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High-altitude freshwater lakes are experiencing ever-increasing risk of harmful algal blooms (HABs) on the face of climate change and a growing demand on agricultural production. The biggest alpine lake of the Caucasus, Lake Sevan, has "blooming" recently almost every year. Thus, the study of phytoplankton community' development patterns in Lake Sevan is gaining urgency. The aim of the work has been the study of the seasonal dynamics of quantitative and qualitative characteristics of phytoplankton in Lake Sevan. Also, we have tried to determine the features of horizontal distribution of phytoplankton within different seasons with the focus on Cyanobacteria distribution to identify current spatial-temporal features of HABs in Lake Sevan. Seasonal ground data collected from the photic zone of 178 stations in 2016-2018 was analysed and spatially interpolated. The results of analysis of seasonal dynamics of phytoplankton groups abundance have revealed the increased role of Cyanobacteria in the algal "blooms". Particularly, HABs were led by the dominant species of the genus Dolichospermum/Anabaena that are potentially toxic. Univariate analysis of variance with the post hoc Tukey test has proved the significance of changes in the quantitative parameters of phytoplankton development within years with the peak in 2018. Some antagonistic relations between the groups of phytoplankton under the HAB events were also shown through factorial and correlation analysis. Spatial interpolations revealed very limited extents of HABs compared with "blooms" led by Bacillariophyta species. HABs were mainly occurring in the littoral zone in a close proximity to the estuaries of Lake Sevan major tributaries.

Blockchain has emerged as one of the most promising and revolutionary technologies in the past years. Companies are exploring use cases in the hope of reaping benefits from this technology. However, to achieve the desired impact, it is not sufficient to merely replace existing technologies. Current business processes must be redesigned to realize benefits. This paper shows how a number of best practices for Business Process Redesign can be applied to leverage blockchain technology. Specifically, we adapt these best practices for redesigning processes intended to execute on blockchain. We further explore their applicability using a case study. The major elements of process redesign for blockchain are: (1) changing the view from intra- to inter-organizational processes by using the shared data ledger of blockchain, (2) using smart contracts performers of tasks and connectors of processes, (3) using blockchain as means for data communication, and (4) using tokens to manage digitally represented assets.

The development of antibiotics with new modes of action and specificity are necessary with the emergence of multidrug resistant Gram-negative bacteria. Antimicrobial photodynamic therapy (aPDT) affords reactive oxygen species, which generally overcomes the conventional bacterial resistance mechanisms, but typical aPDT agents do not strongly associate with Gram-negative bacteria. However, by covalently coupling a Ru-based chromophore with a cis-PtCl2 bioactive site, covalent interactions with the cell at the Pt moiety provides localization of the singlet oxygen generating chromophore. Reported here is the photoinhibition and photocytotoxicity of Escherichia coli, using the mixed-metal complex [Ru(Ph2phen)2(dpp)PtCl2]2+ (Ph2phen = 4,7-diphenyl-1,10-phenanthroline and dpp = 2,3-bis(2-pyridyl)pyrazine) in the presence of oxygen and low energy visible light. The Ru(II)–Pt(II) bimetallic complex shows promise as a photoactivated antibacterial agent that interacts with cells in a fundamentally different mode of action than cisplatin.

Human leukocyte antigen (HLA) genes are the most polymorphic in the human genome. They play a pivotal role in the immune response and have been implicated in numerous human pathologies, especially autoimmunity and infectious diseases. Despite their importance, however, they are rarely characterized comprehensively because of the prohibitive cost of standard technologies and the technical challenges of accurately discriminating between these highly related genes and their many allelles. Here we demonstrate a high-resolution, and cost-effective methodology to type HLA genes by sequencing, which combines the advantage of long-range amplification, the power of high-throughput sequencing platforms, and a unique genotyping algorithm. We calibrated our method for HLA-A, -B, -C, and -DRB1 genes with both reference cell lines and clinical samples and identified several previously undescribed alleles with mismatches, insertions, and deletions. We have further demonstrated the utility of this method in a clinical setting by typing five clinical samples in an Illumina MiSeq instrument with a 5-d turnaround. Overall, this technology has the capacity to deliver low-cost, high-throughput, and accurate HLA typing by multiplexing thousands of samples in a single sequencing run, which will enable comprehensive disease-association studies with large cohorts. Furthermore, this approach can also be extended to include other polymorphic genes.