Stable Pyrrole-Linked Bioconjugates through Tetrazine-Triggered Azanorbornadiene Fragmentation

An azanorbornadiene bromovinyl sulfone reagent for cysteine-selective bioconjugation has been developed. Subsequent reaction with dipyridyl tetrazine leads to bond cleavage and formation of a pyrrole-linked conjugate. The latter involves ligation of the tetrazine to the azanorbornadiene-tagged protein through inverse electron demand Diels–Alder cycloaddition with subsequent double retro-Diels–Alder reactions to form a stable pyrrole linkage. The sequence of site-selective bioconjugation followed by bioorthogonal bond cleavage was efficiently employed for the labelling of three different proteins. This method benefits from easy preparation of these reagents, selectivity for cysteine, and stability after reaction with a commercial tetrazine, which has potential for the routine preparation of protein conjugates for chemical biology studies.     

Comprehensive Knowledge Archive Network harvester improvement for efficient open-data collection and management

With the recent increase in data disclosure, the Comprehensive Knowledge Archive Network (CKAN), which is an open-source data distribution platform, is drawing much attention. CKAN is used together with additional extensions, such as Datastore and Datapusher for data management and Harvest and DCAT for data collection. This study derives the problems of CKAN itself and Harvest Extension. First, CKAN causes two problems of data inconsistency and storage space waste for data deletion. Second, Harvest Extension causes three additional problems, namely source deletion that deletes only sources without deleting data themselves, job stop that cannot delete job during data collection, and service interruption that cannot provide service, even if data exist. Based on these observations, we propose herein an improved CKAN that provides a new deletion function solving data inconsistency and storage space waste problems. In addition, we present an improved Harvest Extension solving three problems of the legacy Harvest Extension. We verify the correctness and the usefulness of the improved CKAN and Harvest Extension functions through actual implementation and extensive experiments.     

Electrochemical characterization of carbon paste electrodes modified with MgZnGa and ZnGaAl hydrotalcite-like compounds

Two hydrotalcite-like compounds (HTs) were synthesized by coprecipitation. The electrochemical behavior of MgZnGa ([Mg_0.58 Zn_0.17Ga_0.25 (OH)₂] (CO₃)^2? _0.125 1.5 H₂O) and ZnGaAl ([Zn_0.75Ga_0.19 Al_0.06 (OH)₂] (CO₃)^2? _0.125·1.5 H₂O) Hydrotalcite-like compounds (HTs) was studied in NaOH at different concentrations. Voltammetric and chronoamperometric studies were performed to identify oxidation and reduction processes and the effect of the cations in total reactivity. Electrocatalytic effect of HTs on hydroxide electrochemical oxidation shows better performance of MgZnGa; this is apparently due to the presence of Mg and a greater amount of Ga³⁺ in the lattice of this HT. As far as reduction is concerned, Zn(II) reduction process is observed within the lattices of both HTs and is influenced by both the amount of OH^? in the solution and the potential which the previous oxidation has been performed.     

Target training with soft computing tools

The personal capabilities and intentions of employees indicate their performance within their organization. It is important for the organization to capture this kind of tacit knowledge since the workforce are the true experts in perceiving the organization's current reality and evaluating which assets require development – including themselves as knowledge assets. The collective inner voice of the workforce helps the organization's management to steer the company and its assets in a sustainable direction.This article presents how the collective inner voice of the workforce can be captured and how it can be used for the benefit of the organization and its employees. The objective is to support individuals’ personal aspirations, as well as to save the money, time and resources that an organization spends on personnel training.The focus of this article is on demonstrating a possible soft-computing method used for competency simulation. The process starts with a linguistic self-evaluation conducted by employees, where individuals’ own perception of current and target competence levels is captured. The self-evaluation is conducted with the help of fuzzy logic. Clusters are formed from the result dataset using an unsupervised neural network clustering method: self-organizing maps. A demonstrator tool is then used to perform a “what-if” type of analysis/simulation on the clusters in the results. With the demonstrator tool, employees can roughly test the impact of alternative training scenarios for themselves. For individuals this may open up new directions for self-development, and for organizations this may allow the efficient use of training resources. We tested the approach with a dataset from a real human resource development project among nuclear power plant operators.The case study reveals the potential of soft-computing based collective competency simulation as one part of personnel development projects in the future. Yet the techniques and the demonstrator tool used in this experiment are far from being products that employees could easily use as part of their training project. Possible benefits of the proposed approach are demonstrated in this article.