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1.
Microorganisms ; 11(9)2023 Sep 05.
Article in English | MEDLINE | ID: mdl-37764079

ABSTRACT

Bacteria, designated as A1.1 and A1.2, were isolated from poultry waste based on the ability to form ammonia on LB nutrient medium. Whole genome sequencing identified the studied strains as Peribacillus frigoritolerans VKM B-3700D (A1.1) and Bacillus subtilis VKM B-3701D (A1.2) with genome sizes of 5462638 and 4158287 bp, respectively. In the genome of B. subtilis VKM B-3701D, gene clusters of secondary metabolites of bacillin, subtilisin, bacilisin, surfactin, bacilliacin, fengycin, sactipeptide, and ratipeptide (spore killing factor) with potential antimicrobial activity were identified. Clusters of coronimine and peninodin production genes were found in P. frigoritolerans VKM B-3700D. Information on coronimine in bacteria is extremely limited. The study of the individual properties of the strains showed that the cultures are capable of biosynthesis of a number of enzymes, including amylases. The B. subtilis VKM V-3701D inhibited the growth of bacterial test cultures and reduced the growth rate of the mold fungus Aspergillus unguis VKM F-1754 by 70% relative to the control. The antimicrobial activity of P. frigoritolerans VKM V-3700D was insignificant. At the same time, a mixture of cultures P. frigoritolerans VKM B-3700D/B. subtilis VKM B-3701D reduced the growth rate of A. unguis VKM F-1754 by 24.5%. It has been shown that strain A1.1 is able to use nitrogen compounds for assimilation processes. It can be assumed that P. frigoritolerans VKM V-3700D belongs to the group of nitrifying or denitrifying microorganisms, which may be important in developing methods for reducing nitrogen load and eutrophication.

2.
Materials (Basel) ; 14(13)2021 Jul 05.
Article in English | MEDLINE | ID: mdl-34279328

ABSTRACT

A laboratory technology for a new ultra-low background hybrid material (HM) which meets the requirements for neutron absorption with simultaneous neutron detection has been developed. The technology and hybrid material can be useful for future low background underground detectors designed to directly search for dark matter with liquid noble gases. The HM is based on a polymethylmethacrylate (PMMA) polymer matrix in which gadolinium nuclei are homogeneously distributed up to 1.5 wt% concentration in polymer slabs of 5 cm thickness. To determine the 65 impurity elements by the inductively coupled plasma mass-spectrometry (ICP-MS) technique in the Gd-based preparations in 100-0.01 ppb range, the corresponding method has been developed. Limits of determination (LD) of 0.011 ppb for uranium, and 0.016 ppb for thorium were achieved. An analysis of Gd raw materials showed that the lowest contents of U and Th (1.2-0.2 ppb) were detected in commercial Gd-based preparations. They were manufactured either from secondary raw materials (extraction phosphoric acid) or from mineral raw materials formed in sedimentary rocks (phosphogypsum). To produce the Gd-doped HM the commercial GdCl3 was purified and used for synthesis of low-background coordination compound, namely, acetylacetonate gadolinium (Gd(acac)3) with U/Th contents less than LD. When dissolving Gd(acac)3 in methylmethacrylate, the true solution was obtained and its further thermal polymerization allowed fabrication of the Gd-doped PMMA with ultra-low background.

3.
Sci Rep ; 10(1): 17861, 2020 Oct 20.
Article in English | MEDLINE | ID: mdl-33082365

ABSTRACT

We stated and solved three successive problems concerning automatization of geological mapping using the case of the Bolshetroitskoe high-grade iron ore deposit in weathered crust of Banded Iron Formation (Kursk Magnetic Anomaly, Belgorod Region, Russia). (1) Selecting a classification (clustering) method of geochemical data without reference sampling, i.e., solution of an "unsupervised clustering task". We developed 5 rock classifications based on different principles, i.e., classification by visual description, by distribution of economic component (Fe2O3), by cluster analysis of raw data and centered log-ratio transformation of the raw data, and by artificial neural network (Kohonnen's self-organized map). (2) Non-parametric comparison of quality of the classifications and revealing the best one. (3) Automatic 3D geological mapping in accordance with the best classification. The developed approach of automatic 3D geological mapping seems to be rather simple and plausible.

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