5 research outputs found
Synthesis, crystal structures, and fluorescent properties of zinc(II) complexes with benzazino-2-carboxalidin-2-aminophenols
New 2,5-bis(2-ethylhexyl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione-2,2’-bipyridine-based co-polymer, synthesis, photophysical properties and response to metal cations
A new co-polymer based on fragments of 2-(2-pyridyl)monoazatriphenylene and 2,5-bis (2-ethylhexyl)-3,6-di(thiophen-2-yl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione was prepared by using the Sonogashira reaction. The photophysical properties of the polymer were studied. The presence of a strong bathochromic shift of the absorption and emission maxima in comparison with the previously described monomer units is shown. The polymer exhibits an intense “turn-off” response toward Cu2+ cations
Chemical Composition and Content of Biologically Active Substances Found in <i>Cotinus coggygria, Dactylorhiza maculata, Platanthera chlorantha</i> Growing in Various Territories
Medicinal plants (Cotinus coggygria, Dactylorhiza maculata, Platanthera chlorantha) growing in various territories (Kaliningrad, Moscow, and Minsk regions) were the objects of research. This paper presents a study of the chemical composition of these plants. To analyze the qualitative and quantitative composition of biologically active substances, the method of high-performance liquid chromatography was used. Atomic absorption spectrometry was used to study the content of trace elements. The content of organic acids and vitamins was determined by capillary electrophoresis using the Kapel-105/105M capillary electrophoresis system with high negative polarity. Extracts of medicinal plants were obtained on a Soxhlet apparatus using 70% ethanol as an extractant. It was found that among the biologically active substances in the plants under discussion, hyperoside, rutin (C. coggygria), Ferulic acid and Gallic acid (D. maculata), triene hydrocarbon (3,7-Dimethyl-1,3,6-octatriene), unsaturated alcohol (3,7-Dimethyl-2,6-octadien-1-ol), and benzyl acetate (P. chlorantha) prevailed. Samples of these medicinal plants contained trace elements (phosphorus, potassium, calcium, sodium, magnesium, and sulfur) and many aliphatic organic acids (succinic acid, benzoic acid, fumaric acid, citric acid, oxalic acid, and tartaric acid). The largest amount of biologically active substances and secondary metabolites of the studied plants from the Eastern Baltic is associated with climatic and ecological differences from other regions. The composition of these plants determines the potential of their use in feed additives for livestock and poultry as part of measures to improve the quality of livestock products. The use of medicinal plants for the production of feed additives is relevant in terms of improving regional economies, as well as improving the quality of life and nation’s health by providing ecologically clean livestock products
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Computer vision vs. spectrofluorometer-assisted detection of common nitro-explosive components with bola-type PAH-based chemosensors
Computer vision (CV) algorithms are widely utilized in imaging processing for medical and personal electronics applications. In sensorics CV can provide a great potential to quantitate chemosensors' signals. Here we wish to describe a method for the CV-assisted spectrofluorometer-free detection of common nitro-explosive components, e.g. 2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT), by using polyaromatic hydrocarbon (PAH, PAH = 1-pyrenyl or 9-anthracenyl) – based bola-type chemosensors. The PAH components of these chemical bolas are able to form stable, bright emissive in a visual wavelength region excimers, which allows their use as extended matrices of the RGB colors after imaging and digital processing. In non-polar solvents, the excimers have poor chemosensing properties, while in aqueous solutions, due to the possible micellar formation, these excimers provide “turn-off” fluorescence detection of DNT and TNT in the sub-nanomolar concentrations. A combination of these PAH-based fluorescent chemosensors with the proposed CV-assisted algorithm offers a fast and convenient approach for on-site, real-time, multi-thread analyte detection without the use of fluorometers. Although we focus on the analysis of nitro-explosives, the presented method is a conceptual work describing a general use of CV for quantitative fluorescence detection of various analytes as a simpler alternative to spectrofluorometer-assisted methods