. The proposed model of this decision support system enables easy modifications and is thus suitable for any other application of complex analytical methods.     

The Young Scientists Network: How the European Federation for Medicinal Chemistry (EFMC) Became Young Again

The European Federation for Medicinal Chemistry (EFMC) created the Young Scientists Network (YSN) to support early-career medicinal chemists and chemical biologists. By doing this, it addressed the rapid changes taking place in the scientific community and in our society, such as the rise of social media, the evolution of the gender balance in the scientific population, and educational needs. Creating the YSN was also a way to ensure that the next generation of scientists would contribute to shaping EFMC's strategy, while recognizing and addressing their needs. The YSN was set up as a very dynamic concept, and has now developed to the point where its impact is evident. The activities it promotes complement EFMC's community support and scientific opportunities, rejuvenating the Federation and preparing it for the future. It also provides opportunities for many brilliant young scientists, who do not hesitate to invest time and energy in supporting our community and shaping their own future.     

Implementing lean practices in manufacturing SMEs: testing ‘critical success factors’ using Necessary Condition Analysis

Lean practices are known to increase operational performance. Previous research has identified critical success factors for implementing lean practices. This research aims to examine the extent to which success factors are critical for various degrees of lean practice implementation. Using multiple-respondent self-assessments from 33 Dutch manufacturing small and medium-sized enterprises (SMEs), we conducted a Necessary Condition Analysis. Our findings indicated that the criticality of success factors is progression dependent. In the initial stages of the lean journey, SMEs could improve their lean practices in a bottom-up manner through local factors such as a learning focus, improvement training and support congruence. When lean practices are more advanced, some company-wide factors must be present: top management support, a shared improvement vision and a supplier link. Our findings question the universality of success factors such as strategic involvement and indicate the need for a more dynamic model of lean implementation.     

Detection and analysis of triterpenic compounds in apple extracts

A new technique for the rapid detection and analysis of triterpenic compounds in apple extracts using HPLC was developed and validated. The main advantage of this technique is the short duration of the analysis – this makes this technique superior to others currently applied for the routine HPLC analysis of triterpenic compounds. The developed, optimized, and validated technique was used for the evaluation of triterpenic compounds in samples of different cultivars of apples, their peels, and flesh. In total, four triterpenic compounds were isolated and identified. Ursolic acid was the dominant compound in all the tested apple samples. The highest amounts of triterpenic compounds were detected in the peels of the ‘Lodel’ apple cultivar, and thus apples of this cultivar may be potentially useful for the isolation of individual compounds and the production of functional food and dietary supplements.     

Identification of Phenylpyrazolone Dimers as a New Class of Anti-Trypanosoma cruzi Agents

Chagas disease is becoming a worldwide problem; it is currently estimated that over six million people are infected. The two drugs in current use, benznidazole and nifurtimox, require long treatment regimens, show limited efficacy in the chronic phase of infection, and are known to cause adverse effects. Phenotypic screening of an in-house library led to the identification of 2,2′-methylenebis(5-(4-bromophenyl)-4,4-dimethyl-2,4-dihydro-3H-pyrazol-3-one), a phenyldihydropyrazolone dimer, which shows an in vitro pIC₅₀ value of 5.4 against Trypanosoma cruzi. Initial optimization was done by varying substituents of the phenyl ring, after which attempts were made to replace the phenyl ring. Finally, the linker between the dimer units was varied, ultimately leading to 2,2′-methylenebis(5-(3-bromo-4-methoxyphenyl)-4,4-dimethyl-2,4-dihydro-3H-pyrazol-3-one (NPD-0228) as the most potent analogue. NPD-0228 has an in vitro pIC₅₀ value of 6.4 against intracellular amastigotes of T. cruzi and no apparent toxicity against the human MRC-5 cell line and murine cardiac cells.     

Understanding CO2 electrochemical reduction kinetics of mixed-conducting cathodes by the electrical conductivity relaxation method

Electrochemical reduction reaction is an important approach to utilize CO₂ and convert it into valuable products. Exceptional reaction kinetics at a high temperature of solid oxide electrolysis cells (SOECs) attracts particular attention. In this work, we propose to investigate CO₂-RR kinetics using a new theoretical method based on the electrical conductivity relaxation (ECR) technique on a typical mixed-conducting Sr₂Fe_1.5Mo_0.5O_6-δ (SFM) electrode. Three kinetic parameters that are commonly adopted in the typical electrochemical test experiments consisting of overpotential, current density and area-specific resistance (ASR) are derived. The overpotential resulted from the difference in the oxygen partial pressure is caused by the change of CO₂ partial pressure, while current density from the surface reaction rate constant. Accordingly, area-specific resistance, as well as overpotential-current density relationship, can be derived. We believe that this work brings a new method to study the kinetic process of CO₂ electrolysis and to evaluate the electrocatalyst activity of developed new electrode materials as well as to benefit the designing of novel electrode electrocatalysts for highly efficient solid oxide electrolysis cells.     

Survey of data-selection methods in statistical machine translation

Statistical machine translation has seen significant improvements in quality over the past several years. The single biggest factor in this improvement has been the accumulation of ever larger stores of data. We now find ourselves, however, the victims of our own success, in that it has become increasingly difficult to train on such large sets of data, due to limitations in memory, processing power, and ultimately, speed (i.e. data-to-models takes an inordinate amount of time). Moreover, the training data has a wide quality spectrum. A variety of methods for data cleaning and data selection have been developed to address these issues. Each of these methods employs a search or filtering algorithm to select a subset of the data, given a defined set of feature functions. In this paper we provide a comparative overview of research in this area based on application scenario, feature functions and search method.